Sleep and Circadian Rhythms from Mechanisms to … Anezka Macey-Dare, Imperial College London, UK 13.45 “Flying on Empty” – The effects of sleep loss on mood and task-specific

5–6 December 2018 | Barbican Centre, London, UK

Sleep and Circadian Rhythms from Mechanisms to Function

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The Physiological Society Topic MeetingSleep and Circadian Rhythms from Mechanisms to Function

5 – 6 December 2018

Barbican CentreSilk St, London EC2Y 8DS, UK Organised by Mary Morrell, Imperial College London, UK and Jason Rihel, University College London, UK

Contents

Welcome 4

Programme 6

General information 23

Abstracts Symposia 26 Communications 45

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It is a pleasure to welcome you to this special Physiological Society Meeting on Sleep and Circadian Rhythms, which is part of The Society’s Year of Sleep and Chronobiology. This meeting is focused on the mechanisms and functions of sleep and circadian rhythms.

Sleep and circadian research brings together many specialities. We are especially excited by the excellent programme that will explore many aspects of basic physiology, through to the impact of sleep and circadian function on health.

We have scheduled talks ranging from studies on neuronal mechanisms in animal models and humans, to genetics and sleep disorders. We are delighted to be showcasing so much excellent research and are especially grateful to our international attendees who have travelled long distances to share their expertise with us.

We specifically aimed to cover topics that we hope will encourage early career scientists, from all disciplines, to come together and solve the many questions and health-related issues in our field. A significant majority of the talks you will hear over the next two days will be given by early career scientists and we thank them for presenting their cutting edge studies.

At the end of the first day we have scheduled our public lecture, Sound Asleep: Harmonic cadences in the human sleep cycle. Please do come along and invite your friends and colleagues to hear this unique description of sleep. Morten Kringelbach, University of Oxford, UK and Milton Mermikides, University of Surrey, UK will discuss the neuroscience of human sleep and how this can be used to inform and

Welcome

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create musical compositions arising from the cyclical choreography of sleep in health and disease.

Finally, don’t forget to attend the poster and oral presentations, which will highlight the best of sleep and circadian research from around the UK and beyond. We will also be awarding a best poster prize for the earlycareer researchers starting on their research careers.

The success of any meeting is due to the interaction of the attendees and speakers. We thank you all for participating in the meeting and I hope you enjoy hearing about the latest developments in the exciting field of sleep and circadian physiology. London is a wonderful city and we hope you will enjoy your wake and sleep time with us.

Mary MorrellImperial College London, UK

Jason RihelUniversity College London, UK

Welcome

The Physiological Society, through its programme of scientific meetings, aims to support scientists in the United Kingdom, and across the world to communicate their latest research to peers, policymakers and funding bodies. These meetings are recognised for their high quality and impact on scientific discovery.

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9.00 Welcome and Introduction Mary Morrell, Imperial College London, UK

Session I: Sleep homeostasis

ChairsBill Wisden, Imperial College London, UK Mary Morrell, Imperial College London, UK

9.10 Neural circuits in sleep and anaesthesiaSA01 Nick Franks, Imperial College London, UK

9.50 Sleep function and control in Drosophila melanogasterSA02 Giorgio F Gilestro, Imperial College London, UK

10.10 Neural networks and sleepSA03 Vladyslav Vyazovskiy, University of Oxford, UK

10.30 Sleep, synaptic homeostasis and neuronal firing ratesSA04 Chiara Cirelli, University of Wisconsin, US

11.10 Refreshment break

Session II: Sleep genes and neurons

ChairsVladyslav Vyazovskiy, University of Oxford, UK Jason Rihel, University College London, UK

11.30 Autoimmunity to hypocretin and molecular mimicry to flu in type 1 narcolepsySA05 Emmanuel Mignot, Stanford University, USA

Wednesday, 5 December

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12.10 Genes and neurons that regulate sleep in zebrafishSA06 Jason Rihel, University College London, UK

12.30 Brain activity drives homeostatic rebound sleep through the engagement of the hypothalamic neuropeptide, galaninSA07 Sabine Reichert, University College London, UK

12.50 Genomic wide associations using the UK BiobankSA08 Martin Rutter, University of Manchester, UK

13.30 Lunch

Session III: Sleep and health (in collaboration with the British Sleep Society)

ChairsTim Quinnell, Royal Papworth Hospital NHS Foundation Trust, UK Joerg Steier, Guy’s & St Thomas’ NHS Foundation Trust King’s College London, UK

14.30 How does sleepiness impact performances, from normal subjects to patientsSA09 Pierre Philip, USR SANPSY, France

15.10 Sleep in spaceSA10 Ivana Rosenzweig, King’s College London, UK

15.30 Strategic decision making and potential drug targets for sleep apnea pharmacotherapySA11 Richard Horner, University of Toronto , Canada


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15.50 Intermittent hypoxia and obstructive sleep apnoeaSA12 Chris Turnbull, University of Oxford, UK

16.30 Poster Session and refreshments

18.00 Public Lecture Sound Asleep: Harmonic cadences in the human sleep cycleSA13 Morten Kringelbach, University of Oxford, UK Milton Mermikides, University of Surrey, UK

A dialogue between neuroscientist Morten Kringelbach and composer Milton Mermikides about the neuroscience of human sleep, and how this can be used to inform and create musical compositions arising from the cyclical choreography of sleep in health and disease. 19.30 Society Dinner by the river Little Ship Club


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Session IV: Sleep, metabolism, health and the circadian clock

ChairDebra Skene, University of Surrey, UK

9.00 Cellular and molecular basis to circadian rhythms in mammals and its relevance to metabolic and neurological diseaseSA15 Michael Hastings, MRC Laboratory of Molecular Biology, Cambridge, UK

9.40 Circadian modifiers of food intake David Bechtold, University of Manchester, UK

10.00 REM sleep in blind peopleSA17 Julie Christensen, University of Copenhagen, Denmark

10.20 Light, sleep and circadian interactions: Biology to new therapeutic targetsSA18 Russell Foster, University of Oxford, UK

11.00 Refreshment break

Oral communications

ChairsMary Morrell, Imperial College London, UKRichard Horner, University of Toronto, CanadaMarco Brancaccio, Imperial College London, UK

11.20 Interrelationship between sleep stability and glymphatic functionC01 Natalie Linea Hauglund, University of Copenhagen, Denmark

Thursday, 6 December

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11.35 Sleep-wake regulation in mice: insights from a synaptobrevin-2 mutant line and computational modelling C03 Mathilde Guillaumin, University of Oxford, UK

11.50 Effects of selective silencing of layer 5 pyramidal neurons on sleep-wake regulation and cortical network dynamicsC10 Lukas Krone, University of Oxford, UK 12.05 GABA and glutamate networks in the VTA regulate vigilance stateC28 Xiao Yu, Imperial College London, UK 12.20 Amyloid beta oligomeric structure governs sleep/wake states in zebrafish C17 Guliz Ozcan, University College London, UK

12.35 Lunch

Oral communications

13.15 Circadian control of paraventricular hypothalamic activity by suprachiasmatic VIP neurons C07 Sarika Paul, University of Manchester, UK 13.30 Do women experience more sleep deprivation when the clocks go forward, compared to men? C09 Anezka Macey-Dare, Imperial College London, UK 13.45 “Flying on Empty” – The effects of sleep loss on mood and task-specific competencies in commercial airline pilotsC06 Anna Donnla O’Hagan, Dublin City University, Ireland


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14.00 Effects of sleep extension and sleep restriction on the performance and cardiac autonomic function of endurance cyclistsC15 Spencer Roberts, Deakin University, Australia

Session V: Sleep disorders and new treatment

ChairChristopher-James Harvey, University of Oxford, UK

14.15 Metabolic profiling of sleep deprivation and circadian misalignmentSA19 Debra Skene, University of Surrey, UK

14.55 New Models for sleep analysis Danielo Mandic, Imperial College London, UK

15.35 Sleep and public policy – bridging the gap with what the public want to know Christopher-James Harvey, University of Oxford, UK

16.15 End of Meeting


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C01Interrelationship between sleep stability and glymphatic functionNatalie L. HauglundCenter for Translational Neuromidicine, University of Copenhagen, Copenhagen N, Denmark

C02Improving student sleep quality and quantity to improve higher educational experienceConnor S. Qiu1, 2, Yizhou Yu2, Abdullah Cheema2, Christopher James-Harvey3, Mary J. Morrell2 1Isle of Wight NHS Trust, Newport, United Kingdom, 2Imperial College London, United Kingdom, 3University of Oxford, Oxford, United Kingdom

C03Sleep-wake regulation in mice: insights from a synaptobrevin-2 mutant line and computational modellingMathilde Guillaumin1, Peter Achermann2, Patrick Nolan4, Stuart Peirson1, Vladyslav Vyazovskiy3

1Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 2Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland, 3Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom, 4MRC Harwell Institute, Harwell, United Kingdom

C04Heart rate dynamics during NREM sleep in rats under cold environmentOleksandr Shylo, Victoria Lomako, Georgiy BabiychukCryophysiology, Institute for Problems of Cryobiology and Cryomedicine of the National Academy of Sciences of Ukraine, Ukraine

Poster Communications

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C05How is valence encoded during sleep?Alice T. French, Quentin Geissmann, Esteban Beckwith, Giorgio F. GilestroImperial College London, United Kingdom

C07Circadian control of paraventricular hypothalamic activity by suprachiasmatic VIP neuronsSarika Paul, Lauren Walmsley, Court Harding, Timothy BrownFaculty of Medicine, Biology & Health, University of Manchester, Manchester, United Kingdom

C08Age, Alzheimers, circadian rhythms and sleep in DrosophilaEdgar Buhl, Jack Curran, James Higham, James HodgeUniversity of Bristol, Bristol, United Kingdom

C09Do women experience more sleep deprivation when the clocks go forward, compared to men?Anezka Macey-Dare1, Shifa Bangi1, William Jackson1, Connor S. Qiu4, 1, Yousef Alqurashi2, Joshua Benson2, 3, Julia Kelly2, 3, Christopher James-Harvey5, Mary J. Morrell1, 2, 3

1Clinical Research and Innovation Theme, Imperial College London, London, United Kingdom, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, United Kingdom, 3National Institute for Health Research Respiratory Disease Biomedical Research Unit , Royal Brompton and Harefield National Health Service Foundation Trust and Imperial College London, London, United Kingdom, 4St Mary’s Hospital, Isle of Wight NHS Trust , Newport, United Kingdom, 5Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom


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C10Effects of selective silencing of layer 5 pyramidal neurons on sleep-wake regulation and cortical network dynamicsLukas Krone1, 2, Tomoko Yamagata2, Anna Hoerder-Suabedissen1, Zoltán Molnár1, Vladyslav Vyazovskiy1, 2

1Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom, 2Sleep and Circadian Neuroscience Institute, University of Oxford, Oxford, United Kingdom

C11The impact of colour on circadian photoentrainment in miceJoshua Mouland, Franck Martial, Timothy Brown, Robert LucasUniversity of Manchester, United Kingdom

C12Can a Visual Analogue Scale (VAS) be used to measure sleepiness in patients diagnosed with Obstructive Sleep Apnoea (OSA)?Aleksander Dawidziuk2, Yousef Alqurashi1, James Moss1, Michael Polkey1, Mary J. Morrell1 1National Heart and Lung Institute, Imperial College London, London, United Kingdom, 2College of Medicine, Imperial College London, London, United Kingdom

C13Exploring the molecular clock in sympathetic preganglionic neuronsChristian Nathan, Julie Aspden, Susan Deuchars, Jim DeucharsFaculty of Biological Sciences, University of Leeds, Leeds, United Kingdom


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C14High intensity interval running increases cardiac autonomic activity but does not disrupt subsequent night's sleep in trained runners Craig ThomasResearch Institute For Sport And Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom

C15Effects of sleep extension and sleep restriction on the performance and cardiac autonomic function of endurance cyclistsSpencer Roberts, Wei-Peng Teo, Brad Aisbett, Stuart A. WarmingtonInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria, Australia

C16The use of melatonin in the treatment of paediatric sleep disorders in the UKMeirvaan Basra1, Sophia Terry1, David Wringe1, Mary J. Morrell1, 2, 3 1Clinical Research and Innovation Theme, Imperial College School of Medicine, London, United Kingdom, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, United Kingdom, 3National Institute for Health Research Respiratory Biomedical Research Unit, Royal Brompton & Harefield National Health Service Foundation Trust, London, United Kingdom

C17Amyloid beta oligomeric structure governs sleep/wake states in zebrafishGuliz Ozcan, Sumi Lim, Jason RihelCell and Developmental Biology, University College London, London, United Kingdom


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C18The impairment in insulin sensitivity after sleep restriction does not increase with more nights of sleep restrictionEmma Sweeney1, Daniel J. Peart1, Jason G. Ellis2, Ian H. Walshe1 1Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle Upon Tyne, United Kingdom, 2Northumbria Sleep Research Laboratory, Northumbria University, Newcastle Upon Tyne, United Kingdom

C19Modelling local sleep homeostasisChristopher W. Thomas1, Mathilde Guillaumin1, Laura McKillop1, Peter Achermann2, Vladyslav Vyazovskiy1 1Department of Physiology, Anatomy & Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom, 2Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland

C20Investigating the neural circuit basis of sleep disturbance-induced cognitive deficits using the larval zebrafish (Danio rerio)Declan G. Lyons, Sabine Reichert, Jason RihelDepartment of Cell and Developmental Biology, University College London, London, United Kingdom

C21Torpor preferentially induces c-fos expression in dorsomedial and posterior hypothalamus in miceMichael T. Ambler1, Matteo Cerri2, Anthony Pickering1 1Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, Bristol, United Kingdom, 2Department of biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy


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C22Can blue light exposure influence mood in night shift workers?Whei-Chang Kim1, Wayne Han1, Thomas Rose1, Christopher James-Harvey2, Mary J. Morrell1, 3, 4

1Clinical Research and Innovation Theme, Imperial College School of Medicine, London, United Kingdom, 2Nuffield Department of Clinical Neurosciences, Sleep & Circadian Neuroscience Institute, University of Oxford, Oxford, United Kingdom, 3National Institute for Health Research Respiratory Disease Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom, 4Imperial College, London, United Kingdom

C23Does exposure to blue light reduce sleepiness in night shift workers?Tenzin Dorji1, Shubham Sharma1, Samuel Lowe1, Mary J. Morrell2, 1, 3, Christopher James-Harvey4 1School of Medicine, Imperial College London, London, United Kingdom, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, United Kingdom, 3Respiratory Biomedical Research Unit at the Royal Brompton Hospital, Imperial College London, London, United Kingdom, 4Nuffield Department of Clinical Neurosciences, University of Oxford, London, United Kingdom

C24The relationship between fasting-induced torpor and sleep in miceYige Huang, Vladyslav VyazovskiyPhysiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom


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C25Is self-reported chronotype associated with caffeine intake in male night shift workers?Abeku Koomson1, Shao Ting, Pearlyn Lee1, Michael Samy1, Christopher James-Harvey4, Mary J. Morrell1, 2, 3

1Clinical Research and Innovation Theme, Imperial College School of Medicine, London, United Kingdom, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, United Kingdom, 3National Institute for Health Research Respiratory Disease Biomedical Research Unit at the Royal Brompton and Harefield National Health Service Foundation Trust and Imperial College London, London, United Kingdom, 4Sleep and Circadian Neuroscience Institute, Oxford University, Oxford, United Kingdom

C26Circadian disruption and sleep regulation in miceAngus Fisk, VV Vyazovskiy, SN PeirsonNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

C27GRIA1 knockout mice show reduced global EEG sleep spindles, preserved local LFP spindles an retain long-term memoryCristina Blanco Duque1, Ross J. Purple2, Tomoko Yamagata1, Lukas Krone1, Laura McKillop1, David M. Bannerman1, Vladyslav Vyazovskiy1 1University of Oxford, Oxford, United Kingdom, 2University of Bristol, Bristol, United Kingdom


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C28GABA and glutamate networks in the VTA regulate govern vigilance stateXiao Yu1, Wen Li2, Ying Ma1, Kyoko Tossell1, Julia J. Harris1, 3, Edward C. Harding1, Wei Ba1, Giulia Miracca1, Dan Wang2, Long Li2, Juan Guo2, Ming Chen4, Yuqi Li1, Raquel Yustos1, Alexei L. Vyssotski5, Denis Burdakov3, Qianzi Yang2, Hailong Dong2, Nicholas P. Franks1, 6, William Wisden1, 6

1Department of Life Sciences, Imperial College London, London, United Kingdom, 2Department of Anesthesiology & Perioperative Medicine, Xijing Hospital, Xi’an, China, 3The Francis Crick Institute, London, United Kingdom, 4iHuman Institute, ShanghaiTech University, Shanghai, China, 5Institute of Neuroinformatics, University of Zürich/ETH Zürich, Zürich, Switzerland, 6Centre of Excellence in Neurotechnology and UK Dementia Research Institute, Imperial College London, London, United Kingdom

C29The functional anatomy the connections between the amygdala and other limbic regions Anam Saifullah, King’s College London, United KingdomAdditional authors: Marco Catani and Ahmad Beyh, King’s College London

C30Neurocalcin regulates night sleep in Drosophila Ko-Fan Chen, UCL QS Institute of Neurology, London


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C31Smartphones: The future of sleep measurement?Sophie Wouters, Imperial College School of Medicine, London, United KingdomAdditional authors: A Smith (1)

A Miller (1)

Y Alqurashi (2)

MJ Morrell (1,2,3)

1 Imperial College School of Medicine, London, United Kingdom2 Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, United Kingdom3 National Institute for Health Research Respiratory Disease Biomedical Research Unit at the Royal Brompton and Harefield National Health Service Foundation Trust and Imperial College, London, United Kingdom

C32Effects on physical performance of one night’s sleep deprivation Lindy Castell, Green Templeton College, University of Oxford, United KingdomAdditional authors: J. C. Miller - US Air Force Research Laboratory (Retd) Brooks City-Base, San Antonio, Texas, USA

C33Stereotypical task performance reduces sleep need in mice Linus Milinski, University of Oxford, United KingdomAdditional authors: David M. Bannerman (Department of Experimental Psychology; University of Oxford, United Kingdom)Vladyslav V. Vyazovskiy (Department of Physiology, Anatomy and Genetics; University of Oxford, United Kingdom)


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C34Sleep during a mountain ultra-marathon: A case study Borja Martinez-Gonzalez, University of Kent, United KingdomAdditional authors: Glen Davison (University of Kent)Samuele M. Marcora (University of Kent)

C35Characterisation of individual slow waves under propofol anaesthesia Lucy Mellers, University of Oxford, United KingdomAdditional authors: Jostein Holmgren (1,2), Jamie Sleigh (3), Katie Warnaby (1,2)

1) Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom2) Nuffield Division of Anaesthetics, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom3) Department of Anaesthesia, University of Auckland, Waikato Hospital, Hamilton, New Zealand


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The Physiological Society team can always be found at the registration desk. We will be happy to help with any queries you may have but you might be able to find an answer to your question on these pages.

RegistrationThe registration desk is outside the Garden Room on level three and will be open at the following times: Wednesday, 5 December 8.00 – 18.00Thursday, 6 December 8.00 – 16.15

Poster help deskThis is at the registration desk. You can find Velcro to affix your poster here. No other fixings may be used. You can also find out when you are scheduled to present.

Poster session on Wednesday, 5 DecemberOdd numbers will present from 16.30 – 17.15Even numbers will present from 17.15 – 18.00

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Video or audio recording of presentationsAttendees are reminded that the video and audio recording of ANY session or presentation using mobile devices or any such recording equipment is strictly prohibited.

Changes to abstractsWe cannot make changes to abstracts.

General information

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SmokingIt is illegal to smoke in enclosed public spaces. If you wish to smoke then you need to go to the designated smoking area.

Arriving late to sessionsWe know it is not always possible to get to sessions on time but we do ask that if you are running late, to take your seat quietly.

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In case of emergencyThe Physiological Society team are your first point of contact in any emergency. They will help you or find the person who can.

General information

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Ethical requirements

Experiments on animals or animal tissue

For work conducted in the UK all procedures must conform with current UK legislation. For work conducted elsewhere all procedures must accord with current national guidelines or, in their absence, with current local guidelines.

Experiments on humans or human tissue

All procedures must accord with the ethical standards of the relevant national, institutional or other body responsible for human research and experimentation, and with the principles of the World Medical Association’s Declaration of Helsinki.

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Symposia

SA01

Neural circuits in sleep and anaesthesia

N. Franks

Imperial College, London, UK

Putting a patient to sleep has been used as a metaphor for drug-induced sedation and anaesthesia ever since general anaesthetics were first used clinically during the 1840s. Only relatively recently, however, has the possibility that general anaes-thetics may act, at least in part, by affecting some of the natural pathways of sleep and arousal, been investigated in detail. I will discuss some of the evidence that sleep and anaesthesia may affect common neuronal pathways, and then go on the describe experiments showing that overlapping ensembles of neurons in the hypo-thalamus are involved in both deep sleep and drug-induced sedation, and that the same networks may also be responsible for the hypothermia seen in both states.“General anaesthesia: from molecular targets to neuronal pathways of sleep and arousal” Franks NP. Nature Reviews Neuroscience 9:370-86 (2008).

“Neuronal ensembles sufficient for recovery sleep and the sedative actions of α2 adrenergic agonists” Zhang Z et al. Nature Neuroscience 18:553-561 (2015).

“A Neuronal Hub Binding Sleep Initiation and Body Cooling in Response to a Warm External Stimulus” Harding EC et al. Current Biology 28:2263-2273 (2018).

Funded by the Wellcome Trust and the UK Dementia Research Institute.

Where applicable, the authors confirm that the experiments described here conform with the Physiological Society ethical requirements.

SA02

Sleep function and control in Drosophila melanogaster

G.F. Gilestro

Department of Life Sciences, Imperial College London, London, UK

Sleep appears to be a universally conserved phenomenon among the animal kingdom but whether this striking evolutionary conservation underlies a basic vital function is still an open question. Using novel technologies, we conducted an unprecedentedly detailed high-throughput analysis of sleep in the fruit fly Drosophila melanogaster, coupled with a life-long chronic and specific sleep restric-tion. Our results show that some wild-type flies are virtually sleepless in baseline conditions and that complete, forced sleep restriction is not necessarily a lethal treatment in wild-type Drosophila melanogaster. We also show that circadian drive, and not homeostatic regulation, is the main contributor to sleep pressure in flies.

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Symposia

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We propose a three-partite model framework of sleep function, according to which, total sleep accounts for three components: a vital component, a useful component, and an accessory component.Most sleep does not serve a vital function. Evidence from Drosophila melanogaster Quentin Geissmann, Esteban J. Beckwith, Giorgio F. Gilestro doi: https://doi.org/10.1101/361667

Quentin Geissmann, Esteban Beckwith, Anne Petzold


SA03

Neural Networks and Sleep

V. Vyazovskiy

University of Oxford, Oxford, UK

Sleep has been found in all animal species carefully studied to date; yet, the biolog-ical function of sleep remains unclear. Sleep can be defined on at least two distinct levels: the behaviour of the whole organism and the spatiotemporal patterns of neuronal activity in the brain. Upon falling asleep, cortical networks alternate between periods of generalized population firing and periods of relative silence. This pattern of neuronal activity gives rise to electroencephalogram (EEG) oscil-lations at a frequency of approximately 1-4 Hz, which are termed slow waves. Contrary to the widely-held notion, waking and sleep are not global, mutually exclusive states, and research over the last decades has revealed that sponta-neous brain activity during sleep can be locally modulated. For example, slow wave activity (SWA) is more intense in frontal compared to more posterior areas, especially in early sleep or after sleep deprivation, and regional differences are apparent at the level of individual sleep slow waves. Although the alternation of periods of increased neuronal activity and silence is usually correlated across cortical regions and individual neurons, up-states can sometimes be seen in one region of the cortex while another region is in a down-state, with these states often spreading as travelling waves. Sleep deprivation is associated with increased low-frequency EEG activity during waking in both animals and humans, and record-ings in rodents suggested that this EEG pattern reflects local neuronal OFF periods in the neocortex. Although the role of subcortical neuromodulatory areas in gener-ating and maintaining sleep and wakefulness is well established, the possibility remains that the neocortex is also involved in sleep regulation. Consistent with this hypothesis, we observed a marked increase in the amount of wakefulness and a diminished increase in SWA after sleep deprivation in transgenic mice, in which a subset of pyramidal cells in layer 5 is functionally silenced by removal of the t-SNARE protein SNAP25 (Rbp4-Cre;Ai14;Snap25fl/fl). These notions suggest that

283P

Symposia

sleep need accumulates at the level of local cortical networks, which are directly implicated in global sleep regulation.McKillop, L. E., Fisher, S. P., Cui, N., Peirson, S. N., Foster, R. G., Wafford, K. A., and Vyazovskiy, V. V. (2018) Effects of ageing on cortical neural dynamics and local sleep homeostasis in mice. J Neurosci 38, 3911-3928

Fisher, S. P., Cui, N., McKillop, L. E., Gemignani, J., Bannerman, D. M., Oliver, P. L., Peirson, S. N., and Vyazovskiy, V. V. (2016) Stereotypic wheel running decreases cortical activity in mice. Nat Commun 7, 13138

Vyazovskiy, V. V., and Harris, K. D. (2013) Sleep and the single neuron: the role of global slow oscillations in individual cell rest. Nat Rev Neurosci 14, 443-451

Vyazovskiy, V. V., Olcese, U., Hanlon, E. C., Nir, Y., Cirelli, C., and Tononi, G. (2011) Local sleep in awake rats. Nature 472, 443-447

Vyazovskiy, V. V., Olcese, U., Lazimy, Y. M., Faraguna, U., Esser, S. K., Williams, J. C., Cirelli, C., and Tononi, G. (2009) Cortical firing and sleep homeostasis. Neuron 63, 865-878

Supported by MRC NIRG MR/L003635/1, Wellcome Trust Strategic Award 098461/Z/12/Z, Wellcome Trust Senior Investigator Award 106174/Z/14/Z, BBSRC Industrial CASE grant BB/K011847/1 and John Fell OUP Research Fund Grant (131/032).


SA04

Sleep and synaptic down-selection

C. Cirelli

Psychiatry, University of Wisconsin-Madison, Madison, United States Minor Outlying Islands

The synaptic homeostasis hypothesis (SHY) proposes that sleep is an essential process needed by the brain to maintain the total amount of synaptic strength under control. SHY predicts that by the end of a waking day the synaptic connec-tions of many neural circuits undergo a net increase in synaptic strength due to ongoing learning, which is mainly mediated by synaptic potentiation. Stronger synapses require more energy and supplies and are prone to saturation, creating the need for synaptic renormalization. Such renormalization should mainly occur during sleep when the brain is disconnected from the environment and neural circuits can be broadly reactivated off-line to undergo a systematic and yet specific synaptic down-selection. In short, according to SHY, sleep is the price to pay for waking plasticity to avoid runaway potentiation, decreased signal-to-noise ratio, and impaired learning due to saturation. I will discuss the rationale underlying this hypothesis and summarize electrophysiological, molecular and ultrastructural

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Symposia

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studies in flies, rodents and humans that confirmed SHY’s main predictions, including the recent observation, obtained using serial block face scanning electron microscopy, that most synapses in mouse primary motor and sensory cortices grow after wake and shrink after sleep. I will then present unpublished ultrastructural data obtained in the hippocampus and in the cortex of mouse pups. Finally, I will examine recent studies by other groups showing the causal role of cortical slow waves and hippocampal ripples in sleep-dependent synaptic down-selection, and discuss some of the molecular mechanisms that can mediate this process.Tononi G, Cirelli C (2014) Sleep and the price of plasticity: from synaptic and cellular homeo-stasis to memory consolidation and integration. Neuron 81:12-34.

Acknowledgements:This work was supported by NIH Grants DP 1OD579, 1R01MH091326, 1R01MH099231, and 1P01NS083514.


SA10

Sleep in space

C. Tsai1,2, H. Hasegawa1,3, T. Morris-Paterson4, S. Higgins1,2, A. Keyoumars1,3, D. Green4,5, P. Goadsby6, G.D. Leschziner1,2, S. Harridge4 and I. Rosenzweig1,2

1Sleep and Brain Plasticity Centre, Department of Neuroimaging, King’s College London, London, UK, 2Sleep Disorders Centre, Guy’s Hospital, London, UK, 3Department of Neurosurgery, King’s College Hospital, London, UK, 4Centre of Human and Applied Physiological Sciences, King’s College London, London, UK, 5KBRwyle, European Astronaut Centre, European Space Agency, Cologne, Germany and 6NIHR, Wellcome Trust King’s Clinical Research Facility, London, UK, UK

With rapid scientific development and interest in interplanetary travel in the 20th century, there has been an increasing focus on the effects of spaceflight and micro-gravity on human physiology. Whilst the effects of spaceflight on cardiovascular and respiratory physiology are well recognized, the effect on the brain has not been widely studied. Astronauts have long been reported to experience impairments in sensorimotor function including posture control, spatial orientation, manual tracking, and cerebellar dysfunction.Significantly shortened and disrupted sleep has also been consistently reported in space missions. Sleep serves a restorative function for the brain and cognition and involves dramatic changes to our perception, consciousness, cognition and health. The perpetual activity of the brain is largely supported by a variety of oscil-lations and rhythms it generates. Sleep and sleep stages are also characterized by specific brain oscillations, which, unlike those of wakefulness, are maintained free of external inputs. This means that a transient perturbation during sleep can have a lasting impact. Recent studies on astronauts have shown that weightlessness

S05 Autoimmunity to hypocretin and molecular mimicry to flu in type 1 narcolepsyEmmanuel Mignot, Stanford University, USA

Additional authorsGuo Luo, Aditya Ambati, Ling Lin

Type 1 narcolepsy (T1N) is caused by hypocretin/orexin (HCRT) neuronal loss. Association with the Human Leukocyte Antigen DQB1*06:02/DQA1*01:02 (98% vs 25%) heterodimer (DQ0602), T cell receptor (TCR) and other immune loci such as T cell receptor loci suggests autoimmunity but autoantigen(s) are unknown. Onset is seasonal and associated with influenza A, notably pandemic 2009 H1N1 (pH1N1) infection and vaccination (Pandemrix®). Peptides derived from HCRT and influenza A including pH1N1 were screened for DQ0602 binding and presence of cognate DQ0602 tetramer-peptide specific CD4+ T cells tested in 35 T1N cases and 22 DQ0602 controls. Higher reactivity to influenza pHA273-287 (pH1N1 specific), PR8 (H1N1 pre-2009 and H2N2)-specific NP17-31 and C-amidated but not native version of HCRT54-66 and HCRT86-97 (HCRTNH2) were

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observed in T1N. Single cell TCR sequencing revealed sharing of CDR3β TRBV4-2-CASSQETQGRNYGYTF in HCRTNH2 and pHA273-287-tetramers, suggesting molecular mimicry. This public CDR3β uses TRBV4-2, a segment modulated by T1N-associated Single Nucleotide Polymorphism (SNP) rs1008599, suggesting causality. TCRα/β CDR3 motifs of HCRT54-66-NH2 and HCRT86-97-NH2 tetramers were extensively shared notably public CDR3α, TRAV2-CAVETDSWGKLQF-TRAJ24, that uses TRAJ24, a chain modulated by T1N-associated SNPs rs1154155 and rs1483979. TCRα/β CDR3 sequences found in pHA273-287, NP17-31 and HCRTNH2 tetramer-positive CD4+ cells were also retrieved in single INFγ-secreting CD4+ sorted cells stimulated with Pandemrix®, independently confirming these results. Our results provide evidence for autoimmunity and molecular mimicry with flu antigens modulated by genetic components in the pathophysiology of T1N.

Acknowledgements The study was primarily funded by gifts from Wake Up Narcolepsy, Jazz Pharmaceutical and individual patients to Stanford University.

S06 Genes and neurons that regulate sleep in zebrafishJason Rihel, University College London, United Kingdom

Sleep is a deeply conserved phenomenon, yet the genetic and neuronal mechanisms that regulate sleep are still being uncovered. Zebrafish are an excellent model system in which to investigate sleep, because of the capacity for cost-effective genetic and pharmacological screening and the larval brain’s optical translucency facilitates functional neuroanatomical studies. Zebrafish larvae as young as five days post fertilization display circadian-regulated periods of quiescence, during which the larvae are less sensitive to their environment. These sleep states are under homeostatic regulation, as depriving larvae of sleep subsequently leads to increased, deeper sleep states. Furthermore, zebrafish sleep is regulated by systems shared by humans, including the hypocretin/orexin system that is lost in narcoleptic patients. This

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presentation will highlight novel sleep regulatory networks unearthed through zebrafish drug and genetic screens and suggest a template for mapping the function of sleep genes onto discrete neuronal circuits.

S07 Brain activity drives homeostatic rebound sleep through the engagement of the hypothalamic neuropeptide, galaninSabine Reichert, University College London, United Kingdom

Additional authorsOriol Pavón Arocas 2, Jason Rihel*1

1 Division of Biosciences, Department of Cell and Developmental Biology, University College London, Gower Street, London, United Kingdom WC1E 6BT2 Current address: Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, Howland Street, London, United Kingdom W1T 4JG.

Sleep pressure homeostatically increases during wake and dissipates during sleep, but the molecular signals and neuronal substrates that measure homeostatic sleep pressure remain poorly understood. Using a pharmacological assay to generate acute, short-term increases in wakefulness in larval zebrafish, we found that subsequent rebound sleep is dependent on the intensity of global neuronal activity. Whole brain activity mapping identified preoptic Galanin-positive neurons as selectively active during rebound sleep, and the induction of galanin transcripts was predictive of total rebound sleep time. Galanin is required for sleep homeostasis, as galanin mutants almost completely lack rebound sleep following both pharmacologically induced neuronal activity as well as sleep deprivation. We propose that galaninergic neurons integrate sleep pressure signals from global neuronal activity and act as an output arm for the vertebrate sleep homeostat.

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S08 Genomic wide associations using the UK BiobankMartin Rutter, University of Manchester, UK

1. Motivation: Prior genome-wide association studies relating to sleep traits and chronotype have been underpowered and have provided limited data.2. Methods: We used UK Biobank and 23andMe data to generate novel data on the genetic basis for sleep traits and chronotype including data on objectively-determined sleep traits from actigraphy.3. Results: a) For self-reported insomnia we identified 57 loci and shared genetic factors with restless legs syndrome, ageing, cardiometabolic, behavioural, psychiatric and reproductive traits. We found evidence is found for a possible causal link between insomnia symptoms and coronary artery disease, depressive symptoms and subjective wellbeing; b) for self-reported sleep duration we discovered 78 loci and Mendelian Randomisation highlighted a potential causal link between longer sleep and schizophrenia; c) for self-reported excessive daytime sleepiness (EDS) we identified 42 loci. Mendelian Randomisation analysis indicated that higher BMI and type 2 diabetes were causally associated with EDS risk, but not in reverse; d) using UK Biobank and 23andMe data we identified 351 loci associated with chronotype and validated there using activity-monitor derived measures of sleep timing. These loci were enriched for genes involved in circadian rhythm and insulin pathways, and those expressed in the retina, hindbrain, hypothalamus and pituitary. Mendelian Randomisation analysis suggested that being a morning person was causally associated with reduced risk of schizophrenia and depression but was not associated with BMI or type 2 diabetes - contrary to prior epidemiological findings.4. Conclusion: These studies offer new insights into the biology of sleep and circadian rhythms and identify causal links to human disease. These data offer new leads to discover new mechanisms of disease and identify novel treatment targets.Acknowledgements UK Biobank and 23andMe participants; co authors

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S09 How does sleepiness impact performances, from normal subjects to patientsPierre Philip, SANPSY, USR 3413-CNRS, France

Sleep is strongly related to cognitive functions and sleep loss and sleep disorders have been associated with an increased risk of human errors. This can be explained by an impact on different cognitive functions, the most sensitive to sleep loss being the simple time reaction. Other functions like memory, divided attention or higher functions (i.e. judgment) are also frequently affected in sleepy subjects. One common biomarker of performance loss is excessive daytime sleepiness (EDS) either measured subjectively (i.e. Epworth sleepiness scale or Karolinska sleepiness scale) or objectively (multiple sleep latency or maintenance of wakefulness test). Epidemiological studies show that up to 25% of the general population report an Epworth sleepiness Score above 11 (a supposedly pathological score), EDS is therefore a public health problem and simple tools have to be validated to quickly differentiate fatigue from sleepiness. A simple subjective biomarker could be a candidate to predict the risk. Excessive daytime sleepiness as quantified by the Epworth Sleepiness Scale has a poor predictive value for accidents mainly because it does not provide linear relationship to this risk. One possible explanation for this is related to the fact that most of the questions of the EES do not explore conditions where the subject has to fight against sleepiness. Several epidemiological studies have shown that Situational instant sleepiness (i.e. sleepiness at the wheel) give a much stronger predictive risk in normal but also in patients with obstructive sleep apnea syndrome.

Interestingly, the relationship between self-perceived sleepiness and performance decrements is not homogeneous between subjects and some physiological determinants (i.e. age) can account for this discrepancy. Sleep loss or sleep disorders impact performance on accidental risk (i.e traffic accidents) differently in different types of subjects. Sleep/wake regulating systems (homeostatic/chronobiological) have been proposed as candidates to explain these

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differences but the results are not convincing. Genotypes are currently explored to identify specific phenotypes explaining resilience to sleep loss.

Another important question is how do the different types of sleep deprivation (acute, chronic) impact perceived sleepiness and performance loss and here again, important differences have been found. This is of importance to quantify the risk of people suffering from insufficient sleep syndrome but also to better predict in patients who is going to be at risk. Experimental sleep deprivation studies have shown (on a limited number of subjects) that the relationship between self-perceived sleepiness and reaction time is very strong during total repetitive sleep deprivation but that relationship disappears during a chronic partial sleep deprivation protocol (i.e. 4 hours of sleep during 14 consecutive nights).

Obstructive sleep apnea is a very common sleep disorder and several studies have linked this disease to accidental risk. Interestingly, a debate exists between the respective roles of AHI versus self-perceived sleepiness to best predict the crash risk. Several studies including meat analysis present conflicting results and more studies need to be conducted to better understand the best predictive biomarker. A recent study on 70000 subjects suspected of obstructive sleep apnea show that AHI alone is a poor predictor of accidental risk with self-reported excessive daytime sleepiness at the wheel and inappropriate line crossings related to EDS predict much more strongly the risk.

Western societies tend to develop work organizations (24/7/7) which strongly challenges sleep hygiene. Healthy subjects face sleep deprivation but interestingly OSAS patients are also exposed to extended work hours (i.e. transport industry). It is therefore crucial for professional drivers to have a robust evaluation of their level of sleepiness during a normal sleep schedule; to prevent any misinterpretation of causal factors in case of sleep related accidents (i.e. sleep deprivation versus untreated pathological AHI). A lack of

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studies in flies, rodents and humans that confirmed SHY’s main predictions, including the recent observation, obtained using serial block face scanning electron microscopy, that most synapses in mouse primary motor and sensory cortices grow after wake and shrink after sleep. I will then present unpublished ultrastructural data obtained in the hippocampus and in the cortex of mouse pups. Finally, I will examine recent studies by other groups showing the causal role of cortical slow waves and hippocampal ripples in sleep-dependent synaptic down-selection, and discuss some of the molecular mechanisms that can mediate this process.Tononi G, Cirelli C (2014) Sleep and the price of plasticity: from synaptic and cellular homeo-stasis to memory consolidation and integration. Neuron 81:12-34.

Acknowledgements:This work was supported by NIH Grants DP 1OD579, 1R01MH091326, 1R01MH099231, and 1P01NS083514.


SA10

Sleep in space

C. Tsai1,2, H. Hasegawa1,3, T. Morris-Paterson4, S. Higgins1,2, A. Keyoumars1,3, D. Green4,5, P. Goadsby6, G.D. Leschziner1,2, S. Harridge4 and I. Rosenzweig1,2

1Sleep and Brain Plasticity Centre, Department of Neuroimaging, King’s College London, London, UK, 2Sleep Disorders Centre, Guy’s Hospital, London, UK, 3Department of Neurosurgery, King’s College Hospital, London, UK, 4Centre of Human and Applied Physiological Sciences, King’s College London, London, UK, 5KBRwyle, European Astronaut Centre, European Space Agency, Cologne, Germany and 6NIHR, Wellcome Trust King’s Clinical Research Facility, London, UK, UK

With rapid scientific development and interest in interplanetary travel in the 20th century, there has been an increasing focus on the effects of spaceflight and micro-gravity on human physiology. Whilst the effects of spaceflight on cardiovascular and respiratory physiology are well recognized, the effect on the brain has not been widely studied. Astronauts have long been reported to experience impairments in sensorimotor function including posture control, spatial orientation, manual tracking, and cerebellar dysfunction.Significantly shortened and disrupted sleep has also been consistently reported in space missions. Sleep serves a restorative function for the brain and cognition and involves dramatic changes to our perception, consciousness, cognition and health. The perpetual activity of the brain is largely supported by a variety of oscil-lations and rhythms it generates. Sleep and sleep stages are also characterized by specific brain oscillations, which, unlike those of wakefulness, are maintained free of external inputs. This means that a transient perturbation during sleep can have a lasting impact. Recent studies on astronauts have shown that weightlessness

this would mean that subjective perception of sleepiness could be challenged as a reliable marker (especially when legal responsibility is involved). Several studies compared objective and subjective excessive daytime sleepiness versus accidental risk. If the objective measures of EDS are very reliable, they do not always predict the accidental risk, mainly because objective sleep subjects can still sustain performances. There are also a limited number of studies which explore the predictive value of MSLT or MWT versus occurrence of traffic accidents. This research will be mandatory in the near future. Because the prevalence of poor sleep hygiene among the general population is potentially increasing, it is important to support epidemiological and physiological studies to better target the at-risk population of subjects susceptible to develop excessive daytime sleepiness.

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induces neurophysiological changes including a cephalic fluid shift which alters cerebrospinal fluid volume, cerebrovascular flow and autoregulation, and intra-cranial pressure. These changes may also induce various neuroplastic changes and significant structural and functional remodeling in the central nervous system including the effect on the oscillations of sleep, positing that spaceflight might be associated with structural, functional and cognitive deficits of, as of yet unclear, longer-term impact. In that background, the results of our recent study that investigated the effects of seven days of supine unloading on a hyper-saline filled water bed (hyper buoyancy floatation), a novel Earth-based novel analogue of microgravity will be discussed. In our study, twelve healthy male subjects (flotonauts), aged (27.2±4.2 years), with no previous neuro/psychiatric history, underwent a multimodal imaging and an overnight in-laboratory polysomnography (PSG/EEG) recordings during seven days of an unloading period. For the duration of the intervention period, the subjects lied supine, followed controlled sleep/wake schedules, they were fed a controlled diet and allowed a maximum of 15 minutes per day off the hyper buoyancy floa-tation bed (for personal hygiene etc). Several significant changes in sleep rhythms were found, with associated changes in neuroanatomy, cognition and neuroelec-trical activity and connectivity. These changes will be presented with particular emphasis on changes in slow oscillations during sleep, which have recently been associated with amyloid load in the brain. The proposed underlying mechanisms will be discussed in some detail.


SA11

Strategic Decision Making and Potential Drug Targets for Obstructive Sleep Apnea Pharmacotherapy

R. Horner

Medicine, and Physiology, University of Toronto, Toronto, ON, Canada

The root cause of some of the most common and serious sleep problems is impaired breathing. Of the sleep-related breathing disorders, obstructive sleep apnea (OSA) is the most prevalent and is associated with significant clinical, social and economic consequences. OSA is ultimately caused by closure of the pharyngeal airspace during sleep due largely to relaxation of the tongue muscles whose activity normally keeps the airspace open. The hypoglossal motoneuron pool is the source of motor output to the tongue, and in theory strategies to modulate its activity may lead to identification, development and testing of new pharmacological treatments for OSA. The first part of this symposium presentation will identify the four principal factors underpinning the pathophysiology of OSA. Two of these factors are strongly influenced by upper airway muscle activity, and as such are amenable to targeted

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manipulation. The presentation will then identify the two major mechanisms operating at the hypoglossal motoneuron pool in rats to modulate tongue muscle activity across natural sleep-wake states. Such studies have identified that there is a functional endogenous noradrenergic drive to the hypoglossal motoneuron pool that activates motor output to the tongue muscle in wakefulness via an α1 receptor mechanism, with this drive being withdrawn in sleep. The presentation will also identify the mechanism of tongue muscle inhibition in REM sleep in rats, this being an acetylcholine mediated G protein-coupled inwardly-rectifying potassium (GIRK) channel mechanism. In addition, modulation of certain K+ channels can reacti-vate tongue muscle activity throughout sleep in rats. Others have manipulated (with success) such mechanisms as potential OSA pharmacotherapies in humans (e.g., trial IDs: NCT02428478, NCT02656160, NCT02908529 at clinicaltrials.gov). The presentation will conclude with the identification and description of a resource of potential drug targets for OSA pharmacotherapy. Some of these targets and their pharmacological agents (e.g., thyrotropin releasing hormone analogs) have been studied in pre-clinical rodent models. Overall, these basic science findings inform current and future studies in humans to identify the potential beneficial effects of pharmacological agents for breathing during sleep and OSA.

The work presented in this symposium presentation was supported by funds from the Canadian Institutes of Health Research (CIHR, Grant MT-15563 awarded to RLH), and the National Sanitarium Association Innovative Research Program (fund number 00144051 awarded to RLH). RLH is supported by a Tier I Canada Research Chair in Sleep and Respiratory Neurobiology (fund number 950-229813).


SA15

Cellular and molecular basis to circadian rhythms in mammals and its relevance to metabolic and neurological disease

M. Hastings

Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK

Circadian rhythms are cycles of metabolism, physiology or behaviour that persist with a period of approximately one day (hence circa- -dian) when organisms are held in temporal isolation. Their persistence is evidence of an internal timing mechanism, a circadian clock. The award of the 2017 Nobel Prize in Physiology or Medicine to Hall, Rosbash and Young provided the climax to a decades-long pursuit to identify the molecular-genetic basis of such clocks, in their case that of the fruit-fly Drosophila. In mammals, as in flies, the circadian mechanism is a transcriptional/ translational negative feedback loop (TTFL). The positive regulators CLOCK and BMAL1 drive expression of Period and Cryptochrome genes, the protein

S12 Intermittent hypoxia and obstructive sleep apnoeaChristopher Turnbull, University of Oxford, UK

Additional authorsDushendree Sen, Oxford Centre for Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.Lennard Lee, Institute of Cancer and Genomic Sciences, University of Birmingham, UK. Nayia Petousi, Nuffield Department of Medicine, University of Oxford, UK.John Stradling,NIHR Biomedical Research Centre Oxford, University of Oxford, UK.

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OSA is associated with hypertension and cardiovascular disease. The underlying causes of cardiovascular disease and hypertension in OSA are not fully understood. Intermittent hypoxia is one of the hallmark features of OSA. However, the role of intermittent hypoxia in daytime elevations in blood pressure in OSA is controversial, with some arguing that arousal mediated sympathetic activation is more important. Animal and human models of intermittent hypoxia lead to elevated blood pressure. However, previous randomised control trials (RCTs) assessing the effects of supplemental oxygen on daytime blood pressure have shown no effect on daytime blood pressure. These previous RCTs have methodological limitations, particularly in including patients with relatively mild OSA, and therefore mild intermittent hypoxia. We present data from an RCT testing the hypothesis that supplemental oxygen, by attenuating intermittent hypoxia, reduces the rise in morning blood pressure seen during continuous positive airway pressure (CPAP) withdrawal. CPAP withdrawal is an experimental model that allows inclusion of patients with much more significant OSA than traditional RCTs, to explore physiological outcomes in OSA. We conducted a single centre, double blind, cross over, randomised control trial assessing the effects of supplemental oxygen versus air, during two weeks of CPAP withdrawal on morning awake blood pressure, with randomised treatment order. The primary outcome was the change in home systolic and diastolic blood pressure from baseline to follow-up, oxygen versus air. Important secondary outcome measures were the change the severity of intermittent hypoxia (oxygen desaturation index or ODI), change in the severity of obstructive events (apnoea hypopnoea index or AHI), and measures of subjective and objective daytime sleepiness. Twenty five patients completed the supplemental oxygen trial. In the oxygen arm there were no significant increases in either systolic or diastolic blood pressure. Supplemental oxygen had a marked effect of attenuating the rise in morning systolic ( 6.6mmHg, p=0.008, 95% CI 11.3 to 1.9) and diastolic ( 4.6mmHg, p=0.006, 7.8 to 1.5) blood pressure during CPAP withdrawal compared to air. Supplemental oxygen markedly attenuated intermittent hypoxia with a median reduction in the ODI of 23.8/h (interquartile range 31.0, 16.3; p<0.001),

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compared to air, following CPAP withdrawal. There was no significant difference, oxygen versus air, in AHI, subjective or objective sleepiness. Supplemental oxygen virtually abolished the rise in morning blood pressure during CPAP withdrawal. Supplemental oxygen substantially reduced intermittent hypoxia, but had a minimal effect on markers of arousal (including AHI), subjective or objective sleepiness. Therefore intermittent hypoxia, and not recurrent arousals, appears to be the dominant cause of daytime increases in BP in OSA.Acknowledgements This work was funded by the Oxford Radcliffe Hospital Charitable Funds and ResMed UK. This research was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). The views expressed are those of the authors and not necessarily of the NHS, the NIHR, or the Department of Health. NP was supported by a NIHR Academic Clinical Lectureship

SA13Sound Asleep: Harmonic cadences in the human sleep cycle Morten Kringelbach, University of Oxford, UK & Milton Mermikides, University of Surrey, UK

A dialogue between neuroscientist Morten L Kringelbach and composer Milton Mermikides about the neuroscience of human sleep, and how this can be used to inform and create musical compositions arising from the cyclical choreography of sleep in health and disease.

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manipulation. The presentation will then identify the two major mechanisms operating at the hypoglossal motoneuron pool in rats to modulate tongue muscle activity across natural sleep-wake states. Such studies have identified that there is a functional endogenous noradrenergic drive to the hypoglossal motoneuron pool that activates motor output to the tongue muscle in wakefulness via an α1 receptor mechanism, with this drive being withdrawn in sleep. The presentation will also identify the mechanism of tongue muscle inhibition in REM sleep in rats, this being an acetylcholine mediated G protein-coupled inwardly-rectifying potassium (GIRK) channel mechanism. In addition, modulation of certain K+ channels can reacti-vate tongue muscle activity throughout sleep in rats. Others have manipulated (with success) such mechanisms as potential OSA pharmacotherapies in humans (e.g., trial IDs: NCT02428478, NCT02656160, NCT02908529 at clinicaltrials.gov). The presentation will conclude with the identification and description of a resource of potential drug targets for OSA pharmacotherapy. Some of these targets and their pharmacological agents (e.g., thyrotropin releasing hormone analogs) have been studied in pre-clinical rodent models. Overall, these basic science findings inform current and future studies in humans to identify the potential beneficial effects of pharmacological agents for breathing during sleep and OSA.

The work presented in this symposium presentation was supported by funds from the Canadian Institutes of Health Research (CIHR, Grant MT-15563 awarded to RLH), and the National Sanitarium Association Innovative Research Program (fund number 00144051 awarded to RLH). RLH is supported by a Tier I Canada Research Chair in Sleep and Respiratory Neurobiology (fund number 950-229813).


SA15

Cellular and molecular basis to circadian rhythms in mammals and its relevance to metabolic and neurological disease

M. Hastings

Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK

Circadian rhythms are cycles of metabolism, physiology or behaviour that persist with a period of approximately one day (hence circa- -dian) when organisms are held in temporal isolation. Their persistence is evidence of an internal timing mechanism, a circadian clock. The award of the 2017 Nobel Prize in Physiology or Medicine to Hall, Rosbash and Young provided the climax to a decades-long pursuit to identify the molecular-genetic basis of such clocks, in their case that of the fruit-fly Drosophila. In mammals, as in flies, the circadian mechanism is a transcriptional/ translational negative feedback loop (TTFL). The positive regulators CLOCK and BMAL1 drive expression of Period and Cryptochrome genes, the protein

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products of which, PER and CRY, subsequently inhibit CLOCK/BMAL1-dependent transcription. Progressive degradation of PER and CRY then releases the negative regulation and a new cycle is initiated approximately 24 h after the previous one. Remarkably, the self-sustaining TTFL mechanism is present in just about every cell-type and major organ system. These local TTFLs drive cell-type-specific circadian programmes of gene expression that are the determinants of the circadian cycles of metabolism, physiology or behaviour that anticipate, and thereby adapt organisms to, the solar cycle of light and darkness.Circadian regulation of cellular functions is therefore pervasive, and ab initio, critical to health. It is regulated in a hierarchical manner, with the principal circadian clock of mammals being the suprachiasmatic nucleus (SCN) of the hypothalamus. The 10,000 or so neurons and astrocytes of the SCN are capable of maintaining circadian cycles of TTFL function and electrical activity indefinitely when isolated in culture. It is a powerful circadian timing circuit that in vivo is entrained to solar time by direct innervation from retinal ganglion cells. In turn, via its innervation of the hypothalamus and brain stem, the SCN directs a complex series of endo-crine, autonomic and behavioural cues that synchronise the innumerable local TTFLs across the body, forging them into a single adaptive temporal programme. This presentation will review recent developments in understanding the cellular and network-level properties of SCN time-keeping, and highlight how the new understanding of the TTFL and the hierarchical organisation of the mammalian circadian timing system will provide a platform for the next challenge to circadian biologists: how to apply circadian knowledge to understand and treat metabolic and neurological disease.

Funded by UK Medical Research Council, award MC_U105170643.


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SA17

REM sleep in blind people

J.A. Christensen1,2, S. Aubin3,4,5, T. Nielsen6, M. Ptito4,5,7, R. Kupers4,8 and P.J. Jennum1

1Danish Center for Sleep Medicine, Rigshospitaet, Glostrup, Glostrup, Denmark, 2Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark, 3Department of Neuroscience, University of Montreal, Montreal, QC, Canada, 4Brain Research and Integrative Neuroscience Laboratory, Danish Center for Sleep Medicine, Rigshospitalet, Glostrup, Denmark, 5Harland Sanders Chair in Visual Science, School of Optometry, University of Montreal, Montreal, QC, Canada, 6Dream and Nightmare Laboratory, Center for Advanced Research in Sleep Medicine, Department of Psychiatry, University of Montreal, Montreal, QC, Canada, 7Laboratory of Neuropsychiatry and Psychiatric Centre Copenhagen, University of Copenhagen, Copenhagen, Denmark and 8Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA

Abstract Body : Study objectives: There is an ongoing controversy regarding the role of rapid eye movements (EMs) during REM sleep. One prevailing hypothesis is that EMs during REM sleep are indicative of the presence of visual imagery in dreams. Congenital blindness appears as a good model to test empirically the validity of this claim since congenitally blind (CB) individuals never developed a visual repertoire. We therefore tested the validity of the scanning of visual dreams hypothesis by measuring EMs in CB individuals, individuals that became blind later in life (LB) and sighted controls (SC) and correlated these with visual dream content.Methods: Eleven blind, of whom 5 were blind from birth (CB; 40.8±16.1 years of age) and 6 that became blind later in life (LB; 47.5±14.7 years of age) and 11 matched sighted control (SC; 43.9±14.8 years of age) subjects participated in this study. The Blindness Duration Index (BDI), calculated as the duration of blindness over age, represents the relative amount of time a subject has been blind, where high scores indicate that they have been blind for the majority of their life, and low scores indicate a recent onset of blindness. All participants underwent full-night polysomnography (PSG) recordings staged manually following American Academy of Sleep Medicine (AASM) scoring criteria. Periods with any kind of EMs were detected automatically by using a validated EM detector, and the EM coverage was measured as the percentage of time containing EMs, during wakefulness, N1, N2, N3 and REM sleep. Frequency of sensory dream elements was measured in dream recall questionnaires over a 30-day period.Results: Both blind groups showed a lower EM coverage during wakefulness, N1, N2 and REM sleep than did controls. CB and LB participants did not differ in EM coverage. Post-validation of the detector applied to blind subjects revealed an overall accuracy of 95.6±3.6%. There were no significant correlations between the incidence of nocturnal EMs and BDI. Analysis of dream reports revealed that CB

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participants reported very few or no visual dream elements, which was significantly lower as compared to both LB and SC participants.Conclusions: We found dissociation between EMs and visual dream content in the two groups of blind participants. The quasi absence of nocturnal EMs in LB individ-uals despite preserved visual dream content does not support the visual scanning of dreams hypothesis. It might be argued that extended blindness in LB has led to an uncoupling of EMs from visual dream content.Eiser AS. Physiology and psychology of dreams. Semin Neurol 2005; 25: 97-105.

Leclair-Visonneau L, Oudiette D, Gaymard B, Leu-Semenescu S, Arnulf I. Do the eyes scan dream images during rapid eye movement sleep? Evidence from the rapid eye movement sleep behaviour disorder model. Brain 2010; 133: 1737-1746.

Iber C, Ancoli-Israel S, Chesson AL, et al. The AASM mannual for the scoring of sleep and associated events: rules, terminology, and technical specification. Westchester, IL: American Academy of Sleep Medicine, 2007.

Christensen JAE, Kempfner L, Leonthin HL, et al. Novel method for evaluation of eye movements in patients with narcolepsy. Sleep Med 2017; 33: 171-180.


SA18

Light, sleep and circadian interactions: Biology to new therapeutic targets

R.G. Foster, A. Jagannath and S. Vasudevan

Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK

By studying how circadian rhythms and sleep are regulated by the dawn/dusk cycle we demonstrated that there exists a “3rd class” of photoreceptor within the eye based upon a small number of photosensitive retinal ganglion cells (pRGCs) that utilise the blue light sensitive photopigment melanopsin (OPN4). Whilst there has been remarkable progress in understanding the complex intracellular mechanisms that generate circadian rhythms, the molecular pathways whereby the pRGCs entrain circadian biology and sleep has remained poorly understood. The suprachiasmatic nuclei (SCN) are the site of the primary circadian pacemakers within the mammalian brain. Until recently, the model for entrainment involved a simple linear pathway whereby glutamate release from the pRGCs resulted in Ca2+ influx and raised intracellular cAMP in SCN neurones, which in turn resulted in CREB phosphorylation leading to increased transcription of two key clock genes, Per1 and Per2. This signal then advanced or delayed the molecular clockwork. However, an important feature of entrainment is that circadian responses to light are limited – as typified by jet-lag. Full recovery from jet-lag requires a day for every time-zone crossed. We addressed this issue and have identified and characterized a key role for Salt Inducible Kinase 1 (SIK1) and the CREB-regulated transcription co-activator 1 (CRTC1) in clock re-setting. However, our more recent and unpublished

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findings have shown that light entrainment also involves the parallel activation of a Ca2+-ERK1/2-AP-1 signalling pathway. Thus both CRE and AP-1 regulatory elements drive light-induced clock gene expression. In addition, whilst light activation of the Ca2+-ERK1/2-AP-1 signalling pathway increases Per1 and Per2 expression, sleep/wake behaviour alters the effects of light on the clock. Our proposed mech-anism suggests that adenosine acts as a signalling molecule that encodes wake duration. Adenosine acts via inhibitory A1 receptors on the SCN to inhibit the Ca2+-ERK1/2-AP-1 signalling pathway, which in turn, reduces the expression of Per1 and Per2. Thus sleep/wake history, encoded by adenosine, reduces the phase shifting effects of light upon the circadian system, altering sleep/wake timing. These new pathway will be presented and placed into an ecological context. Furthermore, we will explore the possibility of how such signalling mechanisms provide a poten-tially new target for the regulation of circadian rhythms and the “pharmacological” replacement of light for sleep/wake re-setting in individuals lacking eyes or other individuals with severe circadian rhythm disruption.


S19 Metabolic profiling of sleep deprivation and circadian misalignmentDebra J. Skene, University of Surrey, UK

Sleep restriction and circadian clock disruption are associated with metabolic disorders including obesity and diabetes. Metabolomics (metabolic profiling) offers the potential to identify metabolic phenotypes associated with sleep restriction and circadian misalignment. Using a variety of sleep and circadian protocols, plasma metabolite rhythms have been characterised in humans using targeted and untargeted liquid chromatography–mass spectrometry (LC/MS) metabolomics. Time of day and circadian variation in the metabolome as well as the effect of total sleep deprivation has been assessed1,2. In addition, the effect of simulated shift work on circulating metabolite rhythms has recently been studied3.

In entrained conditions, clear daily 24 h rhythms were observed in approximately 60% of the quantified metabolites, most (>70%) maintaining their rhythmicity during the subsequent 24 h of wakefulness1. Simulated night shift produced a ~12-h phase shift of most of the rhythmic metabolites compared to day shift conditions,

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the metabolite rhythms aligning with the behavioural timing of the prior 3-day simulated shift schedule.

Circulating metabolite rhythms depend on time of day, feeding/fasting state, the circadian timing system and the sleep/wake state. Using metabolomics to identify metabolites that are driven by the circadian timing system as well as those that are driven by behavioural cycles (sleep/wake, feeding/fasting, light/dark) will help to determine the underlying mechanisms linking circadian misalignment, sleep restriction and metabolic disorders.

References1Davies, S.K., Ang, J.E., Revell, V.L., Holmes, B., Mann, A., Robertson, F.P., Cui, N., Middleton, B., Ackermann, K., Kayser, M., Thumser, A.E., Raynaud, F.I. and Skene, D.J. Effect of sleep deprivation on the human metabolome. Proc. Natl. Acad. Sci. USA (2014) 111, 10761-10766.2Isherwood C.M., Van der Veen D.R., Johnston J.D. and Skene D.J. 24 hour rhythmicity of circulating metabolites: effect of body mass and type 2 diabetes. FASEB J. (2017) 31, 5557-5567.3Skene D.J., Skornyakov E., Chowdhury N.R., Gajula R.P., Middleton B., Satterfield B.C., Porter K., Van Dongen H.P.A. and Gaddameedhi, S. Separation of circadian- and behavior-driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism. Proc. Natl. Acad. Sci. USA (2018) 115, 7825-7830.

Acknowledgements UK BBSRC Grant BB/I019405/1European Union FP7-HEALTH-2011 EuRhythDia Grant 27839

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Interrelationship between sleep stability and glymphatic function

N.L. Hauglund

Center for Translational Neuromidicine, University of Copenhagen, Copenhagen N, Denmark

It was recently discovered that waste products, such as amyloid-b, are cleared from the brain by cerebrospinal fluid via what was named the glymphatic system, and that this cleaning of the brain is only active during sleep [1], [2]. Neurodegenerative diseases, such as Alzheimer’s disease, are often comorbid with sleep disturbances [3], and impaired glymphatic clearance has been proposed as a possible risk factor of amyloid build-up [1]. Therefore, a better understanding of the link between the glymphatic system and sleep could have important implications for treatment of diseases that share this common link. In this study, we explored the possibility that glymphatic flux might not only be controlled by sleep, but in itself participate in stabilization of the sleep state.To test this, sleep was measured in mouse models of impaired glymphatic flux previously used in our laboratory, namely aquaporin 4 knockout mice (AQP4 KO), mice subjected to cisterna magna puncture (CM puncture, performed under anes-thesia with a mixture of ketamine (100 mg/kg) and xylazine (10 mg/kg) intraper-itoneally (i.p.)), and mice subjected to acetazolamide treatment (20 mg/kg i.p. every 6 hour for a total of 4 injections) [4]. To investigate whether glymphatic impairment leads to decreased sleep stability, sleep was monitored using EEG and EMG electrodes that had been implanted under isoflurane anesthesia and i.p. injections of carprofen (5 mg/kg) and buprenorphine (0,05 mg/kg) 2 weeks prior to recording. Furthermore, sleep characteristics of a second group of mice were monitored non-invasively using immobility-defined sleep analysis.Non-invasive sleep analysis and EEG did not show any overall differences in sleep pattern between mice treated with saline, acetazolamide, CM puncture or sham surgery (figure 1A-C). However, AQP4 KO mice were found to have shorter nREM bouts than all other groups, and shorter REM bouts compared to saline-treated mice. Spectral analysis of nREM sleep during the first 4 hours of the light period after glymphatic manipulations did not show any differences between mice treated with acetazolamide, saline or sham surgery (figure 1D). However, AQP4 KO mice displayed a right shift in delta power with significantly higher power in the high end of the delta spectrum. Furthermore, mice subjected to CM puncture displayed increased power in the low delta frequencies.Our study did not show a causative relationship between glymphatic flux and sleep stability. However, it does not rule out that water transport through AQP4 water channels could have implications for sleep, as AQP4 KO mice were found to have fewer bouts of nREM sleep and REM sleep, and displayed a right shift in nREM delta frequency. In conclusion, this study supports a model where sleep drives

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glymphatic clearance, but glymphatic flux does not have a direct and acute effect and sleep stability or sleep quality (figure 1E).

Figure 1. EEG analysis of sleep in control mice (saline injections or sham surgery) and mice with impaired glymphatic function (acetazolamide injections (20 mg/kg), CM puncture, AQP4 KO). (A) average duration/hour of wake, nREM, and REM sleep. (B) average number of bouts/hour for each state. (C) average bout length for each state. Two-way Anova and Tukey’s test, n=5. (D) normalized power spectrum of nREM sleep during the first 4 hours of the light period following glymphatic manipulations. Two-way Anova and Dunnet’s test, n=4-5. (E) these results indicate that there is a one-way relationship between sleep and glymphatic flux, as sleep drives glymphatic clearance but impaired glymphatic flux does not acutely decrease sleep stability. Error bars are mean +/- SEM. Significance is shown as * = p<0.05, ** = p<0.01 and *** = p<0.001. CM = cisterna magna, AQP4 = aquaporin-4, KO = knockout, ns = not significant.

J. J. Iliff, M. Wang, Y. Liao, B. A. Plogg, W. Peng, G. A. Gundersen, H. Benveniste, G. E. Vates, R. Deane, S. A. Goldman, E. A. Nagelhus, and M. Nedergaard, “A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid β.,” Sci. Transl. Med., vol. 4, no. 147, pp. 1–11, 2012.

L. Xie, H. Kang, Q. Xu, M. J. Chen, Y. Liao, M. Thiyagarajan, J. O. Donnell, D. J. Christensen, C. Nicholson, J. J. Iliff, T. Takano, R. Deane, and M. Nedergaard, “Sleep Drives Metabolite Clearance from the Adult Brain,” Science (80-.)., vol. 342, pp. 373–377, 2013

A. P. Spira, A. a. Gamaldo, Y. An, M. N. Wu, E. M. Simonsick, M. Bilgel, Y. Zhou, D. F. Wong, L. Ferrucci, and S. M. Resnick, “Self-reported Sleep and β-Amyloid Deposition in Community-Dwelling Older Adults,” JAMA Neurol., vol. 70, no. 12, pp. 1537–1543, 2013.

I. Lundgaard, M. L. Lu, E. Yang, W. Peng, H. Mestre, E. Hitomi, R. Deane, and M. Nedergaard, “Glymphatic clearance controls state-dependent changes in brain lactate concentration,” J. Cereb. Blood Flow Metab., vol. 0, no. 00, pp. 1–13, 2016.


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Improving Student Sleep Quality and Quantity to Improve Higher Educational Experience

C. Qiu1,2, Y. Yu2, A. Cheema2, C. James-Harvey3 and M.J. Morrell2

1Isle of Wight NHS Trust, Newport, UK, 2Imperial College London, London, UK and 3University of Oxford, Oxford, UK

Background: Poor sleep hygiene negatively impacts cognitive and physical abilities in students (Mah et al., 2018) and is common among students of higher education (Curcio et al., 2006). Moreover, a wide-range of literature explores the detrimental effect of poor sleep quality on learning.Methods: An anonymous, voluntary and self-administered questionnaire was made available to a cohort of medical students at Imperial College London (n = 113; 60 female). Demographic information was collected to determine existing sleep quality. Questions regarding understanding of, and desire for sleep hygiene interventions to improve their experience of medical education were created on a 5-point Likert scale, ranging from 5 (strongly agree) to 1 (strongly disagree). Students were also asked to rank, the aspects in their lifestyle that warranted the most attention for improvement.Results: Students from across all years strongly agreed that their sleeping habits could be improved (Mean [SD]: 4.13±0.86). Quantitative analysis revealed that there was strong consensus about the need to sleep better with sleep ranking top out of the six suggested categories for improvement. Equipping students with the time and energy management tools needed to maintain consistent sleep of adequate duration would be well received (3.73±0.97). Students understand the beneficial relationship between sleep with learning, and agree that a concerted intervention effort, such as having sleep promotion activities across campus would be beneficial for their education (3.65±0.90).A low quality of sleep negatively impacts activities in the morning (linear model, p=0.0006, overall adjusted r2=0.17) and in the afternoon (p=0.02), but not in the evening (p=0.06): more precisely, subjects reported to be more tired in the morning (1.03±0.97; 0=always tired, 3=never tired) than in the afternoon (1.52±0.83; Wilcoxon rank test, W=4011, p=0.0002). This study identified the main factors influencing sleep quality as the latency to fall asleep (p=0.00001), sleep duration (p=0.002) and frequency of dreams (p=0.03), together accounting for 29.0% (r2) of the variation in sleep quality using a linear model (p<0.0000001). The presence of a bed partner, pain, temperature, breathing problems and waking up at night did not significantly influence sleep quality (generalised linear model, p>0.05 for all variables).Summary: Students understand the importance of sleep and would be receptive of initiatives to improve sleep quality. Efforts in improving sleep quality should be directed in providing the resources to decrease the latency to sleep onset (Bartel et al., 2018) and to deep sleep to prevent dreams and increase sleep duration via

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naps (Hayashi, Motoyoshi & Hori, 2005). This may further improve the tangible results of the ever-increasing drive and innovation occurring in the higher educa-tion landscape.Bartel, K., Huang, C., Maddock, B., Williamson, P. & Gradisar, M. (2018) Brief school based interventions to assist adolescents’ sleep onset latency. Journal of Sleep Research. 27 (3), e12668.

Curcio G, Ferrara M, De Gennaro L. 2006. Sleep loss, learning capacity and academic perfor-mance. Sleep Medicine Reviews. 10(5):323-337.

Hayashi, M., Motoyoshi, N. & Hori, T. (2005) Recuperative power of a short daytime nap with or without stage 2 sleep. Sleep. 28 (7), 829-836.

Mah, C. D., Kezirian, E. J., Marcello, B. M. & Dement, W. C. (2018) Poor sleep quality and insufficient sleep of a collegiate student athlete population. Sleep Health. 4 (3), 251-257.


C03

Sleep-wake regulation in mice: insights from a synaptobrevin-2 mutant line and computational modelling

M. Guillaumin1, P. Achermann2, P. Nolan4, S. Peirson1 and V. Vyazovskiy3

1Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK, 2Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland, 3Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK and 4MRC Harwell Institute, Harwell, UK

The alternation between waking and sleep is regulated by the internal circadian clock and sleep-wake history, and is also influenced by the external environment. Although our understanding of the circadian aspect of sleep regulation has increased, the mechanisms underlying sleep homeostasis are still largely unknown. Independent of the circadian clock, only a limited number of genes have been asso-ciated with specific sleep-wake properties. Forward genetics provides an unbiased approach, which seeks to identify genes involved in specific biological processes1. This project has focused on the Sleepy6 mouse line, obtained via a forward genetics sleep screen, with a mutation in synaptobrevin 2, giving rise to decreased sleep duration. We aimed to further characterise the sleep phenotype of this line, at a molecular and behavioural level, to gain novel insights into the regulation of sleep.Using molecular techniques (high-performance liquid chromatography, quanti-tative PCR) to evaluate neurotransmitter levels and gene expression, we found no significant difference in the neurotransmitter pathways investigated (n(wild-type-WT)= 8, n(mutant)=10, measured compounds and levels of expres-sion of genes involved in serotonergic and dopaminergic pathways, mixed-design ANOVA followed by t-tests, p-values all > 0.05). Behavioural assays highlighted hyper-activity, with a mild learning impairment (n(WT)=28, n(mutant)=21, mixed-design

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ANOVA revealed a significant main effect of genotype: F(1,45)=8.93, p=0.005). Electrophysiology recordings revealed striking differences at global (electroen-cephalography - EEG) and neuronal levels, with Sleepy6 homozygous mice showing a decreased ability to switch between vigilance states, and notable alterations in neuronal firing patterns during slow-wave sleep (surgeries were performed under isoflurane anaesthesia, inhalation, 1.5-2.5%; n(WT)=5, n(mutant)=5, mixed- design ANOVA, p-values ranging from 0.001 to 0.041 when analysing time spent in vigilance states and episode durations). Finally, the successful adaption of an elaborated version of the “two-process” model2 of sleep regulation furthered our understanding of sleep/wake control in both wild-types and Sleepy6 homozygotes (n(WT)=5, n(mutant)=5, non-parametric Mann-Whitney tests, p<0.01 for the rate of decrease (WT: 60±8 *10-5 (4s)-1; mutant: 23±3 *10-5 (4s)-1, mean±SEM) and upper asymptote (WT: 447±33 %; mutant: 172±15 %, mean±SEM) of the simulated homeostatic process in the frontal EEG derivation). This combination of in vivo and computational work provides new insights into the mechanisms that underlie the homeostatic regulation of sleep, and more particularly, the alternation between vigilance states. It furthers our comprehension of a putative “sleep-switch”, which allows animals to transfer between sleep and wakefulness in a biologically relevant manner.Acevedo-Arozena A et al. (2008) Annu. Rev. Genomics Hum. Genet. 9, 49-69.

Achermann P et al. (1993) Brain Res. Bull. 31, 97-113.


C04

Heart rate dynamics during NREM sleep in rats under cold environment

O. Shylo, V. Lomako and G. Babiychuk

Cryophysiology, Institute for Problems of Cryobiology and Cryomedicine of the National Academy of Sciences of Ukraine, Kharkiv, Ukraine, Kharkiv, Ukraine

Autonomic activation caused by contact to low temperature environment may increase the number of activation phenomena on sleep EEG, sleep fragmentation and sleep onset latency, as well as depress sleep at all.It should be note that the episodes of autonomic activation are clearly seen in NREMS even at thermoneutral zone and characterized by the pseudo-rhythmic appearance of arousal phenomena in EEG. To what extend the cold influences the vegetative background of such phenomena is still poorly understood. The research aimed to study the long-term heart rate (HR) variations as a marker of autonomic activity changes in NREM after periodic cold exposures in rats.The experiments were performed in 7-8-month male white breedless rats males (m=250-300 g, n=14). Heart rate (HR) and EEG were recorded and processed using a Poly-Spectrum-8 ECG system and Neuron-Spectrum-2 EEG system (Neurosoft).

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Under general anaesthesia (i/p, thiopental sodium–oxybutyrate sodium mixture, 30 and 100 mg/kg) 4 electrodes for HR registration were secured under the skin in the paws’ areas, tunnelled subcutaneously, fixed to the skull (together with 2 EEG electrodes) by dental acrylic and connected to the registration systems via electric swivel (Moog). Animals were exposed to cold over two days to +10°C or -12°C in the light period for 15 min hourly, for a total of nine exposures per day. Sleep stages were scored following the standard criteria on 4-second epochs. Continuous (45 min) HR registration after every cold exposure was performed. To minimize a transition effect, after each cold exposure the corresponding 46 s’ interval during NREMS toward the end of the registration period were chosen for the analysis. Artefact-free, visually corrected R-R intervals data were imported into Kubios 2.2 software (Kubios Oy). Data were means±SD, compared by ANOVA.Every cold exposure awaked the animals and different time was needed for them to enter sleep and achieve the stable HR level in NERMS again. However, RR temporary dynamics in NREMS consisted of rather stable episodes (40-200 s) interrupted by short (10-20 s) activation-deactivation periods. The mean distance between acceleration-deceleration episodes in control NREMS was 86.78±35.47, n=6, but decreased in NREMS both after +10°C (37.69±21.88, n=9, p=0.0001) and -12°C (77.37±38.16 s, n=6, p=0.0003). The mean HR increased significantly during NREMS after -12°C (from 336.3±9.7 at control to 352.3±29.2, n=6, p=0.05) and had a positive tendency after +10°C (347.2±27.5 ms, n=9, p=0.07). According to LF/HF ratio calculations the slight shift in sympatho-vagal balance was shown from 0.40± 0.19, n=6, at control, to 0.55± 0.36, n=6, p=0.06 and 0.53± 0.24, n=9, p=0.02, after -12°C and +10°C, correspondently. Thus, the studied periodic cold effects slightly change the sympatho-vagal balance and probably influence brain arousability as well as recuperative value of sleep.


C05

How is valence encoded during sleep?

A.T. French, Q. Geissmann, E. Beckwith and G.F. Gilestro

South kensington campus, Imperial college london, Wandsworth, UK

Sleep, with a few exceptions, is characterised by a state of immobility and reduced awareness of the surrounding environment. While sleep is a fundamental process, it has drawbacks in that a sleeping individual is less likely to detect cues signal-ling danger, food or mating opportunities which has a direct impact on fitness. While increased arousal thresholds are typical during sleep, some stimuli are more arousing than others. This begs the question: how do certain sensory pathways remain sensitised during sleep and differentially interact with sleep centres?

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Here we present a new paradigm in order to study arousal in Drosophila (Geissmann et al., 2017). Acetic acid, which is produced by fermenting fruits, was delivered to sleeping flies. Our results show that different concentrations, which signal ripe to rotten fruit, and activate different subsets of olfactory neurons differ in their ability to wake sleeping flies (Semmelhack and Wang 2012). The most arousing concentrations were those with appetitive connotations and were not the most intense. Further we show that valence is an attribute that is highly plastic: both experience and internal state (changes in satiety, sleep pressure and intoxi-cation) can shift arousal thresholds.The mechanisms through which our sensory systems encode valence during sleep remain elusive and the subject represents an exciting yet understudied field.

Geissmann Q, Garcia Rodriguez L, Beckwith EJ, French AS, Jamasb AR, Gilestro GF (2017) “Ethoscopes: An open platform for high-throughput ethomics” PLoS Biology, https://doi.org/10.1371/journal.pbio.2003026

Semmelhack JL and Wang JW (2009) “Select Drosophila glomeruli mediate innate olfactory attraction and aversion”, Nature, 14;459(7244):218-23. doi: 10.1038/nature07983

Quentin Geissmann, Esteban Beckwith and Giorgio Gilestro all contributed to this project.


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C06

“Flying on Empty” – The Effects of Sleep Loss on Mood and Task-Specific Competencies in Commercial Airline Pilots

A. O’Hagan1, J. Issartel1, A. Wall1, F. Dunne2, P. Boylan3, M. Herring4, M. Campbell4 and G. Warrington4

1School of Health & Human Performance, Dublin City University, Dublin, Ireland, 2School of Physics, Trinity College Dublin, Dublin, Ireland, 3School of Nursing & Human Sciences, Dublin City University, Dublin, Ireland and 4Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland

Introduction: Current commercial airline flight operations work on a pressurised 24/7 timetable due to the unrelenting escalation in international long-haul, short-haul, regional and overnight flights. As a result, commercial airline pilots are highly suspectible to sleep loss and fatigue. Loss of sleep is proposed to be a key cause of pilot error and could pose a serious threat to flight safety (Caldwell et al., 2009). Therefore, this study examined the effects of 24 hours’ sleep loss on mood, pilot-specific competencies and flying performance.Methods: Seven short-haul commercial airline pilots completed the Samn-Perelli Crew Status Check, Profile of Mood States, Psychomotor Vigilance Task, Dual-N-Back, NASA Task Load Index and aviation-specific mathematical calculations. Participants also flew a 32-minute flight profile on a computerised flight simulator during which they were required to answer mid-flight fuel calculations and situa-tional awareness questions. Testing occurred at 3 hour intervals during the final 12 hours of a 24 hour period of continuous wakefulness.Results: One-way repeated measures ANOVA found that feelings of fatigue decreased (F(6, 36)=6.585, p<.001) whilst total mood disturbance increased (†F(1.756, 10.539)=8.734, p<.01) with increasing time awake. Furthermore, sustained attention (†F(1.193, 7.157)=6.491, p<.05), speed and accuracy of problem solving (F(6, 36)=5.897, p<.001; χ2(6)=20.463, p<.01), multi-tasking ability (†F(2.509, 15.055)=3.486, p<.05), perceived workload (F(4, 24)=2.740, p<.05), speed of mid-flight fuel calculations (F(4, 24)=8.561, p<.001) and situa-tional awareness (F(4, 24)=2.923, p<.05) were all significantly impaired following 24 hours continuous wakefulness. Significant reductions in performance were observed on nearly all tests following 20 hours continuous wakefulness. Flying performance was not significantly impacted.Conclusion: Commercial airline pilots’ mood and pilot specific competencies were significantly impaired following 24 hours’ sleep loss with some impairments becoming evident following 12 hours continuous wakefulness. Whilst most partic-ipants were able to maintain flying precision during the period of wakefulness, it appears they are doing so by overcoming large increases in sleep loss and fatigue which considerably degrades cognitive performance. Alas, the number of serious accidents as a result of operator error in various industries due to sleep loss and

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fatigue is large and appears to be increasing (Lopez et al., 2012) thus warranting further investigation into this area.Caldwell, J. A., Mallis, M. M., Caldwell, J. L., Paul, M. A., Miller, J. C., & Neri, D. F. (2009). Fatigue Countermeasures in Aviation. Aviation Space & Environmental Medicine, 80(1), 29–59.

Lopez, N., Previc, F. H., Fischer, J., Heitz, R. P., & Engle, R. W. (2012). Effects of sleep depriva-tion on cognitive performance by United States Air Force pilots. Journal of Applied Research in Memory and Cognition, 1, 27–33.

The authors would like to sincerely thank those who were involved in and participated in this study. This research was funded by the Irish Research Council.


C07

Circadian control of paraventricular hypothalamic activity by suprachiasmatic VIP neurons

S. Paul, L. Walmsley, C. Harding and T. Brown

Faculty of Medicine, Biology & Health, University of Manchester, Manchester, UK

The co-ordination of our internal physiological rhythms with external time relies on the suprachiasmatic nucleus (SCN) of the hypothalamus. This entrainment with the environment allows organisms to optimise their physiology according to the predict-able changes that occur across the 24 hour day. While it is known that the SCN is necessary for this process, the precise nature of the timing signals supplied by the SCN remains unclear. One hypothesis is that the heterogeneity within this small nucleus may allow for the co-ordination of whole body physiology, with subsets of SCN neurons possessing unique circadian profiles that direct specific physiological processes.We tested this hypothesis using optogenetic manipulations of vasoactive intestinal polypeptide (VIP) neurons in the mouse SCN using selective channel rhodopsin-driven manipulation of VIP cells in the mouse SCN while monitoring hypothalamic network activity. Acute ex vivo brain slices were obtained following cervical dislocation, and continuously perfused with aCSF. Recordings were made on both multielectrode arrays, and with penetrating Buszaki-style octodes. These approaches allowed us identify SCN VIP cells, characterise their daily electrophysiological output profiles and also determine how the spike output from these cells influenced neuronal activity in known SCN target regions such as the sub paraventricular zone (SPZ), the paraventricular nucleus of the hypothalamus (PVN), and the ventral thalamus.We identify a subset of cells (~10% of total; n=60) across these SCN target regions that respond to VIP cell activation with robust inhibitions (VIPin+ cells; 50-200ms). Pharmacological challenge reveals that this involves a GABAergic mechanism, since responses are eliminated by application of bicuculline. VIPin+ cells can be found throughout the SPZ, PVN and ventral thalamus. The majority of VIPin+ cells (~80%)

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show evidence of circadian modulation of firing activity and, collectively, VIPin+ cell activity is lowest during the mid-late afternoon to early night (ZT 5-12). This relative absence of firing corresponds to peak firing phase for SCN VIP cells (~ZT6). Taken together, results from our electrophysiological studies therefore suggest that SCN VIP cells drive rhythmic activity in a subset of responsive downstream neurons in the SPZ, PVN and ventral thalamus. These VIPin+ cells are located in output areas crucial for the control of physiological rhythms, such as the daily rise in corticosterone. These data therefore establish a route by which electrophysio-logical output from a defined population of SCN neurons could influence a range of downstream physiological rhythms.

This work was funded by the BBSRC


C08

Age, Alzheimers, circadian rhythms and sleep in Drosophila

E. Buhl, J. Curran, J. Higham and J. Hodge

Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, UK

All organisms on earth are subject to predictable daily environmental changes caused by the earth’s rotation, therefore they have evolved circadian clocks that regulate changes in behaviour, i.e. activity and sleep, as well as in physiology and metabolism to ensure they occur at certain times allowing adaption to the envi-ronment. All studied animals, from jellyfish to humans, show some form of sleep and while it is still not resolved why we sleep, it is essential for life since sleep deprivation is detrimental to health and shortens lifespan. We use Drosophila to study this fundamental behaviour because flies offer numerous advantages for investigating sleep and the clock, not least the strong history of circadian research in the model organism, genetic tractability, short lifespan, rapid generation time as well as clearly defined and manipulatable neural circuits.Capitalising on fly genetics we are using both behavioural tests of circadian and sleep activity and electrophysiological recordings from the wake-promoting, pigment dispersing factor (PDF)-positive, large lateral ventral neurons (l-LNV). As in humans where it is well established that elderly individuals have increasing difficulties sleeping at night and have an increase in daytime sleep episodes, we show that sleep in aged flies is increased at day but not at night with significantly increasing sleep duration whilst reducing sleep latency. We demonstrate that the age-dependent decline in circadian output is combined with changes in the daily activity of Drosophila, namely a reduction in morning and evening anticipatory behaviour. Furthermore, the arousal specific l-LNVs change their electrical properties with age with a significant decrease in input resistance but no significant changes in spontaneous electrical activity or membrane potential. We also demonstrate a

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reduction in the daily plasticity of the synaptic architecture of the s-LNv neurons, likely to underlie the reduction in circadian rhythmicity during ageing.Alzheimer’s Disease (AD) is the most common cause of dementia, and is associated with sleep and circadian rhythm defects. We show that driving expression of human 4R0N tau – that is associated with AD pathology – in the Drosophila clock gives rise to a phenotype which closely matches the behaviour seen in human AD patients. Tauopathic flies exhibited greater locomotor activity throughout the day and night and displayed a night-time-specific loss of sleep. Under constant darkness, the loco-motor behaviour of tau-expressing flies was less rhythmic than controls indicating a defect in circadian rhythm. Current clamp recordings from l-LNVs revealed elevated spontaneous firing which likely underlies the observed phenotype.These results provide further insights into the effect of ageing and AD on circa-dian biology, demonstrating changes in electrical activity in conjunction with the decline in behavioural outputs.


C09

Do women experience more sleep deprivation when the clocks go forward, compared to men?

A. Macey-Dare1, S. Bangi1, W. Jackson1, C. Qiu4,1, Y. Alqurashi2, J. Benson2,3, J. Kelly2,3, C. James-Harvey5 and M.J. Morrell1,2,3

1Clinical Research and Innovation Theme, Imperial College London, London, UK, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, UK, 3National Institute for Health Research Respiratory Disease Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust and Imperial College London, London, UK, 4St Mary’s Hospital, Isle of Wight NHS Trust, Newport, UK and 5Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK

Background: The impact of, and necessity for the Daylight Saving Time (DST) tran-sition is a debated topic due to the effect of a ‘shifted sleep state’ on the general population. Studies show a significant increase in fatal road traffic collisions1 and heart attacks2 the following day. Females tend to be more affected by shifted sleep states, exhibiting a greater impairment in key cognitive skills such as atten-tion span and working memory3. Chronotype i.e. the behavioural manifestation of underlying circadian rhythms, varies between sexes and also influences the effects of a shifted sleep state.4

Aims: 1. To explore the initial impact of the DST transition on the different sexes, 2. To explore the differences in adjustment to the DST transition from the Sunday-to-Monday between the different sexes and 3. To establish if variation in chronotype confounded our findings.

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Methods: Questionnaire data was collected in 4 sessions over 2 days (Sunday and Monday) following DST transition, March 2018. We questioned 528 (265 females, 27 excluded) participants (157 on Sunday, 371 on Monday) out of a total estimated daily footfall of 10,500 people on Exhibition Road. Self-designed, piloted question-naires determined: a) if they felt sleepy (yes or no) and their self-identified chrono-type (whether people identified as ‘morning larks’ or ‘evening owls’), b) in-depth analysis of sleeping habits such as bedtime, wake time and, daytime sleepiness scored on the Karolinska Sleepiness Scale.Results: A significantly greater proportion of females were sleepy on Sunday as shown in Figure 1 (p=0.015). There was no significant difference in proportion of sleepy males and females on Monday. However, females slept significantly earlier (p=0.011) and significantly longer (p=0.023) than males on Sunday night. The proportion of sleepiness amongst ‘evening owls’ was significantly higher than other chronotypes, but there was no significant variation in chronotype propor-tions between the sexes.Conclusions: Our results suggest that initial impact of the loss of sleep from the DST transition is greater on females. However, our data is insufficient to draw conclusions on how males and females adjusted over the Sunday-to-Monday period immediately following the transition. Variation in chronotype did not confound our study findings. To validate our findings, the study must be repeated, with a refined questionnaire to gather data about potential confounding factors (e.g. age, children in the family, sleep related disorders). These results could potentially be used to generate specific public health guidelines, inform further research, and raise awareness about potential adverse effects of DST transition.

A bar graph showing the proportion of males and females, out of a total of 83 people, who responded ‘yes’ to the question ‘Are you feeling sleepy today?’ on Sunday. Significance was assessed using a z-test for comparing two proportions. There was a significantly higher proportion of sleepy females on Sunday compared to sleepy males (p=0.015).

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Carey R, Sarma K. Impact of daylight saving time on road traffic collision risk: a systematic review. BMJ Open. 2017;7(6):e014319.

Janszky I, Ljung R. Shifts to and from Daylight Saving Time and Incidence of Myocardial Infarction. New England Journal of Medicine. 2008;359(18):1966-1968.

Santhi N, Lazar A, McCabe P, Lo J, Groeger J, Dijk D. Sex differences in the circadian regulation of sleep and waking cognition in humans. Proceedings of the National Academy of Sciences. 2016;113(19):E2730-E2739.

Fischer D, Lombardi D, Marucci-Wellman H, Roenneberg T. Chronotypes in the US – Influence of age and sex. PLOS ONE. 2017;12(6):e0178782.

Thank you to fellow Sleep CRI project members for assistance with data collection, colleagues at the University of Oxford including Karim Farahat, The Physiological Society and all study participants.


C10

Effects of selective silencing of layer 5 pyramidal neurons on sleep-wake regulation and cortical network dynamics

L. Krone1,2, T. Yamagata2, A. Hoerder-Suabedissen1, Z. Molnár1 and V. Vyazovskiy1,2

1Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK and 2Sleep and Circadian Neuroscience Institute, University of Oxford, Oxford, UK

Sleep and wakefulness are controlled by neuronal clusters in brainstem, hypo-thalamus, and basal forebrain in the mammalian brain (1). Although local cortical regulation of sleep depth and sleep slow waves has been shown (2,3), it remains unclear whether cortex contributes to global sleep-wake regulation. Cortical layer 5 pyramidal neurons are a key population in the generation and propagation of cortical slow oscillations (4,5). Slow waves are an electroencephalographic (EEG) hallmark of non-rapid eye movement (NREM) sleep and their spectral power (slow wave activity, SWA, 0.5 – 4 Hz) is a precise marker of sleep pressure. In this study, we probe the role of layer 5 pyramidal neurons in sleep-wake regulation and cortical network dynamics in mice.We performed EEG and 16-channel laminar cortical recordings in a transgenic mouse model, in which a subpopulation (~15-30 %) of pyramidal cells in layer 5 is functionally silenced by removal of the t-SNARE protein SNAP25 (Rbp4-Cre;Ai14;Snap25fl/fl). Male adult mice (10-17 weeks, 5 homozygous, 4 Cre-negative controls) were single-housed on a 12h/12 h light/dark cycle (light onset at 9 am). Sleep deprivation (SD) was performed on one day by exposure to novel objects for 6 hours starting at light onset.In undisturbed 24-hour recordings, layer 5 silenced animals presented anincreased total amount of wakefulness (13.28 hrs, SEM 0.55 hrs) compared to controls (10.52 hrs, SEM 0.36 hrs). In addition, the maximum duration of individual wake

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episodes was longer in layer 5 silenced animals (282.1 min, SEM 84.0 min) compared to controls (89.6 min, SEM 17.5 min). Following six hours of sleep deprivation, the increase of slow wave activity during NREM sleep relative to baseline was diminished in layer 5 silenced animals (134.9%, SEM: 5.7%) compared to controls (190.1%, SEM: 6.9%). The laminar profile of cortical activity revealed recurrent spike-wave patterns in transgenic animals, which did not occur in controls.Our preliminary results indicate altered sleep-wake regulation in transgenic mice with a silenced subpopulation of layer 5 pyramidal neurons. Layer 5 silenced mice exhibit extended wakefulness, a greater capacity to stay awake, and a diminished homeostatic response to sleep deprivation. Furthermore, the fine orchestration of cortical activity appears disturbed. We tentatively interpret this data as first evidence that layer 5 pyramidal neurons contribute to the global regulation of sleep and wakefulness. This specific cortical cell population might represent a core element in a homeostatic circuit, which tracks the cortical need for sleep and translates it into a sleep signal.Saper CB, Fuller PM. Wake–sleep circuitry: an overview. Curr Opin Neurobiol. 2017 Jun;44:186–92.

Vyazovskiy V V., Borbély AA, Tobler I. Unilateral vibrissae stimulation during waking induces interhemispheric EEG asymmetry during subsequent sleep in the rat. J Sleep Res. 2000;9(4):367–71.

Vyazovskiy V V., Olcese U, Hanlon EC, Nir Y, Cirelli C, Tononi G. Local sleep in awake rats. Nature. 2011;472(7344):443–7.

Sanchez-Vives M V, McCormick DA. Cellular and network mechanisms of rhythmic recurrent activity in neocortex. Nat Neurosci. 2000;3(10):1027–34.

Beltramo R, D’Urso G, Dal Maschio M, Farisello P, Bovetti S, Clovis Y, et al. Layer-specific excitatory circuits differentially control recurrent network dynamics in the neocortex. Nat Neurosci. 2013 Jan 13;16(2):227–34.


C11

The impact of colour on circadian photoentrainment in mice.

J. Mouland, F. Martial, T. Brown and R. Lucas

University of Manchester, Manchester, UK

The large daily changes in ambient illumination associated with the earth’s rota-tion are a major source of timing information for the mammalian circadian clock. These ‘irradiance’ signals are encoded via the integration of extrinsic (rod) and intrinsic (melanopsin) photoreceptive signals in the retinal ganglion cells (ipRGCs) that innervate the suprachiasmatic nucleus (SCN). By contrast, cone photorecep-tion makes minimal contributions to this process, despite the appearance of cone photoreceptive signals at the level of ipRGCs and the SCN. Instead cones may play

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at least one alternative function: to provide information about daily changes in the colour of ambient illumination. We previously showed that a subset of SCN neurons exhibit chromatic responses and that naturalistic changes in colour influ-ence phase of entrainment. Here we more thoroughly investigate the contribution of chromatic information to the entrainment mechanism.Human-cone knockin mice (Opn1mwR) were used in conjunction with polychro-matic lighting environments, to allow us to experimentally isolate cone signals. Animals were subjected to a variety of entrainment paradigms (constant light, shifted LD cycles, and brief light pulses) whilst locomotor activity was assessed using running wheels, or a passive infrared system. We observed that stimuli of identical irradiance (melanopsin, rod and net cone flux) but different colour (ratio of L cone to S cone activation) differentially influenced circadian responses in a paradigm dependent manner. For example, while responses to discrete light pulses were independent of colour, the period lengthening effect of constant light was significantly greater when L cone signals ‘yellow’ were dominant (as in during natural daylight). These data therefore support the view that chromatic informa-tion supplied by cones influences entrainment and challenge the popular assump-tion that the circadian system is especially sensitive to ‘blue’ light.


C12

Can a Visual Analogue Scale (VAS) be used to measure sleepiness in patients diagnosed with Obstructive Sleep Apnoea (OSA)?

A. Dawidziuk2, Y. Alqurashi1, J. Moss1, M. Polkey1 and M.J. Morrell1

1National Heart and Lung Institute, Imperial College London, London, UK and 2College of Medicine, Imperial College London, London, UK

Motivation: The Epworth Sleepiness Scale (ESS) is the most commonly used ques-tionnaire for the assessment of sleepiness. However, it is variable between indi-viduals, not applicable in all countries, and requires high level of literacy. Visual analogue scales have been validated in the assessment of chronic symptoms such as anxiety and pain. The aim of this study was to investigate the efficacy of a newly developed Visual Analogue Scale (VAS) for the measurement of sleepiness, compared to ESS, in patients with Obstructive Sleep Apnoea (OSA) and healthy participants.Methods: A prospective, observational study was carried out in patients with OSA and healthy participants. All of the participants completed 2 visits during which they filled in both ESS and VAS. Between visits 1 and 2 the patients diagnosed with OSA were treated with Continuous Positive Airway Pressure (CPAP). The agree-ment between the VAS and ESS results was assessed using Bland-Altman plots.

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Secondary outcomes were the ease of use (0-10 Likert scale) and the time taken in each measurements.Results: 32 patients diagnosed with OSA (age [Mean±SD] 55.80 ± 13.49 years) and 32 healthy participants (age: 36.74 ± 11.65 years) were recruited. Both ESS and VAS detected a reduction in sleepiness after CPAP treatment in patients with OSA (ESS: 11.16 ± 5.53 to 4.74 ± 5.01 a.u., p<0.001, VAS: 50.22 ± 30.08 to 21.90 ± 26.52 mm, p<0.001). There were no significant differences between visit 1 and visit 2 in healthy participants using both ESS and VAS (ESS: 3.91 ± 3.41 to 3.07 ± 3.27 a.u., p=0.31, VAS: 15.58 ± 21.21 to 9.12 ± 10.93 mm, P=0.138). The Bland-Altman agreement is shown in Figure 1. In patient with OSA, the time taken to complete the VAS (visit 1: 14.92 ± 13.76 seconds, Visit 2: 5.67 ± 3.39 seconds) was significantly less compared to ESS (visit 1: 38.75 ± 20.01 seconds, Visit 2: 31.33 ± 23.68, p=0.001).Conclusion: The findings of this study suggest that the new VAS is an effective measure of sleepiness in patients with OSA and healthy participants. The VAS is also able to detect changes in sleepiness in patients with OSA treated with CPAP.

Figure 1. Bland-Altman plots of agreement between ESS and VAS results of healthy participants (n=32) and OSA patients (n=31) collected at visits 1 and 2.


C13

Exploring the molecular clock in sympathetic preganglionic neurons

C. Nathan, J. Aspden, S. Deuchars and J. Deuchars

Faculty of Biological Sciences, University of Leeds, Leeds, UK

Cardiovascular physiology exhibits a diurnal rhythm e.g. blood pressure dips at night and increases in the morning. Loss of diurnal rhythm of blood pressure is correlated to an increased risk of developing cardiovascular diseases. Blood pressure is to a large part controlled by sympathetic nervous system activity, which exhibits diurnal activity. Since sympathetic preganglionic neurons (SPNs) are the final common

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pathway the central nervous system influences blood pressure, this project aims to determine if SPN function could be regulated by diurnal expression of genes.The diurnal expression of genes encoding proteins involved in determining neuronal activity were investigated in RNA extracted from the whole spinal cord and from micro-punches that included the location of the majority of SPNs, the intermediolateral cell column (IML) at 7:30 AM and 7:30 PM of C57/Bl6 mice (N= 10) that were terminally anaesthetised with 80mg/Kg intraperitoneal sodium pentobarbitone and had their spinal cords removed and RNA extracted using an RNA extraction kit. qPCR revealed mRNA levels of Bmal1 and Per2 varied with time of day in the punch and spinal cord samples (N=10); Bmal1 mRNA was higher in the morning while Per2 mRNA was higher during the evening. Diurnal rhythm of Bmal1 and Per2 protein levels in SPNs were then examined using immunofluores-cence. C57/Bl6 mice (N= 15) were terminally anaesthetised as described above at morning and evening time points, perfused with 4% paraformaldehyde and the spinal cords removed and sectioned at 50 µm on a vibrating microtome. Bmal1 and Per2 protein levels within the SPN nucleus vary with time of day with Bmal1 levels being higher in the morning (N=5 animals, n=15 sections). To investigate a broader sample of genes, RNAseq was performed on micropunches obtained as above. Diurnal rhythm of expression was observed in potassium channel subunits (e.g. Voltage-gated potassium channel subunit beta-2, Kcnab2), sodium channel subunits (e.g. Sodium channel subunit beta-1, Scn1B) and glutamate subunits (e.g. Glutamate [NMDA] receptor subunit 3B, Grin3B) consistent with increased neuronal activity. Single cell patch-Seq is currently underway to examine if genes identified in micropunches are present in single SPNs.


C14

High intensity interval running increases cardiac autonomic activity but does not disrupt subsequent night’s sleep in trained runners.

C. Thomas

Research institute for sport and exercise sciences, Liverpool John Moores University, Liverpool, UK

Background: Observational studies have shown sleep quality in athletes is reduced after training sessions. As such, this period is considered a big obstacle to athletes’ recovery, which could hinder future performances. High intensity exercise training in the evening is one of several factors that may explain this phenomenon through its effect on cardiac autonomic activity. Yet, no research has studied the impact of high intensity exercise on sleep within a trained cohort, making it impossible to discern whether it has a positive or negative effect on sleep. The aim of this study was to investigate the effect of exercise intensity on cardiac autonomic activity and

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subsequent night’s sleep in trained runners. Methods: Eight trained male runners (age: 27.8±6.9yrs; height: 1.8±0.1m; weight: 73.5±5.3kg and VO2 max: 57±4ml.kg-1.min-1) completed three experimental trials in a randomised, counterbalanced study design. Following a standardised afternoon meal (2g CHO.kg-1BM) participants either performed: i) a 1h high intensity interval running session (6x5 min @60% VO2 max interspersed with 6x5 min @90% VO2 max); ii) a 1h low intensity running session (45% VO2 max); iii) no exercise. Exercise sessions were performed at 18.00h prior to a fixed bedtime of 22:30h. Sleep was assessed in a temperature controlled laboratory using overnight polysomnography and cardiac autonomic activity was recorded via electrocardiography. A one-way repeated measures ANOVA was performed to compare sleep variables and measures of cardiac autonomic activity between exercise intensities. Results: There were no changes in average nocturnal heart rate variability after exercise but average nocturnal heart rate was higher after high intensity interval running than low intensity running (50±5 bpm v 47±5 bpm, p = 0.02) and no exercise (50±5 bpm v 47±5 bpm, p = 0.028). In the polysomnog-raphy analysis, total sleep time, sleep efficiency and wake after sleep onset were improved after high intensity interval running and low intensity running compared with no exercise (p < 0.05). Conclusions: High intensity interval running increases cardiac autonomic activity but does not disrupt subsequent night’s sleep compared to no exercise in trained runners. It should be considered that poor sleep on the night following a single training session in the evening is not caused by exercise intensity. Future research is warranted to determine if other stressors that are encountered by athletes after intense exercise training cause sleep disruption such as muscle damage and glycogen depletion.

The authors would like to acknowledge S-MED for providing the polysomnography.


C15

Effects of sleep extension and sleep restriction on the performance and cardiac autonomic function of endurance cyclists

S. Roberts, W. Teo, B. Aisbett and S.A. Warmington

Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Burwood, VIC, Australia

Sleep is considered the most important recovery behaviour for athletic success(1). While there is evidence that sleep may affect endurance performance(2), no study has investigated the effects of sleep on the sport-specific performance of trained endurance athletes. In addition, while indices of cardiac autonomic function are increasingly being used to monitor athlete wellbeing(3), little is known of the effects of sleep on such indices. In a balanced crossover experiment, endurance cyclists (n=9) completed three trials; normal sleep (NORS), sleep restriction (SRES),

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and sleep extension (SEXT). Each trial required cyclists to complete a time trial (TT) - based on predicted work achievable in one hour when cycling at anaer-obic threshold - on four consecutive mornings (TT1 – TT4). Cyclists slept habitually prior to TT1 of each trial. However, on the three subsequent nights time in bed either; remained as normal (NORS), was restricted by 30% (SRES), or was extended by 30% (SEXT). A 7-day washout period separated each trial. Actigraphy (sleep-wake threshold 40 counts/min) was used to monitor sleep. Performance time (to the nearest second) and rating of perceived exertion (6-20 scale) were recorded for each TT. Prior to each TT, resting heart rate (HR), HR variability (Ln rMSSD), maximal rate of HR increase during submaximal exercise, HR recovery following submaximal exercise, mean response time during a psychomotor vigilance task (PVT), and mood disturbance were recorded. Data were analysed using a Gener-alised Estimating Equations approach. On each of the three sleep intervention nights, total sleep time was higher (P=0.000) in the SEXT trial compared with both NORS and SRES, and lower (P=0.000) in the SRES trial compared with NORS. TT4 was faster in the SEXT trial (mean±SD, 3409±187sec) compared with both the NORS (3521±204, P=0.013), and SRES (3718±312, P=0.010) trials. Rating of perceived exertion, resting HR, resting Ln rMSSD, maximal rate of HR increase at the onset of submaximal exercise, and HRR following submaximal exercise were unchanged between trials. Prior to TT4, total mood disturbance was higher in the NORS (13±18au, P=0.002) and SRES (28±12, P=0.000) trials compared with SEXT (4±10). Prior to TT3, mean response time was faster in the SEXT trial (346±27ms) compared with SRES (374±31, P=0.008) and NORS (360±28, P=0.021). Prior to TT4, mean response time was faster in the SEXT trial (332±29) compared with both NORS (363±28, P=0.000) and SRES (392±40, P=0.000). Sleep extension for three nights enabled cyclists to better maintain performance compared with normal sleep and sleep restriction. Cardiac autonomic indices were not sensitive to changes in sleep duration. Better mood and vigilant attention following sleep extension suggests psychological factors may explain the effects of sleep on endur-ance performance.1. Venter RE. Perceptions of team athletes on the importance of recovery modalities. Eur J Sport Sci. 2014;14(sup1):S69-S76.

2. Oliver SJ, Costa RJ, Laing SJ, Bilzon JL, Walsh NP. One night of sleep deprivation decreases treadmill endurance performance. Eur J Appl Physiol. 2009;107(2):155-61.

3. Buchheit M. Monitoring training status with HR measures: do all roads lead to Rome? Front Physiol. 2014;5(73):1-19.


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C16

The use of melatonin in the treatment of paediatric sleep disorders in the UK

M. Basra1, S. Terry1, D. Wringe1 and M.J. Morrell1,2,3

1Clinical Research and Innovation Theme, Imperial College School of Medicine, London, UK, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, UK and 3National Institute for Health Research Respiratory Biomedical Research Unit, Royal Brompton & Harefield National Health Service Foundation Trust, London, UK

Sleep disorders such as obstructive sleep apnoea and sleep onset insomnia occur in 3.7% of children. [1] Melatonin is a sleep-promoting pineal hormone, regulated by the suprachiasmatic nucleus [2] that is sometimes prescribed off-label for sleep disorders in children. [3] Oral melatonin is moderately expensive, costing £15-75/month dependent on dosage. [4] Side effects are uncommon, but include hyper-activity, nightmares and constipation. [5] Alternative management strategies for paediatric sleep disorders include behavioural therapies.Aim: To carry out an exploratory study to investigate clinical perspectives on the use of melatonin in the treatment of paediatric sleep disorders.Methods: A Qualitative exploratory study was carried out using semi-structured interviews of 15-30 minutes, either face-to-face or via video or telephone calls; dialogue was transcribed during interviews. Chain sampling was used to select interviewees. Inclusion criteria: professionals with experience of paediatric sleep disorders: 14 contacted, 10 respondents interviewed (Figure 1). Data thematically analysed via open coding (Figure 2).Results: Misconceptions about melatonin and its use in treating paediatric sleep disorders were reported in healthcare professionals and parents, possibly producing suboptimal prescription practices and unrealistic expectations. This could impair the quality of care in paediatric patients with sleep disorders, and may incur costs upon the NHS, as shown in Figure 2. Behavioural interventions could also be useful and implemented prior to or in conjunction with melatonin treatment, but access to behavioural treatments appears to be limited in many parts of England and Scotland. Melatonin has become the “sleeping aid of choice” for paediatricians, and high prescription rates may not be detrimental provided prescribers are well-informed, as sleep deprivation has profound effects in children.Conclusions: Current melatonin prescribing practices could be improved in physicians who treat paediatric sleep disorders but who are not sleep experts. Behavioural interventions may be more effective than melatonin in paediatric sleep disorders. There is an apparent lack of awareness of paediatric sleep disorders amongst medical students, and therefore awareness of treatment options and the role of melatonin vs behavioural treatments.Future work: Investigate current prescribing practices of melatonin in a larger sample of paediatric professionals. Raise awareness of paediatric sleep disorders and the necessary treatments for them. Investigate sleep education across UK

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medical schools and raise awareness of paediatric sleep disorders and treatment options amongst medical students who may become paediatricians.

Figure 1: Interviewees and their roles

Figure 2: Codes (blue), concepts (green) and categories (yellow) from analysis of interviews.

Hoban, T.F. Sleep disorders in children. The Year in Neurology 2. 2009;1184(1): 1-14. [Online] Available from: https://doi.org/10.1111/].1749-6632.2009.05112.x. [Accessed: 11th June 2018]

Claustrat, B. et al. Melatonin: Physiological effects in humans. Neurochirurgie. 2015;61 (2-3): 77-84. [Online] Available from: doi: 10.1016/j.neuchi.2015.03.002. [Accessed: 18th June 2018]

British MA, Royal Pharmaceutical Society of, Great Britain. British National Formulary for Children - BNFC. London: Royal Pharmaceutical Society of Great Britain, British Medical Association.

Sleep disorders in children and young people with attention deficit hyperactivity disorder: melatonin | Guidance and guidelines | NICE. Available from: https://www.nice.org.uk/advice/esuom2/chapter/evidence-review-economic-issues#cost-effectiveness. [Accessed Jun 17, 2018]

Waldron, D.L., et al. Melatonin: prescribing practices and adverse events. Archives of Disease in Childhood. 2005;90(11): 1206-1207. [Online] Available from: http://dx.doi.org/10.1136/adc.2005.077289. [Accessed: 16th June 2018]


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C17

Amyloid Beta Oligomeric Structure Governs Sleep/Wake States in Zebrafish

G. Ozcan, S. Lim and J. Rihel

Cell and Developmental Biology, University College London, London, UK

Introduction - Despite decades of research, the endogenous function of amyloid beta (Aβ), the hallmark protein of Alzheimer’s Disease (AD), remains unknown. Knowing what Aβ does physiologically would enable us to understand what is going wrong in the disease state. Recent studies have highlighted links between Alzheimer’s disease and sleep1. Sleep is disrupted in AD patients, often years before cognitive deficits2. Since Aβ levels cycle across the sleep/wake cycle1, we hypothesized that one in vivo function of Aβ may be to directly modulate sleep/wake states. Several features of zebrafish biology make it an excellent model to investigate the role of Aβ in sleep: Zebrafish have a complete repertoire of amyloid precursor protein (APP) processing machinery and most of the Aβ receptors are highly conserved in zebrafish. In addition, the zebrafish brain is anatomically and molecularly similar to the mammalian brain, and many behaviours like sleep, are controlled by similar neuronal mechanisms.Materials and Methods - Using CRISPRs we mutated the two zebrafish APP genes to downregulate Aβ levels. To upregulate Aβ levels acutely, we injected different oligomeric forms of Aβ with final brain concentrations in the picomolar (i.e. physi-ological) range to anesthetized zebrafish larvae (in 1 mM MS222). Different oligo-mers/fibrils were obtained by incubating Aβ preparations at 4°C or 25°C and the length of oligomers were assessed by TEM (Transmission Electron Microscopy). We determined the effects of Aβ oligomer/fibrils on sleep/wake behaviour via video monitoring and used whole brain activity mapping to identify neurons that differentially respond to Aβ.Results and Conclusions - While APP loss of function mutants had an 11±1.0% decrease in waking activity, Aβ in its shorter oligomeric forms (median oligomer length 45±4 nm); caused strongly increased activity (14±4.9%) and decreased sleep (-12±9.2%). In contrast, longer Aβ oligomers/fibrils (median oligomer length 75±7 nm) acutely increase sleep (30±12.0%) without neurotoxicity. Consistent with their effects on wakefulness, short Aβ oligomers induced neuronal activity in a subset of neurons in the posterior hypothalamus, which is a major wake-promoting center in the vertebrate brain. In contrast, longer oligomeric forms do not activate these wake-promoting neurons but instead globally dampen neuronal activity.Our experiments suggest that physiological and temporary upregulation of Aβ levels can directly promote both zebrafish sleep and wakefulness depending on the oligomeric state of Aβ via activation of discrete subpopulations of neurons. We are now performing a CRISPR-mediated genetic screen in zebrafish to identify the receptors that interact with Aβ to mediate these effects on sleep and wake.

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Understanding neural and molecular mechanisms of Aβ’s effect on sleep/wake behaviour may provide a mechanistic understanding of what goes wrong in AD.Kang et al., Science, 326: 1005-1007, (2009)

Sterniczuk et al., Curr. Alzheimer Res. 10(7): 767-775 (2013)

Ahrens et al., Nature Methods, 10: 413–420, (2013)


C18

The impairment in insulin sensitivity after sleep restriction does not increase with more nights of sleep restriction.

E. Sweeney1, D.J. Peart1, J.G. Ellis2 and I.H. Walshe1

1Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle Upon Tyne, UK and 2Northumbria Sleep Research Laboratory, Northumbria University, Newcastle Upon Tyne, UK

Voluntary sleep curtailment is common in modern society and has been linked to poor glucose control. Many experimental studies have shown impaired glucose regulation after sleep restriction, ranging from one to five nights. However, it remains unclear whether the impairment in glucose regulation is related to the number of nights of sleep restriction, as methodological differences make compari-sons between existing studies difficult. The current study aimed to explore glucose regulation following each night of sleep restriction for four consecutive nights to identify if there is a linear effect of number of nights of restriction on the impair-ment in glucose regulation. We hypothesised that the level of glucose control would decline with each subsequent night of sleep restriction.10 healthy, non-diabetic humans aged between 18 and 50 years were recruited for this randomised crossover study with 4 nights of control sleep (8 h/night) and 4 nights of sleep restriction (4 h/night), separated by a 3 wk washout period. Partic-ipants stayed in the laboratory overnight but were permitted to leave during the day, during which time wrist actigraphy was used to ensure no sleep or physical activity was undertaken. Each morning upon wakening an oral glucose tolerance test was conducted and venous blood samples were collected at regular intervals for 120 min. Glucose and insulin concentrations were determined from the blood samples and area under the curve (AUC) was calculated for each day using the trapezoidal rule. ANOVAs were conducted to compare glucose and insulin AUC for the four days in each condition.Glucose AUC displayed trends for an effect of trial (P = 0.063) and interaction effect (P = 0.098) but no effect of day (P = 0.773). Insulin AUC showed a significant effect of trial (P = 0.020), however there was no effect of day (P = 0.861) or interaction effect (P = 0.129).

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Our findings agree with previous studies which have shown that sleep restriction impairs glucose regulation. However, contrary to our hypothesis, there does not appear to be a significant linear effect of impairment with an increasing number of nights of sleep restriction.


C19

Modelling Local Sleep Homeostasis

C.W. Thomas1, M. Guillaumin1, L. McKillop1, P. Achermann2 and V. Vyazovskiy1

1Department of Physiology, Anatomy & Genetics, University of Oxford, Oxford, UK and 2Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland

Sleep homeostasis refers to the process by which a need for sleep accumulates during wakefulness and dissipates during subsequent sleep. Homeostatic sleep need is typically measured using slow wave activity (SWA); oscillatory power at 0.5 – 4 Hz present in extracellular field potentials during NREM sleep, which is generated by synchronous alternating bouts of neuronal spiking activity (“on periods”) and silence (“off periods”). Existing quantitative descriptions of sleep homeostasis describe the dynamics of slow wave activity only as a function of recent sleep-wake history. However, homeostatic sleep pressure is non-uniform across the brain, originates locally, and changes in association with neuronal activ-ities. This project aims to develop quantitative models that predict homeostatic sleep need markers from multi-unit firing rate history within the same channel. Models were developed and applied to an existing dataset of electrophysiological recordings from 16-channel microwire arrays implanted in mouse frontal cortex (McKillop et al., 2018). Data were obtained continuously for several days while mice were freely behaving, including periods of spontaneous sleep and wake, and periods of 6hr sleep deprivation (by gentle handling and novel object presenta-tion). To assess model fit quality, an error metric was defined as the sum of abso-lute differences between median simulated and empirical values over continuous NREM episodes at least 1 minute duration, weighted by episode length. Model parameters were algorithmically optimised to minimise this error metric. A simple model, in which homeostatic sleep need increases in proportion to multi-unit firing rate and decreases exponentially over time, can often describe the time course of SWA with high accuracy (n=28; 7 mice x 4 best quality channels per mouse). An alternative model, which employs a firing rate threshold, with a saturating expo-nential rise in homeostatic sleep need above threshold, and exponential decrease below, provided an even better fit to SWA, yielding a lower minimal error metric (p < 0.001, n=28, Wilcoxon signed rank test). The time course of off period occu-pancy shows qualitatively similar temporal dynamics to slow wave activity and is a

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viable alternative sleep homeostasis metric. Preliminary results using this suggest that restricting simulated homeostatic sleep need decay to detected off periods improves model fit (p < 0.05, n=6, Wilcoxon signed rank test). In conclusion, the dynamics of local homeostatic sleep need can be well described by models depen-dent solely on local neuronal activities, independent of any information about the animal’s global wake-sleep state. The advancement of models of sleep homeostasis will likely provide means to test competing theories of its mechanistic origin within neurones and local networks.L. E. McKillop, S. P. Fisher, N. Cui, S. N. Peirson, R. G. Foster, K. A. Wafford, and V. V. Vyazovskiy, Effects of Aging on Cortical Neural Dynamics and Local Sleep Homeostasis in Mice,” Journal of Neuroscience, vol. 38, pp. 3911-3928, Apr. 2018.


C20

Investigating the neural circuit basis of sleep disturbance-induced cognitive deficits using the larval zebrafish (Danio rerio)

D.G. Lyons, S. Reichert and J. Rihel

Department of Cell and Developmental Biology, University College London, London, UK

Sleep is vital for brain function, with insufficient or poor sleep inducing severe deficits in cognitive performance. Although these impairments have serious nega-tive effects on health, economic productivity and quality of life, the mechanisms underlying them are not well understood. My work aims to investigate how sleep deprivation leads to performance deficits in simple sensorimotor behavioural tasks. I am employing in vivo functional imaging to characterise the activity of identified task-related circuits as zebrafish larvae perform visually guided behaviours, to attempt to detect the alterations in this activity that are caused by sleep disrup-tion and are associated with impaired task performance. Using an array of different environmental and pharmacological sleep-deprivation paradigms, I then plan to explore the precise pathways leading to this cognitive impairment. Subsequently, by using optogenetic, chemogenetic and pharmacological tools, I aim to mimic, prevent, and reverse these processes to test whether these impairments can be dissociated from sleep loss per se, and determine the sleep-related processes that support efficient cognitive and neurological function. This research will have important implications for understanding of sleep neurobiology, and the develop-ment of therapeutics to effectively manage sleep deprivation induced cognitive problems in healthy individuals and in the numerous neuropsychiatric disorders in which sleep dysfunction is implicated.


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C21

Torpor Preferentially Induces c-Fos Expression in Dorsomedial and Posterior Hypothalamus in Mice

M.T. Ambler1, M. Cerri2 and A. Pickering1

1Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, UK and 2Department of biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy

Torpor is the naturally occurring hypothermic, hypometabolic and hypoactive component of hibernation(1). It is an adaptive, controlled reduction in tempera-ture and metabolic demand in response to reduced availability of substrate. If such a centrally-driven hypothermic and hypometabolic state could be mimicked in a clinical setting it may represent an improved strategy for therapeutic hypo-thermia(2). The purpose of this study was to identify regions of the brain active during torpor in the mouse. Female mice (C57BL/6J, Charles River) were main-tained on a 12-hour reversed light/dark cycle, and acclimatised to an ambient temperature of 30 °C for 5-7 days. Torpor was induced by reducing the ambient temperature to 18°C at lights off, then after 24 hours cold acclimatisation, food was removed for 12 hours(3). Torpor was detected by monitoring surface tempera-ture changes using a thermal imaging camera (Flir C2, ResearchIR 4 software), and defined as a surface temperature greater than 2 standard deviations below the mean during the 24 hours prior to fasting. Controls were fasted at 30°C for 12 hours, or exposed to 18°C ambient temperature with access to food. No control mice entered torpor, and all mice exposed to cooling and fasting entered torpor. The mean nadir surface temperature for torpid mice was 24.2 +/- 0.9°C, 27.8 +/-0.06°C in the cooled controls (p < 0.001) and 34.2+/-0.2°C in the fasted controls (p<0.0001) (one-way ANOVA). Two hours after torpor entry (n=3), at the end of a 12 hour fast (n=4), or after 36 hours cold exposure (n=4), mice were terminally anaesthetised with pentobarbitone (175mg/kg i.p), then transcardially- perfused with formalin. Brains were post-fixed for 24 hours at 4°C before being cryoprotected in 30% sucrose for 48 hours. Sagittal sections of subcortical struc-tures and brainstem (40µm) were cut, blocked with 5% normal donkey serum, and incubated overnight at room temperature in 1:2000 anti-c-fos primary (Cell Signal-ling Technologies, 2250s) followed by a fluorescent secondary antibody (donkey anti-mouse, AlexaFluor488, 1:1000). Sections were tile-scan imaged using a Leica DMI6000 Widefield fluorescence microscope. Images were analysed using ImageJ software with a semi-automated image processing protocol to count c-fos positive nuclei. Figure 1 shows an example plot of surface temperature and activity of a mouse entering several short torpor bouts of increasing depth. Figure 2 shows that cooling increased c-fos expression in the medial preoptic, parabrachial nucleus, and bed nucleus of the stria terminalis. Fasting induced c-Fos expression in the arcuate, the dorsomedial, posterior, and paraventricular hypothalamus. The dorsomedial and posterior hypothalamus increased c-fos expression during torpor compared

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to either cold or fasting alone, and as such they represent potential nodes within the torpor induction circuitry.

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Bouma HR, Verhaag EM, Otis JP, Heldmaier G, Swoap SJ, Strijkstra AM, et al. Induction of torpor: Mimicking natural metabolic suppression for biomedical applications. J Cell Physiol [Internet]. 2012 Jan 11;227(4):1285–90.

Polderman KH. Mechanisms of action, physiological effects, and complications of hypother-mia. Crit Care Med [Internet]. 2009 Jul 1;37(7 Suppl):S186-202.

Swoap SJ, Gutilla MJ. Cardiovascular changes during daily torpor in the laboratory mouse. Am J Physiol - Regul Integr Comp Physiol [Internet]. 2009 Sep 1;297(3):R769-74.


C22

Can blue light exposure influence mood in night shift workers?

W. Kim1, W. Han1, T. Rose1, C. James-Harvey2 and M.J. Morrell1,3,4

1Clinical Research and Innovation Theme, Imperial College School of Medicine, London, UK, 2Nuffield Department of Clinical Neurosciences, Sleep & Circadian Neuroscience Institute, University of Oxford, Oxford, UK, 3National Institute for Health Research Respiratory Disease Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, UK and 4Imperial College, London, UK

Background: Night-shift work is becoming more common as society moves towards services being available 24 hours a day. This is problematic as poor sleep quality in shift workers can lead to mood disorders such as depression and seasonal affective disorder. Phototherapy can be used to treat mood disorders that originate from circadian disruption.One form of phototherapy is the Re-timer light therapy glasses, which emit 500nm of blue-green light. Although the glasses have been shown to be effective in phase-shifting circadian rhythms, it is not known if they are effective in improving sleep or other downstream processes such as mood changes. We aimed to investigate whether the glasses had an effect on the mood of a cohort of night shift workers.Methods: A hypothesis generating, prospective cohort study was conducted in permanent night-shift workers at a supermarket distribution warehouse. Of the 200 warehouse workers working nights, 150 visited the ‘nightclub’ project*. Volunteers were given the glasses and data was collected in 6 night shift workers. Workers were excluded if they had any photosensitive conditions such as epilepsy or were unable to wear the glasses for safety reasons. The positive and negative affect schedule (PANAS) generates a positive and negative arbitrary mood score, and was used to monitor mood, on a twice-daily basis for 18 days. After 9 days of baseline monitoring, phototherapy was administered via the Re-timer glasses for 30 minutes before each subsequent night-shift for another 9 days. The baseline and post-inter-ventional mood scores were compared via a paired two sample Student’s t-test.Results: There was a significant decrease in the negative mood scores with light therapy (baseline: 15.39±5.67 vs intervention: 12.88±2.98 (mean±1 SD), p<0.001).

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Due to the study design, monitoring phototherapy compliance was unfeasible and the participants were not blinded to the intervention. Sample size and study duration were also limited, with little information on demographic stratification. These points need to be considered in future studies.Summary: The results suggest that light therapy was was able to alleviate negative moods in night shift workers. Whether this was due to a physiological response to light or an ensuing effect from circadian stabilisation is unclear. However, these preliminary data do suggest that potential improvements in mental health of shift-workers can be achieved with light therapy. Therefore, making similar adjustments in night shift environments and increasing awareness of available therapies may have positive implications, in the interests of both employers and employees.

Acknowledgements: *These data were collected as part of a wider study funded by the Wellcome Trust, in collaboration with Liminal Space and the Sleep & Circadian Neuroscience Institute, University of Oxford. Ethical approval was obtained from the University of Oxford CUREC.


C23

Does exposure to blue light reduce sleepiness in night shift workers?

T. Dorji1, S. Sharma1, S. Lowe1, M.J. Morrell2,1,3 and C. James-Harvey4

1School of Medicine, Imperial College London, London, UK, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, UK, 3Respiratory Biomedical Research Unit at the Royal Brompton Hospital, Imperial College London, London, UK and 4Nuffield Department of Clinical Neurosciences, University of Oxford, London, UK

Background: Approximately 12% of all employees in the UK undertake night shifts to serve an increasingly 24/7 modern society, according to the Labour Force Survey (2016). Night shift work is thought to cause circadian phase-shift, associated with decreased alertness, workplace accidents, diabetes and cancer.1 Light plays a crucial role in circadian rhythm entrainment and regulating melatonin release.2 Previous experiments3 have shown that blue/green light of wavelength 470-525nm shows the greatest melatonin suppression, reducing and postponing sleepiness within individuals, but this has not been explored outside controlled conditions in a real-world setting.Methods: A prospective cohort study was conducted in long-term night shift (22:00 – 06:00) workers, at a Co-op warehouse in Thurrock. Approximately 150 workers were invited to take part and those who had planned annual leave, a diagnosed sleep disorder or were non-English speaking were excluded. Partici-pants (n=10) who gave their consent filled in two questionnaires at the start and end of each shift every day for two weeks: the Karolinska Sleepiness Scale (KSS)

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scored from 1-9 with 9 indicating extreme sleepiness, and the Epworth Sleepiness Scale (ESS) which is scored from 0-24 (24 being very sleepy).4,5 The first week was assigned as the baseline week in which there was no intervention. During the second week, goggles (Re-TimerTM) emitting blue-green light (500nm) were worn for 30 minutes before the start of each shift. Ethical approval was obtained from the University of Oxford CUREC.Results: KSS and ESS scores from 6 participants were analysed as median and inter-quartile range (IQR). Data from 4 participants were neither returned nor completed properly. The average scores of weeks 1 and 2 were compared. The median KSS score decreased from 4.5 (IQR:3) a.u in week 1 to 4 (IQR:3) a.u in week 2. The median ESS score decreased from 9.5 (IQR:5) a.u to 8 (IQR:8) a.u. Both question-naires revealed that the workers were alert, and their sleepiness was found to be low, albeit higher than normal. It was observed that exposure to blue light may reduce self-perceived sleepiness, however further studies are needed to increase the sample size and add an effective control group.Conclusions: It is important to note that to our knowledge this is the study first to examine the direct real-world effects of blue light on subjective sleepiness in shift warehouse shift workers. The project hopes to raise awareness on improving occupational lighting, encouraging the installation of blue-enriched white lights to boost mental performance and productivity in the workplace setting.Costa G. Shift work and occupational medicine: an overview. Occupational Medicine. 2003; 53(2): p83–88. Available from: https://doi.org/10.1093/occmed/kqg0455

Chellappa SL et al. Non-Visual Effects of Light on Melatonin, Alertness and Cognitive Perfor-mance: Can Blue-Enriched Light Keep Us Alert? PLoS ONE. 2011; 6(1). Available from: https://doi.org/10.1371/journal.pone.0016429

Helen R. Wright & Leon C. Lack. Effect of light wavelength on suppression and phase delay of the melatonin rhythm, Chronobiology International. 2009; 18:5, p801-808. DOI: 10.1081/CBI-100107515

Barile Doneh; Epworth Sleepiness Scale, Occupational Medicine. 2015; 65(6): Pages 508. Avail-able from: https://doi.org/10.1093/occmed/kqv042

Miley AA, Kecklund G, Akerstedt T. Comparing two versions of the Karolinska Sleepiness Scale (KSS). Sleep and Biological Rhythms. 2016;14(3):257-260. DOI: 10.1007/s41105-016-0048-8.

Acknowledgements: These data were collected as part of a wider study funded by the Wellcome Trust, in collaboration with Liminal Space and the Sleep & Circadian Neuroscience Institute, University of Oxford.


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C24

The relationship between fasting-induced torpor and sleep in mice

Y. Huang and V. Vyazovskiy

Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK

Torpor is a regulated and reversible state of metabolic suppression employed by many animals mainly to conserve energy. Torpor can be induced by fasting or by changes in photoperiod (i.e. seasonal torpor, which includes hibernation and daily torpor). Previous studies on seasonal torpor revealed notable similarities and differences between torpor and sleep. Behaviourally, both states are associated with immobility and reduced responsiveness. However, both hibernation and daily torpor induced by shortening of photoperiod appear to be sleep-depriving states. Specifically, animals emerging from torpor usually enter sleep characterised by high encephalographic (EEG) slow-wave activity, an established marker of homeostatic sleep pressure. Much less is known about the relationship between sleep regulation and fasting-induced torpor, which can be readily induced in laboratory mice.In this study, we established a model of fasting-induced torpor in C57BL/6J mice (n=8, male; 12-weeks old; mean weight 26.9 g), and performed continuous elec-trophysiological and surface body temperature (Tsurface) recording (via infra-red cameras) across successive days of food restriction. The animals were implanted with epidural EEG electrodes above the frontal and occipital cortices and electro-myogram (EMG) electrodes in the nuchal muscle, and allowed to recover for at least 7 days after surgery prior to starting the experiment. Mice were kept at a 12:12 light-dark cycle throughout the experiment and provided with approximately 1 g of food daily between ZT6 and ZT9. Ambient temperature was kept at 22 to 24 °C, and body weight was carefully monitored to ensure that it remained above 85% of ad lib feeding weight.Our preliminary analyses revealed that all animals entered torpor bouts (defined as Tsurface<28 °C for at least 1 hour) within 5 days of food restriction. Torpor bouts were invariably initiated via a state that, based on EEG and EMG signals, resembles NREM sleep, but EEG amplitude subsequently showed a prominent and progressive reduction during entrance into torpor, in some cases reaching below 10% of the values during euthermic NREM sleep. We did not observe REM sleep or extended spontaneous wakefulness periods during torpor bouts. However, in all animals the torpor bouts were punctuated by prominent EMG bursts, associated with a tran-sient EEG activation, at a regular periodicity of <5-10 min. Upon spontaneous return to euthermia, the torpor bouts were typically followed by periods of wakefulness and often further torpor bouts until the animals were fed. The animals entered deep sleep with high EEG SWA shortly after feeding.Our study tentatively suggests that fasting-induced torpor and sleep are closely related yet distinct neurophysiological states. It remains to be determined whether fasting-induced torpor is a sleep-depriving state functionally similar to seasonal torpor.

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Vyazovskiy, V. V., Palchykova, S., Achermann, P., Tobler, I. & Deboer, T. Different Effects of Sleep Deprivation and Torpor on EEG Slow-Wave Characteristics in Djungarian Hamsters. Cereb. Cortex 27, 950–961 (2017).

Daan, S., Barnes, B. M. & Strijkstra, A. M. Warming up for sleep? - Ground squirrels sleep during arousals from hibernation. Neurosci. Lett. 128, 265–268 (1991).

Hudson, J. W. & Scott, I. M. Daily torpor in the laboratory mouse, Mus musculus. Physiol. Zool. 52, 205–218 (1979).

Jensen, T., Kiersgaard, M., Sørensen, D. & Mikkelsen, L. Fasting of mice: a review. Lab. Anim. 47, 225–240 (2013).

Berger, R. J. Slow wave sleep, shallow torpor and hibernation: Homologous states of dimin-ished metabolism and body temperature. Biol. Psychol. 19, 305–326 (1984).

Vladyslav Vyazovskiy Group


C25

Is self-reported chronotype associated with caffeine intake in male night shift workers?

A. Koomson1, S. Lee1, M. Samy1, C. James-Harvey4 and M.J. Morrell1,2,3

1Clinical Research and Innovation Theme, Imperial College School of Medicine, London, UK, 2Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, London, UK, 3National Institute for Health Research Respiratory Disease Biomedical Research Unit at the Royal Brompton and Harefield National Health Service Foundation Trust and Imperial College London, London, UK and 4Sleep and Circadian Neuroscience Institute, Oxford University, Oxford, UK

Caffeine is a widely consumed psychoactive drug that increases alertness1. While moderate caffeine intake (<400 mg2) can prevent certain chronic diseases, chronic high caffeine intake increases cardiovascular risk factors such as blood pressure and cholesterol1. Working night shifts is associated with increased caffeine consump-tion3. Individuals’ chronotypes (that which determines preference for day or night) can be categorised into ‘early lark’, ‘intermediate’, and ‘night owl’4. The aim of this study was to investigate if self-reported chronotype is associated with caffeine intake in male night shift workers.The study was carried out as part of a wider project to engage night shift workers, in collaboration with Sleep and Circadian Neuroscience Institute (SCNi), University of Oxford and Liminal Space. Night shift workers at a supermarket distribution warehouse were recruited. Self-reported chronotype was determined via a ques-tionnaire provided by SCNi. Participants were then categorised as ‘lark’, ‘interme-diate’, or ‘owl’. Consumption of caffeinated food and beverages (classified by the National Health and Nutrition Examination Survey5) over a 24-hour period from the end of 1 shift to the end of the next was determined by pictorial questionnaire

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developed by the research team for ease of use. Caffeine intake was then estimated using values made available by the Government of Canada2.Data was collected from 38 male night shift workers over 2 night shifts; approxi-mately 200 staff were on duty per shift. ‘Intermediates’ (n=20) consumed the most caffeine, with 25% consuming more than the 400 mg recommended limit, but the difference between the 3 categories was not statistically significant. Duration of time working night shifts seemed proportionally associated with caffeine intake, with those having worked night shifts for longer consuming more caffeine than those who had recently begun working night shifts.The findings of this study suggest that self-reported chronotype is not associated with caffeine intake in male night shift workers. Duration of time working night shifts could be a better predictor of caffeine intake than self-reported chronotype, and follow-up studies should be performed to investigate this. In addition, associa-tion between genotypic chronotype and caffeine intake could be looked into. These studies could also be performed with the inclusion of female night shift workers. As night shift workers already tend to consume more caffeine than day shift workers, it is hoped that through these studies, public health messages could be tailored to sub-groups in the night shift worker population that may be especially at risk of consuming unhealthy levels of caffeineBae JH, Park JH, Im SS, Song DK. Coffee and Health. Integrative Medicine Research. 2014; 3(4): 189-191.

Government of Canada. Canadian Nutrient File 2016.

Centofanti S, Banks S, Colella A, Dingle C, Devine L, Galindo H et al. Chronobiology Interna-tional. 2018: 1-15.

Urbán R, Magyaródi T, Rigó A. Morningness-Eveningness, Chronotypes and Health-Impairing Behaviors in Adolescents. Chronobiology International. 2011; 28(3).

Ahluwalia N, Herrick K. Caffeine Intake from Food and Beverage Sources and Trends among Children and Adolescents in the United States: Review of National Quantitative Studies from 1999 to 2011. Advances in Nutrition. 2015; 6(1): 102-111.

This data was collected as part of a wider study funded by the Wellcome Trust, in collaboration with Liminal Space and the Sleep & Circadian Neuroscience Institute, University of Oxford.


C26

Circadian disruption and sleep regulation in mice

A. Fisk, V. Vyazovskiy and S. Peirson

Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK

Light is the primary entraining cue for the circadian system, adjusting biological time to the external environment, however it also has direct effects on arousal and

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sleep. The demands of our modern 24/7 society, with increasing exposure to arti-ficial light at inappropriate times of day, is widely considered to be detrimental to our physiology. Evidence comes from studies using aberrant light/dark (LD) cycles to produce circadian disruption in mouse models. A range of different protocols have been used, including constant light (LL), jet-lag (JL), dim light at night (DLAN), and non-24 hour LD cycles (T-cycles). To date, no detailed comparison of the effects of these different protocols has been conducted, and it remains to be determined whether and how circadian disruption affects sleep regulation.Methods: We used passive infra-red (PIR) sensors to simultaneously measure activity and immobility-defined sleep in wild-type C57BL/6J mice under different protocols, including LL, JL, DLAN and T20 (10h light: 10h dark). We compared the effects of these different protocols on commonly used measures of circadian disruption including periodogram power (Qp), intradaily variability (IV) and inter-daily stability (IS), as well on the architecture of immobility-defined sleep. In a sepa-rate cohort of C57BL/6J mice (n=7) we examined the effects of 14 days constant light on sleep architecture and EEG.Results: Different LD conditions produced different effects on circadian activity. Whilst IV is increased and IS were decreased under all conditions (n=24, IV ANOVA F(1,20)=28.8 p<0.0001, IS ANOVA F(1,20) = 295.6, p<0.0001) decreases in Qp were only observed under LL and T20 (LL p<0.0001, T20 p=0.0053). All conditions change the distribution of immobility-defined sleep. Furthermore, our preliminary results suggest that constant light acutely increases the amount of sleep in the first day, which results in an altered distribution of EEG slow-wave activity – the established marker of sleep homeostasis.Conclusions: Our data suggests that commonly used protocols exert different effects on sleep and circadian rhythms. These data provide a framework to under-stand the effects of these protocols on other biological processes such as cognitive functions and physiology.


C27

GRIA1 knockout mice show reduced global EEG sleep spindles, preserved local LFP spindles an retain long-term memory

C. Blanco Duque1, R.J. Purple2, T. Yamagata1, L. Krone1, L. McKillop1, D.M. Bannerman1 and V. Vyazovskiy1

1University of Oxford, Oxford, UK and 2University of Bristol, Bristol, UK

Sleep spindles have been implicated in cognitive functions and memory consoli-dation1,2. Deficits in spindles have been reported in brain disorders (e.g. schizo-phrenia) associated with polymorphisms of the GRIA1 gene3, which codes for the GluA1 AMPA receptor subunit. Here we investigated the dynamics of sleep

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spindles and their relationship with memory performance in GRIA1-/- and wild type (WT) mice.Chronic electroencephalogram (EEG) and the electromyogram (EMG) were recorded during spontaneous sleep in n=14 mice. Multichannel recordings of local field potentials (LFP) were also collected in a subset of mice from layer-V somatosensory cortex (SCx). Surgical procedures were performed under isoflu-rane anaesthesia. EEG and LFP power spectra were calculated with a Fast Fourier Transform using 4-second epochs. For individual spindle event detection, an auto-mated algorithm based on autoregressive modelling was applied to the LFP and EEG signals. Spatial reference memory was assessed in an additional group of mice using a plus maze task.Frontal EEG spectral power during NREM sleep was significantly reduced in the spindle-frequency range (10-15 Hz) in GRIA1-/- relative to WT mice. Furthermore, individual EEG spindle events were readily detected in WT mice with the auto-mated algorithm, while they were absent in GRIA1-/- mice. Interestingly, despite the absence of EEG spindles in GRIA1-/- mice, preliminary analyses of LFP signals revealed an occurrence of local spindle events in the SCx in both genotypes. A repeated measures analysis revealed no significant differences between GRIA1-/- and WT in memory performance (main effect of genotype and interaction by day; F< 1;p>0.20). This is consistent with previous evidence indicating that long-term memory formation is preserved in GRIA1-/- mice.The deletion of GluA1 in mice is associated with a profound reduction of EEG sleep spindling activity; yet local cortical sleep spindles may be preserved. Global EEG spindles do not seem necessary for memory consolidation, although a role for local LFP spindles cannot be excluded. These results suggest an important role of the GRIA1 gene in mediating the link between sleep and cognitive function.Latchoumane CF, Ngo HV, Born J, Shin HS (2017) Thalamic Spindles Promote Memory For-mation during Sleep through Triple Phase-Locking of Cortical, Thalamic, and Hippocampal Rhythms. Neuron 95:424–435

Lüthi A (2014) Sleep Spindles. Neuroscientist 20:243–256

Lencz T, Malhotra AK (2015) Targeting the schizophrenia genome: a fast track strategy from GWAS to clinic. Molecular Psychiatry 20:820–826

This work is supported by the Wellcome Trust, MRC NIRG, and the Clarendon Fund.


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C28

GABA and glutamate networks in the VTA regulate govern vigilance state

X. Yu1, W. Li2, Y. Ma1, K. Tossell1, J.J. Harris1,3, E.C. Harding1, W. Ba1, G. Miracca1, D. Wang2, L. Li2, J. Guo2, M. Chen4, Y. Li1, R. Yustos1, A.L. Vyssotski5, D. Burdakov3, Q. Yang2, H. Dong2, N.P. Franks1,6 and W. Wisden1,6

1Department of Life Sciences, Imperial College London, London, UK, 2Department of Anesthesiology & Perioperative Medicine, Xijing Hospital, Xi’an, China, 3The Francis Crick Institute, London, UK, 4iHuman Institute, ShanghaiTech University, Shanghai, China, 5Institute of Neuroinformatics, University of Zürich/ETH Zürich, Zürich, Switzerland and 6Centre of Excellence in Neurotechnology and UK Dementia Research Institute, Imperial College London, London, UK

We screened for novel circuits in the mouse brain that determine vigilance states. Using chemogenetic activation and EEG recordings, we converged on glutama-tergic/nitrergic (NOS1) and GABAergic neurons in the VTA. Activating glutama-tergic/NOS1 neurons, which were wake- and REM-sleep active, produced wake-fulness via the nucleus accumbens and the lateral hypothalamus. Lesioning the glutamate cells impaired the consolidation of wakefulness, with many extra tran-sitions to NREM sleep. In contrast, activation of GABAergic VTA neurons elicited a long-lasting NREM-like sleep akin to sedation. Lesioning them produced a large increase in wakefulness, which persisted for at least 4 months after lesioning. The VTA GABAergic neurons, however, are selectively wake- and REM sleep-active. Our findings suggest that VTAVgat neurons limit wakefulness by inhibiting the arousal-promoting VTA glutamatergic and/or dopamine neurons, as well as by projections to the lateral hypothalamus. Thus, the VTA, widely investigated for its contribution to goal- and reward-directed behaviors, contains circuitry with an unexpected role in regulating wakefulness.

Xiao Yu and Wen Li contributed to the study equally


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C29The Functional Anatomy the Connections between the Amygdala and Other Limbic Regions Anam Saifullah, King's College London, United Kingdom

Additional authors: Prof. Marco Catani and Mr. Ahmad Beyh at King's College London

The amygdala is a key limbic structure that contains several projections towards other limbic areas in order to regulate limbic functions such as socio-emotional behaviour. One such projection is the ventral amygdalofugal (VAF) pathway, a fundamental efferent tract towards the thalamus, hypothalamus and basal forebrain. Previous studies have described the anatomical properties of the VAF pathway, yet underlying tract-specific measurements of the VAF pathway by use of diffusion tensor imaging (DTI) tractography have never been investigated before.

The current study aimed to explore the anatomical and functional correlates of the amygdalofugal pathway in 200 healthy subjects through delineating in vivo the anatomical features of three VAF tracts using DTI tractography. Tract count, tract volume, fractional anisotropy (FA), radial diffusivity (RD) and mean diffusivity (MD) were measured to investigate differences in the underlying amygdalofugal fibre connections comparing laterality, gender and behavioural inter-individual differences, in addition to post-mortem dissections.

Results demonstrated a significant increase in fractional anisotropy within females across three VAF tracts and a further increase in tract volume within the female thalamic and hypothalamic VAF tract. Tract-specific measurements further indicated a higher RD in the hypothalamic tract within males, suggesting significant myelin differences. The largest laterality differences were found in the thalamic VAF tract, signifying a larger and less myelinated tract within the left hemisphere as a higher volume, streamline count, MD and RD were denoted. Agreeableness, positive emotion recognition and

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neuroticism correlations with the VAF pathway revealed an indication of possible, underlying tract-specific associations.

In summary, our study demonstrated a detailed trajectory of the VAF pathway in healthy subjects and revealed novel evidence for VAF sex differences and laterality differences which could be beneficial in comprehending the morphophysiology and pathophysiology of limbic disorders. It also provided evidence for suggestive associations between VAF white matter microstructure and major traits of human personality and emotional recognition. Comparison between ex vivo post-mortem and in vivo tractography of the VAF further proves its trajectories and anatomical similarities.

C30Neurocalcin regulates night sleep in Drosophila Ko-Fan Chen, UCL QS Institue of Neurology, London

Sleep is conserved across the animal kingdom and is critical for nervous system function. Drosophila sleep occurs during both day and night, and these two sleep stages exhibit distinct arousal thresholds. While circadian clock has been shown to control the timing of sleep onset, the molecular and circuit mechanisms demarcating day from night sleep remain unclear. Using a guilt-by association strategy we have identified a novel night sleep regulator, Neurocalcin (Nca): Both knocking down Nca in nervous system (NcaKD) and the complete knockout of Nca locus resulted in night time specific sleep loss and elevated arousal threshold. We therefore embarked to investigate how photoperiod/circadian clock control the night sleep loss in NcaKD flies. By manipulating LD regimes and light input signals from the visual system and Cryptochrome, we found that NcaKD mediated sleep loss is suppressed by light. Moreover, sleep loss in NcaKD flies is constrained to the subjective night during constant darkness, yet under the same condition, homogenous sleep loss across 24 hours in a clock mutant background (timKO). Collectively, these results suggest that light input signaling and circadian clock redundantly control Nca-mediated sleep. Through combinatorial Gal4 mapping we have

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delineated the neuronal substrates of NcaKD mediated sleep loss to two non-overlapping brain areas. Within these regions, we further establish that Nca promotes night sleep by suppressing synaptic release. In summary, our results define a critical sleep-regulatory role for Neurocalcin in Drosophila and advance our understanding of how distinct sleep periods are genetically regulated.

C31Smartphones: The Future of Sleep Measurement?Sophie Wouters, Imperial College School of Medicine, London, United Kingdom

Additional authors: A Smith (1) A Miller (1)Y Alqurashi (2)MJ Morrell (1,2,3)1 Imperial College School of Medicine, London, United Kingdom2 Academic Unit of Sleep and Ventilation, National Heart and Lung Institute, Imperial College London, United Kingdom3 National Institute for Health Research Respiratory Disease Biomedical Research Unit at the Royal Brompton and Harefield National Health Service Foundation Trust and Imperial College, London, United Kingdom

Background: Sleep tracking applications for smartphones, such as Sleep Cycle, are becoming increasingly popular as a method of monitoring personal sleep. However, their accuracy is disputed. Sleep apps that use the accelerometer have been shown to overestimate sleep onset latency (SOL) and total sleep time (TST) when compared to sleep measured using electroencephalography (EEG) (Bhat et al, 2015). There is no data on the accuracy of the Sleep Cycle application (most popular sleep app on the iPhone) using the microphone. Therefore, we carried out an explorative study to investigate the accuracy of the Sleep Cycle app (with microphone) in detecting TST, SOL, and number of awakenings, compared to sleep diaries and EEG.

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Methods: 11 healthy medical students (aged 18-25) underwent one night of home sleep measurement. This consisted of the Sleep Cycle app, a clinical sleep diary and polysomnography with EEG (10:20 system). Participants used the Sleep Cycle app as instructed in the app instructions. The sleep diary was standardised and participants were asked to complete it the morning after the sleep study. TST, SOL, and the number of awakenings were defined as key parameters and data for each parameter was collected using the three measurement methods. Data was blinded for method of measurement before analysis. Shapiro-Wilk testing for normality was conducted on all TST and SOL data vs EEG data, and was found to be normally distributed in each case (W>0.05). Bland-Altman plots were then created to assess agreement between Sleep cycle app vs EEG and sleep diary vs EEG measurements. Mean of differences and the limits of agreement were set as bias+/- 1.96*standard deviation.

Results: The sleep diary overestimated TST by mean: 62.1 minutes (bias = -62.1), and underestimated SOL by mean: 1.8 minutes (bias = 1.8). The Sleep cycle app underestimated TST by mean: 45.5 minutes (bias = 45.5) and underestimated SOL by mean: 25.1 minutes (bias = 25.1). For the number of awakenings, the mean (±S.D.) difference between EEG- sleep diary was 10.75 ±7.25 minutes and mean difference between EEG- Sleep cycle app was 11.38 ± 7.54 minutes, showing both sleep diary and Sleep cycle app underestimated the number of awakenings to similar extents. Conclusion: These data suggested that the Sleep cycle app was more accurate than the sleep diary at measuring TST, but less accurate at measuring SOL. Both Sleep cycle app and sleep diary underestimated the number of awakenings during sleep. If smartphone sleep apps are to be used clinically, the significance of the underestimation of sleep measurements must be considered when reviewing and offering advice.

References: Bhat S, Ferraris A, Gupta D, Mozafarian M, DeBari V, Gushway-Henry N et al. Is There a Clinical Role For Smartphone Sleep Apps? Comparison of Sleep Cycle Detection by a Smartphone

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Application to Polysomnography. Journal of Clinical Sleep Medicine. 2015; 11(7):709-15.

C32Effects on Physical Performance of One Night’s Sleep Deprivation Lindy Castell, Green Templeton College, University of Oxford, United Kingdom

Additional authors: J. C. Miller - US Air Force Research Laboratory (Retd) Brooks City-Base, San Antonio, Texas, USA

INTRODUCTIONVertical jump performance is a standardized measurement for explosive leg power and has been shown to be sensitive to sustained operations. Previous investigations have included multiple stressors (sleep loss, intense physical work, and hypocaloric diets). The present prospective study investigated the effects of one night’s sleep deprivation on healthy males undertaking this performance test.

METHODS • Fasting blood samples were drawn at 06:30am on Days 1-4 for

biochemical assays.• Participants experienced total, acute sleep deprivation for ca. 36

hours, from Day 1- Day 2 (evening).• Cognitive performance tasks were undertaken daily, and five times

during sleep deprivation.

Subjects. Male subjects (n= 8, aged 21-40 yrs; mainly military) consented to the study. Exclusions included sleep problems, infectious conditions, and/or limb injuries. The USAF Surgeon General’s Office and Brooks AF Base Review Board gave consent for the study.

Performance. Participants performed repeated standing vertical jumps each morning, using a Probiotics timing mat and cable transducer to measure jump height and ground contact time (Wiklander & Lysholm, 1987). Cognitive performance was implemented on desktop personal

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computers with the Navy’s ANAM library (Reeves et al., 2001) and Psychomotor Vigilance Task (PVT: Dinges et al., 1997). Only PVT data are reported here.

Procedures. The subjects started each experiment by fasting overnight at home (20:30-06:30). They gave a 20 ml blood sample for biochemical analysis (data not included here), seated in the Sleep Lab at 06:30 after a 15min rest, They completed one set of cognitive tasks and subjective reports, and ate breakfast on site. Day 1 was spent at work or home. All participants returned to the Sleep Lab by 18.00 for dinner. They remained awake all night, fasted (20:30-06:30). Oral temperature and psychomotor vigilance task (PVT) data was acquired hourly all night. After an 06:30 fasting blood sample (Day 2), tasks and questionnaires were completed, and participants ate breakfast on site. They stayed in the Sleep Lab during Day 2 and slept there that night. The following two mornings (Days 3-4), they completed one set of tasks and subjective reports again before leaving.

Data Analyses. Daily, early-morning data were subjected to a 2-factor, 2- x 4-level analysis of variance (ANOVA) with repeated measures. Significance levels for repeated measures were adjusted using Greenhouse-Geisser; post hoc assessments were conducted using Neuman-Keuls. The sample size of 8 provided a test power of 0.46 for a 2-tail test for an effect size of 1 standard deviation unit with a confidence level of 0.95 and independent groups (Cohen, 1988).

RESULTSVertical JumpThe three measures available were explosive jump power, jump height, and time on the ground between jumps. The 2-factor ANOVA was applied to these as both within-Day means and variabilities (as standard deviation). The analyses revealed only one significant main effect and no significant interactive effects: the effect of Day was statistically significant for jump height (F(3,24) = 6.53, MSe = 0.527,

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p(GG) = 0.099). The post hoc assessment indicated that jump height was significantly lower (about 7.6%) on Day 2 ( p < 0.05) and Day 4 (p < 0.01) than on Day 1.

PVTThere was a significantly more negative effect on PVT response speed after one night’s sleep loss (morning of Day 2).

Figure x. The effect of Day on jump height: significantly lower (7.6%) on Days 2 and 4 than on Day 1 (***p < 0.01, **p < 0.05). (n=8)

DISCUSSIONThis investigation allowedassessment of the effects of a singles stressor|: sleep loss. One night’s sleep deprivation affected sleepiness and fatigue, PVT response time, physical performance. We observed an 8% decrement in jump height between the initial value on the first morning and the morning following sleep deprivation and an 11% decrement in jump height between the initial value and the final value after two subsequent nights of recovery sleep. There was no pattern across days, suggesting a decrement due to the night’s sleep loss and then a monotonic recovery. In fact, there was a possible delayed decline in performance from Day 2 to Day 4.References: Cohen J (1988). Statistical Power Analysis for the

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Behavioral Sciences. Lawrence Erlbaum Associates, Hillsdale NJ.Dinges DF, Pack F, Williams K et al. (1997). Sleep, 20(4), 267-277.Reeves D, Winter K, Kane R et al. (2001). ANAM 2001 User’s Manual. National Cognitive Recovery Foundation, San Diego CA.Wiklander J, Lysholm J (1987). Int J Sports Med, 8(1):50-4.

C33Stereotypical task performance reduces sleep need in mice Linus Milinski, University of Oxford, United Kingdom

Additional authors: David M. Bannerman (Department of Experimental Psychology; University of Oxford, United Kingdom)Vladyslav V. Vyazovskiy (Department of Physiology, Anatomy and Genetics; University of Oxford, United Kingdom)

Objective/Introduction: Sleep need increases during waking and dissipates during subsequent sleep. The nature of the process that keeps track of the time spent awake is unknown, but the type of waking behaviour may influence the accumulation of sleep pressure. Here we tested the hypothesis that wakefulness dominated by a simple stereotypical behaviour (SB) reduces build-up of sleep pressure as compared to exploratory behaviour.

Methods: Adult male C57BL/6 mice (n=5) were anaesthetised with 2-5% isoflorane and implanted with frontal and parietal EEG electrodes and EMG wires, and after 7-10 days of recovery the animals were food restricted (85-90% of free feeding weight) and trained in a task that encouraged stereotypic behaviour (SB task). The task was based on a Bussey-Saksida Touch Screen paradigm, and consisted of initiating a trial by touching a screen followed by collecting reward from a tray on the opposite side of the chamber. The performance was motivated intermittently by providing milkshake (0.0035 ml) in the reward tray. Training was conducted over 2-4 weeks in sessions of 30-45 min per day until steady performance levels were reached. By the end of training animals typically completed 150-300 trials within a 45 min session. On the experimental day,

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the animals were placed in the touch screen chamber at light onset and allowed to perform continuously until they showed 5 consecutive minutes of inactivity. Three to four days later the animals were sleep deprived for the same duration as they had previously performed in the SB task. Sleep deprivation was conducted by providing novel objects to elicit predominantly exploratory behaviour (EB). Continuous EEG/EMG recordings were performed before and after the SB and EB wakefulness.

Results: During the unrestricted SB task performance, which lasted on average 2.5 hours (individual values: 1, 2, 3, 3 and 3.5 hours, n=5), the animals completed 156, 307, 544, 871 and 732 trials, respectively. The overall waking time (wake onset to sleep onset) was nearly identical after SB and EB wakefulness (SB 194.6±76.7min., EB 200.8±66.5min., values are given as means ± standard deviation ). The amount of Non-REM and REM sleep after the two conditions did not differ (NREM: SB 31.7±8.9min., EB 31.2±2.4min., REM: SB 5.6±7.8min., EB 3.6±2.9min.). However, after SB wakefulness, the values of EEG slow wave activity (0.5-4 Hz) during the first hour of recovery sleep was lower in all animals relative to sleep after EB wakefulness (SB 137.6±15.5%, EB 171.1±15.7% of mean SWA during baseline).

Conclusion: Our preliminary results suggest that waking behaviour affects the homeostatic sleep response. Engagement in a stereotypical task appears to reduce the build-up of sleep pressure as compared to diverse exploratory behaviour. We conclude that certain types of wakefulness, which are associated with a low cognitive/attentional demand, correspond to a ‘waking at a lower cost’.

C34Sleep during a mountain ultra-marathon: A case study Borja Martinez-Gonzalez, University of Kent, United Kingdom

Additional authors: Glen Davison (University of Kent)Samuele M. Marcora (University of Kent)

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Mountain ultra-marathon (MUM) is an ultra-endurance event where athletes run or walk over a distance longer than a standard marathon with severe elevation changes (1). No research has been done during a MUM using actigraphy, an objective alternative to polysomnography for sleep/wake behaviour (2). Tor des Geants ® is a 330 km MUM with a cumulative elevation gain of 24,000 m and 150 h time limit. For this study participants were required to wear an actigraph watch (Actiwatch Spectrum PRO, Philips Respironics, Murrysville, PA, USA) in order to monitor sleep/wake activity. Race organisers provided participants with a GPS tracker so they could be monitored on the route continuously. Two participants were recruited during 2018 edition. Participants were fully briefed about the research purposes before the start of the race and asked to sign a written informed consent. The study was approved by the School’s Research Ethics Advisory Group, in accordance to the standards set by the Declaration of Helsinki. Prior to the race, participants completed circadian rhythms (3) and sleep quality (4) questionnaires. During the race, participants were asked questions regarding sleep during the last 24 h in order to cross-check data with actiwatches. To calculate the level of sleep deprivation (SD) that participants experienced during the race, we defined a sleep deprivation index (SDI) taking 8 h of sleep as 0% of SD and calculated consequently every 24 h using the following formula: SDI = | {[(sleep (h) – 8) ÷ 8] · 100} |. Due to the nature of the study, no statistical analysis was performed. Both participants were classified as “Moderately Morning Type” and were assorted as “good sleepers”. Participant 1 completed the race in 108.9 h. Total sleep time (TST) was 3.8 h. Participant 2 finished the event in 145.3 h. TST was 6.8 h. Cumulative sleep over time can be found in Figure 1. SDI over time is shown in Figure 2. Participant 1 held a SDI > 88% for the first three days, dropping to 72% in the fourth day. After one day of total SD Participant 2 sustained SDI between 78% and 91% for the remaining five days of competition. Participant 1 slept 53.6% of total rest time while Participant 2 slept 29.0%. Participant 1 slept 3.5% of total race time while Participant 2 slept 4.7%. These data shed some light on how athletes sleep during a MUM, suggesting that faster athletes spent less time at rest, thus, less sleep, but they sleep more

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efficiently. Faster athletes may be able to hold higher levels of sleep deprivation due to a better capability to sustain a faster pace, hence to complete the race earlier than slower athletes. Further research is required to fully understand the physiological implications of different sleep strategies, including SD management and taking into account estimated race time. This could be a novel approach to optimise performance during MUM, particularly in events longer than 72 h.

Figure 1

Figure 2

Acknowledgements: The authors would like to thank GM, VZ, FG and CG for their involvement in this project.

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References: 1. Millet GP, Millet GY. Ultramarathon is an outstanding model for the study of adaptive responses to extreme load and stress. BMC Med. 2012 Jan;10(1):77. 2. de Souza L, Benedito-Silva AA, Pires ML, Poyares D, Tufik S, Calil HM. Further Validation of Actigraphy for Sleep Studies. Sleep. 2003;1:81–5. 3. Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness– eveningness in human circadian rhythms. Int J Chrono-biology. 1976;4(April):97–110. 4. Buysse DJ, Reynolds III CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A New Instrument for Psychiatric Practice and Research. Vol. 28, Psychiatry Res. 1989. p. 193–213.

C35Characterisation of individual slow waves under propofol anaesthesia Lucy Mellers, University of Oxford, United Kingdom

Additional authors: Jostein Holmgren (1,2), Jamie Sleigh (3), Katie Warnaby (1,2)1) Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom2) Nuffield Division of Anaesthetics, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom3) Department of Anaesthesia, University of Auckland, Waikato Hospital, Hamilton, New Zealand

Background: General anaesthesia is often described as a sleep-like state. Slow wave (0.5-1.5Hz) activity is a key feature of propofol anaesthesia and non-REM stage 3 sleep. Sleep slow waves are travelling waves1. It is thought that anaesthetic slow waves are similar to those observed in sleep2. Previously we showed that saturation of slow wave activity power during an ultraslow induction of propofol can provide an individualised neurophysiological marker for perception loss during anaesthesia3. However, the degree to which

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these individual slow waves share the neurophysiological properties of sleep slow waves is unclear. This study aimed to characterise the underlying waveforms of slow waves produced with increasing levels of propofol anaesthesia in order to further elucidate the underlying neurophysiological mechanisms.

Methods: 32-channel EEG from 14 subjects was acquired during ultra-slow induction of propofol anaesthesia (4μg/ml over 48 minutes). Data was referenced to the average mastoids before importing it into Sleep Wave Analysis Toolbox4. Parameters for detecting slow waves were optimized to adapt the toolbox for study of slow waves produced by anaesthesia instead of sleep. Following automated slow wave detection, each dataset was visually inspected to eliminate false positives and negatives. Each dataset was split into three sections of equal number of slow waves to allow for comparison between light and deep anaesthesia.

Results: All subjects show an exponential increase in the incidence of individual slow waves over time, as shown in A. The mean number of slow waves detected across individuals was 675.4 (SD=125). Slow waves were more likely to be detected in fronto-central areas, as shown in the topographic density map B. Preliminary analysis shows a trend towards early waves showing larger globality (percentage of channels involved in each wave), (M=75.3, SD=3.5) than late waves (M=73.1, SD=5.3, p = 0.057). The negative peak amplitude was largest prefrontally with the increase going in a posterior to anterior direction, as shown in C. These two measures were consistent across volunteers. Individual waves have travelling streams and show the least delay (time between negative peak detection at each channel) in the fronto-central region. There is also a slowing in wavelength of the slow waves over time.

Conclusions: The incidence of slow waves increases with deepening anaesthesia, and properties of individual slow waves change over this course of time as well, with an increase in wavelength and a decrease in globality. Slow waves produced under propofol anaesthesia are

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travelling waves that share certain characteristics with sleep slow waves, namely their areas of high fronto-central density and high pre-frontal amplitude. Going forward, we will further investigate potential changes in slow wave characteristics over the gradual induction to deep propofol anaesthesia.

References: 1. Massimini, M., Huber, R., Ferrarelli, F., Hill, S., & Tononi, G. (2004). The sleep slow oscillation as a traveling wave. Journal of Neuroscience, 24(31), 6862–6870. https://doi.org/10.1523/JNEUROSCI.1318-04.20042. Mensen, A., Riedner, B., & Tononi, G. (2016). Optimizing detection and analysis of slow waves in sleep EEG. Journal of Neuroscience Methods, 274, 1–12. https://doi.org/10.1016/j.jneumeth.2016.09.0063. Mhuircheartaigh, R. N., Warnaby, C., Rogers, R., Jbabdi, S., & Tracey, I. (2013). Slow-wave activity saturation and thalamocortical isolation during propofol anesthesia in humans. Science Translational Medicine, 5(208), 208ra148. https://doi.org/10.1126/scitranslmed.30060074. Murphy, M., Bruno, M.-A., Riedner, B. A., Boveroux, P., Noirhomme, Q., Landsness, E. C., … Boly, M. (2011). Propofol anesthesia and sleep: A high-density EEG study. Sleep, 34(3), 283–291.

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96 47P

AAchermann, P. . . . . . . . . . . . . . . . . . .C03, C19Aisbett, B. . . . . . . . . . . . . . . . . . . . . . . . . . . C15Alqurashi, Y. . . . . . . . . . . . . . . . . . . C09, C12*Ambler, M.T. . . . . . . . . . . . . . . . . . . . . . . C21*Aspden, J. . . . . . . . . . . . . . . . . . . . . . . . . . . C13Aubin, S. . . . . . . . . . . . . . . . . . . . . . . . . . . SA17

BBa, W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C28Babiychuk, G. . . . . . . . . . . . . . . . . . . . . . . . C04Bangi, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . C09Bannerman, D.M. . . . . . . . . . . . . . . . . . . . C27Basra, M. . . . . . . . . . . . . . . . . . . . . . . . . . . C16*Beckwith, E. . . . . . . . . . . . . . . . . . . . . . . . . C05Benson, J. . . . . . . . . . . . . . . . . . . . . . . . . . . C09Blanco Duque, C. . . . . . . . . . . . . . . . . . . . C27*Boylan, P. . . . . . . . . . . . . . . . . . . . . . . . . . . C06Brown, T. . . . . . . . . . . . . . . . . . . . . . .C07, C11Buhl, E. . . . . . . . . . . . . . . . . . . . . . . . . . . . C08*Burdakov, D. . . . . . . . . . . . . . . . . . . . . . . . C28

CCampbell, M. . . . . . . . . . . . . . . . . . . . . . . . C06Cerri, M. . . . . . . . . . . . . . . . . . . . . . . . . . . . C21Cheema, A. . . . . . . . . . . . . . . . . . . . . . . . . C02Chen, M. . . . . . . . . . . . . . . . . . . . . . . . . . . . C28Christensen, J.A. . . . . . . . . . . . . . . . . . . SA17*Cirelli, C. . . . . . . . . . . . . . . . . . . . . . . . . . SA04*Curran, J. . . . . . . . . . . . . . . . . . . . . . . . . . . C08

DDawidziuk, A. . . . . . . . . . . . . . . . . . . . . . . . C12Deuchars, J. . . . . . . . . . . . . . . . . . . . . . . . . C13Deuchars, S. . . . . . . . . . . . . . . . . . . . . . . . . C13Dong, H. . . . . . . . . . . . . . . . . . . . . . . . . . . . C28Dorji, T. . . . . . . . . . . . . . . . . . . . . . . . . . . . C23*Dunne, F. . . . . . . . . . . . . . . . . . . . . . . . . . . C06

EEllis, J.G. . . . . . . . . . . . . . . . . . . . . . . . . . . . C18

FFisk, A. . . . . . . . . . . . . . . . . . . . . . . . . . . . C26*Foster, R.G. . . . . . . . . . . . . . . . . . . . . . . SA18*Franks, N. . . . . . . . . . . . . . . . . . . . . . . . . SA01*Franks, N.P. . . . . . . . . . . . . . . . . . . . . . . . . C28French, A.T. . . . . . . . . . . . . . . . . . . . . . . . C05*

GGeissmann, Q. . . . . . . . . . . . . . . . . . . . . . . C05Gilestro, G.F. . . . . . . . . . . . . . . . . SA02*, C05Goadsby, P. . . . . . . . . . . . . . . . . . . . . . . . SA10Green, D. . . . . . . . . . . . . . . . . . . . . . . . . . SA10Guillaumin, M. . . . . . . . . . . . . . . . . C03*, C19Guo, J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C28

HHan, W. . . . . . . . . . . . . . . . . . . . . . . . . . . . C22Harding, C. . . . . . . . . . . . . . . . . . . . . . . . . . C07Harding, E.C. . . . . . . . . . . . . . . . . . . . . . . . C28Harridge, S. . . . . . . . . . . . . . . . . . . . . . . . SA10Harris, J.J. . . . . . . . . . . . . . . . . . . . . . . . . . . C28Hasegawa, H. . . . . . . . . . . . . . . . . . . . . . . SA10Hastings, M. . . . . . . . . . . . . . . . . . . . . . . SA15*Hauglund, N.L. . . . . . . . . . . . . . . . . . . . . . C01*Herring, M. . . . . . . . . . . . . . . . . . . . . . . . . . C06Higgins, S. . . . . . . . . . . . . . . . . . . . . . . . . SA10Higham, J. . . . . . . . . . . . . . . . . . . . . . . . . . C08Hodge, J. . . . . . . . . . . . . . . . . . . . . . . . . . . . C08Hoerder-Suabedissen, A. . . . . . . . . . . . . . C10Horner, R. . . . . . . . . . . . . . . . . . . . . . . . . SA11*Huang, Y. . . . . . . . . . . . . . . . . . . . . . . . . . C24*

IIssartel, J. . . . . . . . . . . . . . . . . . . . . . . . . . . C06

JJackson, W. . . . . . . . . . . . . . . . . . . . . . . . . C09Jagannath, A. . . . . . . . . . . . . . . . . . . . . . . SA18James-Harvey, C. . . . . . . . . . . .C02, C09, C22,

C23, C25Jennum, P.J. . . . . . . . . . . . . . . . . . . . . . . . SA17

KKelly, J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C09Keyoumars, A. . . . . . . . . . . . . . . . . . . . . . SA10Kim, W. . . . . . . . . . . . . . . . . . . . . . . . . . . . C22*Koomson, A. . . . . . . . . . . . . . . . . . . . . . . . C25Krone, L. . . . . . . . . . . . . . . . . . . . . . C10*, C27Kupers, R. . . . . . . . . . . . . . . . . . . . . . . . . . SA17

LLee, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C25*Leschziner, G.D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .SA10Li, L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C28Li, W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C28

9748P

Li, Y. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C28Lim, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C17Lomako, V. . . . . . . . . . . . . . . . . . . . . . . . . . C04Lowe, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . C23Lucas, R. . . . . . . . . . . . . . . . . . . . . . . . . . . . C11Lyons, D.G. . . . . . . . . . . . . . . . . . . . . . . . . C20*

MMa, Y. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C28Macey-Dare, A. . . . . . . . . . . . . . . . . . . . . C09*Martial, F. . . . . . . . . . . . . . . . . . . . . . . . . . . C11McKillop, L. . . . . . . . . . . . . . . . . . . . .C19, C27Miracca, G. . . . . . . . . . . . . . . . . . . . . . . . . . C28Molnár, Z. . . . . . . . . . . . . . . . . . . . . . . . . . . C10Morrell, M.J. . . . . . . . . . . C02, C09, C12, C16,

C22, C23, C25Morris-Paterson, T. . . . . . . . . . . . . . . . . . SA10Moss, J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C12Mouland, J. . . . . . . . . . . . . . . . . . . . . . . . . C11*

NNathan, C. . . . . . . . . . . . . . . . . . . . . . . . . C13*Nielsen, T. . . . . . . . . . . . . . . . . . . . . . . . . SA17Nolan, P. . . . . . . . . . . . . . . . . . . . . . . . . . . . C03

OO’Hagan, A. . . . . . . . . . . . . . . . . . . . . . . . C06*Ozcan, G. . . . . . . . . . . . . . . . . . . . . . . . . . C17*

PPaul, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . C07*Peart, D.J. . . . . . . . . . . . . . . . . . . . . . . . . . . C18Peirson, S. . . . . . . . . . . . . . . . . . . . . .C03, C26Pickering, A. . . . . . . . . . . . . . . . . . . . . . . . . C21Polkey, M. . . . . . . . . . . . . . . . . . . . . . . . . . C12Ptito, M. . . . . . . . . . . . . . . . . . . . . . . . . . . SA17Purple, R.J. . . . . . . . . . . . . . . . . . . . . . . . . . C27

QQiu, C. . . . . . . . . . . . . . . . . . . . . . . . C02*, C09

RReichert, S. . . . . . . . . . . . . . . . . . . . . . . . . . C20Rihel, J. . . . . . . . . . . . . . . . . . . . . . . . .C17, C20

Roberts, S. . . . . . . . . . . . . . . . . . . . . . . . . C15*Rose, T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C22Rosenzweig, I. . . . . . . . . . . . . . . . . . . . . SA10*

SSamy, M. . . . . . . . . . . . . . . . . . . . . . . . . . . C25Sharma, S. . . . . . . . . . . . . . . . . . . . . . . . . . C23Shylo, O. . . . . . . . . . . . . . . . . . . . . . . . . . . C04*Sweeney, E. . . . . . . . . . . . . . . . . . . . . . . . C18*

TTeo, W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C15Terry, S. . . . . . . . . . . . . . . . . . . . . . . . . . . . C16Thomas, C. . . . . . . . . . . . . . . . . . . . . . . . . C14*Thomas, C.W. . . . . . . . . . . . . . . . . . . . . . C19*Tossell, K. . . . . . . . . . . . . . . . . . . . . . . . . . . C28Tsai, C. . . . . . . . . . . . . . . . . . . . . . . . . . . . SA10

VVasudevan, S. . . . . . . . . . . . . . . . . . . . . . SA18Vyazovskiy, V. . . . . . . . . . . SA03*, C03, C10,

C19, C24, C26, C27Vyssotski, A.L. . . . . . . . . . . . . . . . . . . . . . . C28

WWall, A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C06Walmsley, L. . . . . . . . . . . . . . . . . . . . . . . . C07Walshe, I.H. . . . . . . . . . . . . . . . . . . . . . . . . C18Wang, D. . . . . . . . . . . . . . . . . . . . . . . . . . . C28Warmington, S.A. . . . . . . . . . . . . . . . . . . . C15Warrington, G. . . . . . . . . . . . . . . . . . . . . . C06Wisden, W. . . . . . . . . . . . . . . . . . . . . . . . . C28Wringe, D. . . . . . . . . . . . . . . . . . . . . . . . . . C16

YYamagata, T. . . . . . . . . . . . . . . . . . . .C10, C27Yang, Q. . . . . . . . . . . . . . . . . . . . . . . . . . . . C28Yu, X. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C28*Yu, Y. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .C02Yustos, R. . . . . . . . . . . . . . . . . . . . . . . . . . . C28

98

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