The inhibitory role of top-down alpha-band oscillations in the working memory context

8/12/2019 The inhibitory role of top-down alpha-band oscillations in the working memory context

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The inhibitory role of top-down alpha-band

oscillations in the working memory context

State of the art essay II) MSc in NeuroimagingMario B. Perez

4/4/2014


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State of the Art Essay (II) - Mario B. Perez

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The inhibitory role of top-down alpha-band oscillations inthe working memory context

Index

I. Introduction : Establishing inhibition

II. The roles of alpha inhibitory activity: Enabling, suppressing and rejecting

- Top-down alpha during pre-encoding, stimulus onset, and encoding of items

- Dynamic encoding: Selective processing as a result of instructions

- Inhibiting task-irrelevant areas: Default or on-demand inhibition?

- Alpha inhibition during maintenance: Rejecting distractors and keeping items

uncorrupted.

III. Critical considerations & Future Directions

- Cueing and management of temporal expectations

- Setting up tasks: the importance of tasks properties

- Detaching roles and measuring sources

- Future directions; the interplay between phase and amplitude

IV.Conclusions

V. References


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I. Introdu ct ion : Establ ishing inh ib i t ion

Alpha oscillatory activity was the firstly discovered (Millet, 2001) and is the most prominentneural rhythm recorded in the human brain (Klimesch et al, 1999). Despite his remarkably antique

origin, the number and extent of its competencies is object of a lively and vigorous discussion, and the

study of alpha oscillatory activity has gained great popularity over the last decade (Payne and

Sekuler, 2013).

As it is widely known, alpha oscillations were initially thought to reflect cortical idling (Adrian

and Matthews, 1934). However, this view was later began to be questioned (Pfurtscheller et al, 1996),

and some authors reported the appearance of alpha activity during internal processing which were

supposed to not to require attention from the environment (Ray and Cole, 1985), reflecting the first

observations of alpha activity over disengaged areas. Posterior research by Pfurtscheller (2001),

Klimesch (1996) and many others described in more detail the appearance of alpha rhythm event-

related desynchronization (ERD) in occipital areas during visual information processing, whereasevent-related synchronization (ERS) appears in inactive areas.

The current stage in literature was in part established by a second series of articles which

started to talk about these relations in a generalized way, and which benefited from the accumulated

evidence (e.g Jensen et al, 2002; Sauseng et al 2005) in support of alpha oscillatory activity as a

mechanism to engage and disengage areas from activity (Klimesch et al, 2007; Jensen and Mazaheri,

2010). In particular, the landmark study by Klimesch et al (2007) pointed out that upper-alpha band

frequency power disappearance is particularly coupled with active cognitive processing. Additionally,

both articles stressed that alpha activity can be modulated in a top-down fashion, representing

functional inhibition.

This alpha inhibitory framework has posteriorly gained substantial empirical support which

has increased over the last years (Hanslmayr et al., 2007; van Dijk et al., 2008; Sauseng et al, 2009;

Handel et al 2011; Haegens et al 2011 & 2012; Roux et al, 2012; Klimesch et al, 2012). Many of these

studies used working memory paradigms (Jensen and Mazaheri, 2010), showing how alpha activity

disappeared in engaged areas and reinforced in pertinent ones, or suddenly reappeared when task-

irrelevant stimuli appeared.

However, although evidence appears to be extensive, literature regarding alpha oscillations

has been in occasions chaotic and unclear in the range of processes in which alpha inhibition takes

place. It is frequent to find a lack of agreement in to what extent this phenomenon is present in

working memory or attentional tasks (Palva and Palva, 2007). This may be in part caused by the lack

of replicability in some aspects of the framework described by Klimesch (2007), perhaps due to acertain tendency in finding new contexts and applications instead of securing the grounds.

In the following sections we will try to present a coherent and fluid view of the alpha inhibitory

role in a WM environment. WM tasks normally follow a structured set of processes; the information

needs to be adequately perceived and encoded, then the internal copy of the items presented needs

to be maintained and finally these items will be used for a comparison or perhaps a manipulation task

(Haenschel and Linden, 2011). The relatively developed stage of WM theory (Baddeley,2003) and its

position as binding point between perceptual and cognitive domains makes of WM an excellent

framework to make the most of EEG and MEG measurements, and current electrophysiological

models of WM are being developed (Roux and Uhlhaas, 2014).


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Apart from its theoretical usability, WM proves to be worth of studying as its impairment have

been related with deficits in inhibitory function (Park and Reuter-Lorentz 2009) and failures in

inhibition are considered to be key symptoms of Alzheimers disease (Amieva et al, 2004; Belleville et

al 2006) schizophrenia (Haenschel and Linden, 2011) or even related to normal ageing (Zanto andGazzaley, 2009; Belanger et al, 2010).

II. The roles of alpha inhib i tory act iv i ty: Enabl ing, supp ressing and

reject ing

Once this general inhibitory character of alpha activity has been established, its significance

can vary in function of when these oscillations appear along the timeline (see graph below) and in

which localizations, as these sites may be differently relevant for the WM task (Klimesh et al, 2007).

Hence, alpha power modulations might reflect enabling/disabling of processing at the beginning of atask as a product of cueing (pre-stimulus, Klimesch et al, 2007 or Payne and Sekuler, 2013), selective

suppression of processing in situations in which irrelevant and relevant information appear together

(dynamic encoding, e.g Freunberger, 2009 or Horschig et al, 2014) or perhaps protection of the held

items against distractors in the maintenance phase (rejection of intruders or distractors, Bonnefond

and Jensen, 2012).

Figure 1: The below graph provides an overview of the following sections. Image (left) from Payne and Sekuler

(2013), which provides some examples of pre-stimulus alpha power modulation in somatosensory, ortographic, auditory or

visual tasks. Image (right) from Freunberger et al, (2009) will be discussed in the following. Flow graph created by author.

Pre-encoding

Enabling/disabling

Klimesch et al 2007

Stimulusonset

Readiness

Payne and Sekuler,2013

EncodingSelective

Processing

Freunberger et al2009

Retention

Rejectingintruders

Bonnefond and Jensen 2012

Timeline

CUEING Looking at alpha inhibition in the WM context (Sternberg)


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So far, the vast majority of up to date literature has considered alpha power or alphaamplitude as default elements (Palva and Palva, 2007) and we will do so as well. Therefore, unless

specified we will be always referring to alpha activity as amplitude modulation, although in the closing

sections we will pay attention to other components such as phase coupling or locking.

Top-down alpha during pre-encoding , st imu lus onset, and encodin g of i tems

Enhancement of alpha activity over task-relevant areas may appear at the beginning of a task

when the appearance of an irrelevant item is announced by cueing (Rohenkohl and Nobre,2012;

Payne and Sekuler, 2013 for a good review) and it is not required to be processed, normally known as

suppression of processing by alpha ERS. Conversely, alpha power can drop as a result of cued

relevant itemsappearance, therefore enabling processing through alpha ERD in relevant places for

the task (Klimesch et al, 2007).

This modulatory role extends from pre-encoding to encoding phases, as it can happen either

in the middle of a task or at the beginning of a task when explicit cueing is provided. More importantly,

this process reflects the control of the subject upon its attentional resources (Wilsch et al, 2014) and

can be understood as an electrophysiological correlate of attentional top-down management

(Klimesch, 2012). Impairments in this process would entail deficiencies in WM tasks as suppression is

a key skill in working memory functioning (BelanVogel et al 2005). Clear evidence of this role can be

found at Haegens et al (2011) where a correlation between pre-stimulus alpha suppression and

performance in a somatosensory discriminatory were found in the somatosensory cortex for the

attended side, in which stimuli appearance was expected. As Payne and Sekuler (2013) state, correctdiscrimination increases as pre-stimulus alpha decreases, and accuracy in the task and speed of

response were both correlated with the alpha degree. Additionally, alpha presence varied when the

reliability of the cueing was modified, suggesting a strong top-down modulation.

More sophisticated evidence of cueings and temporal expectations relevance can be found at

the study by Wilsch et al (2014) in which three different types of cueing were used (early,

neutral/uninformative and late) in an auditory delayed-to-match working memory task. This task

consisted in the comparison of two syllables, identifying if the first consonant used was the same in

both cases or different. Items were embedded in a sort of background noise, providing a complex

presentation, perhaps resembling a conversation in a noisy environment.

The authors successfully reasoned that the noise would increase the need of functional

inhibition, thus boosting the presence of alpha rhythm. Critically, temporal expectancy manipulated by

cueing effectively modulated alpha power, which strategically dropped when the task-relevant

information (syllable) was about to be presented knowing when to listen (figures A and B in the

below illustrations). Trials in which a long cueing was provided revealed the higher drops in alpha

inhibition and yielded the best performances (also in Mazaheri et al,2010 and Hanslmayr et al, 2007,

or Obleser and Weisz, 2012 for an auditory example) Moreover, and as can be seen in the illustration

below (figure C), alpha modulations (defined by the difference in power between neutral and cued)

predicted accuracy in the task.


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Figure 2: Wilsch et al, 2014.

Figure 3: Wilsch et al, 2014.

Furthermore, Sauseng et al (2009) conducted an experiment using a WM task which

consisted in two ensembles of differently coloured squares (varying from two to six), one in each hemi

field and which colours have to be memorized . A cue informed the participant of which of the two

arrays have to be ignored and which one has to be remembered. The authors reasoned that if alpha

activity is related with the suppression of irrelevant stimuli's processing, and successful ignoring of

irrelevant information is required for efficient WM performance, then lateralized alpha (difference of

alpha amplitude between hemispheres) must grow as the amount of irrelevant information does.

Illustration B below shows how amplitude increases in the ipsilateral hemisphere to relevant

information while decreasing in the contralateral one (processing relevant items). Illustration C

shows how lateralized alpha predicts capacity to retain items based on the capacity to ignore

irrelevant information as alpha grows. Handel et al (2011) and Mathewson et al (2009) have found

similar results relating successful ignoring and performance.


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Figure 4: Sauseng et al, 2009Figure 5 Sauseng et al, 2009

Additionally, Sauseng et al (2009) used rTMS in an attempt to boost retention capacity by

inducing alpha (10Hz) activity over the task-irrelevant sites. They also applied entrained alpha activity

over task-relevant locations. Results showed a significant increase of short memory capacity when

rTMS was applied over task-irrelevant areas, while a decrease took part when applied over task-

relevant ones (maintaining items). Cleverly, authors delivered also activity of a diverse range of

frequencies, finding these effects specific for induced alpha rhythm, as can be seen in the illustrationbelow. Enhancement in memory capacity for items was specific of alpha rhythm at 10Hz. Romei et al

(2010) found similar results using TMS while inducing impairment for stimulis detection using

entrainment of alpha waves in an attentional task, inducing blindness to targets when oscillations

were delivered over task-irrelevant visual areas.

Figure 6: Sauseng et al, 2009


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Dynamic encoding: Selective encoding and cognitive cherry pickingas result ofinst ruct ions

In a logic extension of the previous role, alpha activity suppression of processing can also be

observed in more dynamic, fast-changing environments taking advantage of MEG/EEG temporal

resolution. The main difference with the previous section is the intermixed, alternative manner in

which the relevant/irrelevant information is presented. In this sense, alpha activity plays a critical role

in successful encoding (Rihs et al 2007; Haegens et al 2010 ; Zanto et al, 2011 ;Haegens et al 2011

;Roux et al 2012; Payne et al 2013 ;Horschig et al 2014). Also, task-relevant and task-irrelevant items

might appear according some instructions given at the beginning and without one-to-one cueing, or

perhaps without explicit cueing at all (Horschig et al,2014). Relevantly, speed in discrimination has

been related with alpha activity (vanRullen et al, 2011).

Irrelevant information in a constantly changing environment can be presented in a very

diverse sort of situations and under different mixes with relevant items. Therefore, alpha activity hasto adapt to the perceptual scene For example, irrelevant information can appear in combination with

relevant information but segregated in space (visually, Sauseng et al, 2009,; tactile presentation in

different points, Haegens et al, 2012) or in the same spatial location but segregated in time

(Freunberger et al, 2009; Payne et al, 2013). It can also be the case that two different features are

present in the same stimuli/items, but only one of them is relevant for further processing, making the

inhibition work only on some aspects of what looks a unitary scene (Snyder and Foxe, 2010 e.g

remember colours and not shapes).Finally, items can appear in different sensorial modalities at the

same time (as exemplified in Klimesch et al, 2012). All of these situations represent a challenge while

picking the important information and forgetting or not processing information. This cognitive cherry

pickingselects the relevant information out from the stimuli stream, and it is key any further cognitive

functions. Alpha is therefore related with the internal control of attention once again (Klimesch et al,2007). Given the remarkably storage-limited capacity of WM (Cowan, 2010), this suppression

character of alpha activity acquires a critical importance, and efficient performance at WM tasks has

been directly related with the successful inhibition of distracting stimuli (Gazzaley and Nobre,2012;

Freunberger et al, 2011). Intrusion of task-irrelevant information is a major cause of failures in WM

(Hasher and Zacks,1988 as quoted in Freunberger et al, 2009; Zanto and Gazzaley, 2009).

Freunberger et al (2009) designed an experiment in the context of a Sternberg WM task. In

this study, a set of 16 items per trial were presented to participants, 8 of them have to be

remembered. After this trial, a probing item was displayed and the subject should indicate if it is an old

(previously presented) or new (not previously presented) item. Activity of alpha waves were expected

in parieto-occipital sites, supposedly related with blocking/enabling memory processing.

Enhancement of alpha power especially of in its upper frequencies was visible during to-be-

remembered items exposition, while functional inhibition took place during the presentation of

irrelevant items evidencing a strong top-down regulation (Leiberg et al, 2006, found similar results for

auditory Sternberg task) the illustration below shows this last effect.


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Figure 7: Freunberger et al, 2009

In a more complex way, the remarkable study by Horschig et al (2014) holds an special

importance among the alpha modulatory activity literature. In this experiment the subjects were

exposed to a task in which the to-be-attended hemi field will change without explicit cueing of it.

However, with each trial in which the attended hemi field remained the same the implicit probabilities

of a change were higher, so the subjects were dedicating an increasing amount of covert attention to

the opposite hemi field. This top-down covert attention was operatized by the amount of anticipatory

posterior alpha, which demonstrated to be correlated with performance.

Inhibi t ing task-irrelevant areas: Default or on -demand inhibi t ion ?

The definition of what it is a task-irrelevant area is slippery. A task-irrelevant area can be so

because the stimulus that is being presented in the perceptual scene is non-pertinent to the task, and

thus, its processing must by inhibited. As an example of this apart from the Sauseng et al (2009),

Haegens et al (2012) showed how subjects who performed better in a somatosensory WM task and

were less affected by the distractors described stronger alpha power ipsilateral to the side in which

relevant stimulation is presented.

However, task-irrelevant areas are also all those locations in which processing is not

expected to happen. Alpha power in these areas has been object of controversy, as some authors

consider that such is only possible as a result of a distractors appearance, or in case that those areasare inhibited by default, like if the mere spatial location will be a distractor itself (Klimesch et al, 2007;

Payne et al 2013). In this line, Klimesch et al (2012) state that alpha ERS in irrelevant areas reflect

protection against potential interfering processes.

Worden et al (2000, as quoted in Horschig et al, 2014) has nonetheless demonstrated the

incensement in irrelevant areas and the decrease in relevant ones without presence of distractors.

Additionally, Haegens et al. (2010) described that alpha activity over occipital sites during the

retention period of a somatosensory WM task was observed and correlated with performance,

constituting initial evidence for the necessity of alpha waves over task irrelevant locations in

distractors absence (see illustration below).


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Tuladhar et al (2007) and Scheeringa et al in a joint EEG/fMRI study (2009) have shown the

same pattern of alpha activity over posterior sites during WM maintenance, and alpha during the

retention period and without the presence of an obvious distractor has been correlated with the

number of items to be remembered (Jensen et al, 2002; Sauseng et al, 2009; Wilsch et al 2014).

Figure 8: Haegens et al, 2010

Some researchers have attached to this activity an additional role, ensuring the correct

distribution of resources (Tuladhar et al, 2007; Jensen and Mazaheri, 2010; Payne and Sekuler,

2013). Additionally, Jensen and Mazaheri (2010) proposed a model of brain communication and

information routing based on the presence of these oscillations, which in theory must help to distributethe information across different areas and subsystems. Evidence in support of this model can at best

be qualified of circumstantial.

Alph a inhibi tory act iv i ty durin g MaintenanceReject ing dis tractors andkeeping items un corrup ted.

As was mentioned in the previous section, alpha activity has been also observed during WM

retention and maintenance (Jensen et al 2002; Jokisch and Jensen, 2007; Haegens et al, 2010;

Bonnefond and Jensen 2012; Payne et al 2013 are some examples). Although there is some debate

concerning the role that alpha might be accomplishing, that we will examine in the last sections, there

are some good examples of the relevance of alpha oscillations in this stage.

Thus, Bonnefond and Jensen (2012) used the Sternberg WM memory task paradigm to test

the impact of two sets of distracting/intrusion items during the retention phase, one of them labelled

as strong, with high resemblance to memorized items, and weak with low resemblance.

Appearance of the distracter was expected by explicit cueing. Alpha oscillations increased previously

to distracters appearance and predicted individual performance in the task, furthermore, differences

in alpha power correlated negatively with divergences in reaction times. Consequently, subjects that

showed an increased alpha power before strong distracters appearance were also the subjects with

quickest response times during memory probing.


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In a thoughtful study, Payne, Guillroy and Sekuler (2013) carried out an experiment to

evaluate the role of alpha oscillations in the protection of retained stimuli using a short-memory task

with Gabor patches. Participants have to remember the spatial frequency of a Gabor patch to later

reproduce it. Before the reproduction test, other Gabor patch with different spatial frequency waspresented to subjects that were instructed to ignore this item. In the test in which the target Gabor

patch has to be reproduced, subjects used a software which allow them to manipulate the spatial

frequency until participant thinks that matches the target stimuli. This allowed the authors to have a

exact measurement of the distortion induced by the presentation of task-irrelevant material over the

target one. Participants with higher alpha activity when the distractor stimulus was presented also

maintained a less corrupted version of the stimuli to be remembered. The authors interpreted this as

evidence that alpha activity acts as a filter for irrelevant information. The illustration below shows the

non-target effect influence of distractor over the target Gabor patch in pre -stimulus and onset of the

distractor during WM maintenance. Note the value of correlation coefficients.

Figure 9: Payne, Guillroy and Sekuler, 2013

Therefore, alpha activity is also key for retaining and maintaining the fidelity of the items in

the WM retention against the possible intrusions. This property is capital as intrusion of task-irrelevant

items is a major cause of failures in WM, particularly in the aged population (Zanto and Gazzaley,

2009).

III. Crit ical considerat ions & Future Direct ions

Cueing and management of temp oral expectat ions

One of the fundamental problems concerning literature about alpha inhibition in pre-encoding

and dynamic encoding roles is how to establish an appropriate cueing to avoid possible confounds.

Alpha suppression or alpha ERD can appear due to incoming activity in a bottom-up fashion as an

stimulus in being processed, as the stimulus simply appear (Ray and Cole, 1985; Klimesch et al,

1999). Thus, cue processing (or stimulus appearance, for that matter) and cues top-down effect can

mix up if cueing and stimulus onset are too close. According to Klimesch et al (2012) alpha

suppression is expected between 200500 ms after stimulus onset whereas Rihs et al (2007) says

that alpha ERD as a result of cueing is expected to appear at 400-600 ms after stimulus onset,

revealing an overlap between the two modalities.


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Conversely, the opposite problem might also appear. Late or very early cueing would not

lead to an immediate appearance of alpha suppression while when short cueing was provided alpha

suppression appeared almost instantly. Payne et al (2013) varied from 300 to 900 ms the cueing of

the distractor stimulus, when cueing was presented 300ms modulation of alpha began straight away,whereas 900 ms cueing resulted in a modulatory effect several hundred milliseconds after onset. A

possible reason for this delay, as we are talking about top-down modulations, would be that the

participant is aware of the incoming appearance of a stimulus, but does not expect it in the immediate

term and therefore delays the action of attention focusing. This could be solved setting intervals of

appearance or jittering like in the study by Wilsch et al (2014). These issues are especially relevant

when we consider the use of time-frequency instead of evoked-response analysis in the field, as

expectancy changes in alpha amplitude might be diffuse over time.

Sett ing up tasks: the impo rtance of tasks proper t ies

The nature of the WM is a common topic of discussion. While there is a trend to use

competitive visual stimuli (for example two arrays of different visual targets e.g Sauseng et al, 2009 or

Handel et al 2011) there is some controversy about how of appropriated these stimuli are. Thus,

modulations in alpha power can be found over the left hemisphere but in occasions not over the right

one, as in Horschig et al (2014). There is some consistency about a differential behaviour between

the two hemispheres, which states that left parietal regions process right hemi field visual stimuli while

right parietal regions process a certain amount of both hem fields output (Sack, 2009 as quoted in

Zanto et al, 2014). A similar effect has been claimed in somatosensory tasks (Haegens et al 2011).

Task properties are also relevant when it comes to ensure that inhibition or suppression has

actually taken place. In the experiment used to exemplify dynamic encoding (Freunberger et al 2009)

the reader will note that there is actually no way to ensure that irrelevant items have in fact being

ignored and not entered the WM retention system.

A way to overcome this problem can be seen in other of the examples, this time by Payne et

al (2013) in which Gabor patches were used. In that case, the impact of the task-irrelevant information

is made explicit by making a discrete (remember/no remember) category quantifiable in terms of the

percentage of the spatial frequency change due to distractors influence in the reproduction made by

the subject. Although witty, this task proved to be very easy for participants, in especial when the

task-irrelevant item was presented in first place and the task-relevant patch in the second.

Detaching ro les and measur ing sources

The tasks inherent properties are perhaps especially important regarding WM maintenance

and retention studies. It is important to notice that caution is advisable while approaching this kind of

experiments as alpha activity can be easily misunderstood if the experimental setting is not correctlysettled. When the stimuli that has to be ignored and the stimuli that has to be memorized are shown

at the same time, and especially if both stimuli are of the same modality (like two visual figures) to

disentangle between the possible contributions of alpha activity can be complicated.

This confusion arises from the potential role that alpha might be accomplishing, if intervening

directly in items maintenance (Palva and Palva, 2007, Roux and Uhlhaas, 2014) or suppressing and

rejecting possible intrusions (Freunberger et al 2009; Bonnefond and Jensen, 2012; Payne and

Sekuler, 2013). Normally, this distinction is drawn based on where the activity is located, if in task-

relevant or in task-irrelevant sites. Noteworthy, this distinction is often difficult to be established as

extensive parts of the current body of evidence supporting the inhibitory role of alpha oscillations are

based in EEG recordings, which involve a considerable spatial smearing (Palva and Palva, 2007).


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Is in this framework in which studies involving joint EEG/fMRI recordings have the best

opportunity to make a unique contribution in finding an answer for this dilemma. Furthermore, BOLD

signal has been found to correlate negatively with alpha activity (Scheeringa et al, 2009; look at

Jensen and Mazaheri 2010 for more examples).There is other issue when recording alpha-band activity regarding the place of its origin.

Alpha activity is thought to appear from cortico-cortico sources or cortico-thalamic sources (Nicolelis

and Fanselow, 2002) and it is thought to accomplish a open/closing function of the thalamic gates

thus enabling or disabling processing. It is less clear how efficiently alpha activity can be measured

from such sources, again being here relevant complementary studies with fMRI or perhaps using

invasive recordings in animal models.

Future direct ions; th e interplay between phase and ampli tud e

Most of the research to date has focused on amplitude measurements to assess the role ofalpha oscillations. However, a significant but yet a reduced part of the research community have

claimed that other components might have something to add to this ongoing conversation, like phase

or perhaps temporal envelopes (Palva and Palva, 2007; Mazaheri and Jensen, 2009; Payne et al,

2013).

More specifically, Palva and Palva (2007) have claimed that it is phase rather than amplitude

the component that carries on with the functional significance of alpha oscillations, attributing to

alpha-band rhythmicity a key role in attention and consciousness and against the widely accepted

alpha amplitude thesis. They also pointed out that alpha phase reordering can take place in the

absence of alpha amplitude changes (supported by Hanslmayr et al,2005), and even during alpha

amplitude suppression. Palva and Palva base their claims of an active role for alpha phase coherence

mainly in studies in which an increase in phase synchrony is spotted around frontal areas (mainly

mental calculations Palva et al, 2005, Halgren et al, 2002 or perceptual selection Mima et al 2001)

although authors intended a broader generalization.

Perhaps more interestingly, Freunberger et al (2009) proposes that alpha phase serves as a

mechanism relevant for neural activity timing and in the binding of memory processes, showing how

increase in alpha phase locking in low alpha frequencies (7-12Hz) takes place for items that have to

be remembered later on in a WM task. Crucially, in this study the amplitude component was also

examined, and authors observed an increase in phase coupling around stimulus onset together with a

ERD for to-be-remembered items. The increase in phase-locking would be then a marker of

information encoding, similarly to the way in which was originally proposed by Klimesch et al (2007),

and possibly a marker of phase resetting. In a later article, Freunberger et al (2011) developed thatthe role played by phase could reside in the segregation of items, while keeping them in a coherent

and integrated whole.

This series of articles by Fruenberger et al (2009; 2011) can provide powerful enriched

framework that might improve our understanding of alpha oscillations in WM tasks as seen in the

below graph


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Amplitude Phase

To-be-remembered amplitude (a) (PLI*)(7-12Hz)Not-to-be-remembered amplitude (a) (PLI*)

(7-12Hz)

*Phase Locking Index --Figure 10:Adapted from Freunberger et al, 2009, made by author.

Klimesch et al (2012) shaped further the Fruenbergers framework of amplitude and phasesuggesting that amplitude manages the width of the encoding slots. This function of amplitude will be

however a question of grading because while in a moderate manner amplitude will serve as referred,

amplitude in the higher extent would inhibit any processing. Is in this sense, phase angle will be

relevant at the start of the information encoding in its interplay with the P1 component.

Figure 11: Klimesch et al, 2012

This hypothesis presented by Klimesch et al (2012) has yet to find solid experimental support,

to the best of the authors knowledge . However, Zanto et al (2014) found promising results when

embracing this framework in an experiment using a WM task context. Briefly, they found improved

performance while TMS pulses were delivered during the peak of the alpha oscillation compared to

when it were delivered in a trough before stimulus onset (illustration above provides a short rationale,

peak must coincide with P1 component appearance). Additional evidence that have taken advantage

of phase can be found in Roux et al (2012), in which interareal phase synchronization was found to

be relevant for WM maintenance.

Perhaps, some of the studies that lack of coherence within the alpha inhibition theory will find

some more sense when phase components are also take into account. Phase measurements might

also prove to be profitable in their integration with cross-frequency models and nested oscillatory

paradigms. To discuss these models will be well beyond the objective of this essay, although the

interested reader could find useful Roux and Uhlhaas (2014) in the WM domain. In a last remark,

studies combining MRS spectroscopy and EEG are suggestive, as alpha is as well thought to beevoked with the help of inhibitory interneurons (Buzsaki and Chrobak, 1995).


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Potential manipulations over GABA levels looking for a correlate in alpha inhibitory activity and

WM performance in studies similar to the one by Freunberger et al (2009) could complement existent

TMS evidence (Sauseng et al 2009; Romei et al, 2010) about the role of alpha oscillations.

IV. Conclus ions

There are several ways in which alpha oscillations contribute to successful performance in

WM tasks by exerting its inhibitory role. The suppression of irrelevant information in early stages of

processing saves valuable resources needed for the correct encoding of pertinent items and posterior

operations. Also, alpha activity supports the rejection of distracters during retention and maintenance

stages protecting relevant items from external disruption, function which impairment has

demonstrated to be critical for WM deficits in several diseases.

All in all, the exact mechanisms underpinning alpha inhibition are yet to be clarified, and the

emergence of other components like phase coupling promises to shed light upon this matter. The

subsequent shaping of alpha-band activity by measuring phase and amplitude in a coherentframework, together with further studies that could provide finer spatial specificity and the addition of

alpha activity to studies seeking to define cross-frequency networks sets an exciting moment for the

research community. This scenario promises to generate powerful tools for the understanding of

perceptual and cognitive abilities, which applications will have a predictable application in disease

models.

V. References

Adrian, E. D., & Matthews, B. H. (1934). The Berger rhythm: potential changes from the occipital lobes in

man. Brain, 57(4), 355-385.

Amieva, H., Phillips, L. H., Della Sala, S., & Henry, J. D. (2004). Inhibitory functioning in Alzheimers

disease. Brain, 127(5), 949-964.

Baddeley, A. (2003). Working memory: looking back and looking forward.Nature Reviews Neuroscience, 4(10),

829-839.

Blanger, S., Belleville, S., & Gauthier, S. (2010). Inhibition impairments in Alzheimer's disease, mild cognitive

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