Slide 1

Abstract

If we assume that neuronal activity encodes a probabilistic representation of the world that optimizes free-energy in a Bayesian fashion, then this optimization can be regarded as evidence accumulation or (generalized) predictive coding. Crucially, both predictions about the state of the world generating sensory data and the precision of (confidence in) those data have to be optimized. In other words, we have to make predictions (test hypotheses) about the content of thesensorium and predict our confidence in those hypotheses. I hope to demonstrate themetacognitiveaspect of thisinference using simulations ofaction observation and sensory attenuation- to illustratethe nature of active inferenceand elucidate the computational anatomy of psychosis.The computational anatomy of psychosis Karl Friston

Opening Symposium of the Translational Neuromodeling Unit Zurich, 18-20 September 2013

Objects are always imagined as being present in the field of vision as would have to be there in order to produce the same impression on the nervous mechanism - von Helmholtz

Thomas BayesGeoffrey HintonRichard FeynmanFrom the Helmholtz machine to the Bayesian brain and self-organizationRichard Gregory

Hermann von Helmholtz Ross Ashby

Self organisation and Hamiltons principle of least actionThe calculus of variations and the enigma of the brain:or how do we resist the second law of thermodynamics?

Ergodic theorem

surprisedivergenceentropyenergy(precise) prediction errorcomplexitywe minimise variational free energy or prediction error

How can we minimize free energy (prediction error)?

Change sensationssensations predictionsPrediction errorChange predictionsActionPerception

Active inference, predictive coding and precision

Precision and false inference

Simulations of :

Auditory perception (and omission related responses)Handwriting (and action observation)Smooth pursuit eye movements (under occlusion)Sensory attenuation (and the force matching illusion)

A simple hierarchyGenerative models and predictions

whatwhereSensory fluctuations

Generative modelModel inversion (inference)A simple hierarchyExpectations:Predictions:Prediction errors:

DescendingpredictionsAscending prediction errorsFrom models to perception

frontal eye fieldsgeniculatevisual cortexretinal inputponsoculomotor signals

Prediction error (superficial pyramidal cells)Conditional predictions (deep pyramidal cells)Top-down or backward predictionsBottom-up or forward prediction errorproprioceptive inputreflex arcPerceptionVTA

David MumfordPredictive coding with reflexesAction

Precision

Prediction error can be reduced by changing predictions (perception)

Prediction error can be reduced by changing sensations (action)

Perception entails recurrent message passing in the brain to optimize predictions

Action fulfils descending predictions

Both perception (attention) and action (affordance) rest on optimizing precision

Precision contextualizes prediction errors though neuromodulatory gain control

+-De-compensation(trait abnormalities)Compensation (to psychotic state)Neuromodulatory failure (of sensory attenuation)Attenuated violation responsesLoss of perceptual GestaltSPEM abnormalitiesPsychomotor povertyResistance to illusionsHallucinationsDelusions

Active inference, predictive coding and precision

Precision and false inference

Simulations of :

Auditory perception (and omission related responses)Handwriting (and action observation)Smooth pursuit eye movements (under occlusion)Sensory attenuation (and the force matching illusion)

Generative process (and model)

SyrinxNeuronal hierarchy Time (sec)Frequency (KHz)sonogram0.511.5

Frequency (Hz)perceptprediction error

Model inversion500100015002000-6-4-20246810peristimulus time (ms)LFP (micro-volts)

Reduced precision at second level

Compensatory reduction of sensory precision

Omission related responses, MMN and hallucinosis

Active inference, predictive coding and precision

Precision and false inference

Simulations of :

Auditory perception (and omission related responses)Handwriting (and action observation)Smooth pursuit eye movements (under occlusion)Sensory attenuation (and the force matching illusion)

00.20.40.60.811.21.40.40.60.811.21.4actionposition (x)position (y)00.20.40.60.811.21.4observationposition (x)Heteroclinic cycle (central pattern generator)

Descendingproprioceptive predictionsAction and agency

retinal inputponsoculomotor signalsproprioceptive inputreflex arc

Angular position of target in intrinsic coordinatesAngular direction of gaze in extrinsic coordinatesAngular direction of target in extrinsic coordinates

timevisual channels

Generative processGenerative model

Smooth pursuit eye movements eye (reduced precision)50010001500200025003000-2-1012Angular positiondisplacement (degrees) 50010001500200025003000-20-1001020304050time (ms)velocity (degrees per second)Angular velocity eye target

Eye movements under occlusion and reduced precision1002003004005006007008009001000-2-1012target and oculomotor anglestime (ms)displacement (degrees) 1002003004005006007008009001000-30-20-100102030target and oculomotor velocitiestime (ms)velocity (degrees per second) eye (reduced precision) eye target

Paradoxical responses to violations

Active inference, predictive coding and precision

Precision and false inference

Simulations of :

Auditory perception (and omission related responses)Handwriting (and action observation)Smooth pursuit eye movements (under occlusion)Sensory attenuation (and the force matching illusion)

Generative processGenerative modelMaking your own sensations

21

motor reflex arcthalamussensorimotor cortexprefrontal cortex

ascending prediction errorsdescending modulationdescending predictionsdescending motor predictionsdescending sensory predictions22High sensory attenuation

51015202530-0.500.511.52prediction and errorTime (bins)51015202530-0.500.511.52hidden statesTime (bins)51015202530-0.500.51hidden causesTime (bins)51015202530-0.8-0.6-0.4-0.200.20.40.60.81Time (bins)perturbation and action

Self-made actsFailure of sensory attenuation51015202530-0.500.511.52prediction and errortime51015202530-0.500.511.52hidden statestime51015202530-0.500.51hidden causestime51015202530-0.8-0.6-0.4-0.200.20.40.60.81timeperturbation and actionand psychomotor poverty102030405060-0.500.511.52prediction and errorTime (bins)102030405060-0.500.511.52hidden statesTime (bins)102030405060-0.500.511.52hidden causesTime (bins)102030405060-0.500.511.52Time (bins)perturbation and action102030405060-0.500.511.52hidden statesForce matching illusion102030405060-0.500.511.52prediction and errorTime (bins)Time (bins)Sensory attenuation102030405060-0.500.511.5hidden causesTime (bins)102030405060-0.500.511.5Time (bins)perturbation and actionIntrinsic and extrinsic

00.511.522.5300.511.522.53 External (target) forceSelf-generated(matched) forceExternal (target) forceSelf-generated(matched) forceSimulatedEmpirical (Shergill et al)

Failures of sensory attenuation, with compensatory increases in non-sensory precisionNormal subjectsSchizophrenic subjectsFailure of sensory attenuation and delusions of control?102030405060-0.500.511.522.533.5prediction and errorTime (bins)102030405060-0.500.511.522.533.5hidden statesTime (bins)102030405060-1-0.500.511.522.533.5hidden causesTime (bins)102030405060-0.500.511.522.533.5Time (bins)perturbation and action

+-Neuromodulatory failure(of sensory attenuation)Signs (of trait abnormalities)Attenuated violation responsesLoss of perceptual GestaltSPEM abnormalitiesPsychomotor povertyResistance to illusionsSymptoms (of the psychotic state)HallucinationsDelusions

Bleuler E. Dementia Praecox oder Gruppe der Schizophrenien, 1911: Disintegration of conscious processing (the psyche) Wernicke C. Grundrisse der Psychiatrie. 1906:Sejunction disruption of associative connectivity

Anatomical disconnectionFunctional disconnection

Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring. Schizophr Bull. 2009 May;35(3):509-27Klaas E. Stephan, Karl J. Friston and Chris D. Frith

What is the functional deficit?

What is the pathophysiology?

How can we measure it?

What is the aetiology?

What is the therapeutic intervention?Summary and a Hilbert list for schizophreniaFalse inference due to aberrant encoding of precisionA neuromodulatory failure of postsynaptic excitability:Aberrant DA/NMDAr subunit interactionsAberrant synchronous gain and fast (gamma) dynamicsAberrant cortical gain control and E-I (GABAergic) balanceAberrant dendritic integration (neuromorphology)Biophysical modelling of non-invasive brain responsesdynamic casual modelling of recurrent inhibition

V5V5V1ITITPCPCVisual inputPrefrontal inputcontrol subjects - predictablecontrol subjects - unpredictableschizophrenia - predictableschizophrenia - unpredictable

V1R V5L V5R ITL ITR PCL PC-2-1.5-1-0.500.511.5cortical sourcelog modulationEffects of predictability on recurrent inhibition control subjectsschizophrenicsNoa Fogelson et al., The functional anatomy of schizophrenia: a DCM study of predictive codingThank you

And thanks to collaborators:

Rick AdamsAndre BastosSven BestmannHarriet BrownJean DaunizeauMark EdwardsXiaosi GuLee HarrisonStefan KiebelJames KilnerJrmie MattoutRosalyn MoranWill PennyLisa Quattrocki Knight Klaas Stephan

And colleagues:

Andy ClarkPeter DayanJrn DiedrichsenPaul FletcherPascal FriesGeoffrey HintonJames HopkinsJakob HohwyHenry KennedyPaul VerschureFlorentin Wrgtter

And many others