Rosalyn J. Moran Wellcome Trust Centre for Neuroimaging

1st Workshop on the Free Energy Principle, ION, UCL, July 5th 2012.

Precision in Cortical Message Passing

Outline

Predicting & Estimating Precision under the Free Energy Principle - Laplace and Mean Field Assumptions

Hypothesised Neuronal Implementation & the role of Neuromodulators - Gain effects on primary neurotransmission

Cholinergic Neuromodulation & Certainty Effects on Auditory mismatch negativity - Theoretical simulation of perception

Testing Cholinergic Neuromodulation - DCM characterization of Event Related Responses

Outline

Predicting & Estimating Precision under the Free Energy Principle - Laplace and Mean Field Assumptions

Hypothesised Neuronal Implementation & the role of Neuromodulators - Gain effects on primary neurotransmission

Cholinergic Neuromodulation & Certainty Effects on Auditory mismatch negativity - Theoretical simulation of perception

Testing Cholinergic Neuromodulation - DCM characterization of Event Related Responses

Predicting & Estimating Precision under the Free Energy Principle

Hierarchical, Dynamic & Uncertain causes in the environment generate sensory signals

Different Levels of the hierarchy and/or different sensory signals may confer more precise Information

The Environment

Hierarchical, Dynamic

The Environment

Hierarchical, Dynamic & Uncertain causes generate sensory signals

y y

The InversionEstimate: Hierarchical, Dynamic & Uncertainty of sensory signals to minimise the surprise of the sensory signals

y y

Minimise Free Energy

)),|(||)(()|)(()()|)(()(

)|)(()|(

)|(ln)|()|(

mypqKLmtyptFmtyptF

dtmtypmyH

dymypmypmyH

Minimise SurpriseTime averaged Surprise(Ergodicity)

Minimise F at every point in time

The Brain’s Response to y… A Tractable Problem

States, parameters & noise

Outline

Predicting & Estimating Precision under the Free Energy Principle - Laplace and Mean Field Assumptions

Hypothesised Neuronal Implementation & the role of Neuromodulators - Gain effects on primary neurotransmission

Cholinergic Neuromodulation & Certainty Effects on Auditory mismatch negativity - Theoretical simulation of perception

Testing Cholinergic Neuromodulation - DCM characterization of Event Related Responses

Minimising Free Energy

The Laplace Assumption: The brain assumes gaussian random fluctuations

)),|(||)(()|)(()( mypqKLmtyptF

y

Gradients a function of error terms weighted by the precisions at each level:How might precisions be encoded?

Smooth noise correlations within levels Markov properties between levels

1 5 1015200 25

1 5 1015200 25

1 5 10 152025

Gradients of Free Energy Precision Dependent

y

A multiplicative term that stays within levels:Candidate mechanisms: local lateral inhibition & neuromodulators

Forward prediction error

Backward predictions

Superficial pyramidal cells

Deep pyramidal cells

Perceiving multiple hierarchical levels together: errors can have a greater or lesser effect

Gain control at superficial pyramidal cells y

Neuromodulators: Anatomically deployed to provide input in multiple regionsEg Sarter et al. 2009

Local Glutamate & GABA

Long Range Glutamate

Diffuse projectionsNeuromodulatorsAcetylcholineDopamine

Gain control at superficial pyramidal cells yNeuromodulators: Physiologically equipped to provide gain control

Cholinergic Projectionsfrom BasalForebrain

Dopaminergic Projections from VTA/SNc

Activity at D1 receptorsstimulates adenylyl cyclasemodulating postsynaptic currentsActivity at muscarinic receptors

enhances EPSPs through K-current modulation

Gain control at superficial pyramidal cells yNeuromodulators: Physiologically equipped to provide gain control

Cholinergic Projectionsfrom BasalForebrain

Dopaminergic Projections from VTA/SNc

Presynaptic terminals

Excitatory (AMPA) receptorsModulatory receptorInhibitory (GABAA) receptors

Dendritic spine

errorprecision Precision-weighted error

Outline

Predicting & Estimating Precision under the Free Energy Principle - Laplace and Mean Field Assumptions

Hypothesised Neuronal Implementation & the role of Neuromodulators - Gain effects on primary neurotransmission

Cholinergic Neuromodulation & Certainty Effects on Auditory mismatch negativity - Theoretical simulation of perception

Testing Cholinergic Neuromodulation - DCM characterization of Event Related Responses

Testing error precision modulation by Acetylcholine:The Framework

7 Auditory Stimuli:Pure tones presented in mini-blocks

time

Freq

Mismatch Negativity ~150 ms

Under Placebo & Cholinergic Enhancement

Simulate Experiment

Recognition Dynamics

v1

x1 x2

There was a particular

sound

The sound has dynamics determined

by properties, Frequency and

Amplitude

Sensationsy~

Recognition Dynamics

Testing error precision modulation by Acetylcholine:The Sensory Data

A two level hierarchytimeFreq

v1

x1 x2

Sensationsy~

Testing error precision modulation by Acetylcholine:The Sensory Data

C =4

A two level hierarchytimeFreq

v1

x1 x2

Sensationsy~

Testing error precision modulation by Acetylcholine:The Sensory Data

C = 2

timeFreq

Sensationsy~

Testing error precision modulation by Acetylcholine:The Inversion: assume different precision estimates

Placebo

ACh

timeFreq

Sensations

y~

Testing error precision modulation by Acetylcholine:The Recognition Dynamics under different precision estimates

Placebo

ACh

Time (msec) Time (msec)

Simulated ERP Placebo Simulated ERP ACh

Prec

ision

wei

ghte

d PE

0 50 100 150 200 250 300-80

-60

-40

-20

0

20

40

60

80

0 50 100 150 200 250 300-80

-60

-40

-20

0

20

40

60

80

d1d2d10

Testing error precision modulation by Acetylcholine:The MMN itself under different precision estimates

Time (msec) Time (msec)

Simulated ERP Placebo Simulated ERP ACh

Prec

ision

wei

ghte

d PE

0 50 100 150 200 250 300-80

-60

-40

-20

0

20

40

60

80

0 50 100 150 200 250 300-80

-60

-40

-20

0

20

40

60

80

d1d2d10

-5

0

5

10

15

20

25

Prec

isio

n we

ight

ed P

E

Simulated MMN Placebo Simulated MMN ACh (more Precision)

CertainEnvironmentUntil oddball

More CertainEnvironmentUntil oddball

Tone is predictedTone is predicted

Outline

Predicting & Estimating Precision under the Free Energy Principle - Laplace and Mean Field Assumptions

Hypothesised Neuronal Implementation & the role of Neuromodulators - Gain effects on primary neurotransmission

Cholinergic Neuromodulation & Certainty Effects on Auditory mismatch negativity - Theoretical simulation of perception

Testing Cholinergic Neuromodulation - DCM characterization of Event Related Responses

Testing error precision modulation by Acetylcholine:

7 Auditory Stimuli:Pure tones presented in mini-blocks

time

Freq

Mismatch Negativity ~150 ms

Under Placebo & Cholinergic Enhancement

Real Experiment

Scalp Effects: MMN

Recorded MMN Placebo

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5 *

chan

nel C

21

*

Recorded MMN Galantamine

-5

0

5

10

15

20

25

Prec

isio

n we

ight

ed P

E

Simulated MMN Placebo Simulated MMN Galantamine (more Precision)

CertainEnvironmentUntil oddball

More CertainEnvironmentUntil oddball

Tone is predictedTone is predicted

Physiological & Hierarchical PredictionsRecall:

Forward prediction error

Backward predictions

Superficial pyramidal cells

Deep pyramidal cells

A multiplicative term that stays within levels:Candidate mechanisms: neuromodulators

Forward (Bottom-up) ConnectionBackward (Top-Down) Connection

IFG

A1MTG

IFG

A1 MTG

What layer? What region?

Acetylcholine: Where does it affect network processing?

( )x

( )x

( )v

( )v

Spiny stellate

Deep pyramidal

Superficial pyramidalInhibitory interneuron

Backward connections

Forward connections

Gain Modulation at Supragranular Pyramidal Cells

Gain Modulation at Deep Pyramidal Cells

Acetylcholine: Where does it affect network processing?

Forward (Bottom-up) ConnectionBackward (Top-Down) Connection

IFG

A1MTG

IFG

A1 MTG

What layer? What region?

Forward (Bottom-up) ConnectionBackward (Top-Down) Connection

IFG

A1MTGIFG

A1MTG

simple neuronal model

Slow time scale

fMRIcomplicated neuronal model

Fast time scale

EEG/MEG

),,( uxFdtdx

Neural state equation:

Hemodynamicforward model:neural activityBOLD

Time Domain Data

Electromagneticforward model:

neural activityEEGMEG

LFP

Time Domain ERP Data…

Neural Mass Model

DCM

Acetylcholine: Where does it affect network processing?

Forward (Bottom-up) ConnectionBackward (Top-Down) Connection

IFG

A1MTG

IFG

A1 MTG

What layer? What region?

Forward (Bottom-up) ConnectionBackward (Top-Down) Connection

IFG

A1MTGIFG

A1MTG

( )x

( )x

( )v

( )v

Spiny stellate

Deep pyramidal

Superficial pyramidalInhibitory interneuron

Backward connections

Forward connections

DCM for ERPs : Canonical Microcircuit

Acetylcholine: Bayesian Model Selection

Forward ConnectionBackward Connection

Model 3IFG

MTG A1

IFG

A1

Model 1

MTG

Model 2IF

GM

TG 1A

IFG

A1

MTG

IFG

MTG A1

IFG

A1

MTG

IFG

MTG A1

IFG

A1

MTG

MTG MTG

A1

Model 5 Model 6

IFG

MTG A1

IFG

A1

MTG MTG MTG

A1

IFG

MTG A1

IFG

A1

MTG

Model 7 Model 8IF

GM

TG A1

IFG

A1

MTG

IFG

MTG A1

IFG

A1

MTG

Model 9 Model 10

IFG

MTG A1

IFG

A1

MTG

IFG

MTG A1

IFG

A1

MTG

Model 3 Model 4

Intrinsic Modulation (models 1-6); Extrinsic Modulation (models 7-10)

Rela

tive

Log

Mod

el E

vide

nce

M1 M2 M3 M4 M5 M60

200

400

600

800

1000

∆F = 153

M7 M8 M9 M10

IFG

( )x

( )x

( )v

( )v

Spiny stellate

Deep pyramidal

Superficial pyramidalInhibitory interneuron

Backward connections

Forward connections

Gain Modulation at Supragranular Pyramidal Cells

In A1

Acetylcholine: Direction of Gain Modulation

Placebo

ACh

Mod

ulat

ory

Effe

ct o

f Gal

anta

min

e

Superficial Pyramidal Cell Gain

0.01

0.02

0.03

0.04

0.05

0.06

PlaceboBaseline

Galantamine

*

Summary

Precision estimates enable Bayes optimal perception - Hierarchical inference enables different precision effects at different

levels- Precision estimates control the impact of errors in Free Energy

minimisation under the Laplace Assumption

Neuromodulators are anatomically & physiologically equipped to signal precision in this scheme

Neuromodulatory systems could control precision at different hierarchical levels

Cholinergic Neuromodulation controls gain in superficial pyramidal cells in early sensory regions; conforming to Free Energy Predictions of enhanced precision on sensory prediction errors

Thank You

Karl FristonRay DolanKlaas Enno StephanMkael SymmondsNicholas WrightPablo CampoMethods GroupEmotion Group

Acknowledgments