the theory and practice of computational cognitive neuroscience

Dr. Brian J. Spieringemail: bspiering@gmail.com

website: brianspiering.com

The Theory & Practice of

Computational Cognitive Neuroscience

Oblate Spheroid

Oblate Spheroidwith unequal mass distribution

Choose the modelbased on the task

OverviewI) Context

II) Theory

III) Practice

1) ContextA) How to Buy a Science model

B) Validating Models

C) Hierarchy of Models

D) The First Step

What to look for when “buying” a science model ...

1) Accounts for previously accounted for data

2) Accounts for previously unaccounted for data

3) Makes novel, falsifiable predictions

Validating Models

It is easy to account for behavioral data

so add constraints ...

- wider (more tasks)

- deeper (more methodologies)

- neuroscience

Hierarchy of Models

No Model

Modules

Circles & Lines

CCN

Why is CCN on the top?

Can predict in these domains:

- Behavioral

- fMRI

- MEG & EEG

- Single-unit recording

Why is CCN on the top?Can predict account for these factors:

- Experimental Manipulation

- Drugs

- Disease

- Genes

- Focal Lesions (injury, ablation, & TMS)

Where do you start?

Model ➜ Brain

or

Brain ➜ Model

II) Theory of ModelingA) Ideals

B) Modeling individual units

C) Learning

D) Behavior

E) Other Issues

A) Ideals1) Neuroscience

2) Simplicity

3) Set-in-Stone

4) Goodness-of-Fit

1) Neurosciencea) Use only found connections

b) Specify excitatory or inhibitory

c) Account for qualitative behavior in units

d) Agree with neuroscience of learning

2) Simplicity

Use enough but not any more

3) Set-in-Stone

Always use the same players and play by

the same rules in the modeling game.

4) Goodness-of-Fit

a) Behavioral

b) Neuroscience

B) Modeling Units1) Leaky integrate-and-fire model

2) Izhikevich model

3) Axon & synaptic delays

C) Learning1) LTP vs. LTD

2) Role of Dopamine

3) Discrete vs. Continuous

4) Local vs. Global

D) Behavior

1) Choose control region

2) Choose function

E) Other Issues1) Overconnectioning

2) Other?

III) Practice of ModelingSPEED Model:

A) Idea

B) Inception

C) Instantiations

A) SPEED Model IdeaAn Contrarian Model of Procedural Expertise

F. Greg Ashby John Ennis

SPEEDAn Contrarian Model of Procedural Expertise

Previous Notions

“It has been widely held that although memory traces are at first formed in the cerebral cortex, they are finally reduced or transferred by long practice to subcortical levels” (p. 466)

Karl Lashley (1950) In search of the engram.

Previous Notions

“Routine, automatic, or overlearned behavioral sequences, however complex, do not engage the PFC and may be entirely organized in subcortical structures” (p. 323)

Joaquin Fuster (2001). The prefrontal cortex – an update.

SPEEDAn Contrarian Model of Procedural Expertise

SPEED Model

Procedural learning is striatum dependent.

Procedural expertise is striatum independent.

SPEED (Subcortical Pathways Enable Expertise Development)

B) Inception

aka, How we built the model.

SensoryAssociation

Cortex

Response

BA

B

A-B difference

A B

A BA

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:

SensoryAssociationA Response

A

A

AA

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

ExcitatoryInhibitory

SPEED Model:Single Subcortical

SensoryAssociation

Cortex

Response

BA

B

A-B difference

A B

A BA

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:Subcortical

SensoryAssociation

Cortex

StriatumSNpc

Dopamine

Excitatory

SPEED Model:Subcortical Learning

SensoryAssociation

Cortex

Response

BA

B

A-B difference

A B

A BA

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:Subcortical

SensoryAssociation

Cortex

Response

BA

A-B difference

SPEED Model:Cortical

SensoryAssociation

Cortex

Response

BA

B

A-B difference

A B

A BA

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:Cortical Learning

SensoryAssociation

Cortex

A

A

A A

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:1st Trial

SensoryAssociation

Cortex

A

A

A A

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:Early Learning

SensoryAssociation

Cortex

A

A

A A

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:Middle Learning

SensoryAssociation

Cortex

A

A

A A

Premotor Area(Cortex)

Thalamus

Globus PallidusStriatum

SPEED Model:Mature Performance

C) Instantiations

See MATLAB code ...

Summary1) Context

II) Theory

III) Practice

?