Interactions Between Category Learning Systems

Interactions Between Category Learning Systems

Matthew J. Crossley UC Berkeley

F. Gregory Ashby UC Santa Barbara

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Trial 1 Trial 2

Where do stimuli come from?

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Where do stimuli come from?

Thick & Shallow

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Where do stimuli come from?Thick & SteepThin & Steep

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Category Structures

Respond A if bars are thinRespond B if bars are thick

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Respond A if bars are steepRespond B if bars are shallow

Category Structures

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Respond A if bars are thin AND steepRespond B otherwise

Category Structures

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Category Structures

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Respond A if bars are steeper than they are thickRespond B otherwise

Category Structures

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Respond A if bars are thicker than they are steepRespond B otherwise

Category Structures

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Different Brain SystemsDeclarative Procedural

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Response remapping impairs procedural more than declarative learning

Train Transfer

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DeclarativeProcedural

Delaying feedback impairs procedural but not declarative

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Declarative

Procedural

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Does the procedural system learn during declarative control?

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Experiment 1: Train procedural categories with declarative strategies

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Experiment 1: Train II categories with RB control

Conditions to rule out innate difficulty differences

Procedural learning during declarative control?

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If procedural learning during declarative control:

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Results are consistent with procedural learning during declarative control

Parsed Training All II Training

Rotated impaired relative to congruent

No innate difficulty difference

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Parsed Training All II Training

Rotated impaired relative to congruent

No innate difficulty difference

Results are consistent with procedural learning during declarative control

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Hard to rule out rules75% correct!

If using rule 1

75% correct!If using rule 2

75% correct!If using rule 1

25% correct!If using rule 2

Rule 1 Rule 2

Rule 1 Rule 2

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Hard to rule out rules

~75% correct!If using rules

~50% correct!If using rules

Rule 1 Rule 2

Rule 1 Rule 2

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Hard to rule out rules

75% correct!If using rules

50% correct!If using rules

Hard to say if results reflect procedural learning or perseveration with rules

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How to rule out rules:Turn off procedural learning during training

See if results hold up

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Recall that delaying feedback impairs procedural but not declarative learning

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If procedural learning during declarative control:

Experiment 2 ResultsImmediate Feedback Delayed Feedback

Rotated impairment replicates

Rotated impairment disappears

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Looks like procedural learning during declarative control

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Category Learning Networks

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Category Learning Networks

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Category Learning Networks

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Category Learning Networks

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471.05/GGG21 - Savings in visuomotor adaptation depends on perturbation magnitude !

J. R. MOREHEAD, S. QASIM, M. CROSSLEY, R. B. IVRY; !

471. Voluntary Motor Control: Motor Learning II Mon, Nov 11, 1:00 - 5:00 PM

771.17/KKK10 - A temporal-difference dopamine-dependent spiking network account of instrumental contingency degradation

!M. J. CROSSLEY, F. ASHBY;

!771. Neural Mechanisms of Appetitive Behavior

Wed, Nov 13, 8:00 AM - 12:00 PM

842.19/VV19 - The difficulties of rapid switching between declarative and procedural learning systems

!J. L. ROEDER, M. J. CROSSLEY, G. CANTWELL, F. ASHBY;

!842. Human Navigation and Spatial Representation

Wed, Nov 13, 1:00 - 5:00 PM

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Thanks

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Immediate Feedback Delayed Feedback

Parsed Training All II Training

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Appropriate Control Conditions?

The issue is that we don’t know what size interference to expect from a rotation during transfer with pure II training.

This is a fair point. We know that pos and neg aren’t different from each other if left in isolation, but we can not rule out the possibility that there is an innate difference in the size of the rotation interference. However, Experiment 2 addresses this since we can make the difference disappear with FB delay.

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Appropriate Control Conditions?

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1) Procedural and declarative systems compete for control of motor resources, preventing trial-by-trial switching between procedural and declarative strategies under normal circumstances. !2) This competition can be reduced, and trial-by-trial switching facilitated, by incorporating explicit cues to signal which strategy is appropriate for a given stimulus. !3) Learning in the procedural system occurs even when the declarative system is in control of behavior. !4) computational cognitive neuroscience model M1 to striatal medium spiny neurons.

My abstract promised too much

No perfect terminology• Procedural vs declarative

• Information-Integration vs rule-based

• Habitual vs goal-directed

• Model-free vs model-based

• Implicit vs explicit

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