Slides for a talk I gave in a symposium at the Society for Neuroscience annual meeting 2014

1. Interactions Between Category Learning Systems
Matthew J. Crossley
UC Berkeley
F. Gregory Ashby
UC Santa Barbara

2. !2

3. !3
Trial 1 Trial 2

4. Where do stimuli come from?
!4

5. Where do stimuli come from?
Thick & Shallow
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6. Where do stimuli come from?
Thick & SteepThin & Steep
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7. Category Structures
Respond A if bars are thin
Respond B if bars are thick
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8. Respond A if bars are steep
Respond B if bars are shallow
Category Structures
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9. Respond A if bars are thin AND steep
Respond B otherwise
Category Structures
!9

10. Category Structures
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11. Respond A if bars are steeper than they are thick
Respond B otherwise
Category Structures
!11

12. Respond A if bars are thicker than they are steep
Respond B otherwise
Category Structures
!12

13. Different Brain Systems
Declarative Procedural
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14. Response remapping impairs procedural more than
declarative learning
Train Transfer
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Declarative
Procedural

15. Delaying feedback impairs procedural but not
declarative
!15
Declarative
Procedural

16. !16
Does the procedural system learn
during declarative control?

17. !17
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?

19. !19
If procedural learning during declarative control:

20. !20
Results are consistent with procedural learning
during declarative control
Parsed Training All II Training
Rotated impaired
relative to congruent
No innate
difficulty difference

21. !21
Parsed Training All II Training
Rotated impaired
relative to congruent
No innate
difficulty difference
Results are consistent with procedural learning
during declarative control

22. !22
Hard to rule out rules
75% 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

23. !23
Hard to rule out rules
~75% correct!
If using rules
~50% correct!
If using rules
Rule 1 Rule 2
Rule 1 Rule 2

24. !24
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

25. !25
How to rule out rules:
Turn off procedural learning during training
See if results hold up

26. !26
Recall that delaying feedback impairs procedural but not
declarative learning

27. !27
If procedural learning during declarative control:

28. Experiment 2 Results
Immediate Feedback Delayed Feedback
Rotated impairment
replicates
Rotated impairment
disappears
!28

29. !29
Looks like procedural learning during
declarative control

30. !30
Category Learning Networks

31. !31
Category Learning Networks

32. !32
Category Learning Networks

33. !33
Category Learning Networks

34. !34
471.05/GGG21 - Savings in visuomotor adaptation depends on perturbation magnitude
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J. R. MOREHEAD, S. QASIM, M. CROSSLEY, R. B. IVRY;
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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
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M. J. CROSSLEY, F. ASHBY;
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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
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J. L. ROEDER, M. J. CROSSLEY, G. CANTWELL, F. ASHBY;
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842. Human Navigation and Spatial Representation
Wed, Nov 13, 1:00 - 5:00 PM

35. !35
Thanks

36. !36
Immediate Feedback Delayed Feedback
Parsed Training All II Training

37. !37
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?

39. !39
1) Procedural and declarative systems compete for control
of motor resources, preventing trial-by-trial switching
between procedural and declarative strategies under normal
circumstances.
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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.
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3) Learning in the procedural system occurs even when the
declarative system is in control of behavior.
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4) computational cognitive neuroscience model M1 to
striatal medium spiny neurons.
My abstract promised too much

40. 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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