Learning Computational Cognitive Neuroscience Randall O’Reilly.

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Presentation transcript:

Learning Computational Cognitive Neuroscience Randall O’Reilly

Overview of Learning Biology: synaptic plasticity Computation:  Self organizing – soaking up statistics  Error-driven – getting the right answers 2

Synapses Change Strength (in response to patterns of activity) 3

What Changes?? 4

Gettin’ AMPA’d 5

Opening the NMDA receptor calcium channel Glutamate NMDAr AMPAr CA2+ Na+ Mg2+

Which Way? 7

XCAL = Linearized BCM Bienenstock, Cooper & Munro (1982) – BCM: adaptive threshold Θ  Lower when less active  Higher when more.. (homeostatic) 8

Threshold Does Adapt 9

Computational: Self-Organizing and Error-Driven Self-organizing = learn general statistics of the world. Error-driven = learn from difference between expectation and outcome. Both can be achieved through XCAL. 10

Floating Threshold = Long Term Average Activity (Self Org) 11

Self Organizing Learning Inhibitory Competition: only some get to learn Rich get richer: winners detect even better  But also get more selective (hopefully) Homeostasis: keeping things more evenly distributed (higher taxes for the rich!) 12

Limitations of Self-Organizing Can’t learn to solve challenging problems – driven by statistics, not error.. 13

Where Does Error Come From? 14

Floating Threshold = Medium Term Synaptic Activity (Error-Driven) 15

Fast Threshold Adaptation: Late Trains Early Essence of Err-Driven: dW = outcome - expectation 16

Backpropagation: Mathematics of Error-driven Learning 17

Biological Derivation of XCAL Curve Can use a detailed model of Spike Timing Dependent Plasticity (STDP) to derive the XCAL learning curve Provides a different perspective on STDP.. 18

Causal Learning? 19

Let’s Get Real.. 20

Urakubo et al, 2008 Model Highly detailed combination of 3 existing strongly-validated models: 21

“Allosteric” NMDA Captures STDP (including higher-order and time integration effects) 22

What About Real Spike Trains? 23

Extended Spike Trains = Emergent Simplicity S = 100HzS = 20HzS = 50Hz r=.894 dW = f(send * recv) = (spike rate * duration) 24

Leabra 25

Hebbian Learns Correlations 26