rt III: Models of synaptic plasticity BOOK: Spiking Neuron Models, W. Gerstner and W. Kistler Cambridge University Press, 2002 Chapters 10-12 aboratory of Computational Neuroscience, LCN, CH 1015 Lausann Swiss Federal Institute of Technology Lausanne, EPFL
Swiss Federal Institute of Technology Lausanne, EPFL. Laboratory of Computational Neuroscience, LCN, CH 1015 Lausanne. Part III: Models of synaptic plasticity. BOOK: Spiking Neuron Models, W. Gerstner and W. Kistler Cambridge University Press, 2002 Chapters 10-12. - PowerPoint PPT Presentation
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Part III: Models of synaptic plasticity
BOOK: Spiking Neuron Models, W. Gerstner and W. Kistler Cambridge University Press, 2002
Chapters 10-12
Laboratory of Computational Neuroscience, LCN, CH 1015 Lausanne
Swiss Federal Institute of Technology Lausanne, EPFL
Chapter 10: Hebbian Models
BOOK: Spiking Neuron Models, W. Gerstner and W. Kistler Cambridge University Press, 2002
Chapter 10
-Hebb rules-STDP
Hebbian Learning
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When an axon of cell j repeatedly or persistently takes part in firing cell i, then j’s efficiency as oneof the cells firing i is increased
Hebb, 1949
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- local rule- simultaneously active (correlations)
Hebbian Learning in experiments (schematic)
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no spike of i
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spikes of i
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Hebbian Learning in experiments (schematic)
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EPSP
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Increased amplitude 0 ijw
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Hebbian Learning
Hebbian Learning
item memorized
Hebbian Learning
item recalled
Recall:Partial info
Hebbian Learning
pre jpost
iijw
When an axon of cell j repeatedly or persistently takes part in firing cell i, then j’s efficiency as oneof the cells firing i is increased
Hebb, 1949
k
- local rule- simultaneously active (correlations)
Hebbian Learning: rate model
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k
- local rule- simultaneously active (correlations)
posti
prej
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activity (rate)
Hebbian Learning: rate modelpre jpost
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Rate-based Hebbian Learning
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Taylor expansion
Rate-based Hebbian Learning
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Oja’s rule
Spike based model
Spike-based Hebbian Learning
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- local rule- simultaneously active (correlations)
0 Prebefore post
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Spike-based Hebbian Learning
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causal rule‘neuron j takes part in firing neuron’ Hebb, 1949
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Spike-time dependent learning window
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Temporal contrast filter
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Spike-time dependent learning window
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Prebefore post
Zhang et al, 1998review:Bi and Poo, 2001
Spike-time dependent learning: phenomenol. model
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spike-based Hebbian Learning
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Translation invariance
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Learning window
Detailed models
BOOK: Spiking Neuron Models, W. Gerstner and W. Kistler Cambridge University Press, 2002
Chapter 10
Detailed models of Hebbian learning
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post i
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i at restingpotential
Detailed models of Hebbian learning
pre j
post i
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i at restingpotential
NMDAchannel
Detailed models of Hebbian learning
pre j
post i
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i at highpotential
BPAP
NMDA channel : - glutamate binding after presynaptic spike - unblocked after postsynaptic spike