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PLOSCB
2016

Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites

7 years 11 months ago
Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites
In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the un...
Mathieu Schiess, Robert Urbanczik, Walter Senn
Added 08 Apr 2016
Updated 08 Apr 2016
Type Journal
Year 2016
Where PLOSCB
Authors Mathieu Schiess, Robert Urbanczik, Walter Senn
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