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Topological Effects of Synaptic Time Dependent Plasticity | | James R. Kozloski
; Guillermo A. Cecchi
; | | Date: |
30 Sep 2008 | | Abstract: | We show that the local Spike Timing-Dependent Plasticity (STDP) rule has the
effect of reducing the trans-synaptic weights of closed loops of any length
within a simulated network of neurons. We further prove analytically that
anti-loop learning and STDP are equivalent for the case of a linear network.
Thus a notable local synaptic learning rule yields structures dominated by
feed-forward connections at their largest scale. Given its widespread
occurrence in the brain, we propose that STDP must be involved in eliminating
long range synaptic loops among individual neurons across all brain scales, up
to, and including, the scale of global brain network topology. | | Source: | arXiv, 0810.0029 | | Services: | Forum | Review | PDF | Favorites | |
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