Pairwise Analysis Can Account for Network Structures Arising from Spike-Timing Dependent Plasticity
- Pairwise Analysis Can Account for Network Structures Arising from Spike-Timing Dependent Plasticity
- Babadi, Baktash
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- PLOS Computational Biology
- Spike timing-dependent plasticity (STDP) modifies synaptic strengths based on timing information available locally at each synapse. Despite this, it induces global structures within a recurrently connected network. We study such structures both through simulations and by analyzing the effects of STDP on pair-wise interactions of neurons. We show how conventional STDP acts as a loop-eliminating mechanism and organizes neurons into in- and out-hubs. Loop-elimination increases when depression dominates and turns into loop-generation when potentiation dominates. STDP with a shifted temporal window such that coincident spikes cause depression enhances recurrent connections and functions as a strict buffering mechanism that maintains a roughly constant average firing rate. STDP with the opposite temporal shift functions as a loop eliminator at low rates and as a potent loop generator at higher rates. In general, studying pairwise interactions of neurons provides important insights about the structures that STDP can produce in large networks.
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- Baktash Babadi, Larry Abbott, 2013, Pairwise Analysis Can Account for Network Structures Arising from Spike-Timing Dependent Plasticity, Columbia University Academic Commons, https://doi.org/10.7916/D8Q81Q3Q.