Name
Title | ||
|---|---|---|
Pairwise analysis can account for network structures arising from spike-timing dependent plasticity. |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1371/journal.pcbi.1002906 | PLOS COMPUTATIONAL BIOLOGY |
Keywords | Field | DocType |
neurosciences,biology | Long-term potentiation,Pairwise comparison,Synapse,Biological system,Biology,Artificial intelligence,Synaptic plasticity,Spike-timing-dependent plasticity,Genetics,Neuroplasticity,Artificial neural network,Plasticity | Journal |
Volume | Issue | ISSN |
9 | 2 | 1553-7358 |
Citations | PageRank | References |
12 | 0.56 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baktash Babadi | 1 | 44 | 3.68 |
| l f abbott | 2 | 182 | 42.07 |