TY - JOUR
T1 - Shaping Neural Circuits by High Order Synaptic Interactions
AU - Ravid Tannenbaum, Neta
AU - Burak, Yoram
N1 - Publisher Copyright:
© 2016 Ravid Tannenbaum, Burak.
PY - 2016/8
Y1 - 2016/8
N2 - Spike timing dependent plasticity (STDP) is believed to play an important role in shaping the structure of neural circuits. Here we show that STDP generates effective interactions between synapses of different neurons, which were neglected in previous theoretical treatments, and can be described as a sum over contributions from structural motifs. These interactions can have a pivotal influence on the connectivity patterns that emerge under the influence of STDP. In particular, we consider two highly ordered forms of structure: wide synfire chains, in which groups of neurons project to each other sequentially, and self connected assemblies. We show that high order synaptic interactions can enable the formation of both structures, depending on the form of the STDP function and the time course of synaptic currents. Furthermore, within a certain regime of biophysical parameters, emergence of the ordered connectivity occurs robustly and autonomously in a stochastic network of spiking neurons, without a need to expose the neural network to structured inputs during learning.
AB - Spike timing dependent plasticity (STDP) is believed to play an important role in shaping the structure of neural circuits. Here we show that STDP generates effective interactions between synapses of different neurons, which were neglected in previous theoretical treatments, and can be described as a sum over contributions from structural motifs. These interactions can have a pivotal influence on the connectivity patterns that emerge under the influence of STDP. In particular, we consider two highly ordered forms of structure: wide synfire chains, in which groups of neurons project to each other sequentially, and self connected assemblies. We show that high order synaptic interactions can enable the formation of both structures, depending on the form of the STDP function and the time course of synaptic currents. Furthermore, within a certain regime of biophysical parameters, emergence of the ordered connectivity occurs robustly and autonomously in a stochastic network of spiking neurons, without a need to expose the neural network to structured inputs during learning.
UR - http://www.scopus.com/inward/record.url?scp=84988955352&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1005056
DO - 10.1371/journal.pcbi.1005056
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C2 - 27517461
AN - SCOPUS:84988955352
SN - 1553-734X
VL - 12
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 8
M1 - e1005056
ER -