Synaptic plasticity in recurrent neural networks

We investigate how local plasticity rules, acting on individual synapses embedded in recurrent neural networks, give rise to large-scale, global structure that can support various forms of computation. We have shown that spike timing dependent plasticity (STDP) induces non-local interactions between different synapses in the network, that can be precisely described in terms of contributions from different structural motifs. By tuning biophysical parameters, such as the time course of synaptic currents or the STDP function, it is possible to place the plasticity in a regime that favors spontaneous formation of global structures such as synfire chains and interconnected neural assemblies.

Selected publications

Ravid Tannenbaum, N, Burak Y.,
Theory of nonstationary Hawkes processes.
Physical Review E 96, 062314 (2017) Editors’ Suggestion. LINK

Ravid-Tannenbaum, N, Burak Y.
Shaping Neural Circuits by High Order Synaptic Interactions.
PLoS Computational Biology 12, e1005056 (2016). LINK