Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity

TL;DR

This paper demonstrates how asymmetric spike-timing-dependent plasticity (STDP) promotes the self-organization of feedforward networks and enhances frequency synchrony in oscillator networks with a pacemaker, highlighting a novel route to neural synchrony.

Contribution

It reveals that asymmetric STDP induces feedforward network formation and facilitates frequency synchrony, differing from traditional mutual coupling mechanisms.

Findings

Asymmetric STDP leads to self-organized feedforward networks.

STDP with asymmetric windows enhances frequency synchrony.

Perfect spike synchrony is not achieved due to finite time lags.

Abstract

Spike-timing-dependent plasticity (STDP) with asymmetric learning windows is commonly found in the brain and useful for a variety of spike-based computations such as input filtering and associative memory. A natural consequence of STDP is establishment of causality in the sense that a neuron learns to fire with a lag after specific presynaptic neurons have fired. The effect of STDP on synchrony is elusive because spike synchrony implies unitary spike events of different neurons rather than a causal delayed relationship between neurons. We explore how synchrony can be facilitated by STDP in oscillator networks with a pacemaker. We show that STDP with asymmetric learning windows leads to self-organization of feedforward networks starting from the pacemaker. As a result, STDP drastically facilitates frequency synchrony. Even though differences in spike times are lessened as a result of synaptic plasticity, the finite time lag remains so that perfect spike synchrony is not realized. In contrast to traditional mechanisms of large-scale synchrony based on mutual interaction of coupled neurons, the route to synchrony discovered here is enslavement of downstream neurons by upstream ones. Facilitation of such feedforward synchrony does not occur for STDP with symmetric learning windows.