Co-existence of synaptic plasticity and metastable dynamics in a spiking model of cortical circuits

Abstract

AbstractEvidence for metastable dynamics and its role in brain function is emerging at a fast pace and is changing our understanding of neural coding by putting an emphasis on hidden states of transient activity. Clustered networks of spiking neurons are capable of producing metastable dynamics, however, it is unclear how their structure may emerge in cortical circuits. Here, we demonstrate the emergence of rich metastable dynamics from a fully local synaptic plasticity rule. The metastable dynamics co-exists with ongoing plasticity; in turn, the synaptic structure is stable to ongoing dynamics and random perturbations, yet it remains sufficiently plastic to remap sensory representations to encode new sets of stimuli. Both the plasticity rule and the metastable dynamics scale well with network size, with synaptic stability increasing with the number of neurons. These results show that it is possible to generate and support metastable dynamics over meaningful hidden states using a simple but biologically plausible plasticity rule which co-exists with ongoing neural dynamics and is independent of network size.