Biological neurons communicate with each other using two broad categories of spike event coding: rate-based and temporal. Rate-based coding communicates analog information on a continuous scale through the intensity of bursts of spikes while temporal coding relies on the timing of spike events. It has been shown that temporal coding has higher information capacity than rate based coding, but is much more challenging to model due to difficulties estimating spike-time statistics. In this paper we demonstrate how history dependent NMDA-modulated ‘resonant’ synapses organised in ‘functional synaptic clusters’ provide a robust mechanism for decoding temporally structured spike trains.
Crook, Nigel Rast, Alex Elia, EleniAoun, Mario Antoine
School of Engineering, Computing and Mathematics
Year of publication: 2023Date of RADAR deposit: 2024-03-21