An interpretable dynamic population-rate equation for adapting non-linear spiking neural populations
Laureline Logiaco,Sean Escola,Wulfram Gerstner · COSYNE 2022
Recently, the field of computational neuroscience has seen an explosion of the use of trained neural networks (NNs) to model patterns of neural activity. These NN models are typically characterized by tuned interactions between rate 'units' whose dynamics are governed by smooth, continuous differential equations. However, the response of biological single neurons is better described by all-or-none events - spikes - that are triggered in response to the processing of their synaptic input by the complex dynamics of their membrane. One line of research has attempted to resolve this discrepancy by
Sat, Mar 19, 2022