Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

ABSTRACT: Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to suc

SUBMITTER: Hu EY 

PROVIDER: S-EPMC4585022 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature