Population models of temporal differentiation (Tripp and Eliasmith 2010)

"Temporal derivatives are computed by a wide variety of neural circuits, but the problem of performing this computation accurately has received little theoretical study. Here we systematically compare the performance of diverse networks that calculate derivatives using cell-intrinsic adaptation and synaptic depression dynamics, feedforward network dynamics, and recurrent network dynamics. Examples of each type of network are compared by quantifying the errors they introduce into the calculation and their rejection of high-frequency input noise. ..."

Model Type: Realistic Network

Cell Type(s): Abstract integrate-and-fire leaky neuron

Receptors: AMPA; Gaba

Model Concept(s): Temporal Pattern Generation; Simplified Models

Simulation Environment: Nengo

Implementer(s): Tripp, Bryan [bryan.tripp at mail.mcgill.ca]; Eliasmith, Chris [celiasmith at uwaterloo.ca]


Tripp BP, Eliasmith C. (2010). Population models of temporal differentiation. Neural computation. 22 [PubMed]

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