Recognition of temporal event sequences by a network of cortical neurons

Authors:
Maciej T. Lazarewicz;Sandhitsu Das;Leif H. Finkel
Affiliations:
Department of Bioengineering, University of Pennsylvania, 301 Hayden Hall, 3320 Smith Walk, Philadelphia, PA 19104, USA;Department of Bioengineering, University of Pennsylvania, 301 Hayden Hall, 3320 Smith Walk, Philadelphia, PA 19104, USA;Department of Bioengineering, University of Pennsylvania, 301 Hayden Hall, 3320 Smith Walk, Philadelphia, PA 19104, USA
Venue:
Neurocomputing
Year:
2005

Citing 2
Cited 1

An efficient method for computing synaptic conductances based on a kinetic model of receptor binding

Neural Computation
The NEURON simulation environment

Neural Computation

2008 Special Issue: Deterministic neural dynamics transmitted through neural networks

Neural Networks

Quantified Score

Hi-index	0.01

Visualization

Abstract

Recognition of ordered sequences of temporal events is central to many perceptual recognition tasks, from speech detection to analysis of biological motion. We describe a simple cortical network capable of recognizing event sequences through a process of encoding followed by detection. The network is composed of regular spiking and fast spiking neurons, with minimal connectivity. Ordered sequences of inputs occurring over tens-to-hundreds of milliseconds, are time compressed by the network into tightly clustered spike outputs occurring over a few milliseconds. We investigate the ability of the network to accurately encode the input pattern, in the presence or absence of noise. We show that information about relative input timings are preserved in the output interspike intervals.