Multichannel time encoding with integrate-and-fire neurons

Authors:
Aurel A. Lazar
Affiliations:
Department of Electrical Engineering, Columbia University, 500 West, 120th Street, New York, NY 10027, USA
Venue:
Neurocomputing
Year:
2005

Citing 0
Cited 5

Information representation with an ensemble of Hodgkin-Huxley neurons

Neurocomputing
Faithful representation of stimuli with a population of integrate-and-fire neurons

Neural Computation
Reconstruction of sensory stimuli encoded with integrate-and-fire neurons with random thresholds

EURASIP Journal on Advances in Signal Processing - Special issue on statistical signal processing in neuroscience
A simple model of spike processing

Neurocomputing
Population encoding with Hodgkin-Huxley neurons

IEEE Transactions on Information Theory - Special issue on information theory in molecular biology and neuroscience

Quantified Score

Hi-index	0.02

Visualization

Abstract

Time encoding is a mechanism of mapping amplitude information into a time sequence. We show that multichannel time encoding using filter banks and integrate-and-fire neurons provides, under natural conditions, an invertible representation of information, i.e., a sensory stimulus can be recovered from its multidimensional spike train representation loss-free. We describe an algorithm for perfect stimulus recovery and derive conditions that guarantee its convergence.