Dynamics of Encoding in Neuron Populations: Some General Mathematical Features
Abstract
The use of a population dynamics approach promises efficient simulation of large assemblages of neurons. Depending on the issues addressed and the degree of realism incorporated in the simulated neurons, a wide range of different population dynamics formulations can be appropriate. Here we present a common mathematical structure that these various formulations share and that implies dynamical behaviors that they have in common. This underlying structure serves as a guide toward efficient means of simulation. As an example, we derive the general population firing-rate frequency-response and show how it may be used effectively to address a broad range of interacting-population response and stability problems. A few specific cases will be worked out. A summary of this work appears at the end, before the appendix.
Cite
Text
Knight. "Dynamics of Encoding in Neuron Populations: Some General Mathematical Features." Neural Computation, 2000. doi:10.1162/089976600300015673Markdown
[Knight. "Dynamics of Encoding in Neuron Populations: Some General Mathematical Features." Neural Computation, 2000.](https://mlanthology.org/neco/2000/knight2000neco-dynamics/) doi:10.1162/089976600300015673BibTeX
@article{knight2000neco-dynamics,
title = {{Dynamics of Encoding in Neuron Populations: Some General Mathematical Features}},
author = {Knight, Bruce W.},
journal = {Neural Computation},
year = {2000},
pages = {473-518},
doi = {10.1162/089976600300015673},
volume = {12},
url = {https://mlanthology.org/neco/2000/knight2000neco-dynamics/}
}