Computing with Action Potentials
Abstract
Most computational engineering based loosely on biology uses contin(cid:173) uous variables to represent neural activity. Yet most neurons communi(cid:173) cate with action potentials. The engineering view is equivalent to using a rate-code for representing information and for computing. An increas(cid:173) ing number of examples are being discovered in which biology may not be using rate codes. Information can be represented using the timing of action potentials, and efficiently computed with in this representation. The "analog match" problem of odour identification is a simple problem which can be efficiently solved using action potential timing and an un(cid:173) derlying rhythm. By using adapting units to effect a fundamental change of representation of a problem, we map the recognition of words (hav(cid:173) ing uniform time-warp) in connected speech into the same analog match problem. We describe the architecture and preliminary results of such a recognition system. Using the fast events of biology in conjunction with an underlying rhythm is one way to overcome the limits of an event(cid:173) driven view of computation. When the intrinsic hardware is much faster than the time scale of change of inputs, this approach can greatly increase the effective computation per unit time on a given quantity of hardware.
Cite
Text
Hopfield et al. "Computing with Action Potentials." Neural Information Processing Systems, 1997.Markdown
[Hopfield et al. "Computing with Action Potentials." Neural Information Processing Systems, 1997.](https://mlanthology.org/neurips/1997/hopfield1997neurips-computing/)BibTeX
@inproceedings{hopfield1997neurips-computing,
title = {{Computing with Action Potentials}},
author = {Hopfield, John J. and Brody, Carlos D. and Roweis, Sam},
booktitle = {Neural Information Processing Systems},
year = {1997},
pages = {166-172},
url = {https://mlanthology.org/neurips/1997/hopfield1997neurips-computing/}
}