Barlow, H;
Gardner-Medwin, A;
(2000)
Localist representation can improve efficiency for detection and counting.
Behavioral and Brain Sciences
, 23
(4)
467 - 468.
10.1017/S0140525X00223352.
![[thumbnail of download.pdf]](https://discovery.ucl.ac.uk/style/images/fileicons/application_pdf.png) Preview |
PDF
download.pdf Available under License : See the attached licence file. Download (930kB) |
Abstract
Almost all representations have both distributed and localist aspects, depending upon what properties of the data are being considered. With noisy data, features represented in a localist way can be detected very efficiently, and in binary representations they can be counted more efficiently than those represented in a distributed way. Brains operate in noisy environments, so the localist representation of behaviourally important events is advantageous, and fits what has been found experimentally. Distributed representations require more neurons to perform as efficiently, but they do have greater versatility.
| Type: | Article |
|---|---|
| Title: | Localist representation can improve efficiency for detection and counting |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1017/S0140525X00223352 |
| Publisher version: | http://dx.doi.org/10.1017/S0140525X00223352 |
| Language: | English |
| Additional information: | © 2000 Cambridge University Press |
| Keywords: | neural coding, representation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/185671 |
Archive Staff Only
 |
View Item |
