English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  A simple population code for a fast-changing world

Huys, Q., Zemel, R., Natarajan, R., & Dayan, P. (2005). A simple population code for a fast-changing world. Poster presented at 35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005), Washington, DC, USA.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0005-AAB9-B Version Permalink: http://hdl.handle.net/21.11116/0000-0005-AABA-A
Genre: Poster

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Huys, QJM, Author
Zemel, RS, Author
Natarajan, R, Author
Dayan, P1, Author              
Affiliations:
1External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: There is a wealth of approaches to understanding the ways that populations of neurons encode static, unchanging, stimuli in their spiking activity and how the code thus generated may support relevant computations in neural networks. Bar some notable exceptions, substantially less effort has been devoted to the dynamic case in which the stimuli follow trajectories, changing over the same timescale as the production of the spikes. One instructive instance concerns a population of independent inhomogenous Poisson neurons whose instantaneous firing rates are determined by the immediate value of an evolving stimulus. Decoding the spikes generated by the population is formally an ill-posed problem, whose solution, a posterior distribution over possible stimulus trajectories, depends crucially on prior knowledge about such trajectories. We show that the ideal observer in this case has a simple and intuitive structure, with a posterior mean of the stimulus value that is a weighted average of the preferred stimulus values of the neurons that recently spiked. The prior distribution over trajectories controls how the weights in the average decrease as a function of elapsed time since the spikes. In such population codes, the stimulus trajectory induces strong dependencies among the population of spikes, which the observer needs to take into account when decoding. Thus the code is very complicated, even in this extremely simple, instantaneous encoding scheme. Downstream neurones would need access to many spikes from the entire population to process any individual spike consistently. We show how the implied distribution can be recoded by population spikes that can be treated independently, and finally discuss the relationship between this process of recoding and adaptation.

Details

show
hide
Language(s):
 Dates: 2005-11
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: -
 Degree: -

Event

show
hide
Title: 35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)
Place of Event: Washington, DC, USA
Start-/End Date: 2005-11-12 - 2005-11-16

Legal Case

show

Project information

show

Source 1

show
hide
Title: 35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: 735.16 Start / End Page: - Identifier: -