Title
Optimal tuning widths in population coding of periodic variables
Abstract
We study the relationship between the accuracy of a large neuronal population in encoding periodic sensory stimuli and the width of the tuning curves of individual neurons in the population. By using general simple models of population activity, we show that when considering one or two periodic stimulus features, a narrow tuning width provides better population encoding accuracy. When encoding more than two periodic stimulus features, the information conveyed by the population is instead maximal for finite values of the tuning width. These optimal values are only weakly dependent on model parameters and are similar to the width of tuning to orientation or motion direction of real visual cortical neurons. A very large tuning width leads to poor encoding accuracy, whatever the number of stimulus features encoded. Thus, optimal coding of periodic stimuli is different from that of nonperiodic stimuli, which, as shown in previous studies, would require infinitely large tuning widths when coding more than two stimulus features.
Year
DOI
Venue
2006
10.1162/neco.2006.18.7.1555
Neural Computation
Keywords
Field
DocType
population coding
Population,Topology,Neuroscience,Mathematical optimization,Neural coding,Models of neural computation,Coding (social sciences),Stimulus (physiology),Artificial neural network,Periodic graph (geometry),Mathematics,Encoding (memory)
Journal
Volume
Issue
ISSN
18
7
0899-7667
Citations 
PageRank 
References 
5
0.65
8
Authors
2
Name
Order
Citations
PageRank
Marcelo A. Montemurro118219.95
Stefano Panzeri240462.09