TY - GEN
T1 - Correlation codes in neuronal populations
AU - Shamir, Maoz
AU - Sompolinsky, Haim
PY - 2002
Y1 - 2002
N2 - Population codes often rely on the tuning of the mean responses to the stimulus parameters. However, this information can be greatly suppressed by long range correlations. Here we study the efficiency of coding information in the second order statistics of the population responses. We show that the Fisher Information of this system grows linearly with the size of the system. We propose a bilinear readout model for extracting information from correlation codes, and evaluate its performance in discrimination and estimation tasks. It is shown that the main source of information in this system is the stimulus dependence of the variances of the single neuron responses.
AB - Population codes often rely on the tuning of the mean responses to the stimulus parameters. However, this information can be greatly suppressed by long range correlations. Here we study the efficiency of coding information in the second order statistics of the population responses. We show that the Fisher Information of this system grows linearly with the size of the system. We propose a bilinear readout model for extracting information from correlation codes, and evaluate its performance in discrimination and estimation tasks. It is shown that the main source of information in this system is the stimulus dependence of the variances of the single neuron responses.
UR - http://www.scopus.com/inward/record.url?scp=36849003600&partnerID=8YFLogxK
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AN - SCOPUS:36849003600
SN - 0262042088
SN - 9780262042086
T3 - Advances in Neural Information Processing Systems
BT - Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001
PB - Neural information processing systems foundation
T2 - 15th Annual Neural Information Processing Systems Conference, NIPS 2001
Y2 - 3 December 2001 through 8 December 2001
ER -