nips nips2001 nips2001-57 nips2001-57-reference knowledge-graph by maker-knowledge-mining
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Author: Maoz Shamir, Haim Sompolinsky
Abstract: 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.
[1] E. Fetz, K. Yoyoma and W. Smith, Cerebral Cortex (Plenum Press, New York, 1991).
[2] D. Lee, N.L. Port, W. Kruse and A.P. Georgopoulos, J. Neurosci. , 1161 (1998). ¢ £¡
[3] E.M. Maynard, N.G. Hatsopoulos, C.L. Ojakangas, B.D. Acuna, J.N. Sanes, R.A. Normann, and J.P. Donoghue, J. Neurosci. 19, 8083 (1999).
[4] E. Zohary, M.N. Shadlen and W.T. Newsome, Nature , 140 (1994).
[5] L.F. Abbott and P. Dayan, Neural Computation , 91 (1999). ¦¤ ¥ ¡ §¡
[6] H. Sompolinsky, H. Yoon, K. Kang and M. Shamir, Phys. Rev. E, , 051904 (2001); H. Yoon and H. Sompolinsky, Advances in Neural Information Processing Systems 11 (pp. 167). Kearns M.J, Solla S.A and Cohn D.A, Eds., (Cambridge, MA: MIT Press, 1999).
[7] S. Seung and H. Sompolinsky, Proc. Natl. Acad. Sci. USA , 10794 (1993). © ¨
[8] E. Salinas and L.F. Abbott, J. Comp. Neurosci. , 89 (1994). ¡