Temporal correlations and neural spike train entropy.

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a "brute force" approach.

[1]  W. McCulloch,et al.  The limiting information capacity of a neuronal link , 1952 .

[2]  G D Lewen,et al.  Reproducibility and Variability in Neural Spike Trains , 1997, Science.

[3]  Peter Dayan,et al.  The Effect of Correlated Variability on the Accuracy of a Population Code , 1999, Neural Computation.

[4]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[5]  William Bialek,et al.  Synergy in a Neural Code , 2000, Neural Computation.

[6]  E. Adrian,et al.  The impulses produced by sensory nerve endings , 1926, The Journal of physiology.

[7]  Alexander Dimitrov,et al.  Natural time scales for neural encoding , 2000, Neurocomputing.

[8]  J. Miller,et al.  Information theoretic analysis of dynamical encoding by four identified primary sensory interneurons in the cricket cercal system. , 1996, Journal of neurophysiology.

[9]  Michael DeWeese,et al.  Optimization Principles for the Neural Code , 1995, NIPS.

[10]  October I.  Physical Review Letters , 2022 .

[11]  D. Perrett,et al.  The `Ideal Homunculus': decoding neural population signals , 1998, Trends in Neurosciences.

[12]  William Bialek,et al.  Spikes: Exploring the Neural Code , 1996 .

[13]  William Bialek,et al.  Entropy and Information in Neural Spike Trains , 1996, cond-mat/9603127.

[14]  E T Rolls,et al.  Correlations and the encoding of information in the nervous system , 1999, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[15]  W E Skaggs,et al.  Speed, noise, information and the graded nature of neuronal responses. , 1996, Network.

[16]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[17]  T. Albright,et al.  Efficient Discrimination of Temporal Patterns by Motion-Sensitive Neurons in Primate Visual Cortex , 1998, Neuron.

[18]  Shang‐keng Ma.  Calculation of entropy from data of motion , 1981 .