Abstract
Multiple electrodes are now a standard tool in neuroscience research that make it possible to study the simultaneous activity of several neurons in a given brain region or across different regions. The data from multi-electrode studies present important analysis challenges that must be resolved for optimal use of these neurophysiological measurements to answer questions about how the brain works. Here we review statistical methods for the analysis of multiple neural spike-train data and discuss future challenges for methodology research.
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Acknowledgements
Support for this work was provided in part by NIH grants MH66410 to P.M. and E.N.B., MH62528 to P.M., MH64537 to R.E.K., and MH59733, MH61637 and DA015664 to E.N.B. We thank S. Grün for comments on an earlier draft of this manuscript, G. Gerstein for permission to use Fig. 1d and R. Barbieri for help preparing the figures.
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Brown, E., Kass, R. & Mitra, P. Multiple neural spike train data analysis: state-of-the-art and future challenges. Nat Neurosci 7, 456â461 (2004). https://doi.org/10.1038/nn1228
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DOI: https://doi.org/10.1038/nn1228