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Scaling Up Neuroscience
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Nature Neuroscience  7, 456 - 461 (2004)
Published online: 27 April 2004; | doi:10.1038/nn1228

Multiple neural spike train data analysis: state-of-the-art and future challenges

Emery N Brown1, Robert E Kass2 & Partha P Mitra3

1  Emery N. Brown is in the Neuroscience Statistics Research Laboratory, Department of Anesthesia and Critical Care, Massachusetts General Hospital, and the Division of Health Sciences and Technology, Harvard Medical School, Massachusetts Institute of Technology, Boston, Massachusetts 02114, USA.

2  Robert E. Kass is in the Department of Statistics, Carnegie Mellon University and the Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania 15208, USA.

3  Partha P. Mitra is at the Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA.

Correspondence should be addressed to Emery N Brown brown@neurostat.mgh.harvard.edu
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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Nature Neuroscience
ISSN: 1097-6256
EISSN: 1546-1726
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