The Journal of Neurophysiology Vol. 87 No. 3 March 2002, pp. 1659-1663
Copyright ©2002 by the American Physiological Society

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Decoding Neural Spike Trains: Calculating the Probability That a Spike Train and an External Signal Are Related

Department of Child Neurology, Stanford University Medical Center, Stanford, California 94305

Sanger, Terence D. Decoding Neural Spike Trains: Calculating the Probability That a Spike Train and an External Signal Are Related. J. Neurophysiol. 87: 1659-1663, 2002. Experimental and clinical applications of extracellular recordings of spiking cell activity frequently are used to relate the activity of a cell to externally measurable signals such as surface potentials, sensory stimuli, or movement measurements. When the external signal is time-varying, correlation methods have traditionally been used to quantify the degree of relation with the neural firing. However, in some circumstances correlation methods can give misleading results. A new algorithm is described that estimates the extent to which a spike train is related to a continuous time-varying signal. The technique calculates the probability of generating a spike train with Poisson statistics if the time-varying signal determines the Poisson rate. This is accomplished by successive division of the signal and the spike train into halves and recursive calculation of the probability of each half-signal. The performance of the new algorithm is compared with the performance of correlation methods on simulated data.