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Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method.

Neural Computation(2019)

Cited 1|Views18
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Abstract
Beyond average firing rate, other measurable signals of neuronal activity are fundamental to an understanding of behavior. Recently, hidden Markov models (HMMs) have been applied to neural recordings and have described how neuronal ensembles process information by going through sequences of different states. Such collective dynamics are impossible to capture by just looking at the average firing r...
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Key words
future choice better,models,psth-based
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