Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains
نویسندگان
چکیده
منابع مشابه
Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains
Stimulus reconstruction or decoding methods provide an important tool for understanding how sensory and motor information is represented in neural activity. We address Bayesian decoding methods based on an encoding generalized linear model (GLM) [1, 2] that accurately describes how stimuli are transformed into the spike trains of a group of neurons. The log-concave GLM likelihood is combined wi...
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Stimulus reconstruction or decoding methods provide an important tool for understanding how sensory and motor information is represented in neural activity. We discuss Bayesian decoding methods based on an encoding generalized linear model (GLM) that accurately describes how stimuli are transformed into the spike trains of a group of neurons. The form of the GLM likelihood ensures that the post...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2011
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco_a_00059