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Probabilistic Encoding Models for Multivariate Neural Data
2019
Frontiers in Neural Circuits
A key problem in systems neuroscience is to characterize how populations of neurons encode information in their patterns of activity. An understanding of the encoding process is essential both for gaining insight into the origins of perception and for the development of brain-computer interfaces. However, this characterization is complicated by the highly variable nature of neural responses, and thus usually requires probabilistic methods for analysis. Drawing on techniques from statistical
doi:10.3389/fncir.2019.00001
pmid:30745864
pmcid:PMC6360288
fatcat:vqnhoyvhwrdotkbqlrgkeoqu3m