Revealing nonlinear neural decoding by analyzing choices
Sensory data about most natural task-relevant variables are entangled with task-irrelevant nuisance variables. Here, the authors present a theoretical framework for quantifying how the brain uses or decodes its nonlinear information which indicates near-optimal nonlinear decoding.
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Autores principales: | Qianli Yang, Edgar Walker, R. James Cotton, Andreas S. Tolias, Xaq Pitkow |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/8a6c8800814c4391be68ee95e74e47af |
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