An LSTM-based adversarial variational autoencoder framework for self-supervised neural decoding of behavioral choices
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DOI: 10.1088/1741-2552/ad3eb3
Abstract: Objective.This paper presents data-driven solutions to address two challenges in the problem of linking neural data and behavior: (1) unsupervised analysis of behavioral data and automatic label generation from behavioral observations, and (2) extraction of… read more here.
Keywords: autoencoder; variational autoencoder; neural decoding; adversarial variational ... See more keywords