Web: http://arxiv.org/abs/2206.08094

June 17, 2022, 1:10 a.m. | Sabera Talukder, Jennifer J. Sun, Matthew Leonard, Bingni W. Brunton, Yisong Yue

cs.LG updates on arXiv.org arxiv.org

Neuroscientists and neuroengineers have long relied on multielectrode neural
recordings to study the brain. However, in a typical experiment, many factors
corrupt neural recordings from individual electrodes, including electrical
noise, movement artifacts, and faulty manufacturing. Currently, common practice
is to discard these corrupted recordings, reducing already limited data that is
difficult to collect. To address this challenge, we propose Deep Neural
Imputation (DNI), a framework to recover missing values from electrodes by
learning from data collected across spatial locations, days, …

arxiv brain deep framework imputation lg neural

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