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Topographical Estimation of Visual Population Receptive Fields by fMRI
Published on: February 3, 2015
Biraj Pandey1, Marius Pachitariu2, Bingni W Brunton3
1Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.
This study introduces a novel model of neuronal receptive fields as random, variable samples, connecting sensory processing to artificial neural networks. This approach enhances signal detection and improves learning efficiency in artificial tasks.
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