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A texture statistics encoding model reveals hierarchical feature selectivity across human visual cortex
View ORCID ProfileMargaret M. Henderson, View ORCID ProfileMichael J. Tarr, View ORCID ProfileLeila Wehbe
doi: https://doi.org/10.1101/2022.09.23.509292
Margaret M. Henderson
1Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
2Department of Psychology, Carnegie Mellon University, Pittsburgh, USA
3Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA
Michael J. Tarr
1Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
2Department of Psychology, Carnegie Mellon University, Pittsburgh, USA
3Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA
Leila Wehbe
1Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
2Department of Psychology, Carnegie Mellon University, Pittsburgh, USA
3Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA
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Posted September 26, 2022.
A texture statistics encoding model reveals hierarchical feature selectivity across human visual cortex
Margaret M. Henderson, Michael J. Tarr, Leila Wehbe
bioRxiv 2022.09.23.509292; doi: https://doi.org/10.1101/2022.09.23.509292
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