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Estimating and interpreting nonlinear receptive fields of sensory responses with deep neural network models
View ORCID ProfileMenoua Keshishian, Hassan Akbari, Bahar Khalighinejad, Jose Herrero, Ashesh D. Mehta, Nima Mesgarani
doi: https://doi.org/10.1101/832212
Menoua Keshishian
1Department of Electrical Engineering, Columbia University, New York, NY
2Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
Hassan Akbari
1Department of Electrical Engineering, Columbia University, New York, NY
2Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
Bahar Khalighinejad
1Department of Electrical Engineering, Columbia University, New York, NY
2Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
Jose Herrero
4Feinstein Institute for Medical Research, Manhasset, NY
Ashesh D. Mehta
3Department of Neurosurgery, Hofstra-Northwell School of Medicine and Feinstein Institute for Medical Research, Manhasset, NY
4Feinstein Institute for Medical Research, Manhasset, NY
Nima Mesgarani
1Department of Electrical Engineering, Columbia University, New York, NY
2Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
Posted November 07, 2019.
Estimating and interpreting nonlinear receptive fields of sensory responses with deep neural network models
Menoua Keshishian, Hassan Akbari, Bahar Khalighinejad, Jose Herrero, Ashesh D. Mehta, Nima Mesgarani
bioRxiv 832212; doi: https://doi.org/10.1101/832212
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