Abstract

Neural recording technologies increasingly enable simultaneous measurement of neural activity from multiple brain areas. To gain insight into distributed neural computations, a commensurate advance in experimental and analytical methods is necessary. We discuss two opportunities towards this end: the manipulation and modeling of neural population dynamics.

Details

Title
Measurement, manipulation and modeling of brain-wide neural population dynamics
Author
Shenoy, Krishna V 1   VIAFID ORCID Logo  ; Kao, Jonathan C 2 

1  Stanford University, Department of Electrical Engineering, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Department of Bioengineering, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Department of Neurobiology, School of Medicine, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Wu Tsai Neuroscience Institutes, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Bio-X Institute, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Howard Hughes Medical Institute (HHMI) at Stanford University, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956) 
2  University of California, Los Angeles, Department of Electrical and Computer Engineering, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718); University of California, Los Angeles, Neurosciences Program, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-020-20371-1
ProQuest document ID
2481001685
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.