Abstract

Fixation constraints in visual tasks are ubiquitous in visual and cognitive neuroscience. Despite its widespread use, fixation requires trained subjects, is limited by the accuracy of fixational eye movements, and ignores the role of eye movements in shaping visual input. To overcome these limitations, we developed a suite of hardware and software tools to study vision during natural behavior in untrained subjects. We measured visual receptive fields and tuning properties from multiple cortical areas of marmoset monkeys who freely viewed full-field noise stimuli. The resulting receptive fields and tuning curves from primary visual cortex (V1) and area MT match reported selectivity from the literature which was measured using conventional approaches. We then combined free viewing with high-resolution eye tracking to make the first detailed 2D spatiotemporal measurements of foveal receptive fields in V1. These findings demonstrate the power of free viewing to characterize neural responses in untrained animals while simultaneously studying the dynamics of natural behavior.

Studying visual processing during natural eye movements in untrained animals is challenging. Here, the authors provide a method for accurately measuring the retinal input to study visual processing and neural selectivity during natural oculomotor behavior in non-human primates.

Details

Title
Detailed characterization of neural selectivity in free viewing primates
Author
Yates, Jacob L. 1   VIAFID ORCID Logo  ; Coop, Shanna H. 2 ; Sarch, Gabriel H. 3 ; Wu, Ruei-Jr 4 ; Butts, Daniel A. 5   VIAFID ORCID Logo  ; Rucci, Michele 6   VIAFID ORCID Logo  ; Mitchell, Jude F. 6   VIAFID ORCID Logo 

 University of Rochester, Brain and Cognitive Sciences, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174); University of Rochester, Center for Visual Science, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174); University of Maryland, Department of Biology and Program in Neuroscience and Cognitive Science, College Park, USA (GRID:grid.164295.d) (ISNI:0000 0001 0941 7177); UC Berkeley, Herbert Wertheim School of Optometry and Vision Science, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878) 
 University of Rochester, Brain and Cognitive Sciences, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174); University of Rochester, Center for Visual Science, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174); Stanford University, Neurobiology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956) 
 University of Rochester, Brain and Cognitive Sciences, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174); Carnegie Mellon University, Neuroscience Institute, Pittsburgh, USA (GRID:grid.147455.6) (ISNI:0000 0001 2097 0344) 
 University of Rochester, Center for Visual Science, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174); University of Rochester, Institute of Optics, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174) 
 University of Maryland, Department of Biology and Program in Neuroscience and Cognitive Science, College Park, USA (GRID:grid.164295.d) (ISNI:0000 0001 0941 7177) 
 University of Rochester, Brain and Cognitive Sciences, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174); University of Rochester, Center for Visual Science, Rochester, USA (GRID:grid.16416.34) (ISNI:0000 0004 1936 9174) 
Pages
3656
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2827821922
Copyright
© The Author(s) 2023. 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.