Functional interactions among neurons within single columns of macaque V1

Abstract
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Abstract

Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional interactions between neurons thereby providing an unprecedented view of local circuits. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally interacting neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the synchrony and strength of functional interactions within single cortical columns. Despite neurons residing within the same column, both measures of interactions depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of functionally interacting pairs to categorize interactions between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional interactions within the full population. These classes of functional interactions were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.

Data availability

All the raw data generated as part of this study are publicly accessible. All the raw code generated for analyzing the data has already been deposited to GitHub and is currently freely accessible (https://github.com/et22/functional_connections_macaque_v1).

The following data sets were generated

1. Trepka E
2. Zhu S
3. Xia R
4. Chen X
5. Moore T
(2022) Functional Interactions Among Neurons within Single Columns of Macaque V1
Dryad Digital Repository, doi:10.5061/dryad.x3ffbg7p2.

https://dx.doi.org/10.5061/dryad.x3ffbg7p2

Article and author information

Author details

Ethan B Trepka

Neurosciences Program, Stanford University, Stanford, United States

Competing interests
No competing interests declared.
Shude Zhu

Department of Neurobiology, Howard Hughes Medical Institute, Stanford University, Stanford, United States

For correspondence
shude@stanford.edu

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0002-8674-9607
Ruobing Xia

Department of Neurobiology, Howard Hughes Medical Institute, Stanford University, Stanford, United States

Competing interests
No competing interests declared.
Xiaomo Chen

Department of Neurobiology, Physiology, and BehaviorDepartment of Neurobiology, University of California, Davis, Davis, United States

Competing interests
No competing interests declared.
Tirin Moore

Neurobiology, Howard Hughes Medical Institute, Stanford University, Stanford, United States

Competing interests
Tirin Moore, Senior editor, eLife.

"This ORCID iD identifies the author of this article:" 0000-0002-3345-2930

Funding

National Eye Institute (Research Project (R01),EY014924)

Tirin Moore

National Institute of Neurological Disorders and Stroke (NS116623)

Tirin Moore

National Eye Institute (Career transition award (K99),EY029759)

Xiaomo Chen

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All experimental procedures were in accordance with National Institutes of Health Guide for the Care and Use of Laboratory Animals, the Society for Neuroscience Guidelines and Policies, and with approved Institutional Animal Care and Use Committee (IACUC) protocol (#APLAC-9900) of Stanford University.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.