Model discovery to link neural activity to behavioral tasks
- The Ohio State University, United States
Abstract
Brains are not engineered solutions to a well-defined problem but arose through selective pressure acting on random variation. It is therefore unclear how well a model chosen by an experimenter can relate neural activity to experimental conditions. Here we developed 'Model identification of neural encoding (MINE)'. MINE is an accessible framework using convolutional neural networks (CNN) to discover and characterize a model that relates aspects of tasks to neural activity. Although flexible, CNNs are difficult to interpret. We use Taylor decomposition approaches to understand the discovered model and how it maps task features to activity. We apply MINE to a published cortical dataset as well as experiments designed to probe thermoregulatory circuits in zebrafish. MINE allowed us to characterize neurons according to their receptive field and computational complexity, features which anatomically segregate in the brain. We also identified a new class of neurons that integrate thermosensory and behavioral information which eluded us previously when using traditional clustering and regression-based approaches.
Data availability
All data generated in this study is publicly available. Links are provided in the 'Materials and Methods - Code and data availability' section.
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Processed data for "Model-free identification of neural encoding (MINE)" publicationZenodo; doi.org/10.5281/zenodo.7737788.
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Thermoregulatory Responses ForebrainDandi Archive, id:000235.
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Thermoregulatory Responses MidbrainDandi Archive, id:000236.
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Thermoregulatory Responses HindbrainDandi Archive, id:000237.
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Thermoregulatory Responses Reticulospinal systemDandi Archive, id:000238.
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CNN weight data for "Model-free identification of neural encoding (MINE)" publication - Set 1Zenodo; doi.org/10.5281/zenodo.7738603.
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CNN weight data for "Model-free identification of neural encoding (MINE)" publication - Set 2Zenodo; doi.org/10.5281/zenodo.7741542.
Article and author information
Author details
Funding
National Institutes of Health (5R01NS123887-02)
- Jamie D Costabile
- Kaarthik A Balakrishnan
- Martin Haesemeyer
The Ohio State University Wexner Medical Center
- Sina Schwinn
- Martin Haesemeyer
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: Animal handling and experimental procedures were approved by the Ohio State University Institutional Animal Care and Use Committee (IACUC Protocol #: 2019A00000137 and 2019A00000137-R1).
Copyright
© 2023, Costabile et al.
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.
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Model discovery to link neural activity to behavioral tasks
eLife 12:e83289.
https://doi.org/10.7554/eLife.83289
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