Computational Neuroethology: A Call to Action
Abstract
The brain is worthy of study because it is in charge of behavior. A flurry of recent technical advances in measuring and quantifying naturalistic behaviors provide an important opportunity for advancing brain science. However, the problem of understanding unrestrained behavior in the context of neural recordings and manipulations remains unsolved, and developing approaches to addressing this challenge is critical. Here we discuss considerations in computational neuroethology—the science of quantifying naturalistic behaviors for understanding the brain—and propose strategies to evaluate progress. We point to open questions that require resolution and call upon the broader systems neuroscience community to further develop and leverage measures of naturalistic, unrestrained behavior, which will enable us to more effectively probe the richness and complexity of the brain.
Additional Information
© 2019 Elsevier. Available online 9 October 2019. We are unfortunately unable to comprehensively cite the rich literature on this topic due to space limitations—we thank the many talented colleagues working in this area for inspiration. This review was prompted by a symposium sponsored by the Simons Collaboration on the Global Brain. S.R.D., A.L., D.J.A., and P.P. are supported by grants from the Simons Collaboration on the Global Brain. S.R.D. is supported by NIH grants U24NS109520, RO1DC016222, U19NS108179, and U19NS112953. A.L. is supported by NSF CAREER Award 1845137. D.J.A. is supported by NIH grants RO1MH085082 and RO1MH112593. This work was supported in part by the National Science Foundation, through the Center for Physics of Biological Function (PHY-1734030). Declaration of Interests: S.R.D. is a is a founder of Syllable Life Sciences.Attached Files
Accepted Version - nihms-1545584.pdf
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Additional details
- PMCID
- PMC6981239
- Eprint ID
- 99184
- DOI
- 10.1016/j.neuron.2019.09.038
- Resolver ID
- CaltechAUTHORS:20191009-095543534
- Simons Foundation
- NIH
- U24NS109520
- NIH
- RO1DC016222
- MIH
- U19NS108179
- NIH
- U19NS112953
- NSF
- IOS-1845137
- NIH
- RO1MH085082
- NIH
- RO1MH112593
- NSF
- PHY-1734030
- Howard Hughes Medical Institute (HHMI)
- Created
-
2019-10-09Created from EPrint's datestamp field
- Updated
-
2022-02-12Created from EPrint's last_modified field
- Caltech groups
- Tianqiao and Chrissy Chen Institute for Neuroscience