TY - JOUR
T1 - Computational Neuroethology
T2 - A Call to Action
AU - Datta, Sandeep Robert
AU - Anderson, David J.
AU - Branson, Kristin
AU - Perona, Pietro
AU - Leifer, Andrew
N1 - Funding Information:
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 ).
Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2019/10/9
Y1 - 2019/10/9
N2 - 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. The goal of computational neuroethology is to understand the relationship between the brain and purposive behavior that evolved under natural selection. Technology is transforming how we measure and model naturalistic behavior, affording new insight into brain function.
AB - 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. The goal of computational neuroethology is to understand the relationship between the brain and purposive behavior that evolved under natural selection. Technology is transforming how we measure and model naturalistic behavior, affording new insight into brain function.
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U2 - 10.1016/j.neuron.2019.09.038
DO - 10.1016/j.neuron.2019.09.038
M3 - Review article
C2 - 31600508
AN - SCOPUS:85072901822
SN - 0896-6273
VL - 104
SP - 11
EP - 24
JO - Neuron
JF - Neuron
IS - 1
ER -