@article{2bdf2301b7cc4e5c9bd7ae6d64448584,
title = "On the dimensionality of behavior",
abstract = "There is a growing effort in the {"}physics of behavior{"} that aims at complete quantitative characterization of animal movements under more complex, naturalistic conditions. One reaction to the resulting explosion of high-dimensional data is the search for low-dimensional structure. Here I try to define more clearly what we mean by the dimensionality of behavior, where observable behavior may consist of either continuous trajectories or sequences of discrete states.This discussion also serves to isolate situations in which the dimensionality of behavior is effectively infinite.",
keywords = "complexity, information, prediction",
author = "William Bialek",
note = "Funding Information: ACKNOWLEDGMENTS. This paper is based, in part, on a presentation at the Physics of Behavior Virtual Workshop (30 April 2020), organized by G. J. Berman and G. J. Stephens. Videos are available at https://www.youtube. com/watch?v=xSwWAgp2VdU. My sincere thanks go to Gordon, Greg, and all my fellow panelists for this wonderful event, especially in such difficult times. Thanks go to V. Alba, G. J. Berman, X. Chen, A. Frishman, K. Krishnamurthy, A. M. Leifer, C. W. Lynn, S. E. Palmer, J. W. Shaevitz, and G. J. Stephens for many helpful discussions. This work was supported, in part, by the NSF through the Center for the Physics of Biological Function (Award PHY-1734030) and Grant PHY-1607612, and by the NIH (Grant NS104889). Publisher Copyright: {\textcopyright} 2022 National Academy of Sciences. All rights reserved.",
year = "2022",
month = may,
day = "3",
doi = "10.1073/pnas.2021860119",
language = "English (US)",
volume = "119",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
publisher = "National Academy of Sciences",
number = "18",
}