In this section
@article{Ghosh:2020:10.1523/ENEURO.0408-19.2020,
author = {Ghosh, M and Rihel, J},
doi = {10.1523/ENEURO.0408-19.2020},
journal = {eNeuro},
title = {Hierarchical compression reveals sub-second to day-long structure in larval zebrafish behavior},
url = {http://dx.doi.org/10.1523/ENEURO.0408-19.2020},
volume = {7},
year = {2020}
}
TY - JOUR
AB - Animal behavior is dynamic, evolving over multiple timescales from milliseconds to days and even across a lifetime. To understand the mechanisms governing these dynamics, it is necessary to capture multi-timescale structure from behavioral data. Here, we develop computational tools and study the behavior of hundreds of larval zebrafish tracked continuously across multiple 24-h day/night cycles. We extracted millions of movements and pauses, termed bouts, and used unsupervised learning to reduce each larva's behavior to an alternating sequence of active and inactive bout types, termed modules. Through hierarchical compression, we identified recurrent behavioral patterns, termed motifs. Module and motif usage varied across the day/night cycle, revealing structure at sub-second to day-long timescales. We further demonstrate that module and motif analysis can uncover novel pharmacological and genetic mutant phenotypes. Overall, our work reveals the organization of larval zebrafish behavior at multiple timescales and provides tools to identify structure from large-scale behavioral datasets.
AU - Ghosh,M
AU - Rihel,J
DO - 10.1523/ENEURO.0408-19.2020
PY - 2020///
SN - 2373-2822
TI - Hierarchical compression reveals sub-second to day-long structure in larval zebrafish behavior
T2 - eNeuro
UR - http://dx.doi.org/10.1523/ENEURO.0408-19.2020
UR - https://www.ncbi.nlm.nih.gov/pubmed/32241874
VL - 7
ER -
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