Journal Article
Automated behavioral profiling using neural networks reveals differences in stress-like behavior between cave and surface-dwelling Astyanax mexicanus
Padmanaban, N., Ambosie. R., Choy, S., Marcus, S., Nilsson, S.R.O., Keene, A.C., Kowalko, J.E. and Duboué, E.R.
Record Number:
6884
Year:
2025
Journal:
bioRxiv preprint
Notes:
Posted February 5, 2025. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 licence
Abstract:
Behavioral stress responses allow animals to quickly adapt to local environments and are
critical for survival. Stress responses provide an ideal model for investigating the
evolution of complex behaviors due to their conservation across species, critical role in
survival, and integration of behavioral and physiological components. The Mexican
cavefish (Astyanax mexicanus) has evolved dramatically different stress responses
compared to river-dwelling surface fish morphs, providing a model to investigate the
neural and evolutionary basis of stress-like responses. Surface morphs inhabit predator
rich environments whereas cave-dwelling morphs occupy predator-free habitats. While
these key ecological variables may underlie differences in stress responses, the
complexity of the behavioral differences has not been thoroughly examined. By
leveraging automated pose-tracking and machine learning tools, we quantified a range of
behaviors associated with stress, including freezing, bottom-dwelling, and hyperactivity,
during a novel tank assay. Surface fish exhibited heightened stress responses
characterized by prolonged bottom-dwelling and frequent freezing, while cavefish
demonstrated reduced stress behaviors, marked by greater exploration and minimal
freezing. Analysis of F2 hybrids revealed that a subset of behaviors, freezing and bottom
dwelling, co-segregated, suggesting shared genetic or physiological underpinnings. Our
findings illustrate the power of computational tools for high-throughput behavioral
phenotyping, enabling precise quantification of complex traits and revealing the genetic
and ecological factors driving their evolution. This study provides a framework for
understanding how integrated behavioral and physiological traits evolve, offering broader
insights into the mechanisms underlying the diversification of animal behavior in natural
systems.
Times Cited:
1
Relevent Species: