Uncovering multiscale structure in the variability of larval zebrafish navigation

Area of Science:

• Ethology
• Neuroscience
• Computational Biology

Background:

• Animal movement exhibits variability due to internal states and environmental interactions.
• Understanding the structure of this variability is key to deciphering behavioral control.
• Long-lived motor strategies shape behavioral phenotypes across different timescales.

Approach:

• Developed novel computational models to bridge different timescales of movement.
• Enabled quantitative comparison of behavioral phenotypes among individual animals.
• Applied the model to larval zebrafish exposed to diverse sensory cues.

Key Points:

• Identified a hierarchy of motor strategies in zebrafish, primarily cruising and wandering, influenced by light, dark, and prey cues.
• Demonstrated that prior and immediate prey exposure drives exploitation phenotypes.
• Uncovered unexplained behavioral variability, suggesting hidden internal states influencing exploration-exploitation trade-offs.

Conclusions:

• The developed approach extracts movement strategy timescales, revealing hierarchical structure in phenotypic variability.
• Prior experience and internal states significantly influence zebrafish navigation strategies beyond immediate sensory input.
• This work provides insights into the interplay of internal states, experience, and environmental cues in shaping animal behavior.