Probabilistic modeling reveals coordinated social interaction states and their multisensory bases

Area of Science:

• Ethology
• Neuroscience
• Animal Behavior

Background:

• Social behavior in animals is complex, involving sensory input and internal states.
• Understanding pairwise interactions is crucial for deciphering group dynamics.

Purpose of the Study:

• Investigate how zebrafish use multiple sensory modalities for social behavior.
• Uncover complex features of early-developmental pairwise interactions.

Main Methods:

• Developed a novel hidden Markov model (HMM) with constrained linear-model emissions.
• Automatically classified states of coordinated interaction using predictive movement analysis.
• Analyzed spontaneous pairwise interactions in zebrafish (Danio rerio).

Main Results:

• Identified two distinct social interaction states alternating within sessions.
• Long-range interactions (shoaling) primarily use vision.
• Rapid synchronized movements (schooling precursors) rely on mechanosensation.

Conclusions:

• Zebrafish exhibit two fundamental modes of social interaction.
• Sensory systems (vision, mechanosensation) are modality-specific for different social behaviors.
• The HMM approach offers broad applicability for analyzing pairwise interactions across species.