Related Experiment Video
Updated: Aug 6, 2026

08:38
A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
Published on: November 21, 2019
Distinctly structured social behavior across three rodent strains is associated with different neural activity
Rishika Tiwari1, Alok Nath Mohapatra2,3,4, Claudio J Mendes1
1Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel.
Iscience
|July 24, 2026
Summary
Rodent social behavior varies, but its neural basis is unclear. This study reveals distinct brain activity patterns (theta and gamma coherence) in mice and rats, enabling accurate strain identification and highlighting neural signatures of social strategies.
Area of Science:
- Neuroscience
- Animal Behavior
- Computational Biology
Background:
- Mammalian social behavior exhibits significant interspecies variation.
- The underlying neural mechanisms driving these behavioral differences are not well understood.
- Laboratory rodents are crucial models for studying social behavior.
Purpose of the Study:
- To investigate the neural basis of strain-specific social behavior in rodents.
- To compare social motivation and interaction patterns across different rodent strains.
- To identify electrophysiological markers differentiating social strategies.
Main Methods:
- Behavioral analysis of social preference and free interaction tasks in C57BL/6J mice, CD1 mice, and SD rats.
- Chronic electrode implantation in brain regions related to social motivation.
- Electrophysiological recordings of theta and gamma power and coherence.
- Application of machine learning models for strain classification based on neural data.
Main Results:
- Distinct social behavior patterns were observed: SD rats showed high social motivation, CD1 mice were most active, and C57BL/6J mice were most restrained.
- Strain- and task-specific differences in theta and gamma power and coherence were identified.
- SD rats exhibited low baseline coherence with high interaction-induced coherence, while C57BL/6J mice showed the reverse.
- Machine learning accurately separated strains using electrophysiology, with prelimbic cortex-nucleus accumbens shell coherence being a key differentiator.
Conclusions:
- Neural electrophysiology provides distinct signatures for strain-specific social strategies in rodents.
- Theta and gamma coherence, particularly between the prelimbic cortex and nucleus accumbens shell, are critical for defining these signatures.
- This work advances our understanding of the neural underpinnings of social behavior variation.
