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Decision-making neural circuits mediating social behaviors : An attractor network model
Julián Hurtado-López1, David F Ramirez-Moreno2, Terrence J Sejnowski3
1Department of Mathematics, Universidad Autónoma de Occidente, Cll 25 No. 115-85 Km 2 vía Cali-Jamundí, 760030, Cali, Colombia. jhurtado@uao.edu.co.
Journal of Computational Neuroscience
|June 30, 2017
Summary
We developed a mathematical model for social behavior control using continuous attractor networks. This model accurately predicts aggression control and other behaviors observed in experiments.
Area of Science:
- Computational neuroscience
- Mathematical modeling of behavior
Background:
- Understanding the neural mechanisms of social behavior is complex.
- Previous models have not fully captured the dynamics of social control.
Purpose of the Study:
- To propose and analyze a mathematical model of a continuous attractor network for social behavior control.
- To investigate the model's ability to replicate experimentally observed behaviors.
Main Methods:
- Developed a continuous attractor network model.
- Utilized bifurcation analysis.
- Performed computer simulations.
Main Results:
- The model demonstrates stable steady states.
- Identified thresholds for state transitions corresponding to observed social behaviors.
- Showcased potential for modeling aggression control.
Conclusions:
- The proposed mathematical model provides a framework for understanding neural control of social behaviors.
- Model performance aligns with experimental findings, particularly in aggression regulation.
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