Bistability and criticality in the stochastic Wilson-Cowan model

Area of Science:

• Computational Neuroscience
• Theoretical Physics
• Complex Systems

Background:

• The Wilson-Cowan model describes neural population dynamics.
• Understanding neural bistability is crucial for brain function.

Purpose of the Study:

• Investigate a stochastic Wilson-Cowan model with superlinear neuronal response.
• Analyze the emergence and characteristics of bistable neural activity.

Main Methods:

• Simulated a stochastic Wilson-Cowan neural network model.
• Analyzed phase transitions and critical phenomena.
• Examined activity avalanche distributions.

Main Results:

• Identified a parameter region with two coexisting attractive fixed points: a critical low-activity state and a supercritical high-activity state.
• Observed system state switching and a bimodal avalanche distribution (power-law and large avalanche bump).
• Linked bistability to a first-order phase transition and critical behavior to the spinodal line.

Conclusions:

• The stochastic Wilson-Cowan model exhibits bistability with distinct critical and supercritical activity regimes.
• Bimodal avalanche distributions reflect the coexistence of these two states.
• Model provides insights into neural state transitions and criticality.