Bidirectionally Regulating Gamma Oscillations in Wilson-Cowan Model by Self-Feedback Loops: A Computational Study

Area of Science:

• Computational Neuroscience
• Neural Dynamics

Background:

• The Wilson-Cowan model simulates neural activity and gamma oscillations linked to cognition.
• Excitatory and inhibitory inputs modulate gamma oscillations, but self-feedback loop roles are unclear.

Purpose of the Study:

• Investigate the regulatory mechanisms of gamma oscillations by inhibitory and excitatory self-feedback loops.
• Elucidate how these feedback loops cooperate to generate and tune oscillation frequency.

Main Methods:

• Bifurcation analysis
• Spectrum analysis
• Theoretical analysis

Main Results:

• Inhibitory self-feedback hinders gamma oscillation generation but increases frequency.
• Excitatory self-feedback promotes gamma oscillation generation but decreases frequency.
• Feedback loops cooperatively and bidirectionally regulate oscillation frequency.

Conclusions:

• Inhibitory and excitatory self-feedback loops play complementary roles in Wilson-Cowan model gamma oscillations.
• These loops offer a flexible mechanism for generating and regulating neural oscillation frequency.
• Findings provide hypotheses for experimental validation.