Plastic systemic inhibition controls amplitude while allowing phase pattern in a stochastic neural field model

Area of Science:

• Computational Neuroscience
• Theoretical Neuroscience
• Mathematical Biology

Background:

• Neural field models are used to study large-scale brain activity.
• Oscillatory phase patterns are fundamental to neural function.
• Uncontrolled amplitude growth can limit the realism of these models.

Purpose of the Study:

• To investigate oscillatory phase pattern formation and amplitude control in a linearized stochastic neuron field model.
• To explore the role of systemic inhibitory mechanisms in regulating neural field dynamics.
• To determine if plastic inhibition can enable sustained phase patterns with bounded amplitudes.

Main Methods:

• Simulated Mexican-hat-coupled stochastic processes.
• Introduced static and plastic (adaptive) systemic inhibitory mechanisms.
• Analyzed the impact of these mechanisms on amplitude boundedness and phase pattern formation.

Main Results:

• Spatial phase pattern formation required unrealistically large amplitudes without inhibition.
• Static inhibition bounded amplitudes but prevented sustained phase patterns.
• Plastic systemic inhibition achieved both bounded amplitudes and sustained phase patterns.

Conclusions:

• Plastic inhibitory mechanisms are essential for dynamic amplitude control in neural field models.
• These mechanisms allow for the development of phase synchronization patterns.
• Plastic systemic inhibition may play a significant role in regulating brain oscillatory functioning.