Motor-pattern production: interaction of chemical and electrical synapses

Area of Science:

• Computational Neuroscience
• Neural Network Dynamics
• Synaptic Plasticity

Background:

• Neurons exhibiting postinhibitory rebound can generate stable alternating burst patterns when reciprocally inhibited.
• Interactions between oscillating neural circuits are fundamental to understanding complex motor control and network behavior.

Purpose of the Study:

• To investigate the emergent dynamics when two oscillating neuron pairs, with similar but non-identical properties, are coupled.
• To determine how chemical and electrical synapses influence the synchronization and phase relationships of coupled neural oscillators.

Main Methods:

• Theoretical modeling and quantitative calculations of coupled neural pairs.
• Simulation of network behavior under varying strengths of chemical and electrical coupling.
• Analysis of synaptic depression effects on burst pattern dynamics.

Main Results:

• Coupled oscillating neuron pairs exhibit diverse behaviors including synchronized bursts, drifting patterns, antiphase entrainment, intermediate phase locking, and suppression.
• The specific emergent pattern is highly sensitive to the relative strengths of electrical and chemical synaptic connections.
• Synaptic depression at the inhibitory chemical synapse significantly modulates the stability and type of observed network dynamics.

Conclusions:

• The interplay between chemical and electrical coupling, along with synaptic plasticity, dictates the complex emergent dynamics of coupled neural oscillators.
• These findings provide quantitative insights into the mechanisms underlying the flexible control of motor patterns in neural networks.