A modeling approach on why simple central pattern generators are built of irregular neurons

Area of Science:

• Neuroscience
• Computational Biology
• Systems Biology

Background:

• The crustacean pyloric Central Pattern Generator (CPG) produces rhythmic motor patterns, but its rhythm generation mechanism remains unclear due to the irregular intrinsic activity of its neurons.
• Understanding CPG function is crucial for deciphering neural control of rhythmic behaviors.

Purpose of the Study:

• To investigate the potential of using networks of irregularly active neurons to generate periodic oscillations.
• To explore the advantages of non-periodic neurons in the transition from bursting to tonic spiking, mimicking biological CPGs.

Main Methods:

• Mathematical modeling using two- and three-neuron Central Pattern Generator (CPG) models.
• Incorporated Hindmarsh-Rose and Hodgkin-Huxley-like neurons with tunable intrinsic dynamics from bursting to tonic spiking.
• Studied two-neuron half-center oscillators (HCOs) with mutual synaptic inhibition and three-neuron models mimicking the pyloric CPG.

Main Results:

• Networks of intrinsically irregular neurons generated wider burst frequency ranges while maintaining regular oscillatory behavior.
• Periodic neurons resulted in limited adaptability to synaptic strength or inability to produce physiologically relevant rhythms.
• Three-neuron models demonstrated similar outcomes, supporting the findings in a more complex network.

Conclusions:

• Neurons with irregular intrinsic activity are effective components for building robust and adaptable Central Pattern Generators (CPGs).
• Irregularly active neurons offer a more flexible substrate for generating rhythmic motor patterns compared to regularly active neurons.
• These findings provide insights into the design principles of biological neural circuits for rhythm generation.