Emergent Network Topology within the Respiratory Rhythm-Generating Kernel Evolved In Silico

Area of Science:

• Neuroscience
• Computational Biology
• Systems Biology

Background:

• The pre-Bötzinger Complex (preBötC) is the kernel for mammalian respiratory rhythm generation.
• Its network topology may be optimized for efficient and robust respiratory rhythm production.
• Understanding preBötC network structure is crucial for respiratory control research.

Purpose of the Study:

• To identify the synaptic connection topology within the preBötC.
• To investigate how network structure contributes to respiratory rhythm generation.
• To explore the role of inhibitory neurons in preBötC network dynamics.

Main Methods:

• Developed an evolutionary algorithm to optimize neuronal network topology.
• Created an in silico preBötC model with optimized synchronous population bursts.
• Analyzed network connectivity and compared evolved network with small-world (SW) networks.

Main Results:

• The evolved preBötC model exhibits skewed/heavy-tailed degree distribution in its excitatory subnetwork.
• Inhibitory neurons, particularly non-tonic pacemaker inhibitory neurons, significantly influence the excitatory subnetwork.
• The evolved network demonstrates superior performance in generating synchronous bursts compared to SW networks.

Conclusions:

• The preBötC network topology is optimized for efficient respiratory rhythm generation.
• Specific connectivity patterns and the role of inhibitory neurons are key to preBötC function.
• The evolved network provides a more accurate model for preBötC dynamics than traditional SW networks.