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Electrophysiology on Isolated Brainstem-spinal Cord Preparations from Newborn Rodents Allows Neural Respiratory Network Output Recording
Published on: November 19, 2015
Multiple rhythmic states in a model of the respiratory central pattern generator
Jonathan E Rubin1, Natalia A Shevtsova, G Bard Ermentrout
1Dept. of Mathematics, Univ. of Pittsburgh, Pittsburgh, PA, USA. rubin@math.pitt.edu
Journal of Neurophysiology
|February 6, 2009
Summary
Respiratory patterns shift with physiological changes. A minimal neural network model explains how brainstem network reductions alter breathing from three-phase to one-phase oscillations, with persistent sodium current influencing period control.
Area of Science:
- Neuroscience
- Respiratory Physiology
- Computational Biology
Background:
- Normal breathing exhibits a three-phase pattern.
- This pattern is disrupted by metabolic or physiological changes.
- Brainstem respiratory network alterations lead to pattern reorganization.
Purpose of the Study:
- To model a minimal neural network explaining respiratory pattern transformations.
- To analyze the role of persistent sodium current (I(NaP)) in respiratory rhythm generation.
- To investigate state-dependent mechanisms of respiratory rhythm control.
Main Methods:
- Utilized activity-based single-neuron models.
- Employed numerical simulations and bifurcation analysis.
- Applied fast-slow decomposition to study network dynamics.
Main Results:
- Demonstrated a network model reproducing three-, two-, and one-phase respiratory oscillations.
- Showed that I(NaP) is not essential for three- and two-phase oscillations but controls period.
- Identified progressive drive changes as triggers for state transitions, with intermediate regimes observed.
Conclusions:
- The proposed minimal neural network effectively explains respiratory pattern transformations.
- Persistent sodium current plays a crucial role in modulating respiratory oscillation periods.
- Understanding these state-dependent mechanisms is key to respiratory rhythm control.
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