Intersegmental coordination of limb movements during locomotion: mathematical models predict circuits that drive swimmeret beating | JoVE Visualize

Intersegmental coordination of limb movements during locomotion: mathematical models predict circuits that drive swimmeret beating

F K Skinner¹, B Mulloney

¹Playfair Neuroscience Unit, The Toronto Hospital Research Institute, and Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5T 2S8, Canada.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience|June 6, 1998

View abstract on PubMed

Summary

Neural coordination of arthropod locomotion remains elusive. This study models neural circuits, revealing a specific coordinating circuit that maintains rhythmic motor patterns across speeds, preserving phase differences and burst durations.

Area of Science:

Neuroscience
Computational Biology
Comparative Physiology

Background:

Locomotion in arthropods and vertebrates involves complex neural coordination.
Neural mechanisms for limb coordination during varying speeds are not fully understood.
Neural modules controlling rhythmic movements like swimmerets adapt to excitation changes by altering motor pattern periods.

Purpose of the Study:

To investigate the neural mechanisms coordinating limb movements during locomotion.
To model the local pattern-generating circuits and intersegmental coordinating circuits.
To identify a functional intersegmental coordinating circuit that explains observed motor pattern dynamics.

Main Methods:

Constructed a cellular model of the local pattern-generating circuit for swimmerets.
Developed alternative models for intersegmental coordinating circuits based on experimental data.
Compared the dynamics of model circuits with real system performance under altered excitation levels.

Main Results:

Many tested coordinating circuit models failed to replicate observed dynamics.
One specific coordinating circuit model successfully matched the real system's performance across a range of periods (1 to 3.2 Hz).
This successful model maintained consistent intersegmental phase differences and relative burst durations within local modules.

Conclusions:

The study proposes a specific neural coordination mechanism and intersegmental connection pattern in the central nervous system (CNS).
The findings predict a testable framework for understanding rhythmic motor pattern stability during locomotion.
This research advances the understanding of neural control in complex behaviors like locomotion.