Neuronal travelling waves explain rotational dynamics in experimental datasets and modelling

Area of Science:

• Neuroscience
• Computational Neuroscience
• Motor Control

Background:

• Spatiotemporal properties of neuronal activity in motor cortex are crucial for understanding limb movement preparation and execution.
• Two models, representational and dynamical, attempt to explain the link between movement parameters and neuronal activity.
• The dynamical model, using jPCA, characterizes population activity by maximizing rotational dynamics, but the nature of these dynamics is unclear.

Purpose of the Study:

• To investigate the nature of rotational dynamics in neuronal population activity.
• To determine if rotational dynamics and traveling waves are distinct phenomena.
• To develop a quantitative measure for rotational dynamics.

Main Methods:

• Comprehensive analysis of multiple neuronal-population datasets.
• Application of the jPCA (principal component analysis of neural data) method to identify rotational dynamics.
• Development of a complex-valued measure, the gyration number, to quantify rotation strength.

Main Results:

• Rotational dynamics in neuronal population data were consistently explained by a traveling wave pattern.
• The gyration number was developed and utilized to quantify the strength of neuronal rotation.
• Parameters influencing the extent of rotation in the data were identified.

Conclusions:

• Rotational dynamics and traveling waves in neuronal population activity are typically the same phenomenon.
• Previous interpretations viewing them as separate entities require reevaluation.
• The findings provide a unified understanding of neuronal population dynamics during movement.