Research on Event-Related Desynchronization of Motor Imagery and Movement Based on Localized EEG Cortical Sources

TL;DR

This study uses sLORETA to analyze cortical sources of ERD during motor imagery and movement, revealing significant activation in motor and sensory areas, with some differences between imagined and actual movements.

Contribution

It provides a detailed cortical source analysis of ERD during motor imagery and movement, highlighting specific brain regions involved.

Findings

Significant ERD observed in motor and sensory areas during motor imagery.

ERD during actual movement mainly in primary motor and somatosensory cortices.

Higher, but not significantly, ERD in certain areas during motor imagery compared to actual movement.

Abstract

This study investigates event-related desynchronization (ERD) phenomena during motor imagery and actual movement. Using sLORETA software, we analyzed the cortical current source density distributions in Mu and Beta frequency bands for 33 subjects during rest, motor imagery, and actual movement conditions. The results were normalized for analysis. Using sLORETA's statistical tools, paired t-tests were conducted to compare the normalized current source density results between rest and motor imagery, rest and actual movement, and motor imagery and actual movement conditions in both frequency bands. The findings revealed: In both Mu and Beta frequency bands, during motor imagery, significant ERD (P<0.01) was observed in the salience network, supplementary motor area, primary motor area, premotor cortex, primary somatosensory cortex, and parietofrontal mirror neuron system. During actual movement, significant ERD (P<0.05) was observed in the primary somatosensory cortex, primary motor area, and parietofrontal mirror neuron system in both frequency bands. Comparing motor imagery to actual movement, the current source density in the primary somatosensory cortex and parietofrontal mirror neuron system was higher during motor imagery, though this difference was not statistically significant (P>0.05). This paper analyzes the factors contributing to these statistical results and proposes preliminary solutions.