Corrigendum: Classifying Vulnerability to Sleep Deprivation Using Resting-State Functional MRI Graph Theory Metrics
Yongqiang Xu1, Ping Yu2, Jianmin Zheng1
1Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Frontiers in Neuroscience
|July 11, 2022
Summary
This study investigates the impact of brain-computer interfaces on motor imagery. Enhanced brain-computer interface use may improve motor function recovery in neurological patients.
Area of Science:
- Neuroscience
- Biomedical Engineering
Context:
- Brain-computer interfaces (BCIs) are emerging technologies for neurological rehabilitation.
- Motor imagery (MI) is a cognitive process used in BCI applications.
Purpose:
- To explore the effectiveness of BCIs in enhancing motor imagery.
- To analyze the impact of BCI training on motor function.
Summary:
- The study reviewed existing literature on BCI-driven motor imagery.
- Findings suggest that BCI training can positively influence motor imagery performance.
- Improvements in motor imagery correlate with potential gains in motor function.
Impact:
- BCIs show promise as a therapeutic tool for motor rehabilitation.
- This research contributes to understanding BCI mechanisms in neurological recovery.
- Further investigation into BCI applications for stroke and other neurological conditions is warranted.
