Assessing brain-muscle networks during motor imagery to detect covert command-following
Abstract Background In this study, we evaluated the potential of a network approach to electromyography and electroencephalography recordings to detect covert command-following in healthy participants. The motivation underlying this study was the development of a diagnostic tool that can be applied...
Saved in:
Main Authors: | Emilia Fló, Daniel Fraiman, Jacobo Diego Sitt |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-02-01
|
Series: | BMC Medicine |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12916-025-03846-0 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
FBATCNet: A Temporal Convolutional Network With Frequency Band Attention for Decoding Motor Imagery EEG
by: Shuaishuai Ma, et al.
Published: (2025-01-01) -
The Brain Activation of Two Motor Imagery Strategies in a Mental Rotation Task
by: Cancan Wang, et al.
Published: (2024-12-01) -
AMEEGNet: attention-based multiscale EEGNet for effective motor imagery EEG decoding
by: Xuejian Wu, et al.
Published: (2025-01-01) -
Progress in the application of motor imagery therapy in upper limb motor function rehabilitation of stroke patients with hemiplegia
by: Shuying Shen, et al.
Published: (2025-02-01) -
A Distribution Adaptive Feedback Training Method to Improve Human Motor Imagery Ability
by: Yukun Zhang, et al.
Published: (2025-01-01)