Mu down regulation EEG-neurofeedback training combined to motor imagery facilitates early consolidation in a sequential finger tapping task

<i>Objective.</i>Motor imagery (MI) has demonstrated positive effects on motor performance and triggers activation in the motor cortex (MC). EEG-Neurofeedback (EEG-NF) is a neuromodulation technique that provides real-time feedback on one's brain activity, enabling self-regulation of brain states. While there is increasing evidence of humans controlling the activity of various brain networks, including the MC, through EEG-NF, the tangible benefits of this self-regulation on motor performance remain uncertain. This study investigates the potential benefits of EEG-NF training in explicit learning of a sequential movement, in comparison to MI training and to a combined EEG-NF and MI training.<i>Approach.</i>Ninety-one right-handed healthy adults were randomly assigned to one of four groups (a)NF(<i>n</i>= 24), (b)MI(<i>n</i>= 22), (c)MI + NF(<i>n</i>= 23) and (d)control(<i>n</i>= 22). Participants performed a sequential finger tapping task before and after (immediately, 20 min and 24 h) a single 30 min training session. Motor performance, movement speed and event related desynchronization data were analyzed.<i>Main results.</i>MI training led to a better motor performance compared to control condition immediately after training that was sustained at the 20 min retest time point (<i>p</i>= 0.02 and 0.05). In contrast, EEG-NF training alone did not yield better motor performance compared to control condition at any time-point (<i>p</i>> .05). Remarkably, only the combination of both trainings led to superior motor performance 24 h after training in comparison to control group (<i>p</i>= 0.02). Additionally, all experimental groups successfully decreased mu rhythm amplitude throughout most of the training.<i>Significance.</i>Combined EEG-NF and MI training appears particularly promising for enhancing motor consolidation holding the potential to advance rehabilitation approaches.

Authors

Institutions

Publication Details

Journal
Journal of Neural Engineering
Published
2024-12-01
DOI
https://doi.org/10.1088/1741-2552/ad8efb
Citations
3
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.03
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mu down regulation EEG-neurofeedback training combined to motor imagery facilitates early consolidation in a sequential finger tapping task

Joseph Maarrawi, M. Hanna, Sandra Kobaïter Maarrawi, Rami Abdul Malak et al.
3 citations
Journal of Neural Engineering
EEG and Brain-Computer Interfaces
1.03
article

Mu down regulation EEG-neurofeedback training combined to motor imagery facilitates early consolidation in a sequential finger tapping task

Joseph Maarrawi, M. Hanna, Sandra Kobaïter Maarrawi, Rami Abdul Malak, Rose Mery Bou Merhy
article en
3 citations

Abstract

<i>Objective.</i>Motor imagery (MI) has demonstrated positive effects on motor performance and triggers activation in the motor cortex (MC). EEG-Neurofeedback (EEG-NF) is a neuromodulation technique that provides real-time feedback on one's brain activity, enabling self-regulation of brain states. While there is increasing evidence of humans controlling the activity of various brain networks, including the MC, through EEG-NF, the tangible benefits of this self-regulation on motor performance remain uncertain. This study investigates the potential benefits of EEG-NF training in explicit learning of a sequential movement, in comparison to MI training and to a combined EEG-NF and MI training.<i>Approach.</i>Ninety-one right-handed healthy adults were randomly assigned to one of four groups (a)NF(<i>n</i>= 24), (b)MI(<i>n</i>= 22), (c)MI + NF(<i>n</i>= 23) and (d)control(<i>n</i>= 22). Participants performed a sequential finger tapping task before and after (immediately, 20 min and 24 h) a single 30 min training session. Motor performance, movement speed and event related desynchronization data were analyzed.<i>Main results.</i>MI training led to a better motor performance compared to control condition immediately after training that was sustained at the 20 min retest time point (<i>p</i>= 0.02 and 0.05). In contrast, EEG-NF training alone did not yield better motor performance compared to control condition at any time-point (<i>p</i>> .05). Remarkably, only the combination of both trainings led to superior motor performance 24 h after training in comparison to control group (<i>p</i>= 0.02). Additionally, all experimental groups successfully decreased mu rhythm amplitude throughout most of the training.<i>Significance.</i>Combined EEG-NF and MI training appears particularly promising for enhancing motor consolidation holding the potential to advance rehabilitation approaches.

Journal of Neural EngineeringVol. 21(6)
Saint Joseph University (LB), Hôtel-Dieu de France (LB)
Good health and well-being
Openalex Percentile: Top 23%
EEG and Brain-Computer Interfaces
1.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.