Literature DB >> 36136166

Relation Between EEG Measures and Upper Limb Motor Recovery in Stroke Patients: A Scoping Review.

Giada Milani1,2, Annibale Antonioni3, Andrea Baroni2, Paola Malerba4, Sofia Straudi5,6.   

Abstract

Current clinical practice does not leverage electroencephalography (EEG) measurements in stroke patients, despite its potential to contribute to post-stroke recovery predictions. We review the literature on the effectiveness of various quantitative and qualitative EEG-based measures after stroke as a tool to predict upper limb motor outcome, in relation to stroke timeframe and applied experimental tasks. Moreover, we aim to provide guidance on the use of EEG in the assessment of upper limb motor recovery after stroke, suggesting a high potential for some metrics in the appropriate context. We identified relevant papers (N = 16) from databases ScienceDirect, Web of Science and MEDLINE, and assessed their methodological quality with the Joanna Briggs Institute (JBI) Critical Appraisal. We applied the Preferred Reporting Systems for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) Framework. Identified works used EEG to identify properties including event-related activation, spectral power in physiologically relevant bands, symmetry in brain dynamics, functional connectivity, cortico-muscular coherence and rhythmic coordination. EEG was acquired in resting state or in relation to behavioural conditions. Motor outcome was mainly evaluated with the Upper Limb Fugl-Meyer Assessment. Despite great variability in the literature, data suggests that the most promising EEG quantifiers for predicting post-stroke motor outcome are event-related measures. Measures of spectral power in physiologically relevant bands and measures of brain symmetry also show promise. We suggest that EEG measures may improve our understanding of stroke brain dynamics during recovery, and contribute to establishing a functional prognosis and choosing the rehabilitation approach.
© 2022. The Author(s).

Entities:  

Keywords:  EEG; Motor recovery; Rehabilitation; Stroke; Upper limb motor outcome

Year:  2022        PMID: 36136166     DOI: 10.1007/s10548-022-00915-y

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   4.275


  38 in total

1.  Changes in mu and beta amplitude of the EEG during upper limb movement correlate with motor impairment and structural damage in subacute stroke.

Authors:  Gadi Bartur; Hillel Pratt; Nachum Soroker
Journal:  Clin Neurophysiol       Date:  2019-07-01       Impact factor: 3.708

Review 2.  Predictors of upper limb recovery after stroke: a systematic review and meta-analysis.

Authors:  Fiona Coupar; Alex Pollock; Phil Rowe; Christopher Weir; Peter Langhorne
Journal:  Clin Rehabil       Date:  2011-10-24       Impact factor: 3.477

3.  Low-Frequency Oscillations Are a Biomarker of Injury and Recovery After Stroke.

Authors:  Jessica M Cassidy; Anirudh Wodeyar; Jennifer Wu; Kiranjot Kaur; Ashley K Masuda; Ramesh Srinivasan; Steven C Cramer
Journal:  Stroke       Date:  2020-04-17       Impact factor: 7.914

Review 4.  Early Rehabilitation After Stroke: a Narrative Review.

Authors:  Elisheva R Coleman; Rohitha Moudgal; Kathryn Lang; Hyacinth I Hyacinth; Oluwole O Awosika; Brett M Kissela; Wuwei Feng
Journal:  Curr Atheroscler Rep       Date:  2017-11-07       Impact factor: 5.113

5.  Poor motor function is associated with reduced sensory processing after stroke.

Authors:  S Floor Campfens; Sarah B Zandvliet; Carel G M Meskers; Alfred C Schouten; Michel J A M van Putten; Herman van der Kooij
Journal:  Exp Brain Res       Date:  2015-02-05       Impact factor: 1.972

6.  EEG-based motor network biomarkers for identifying target patients with stroke for upper limb rehabilitation and its construct validity.

Authors:  Chun-Chuan Chen; Si-Huei Lee; Wei-Jen Wang; Yu-Chen Lin; Mu-Chun Su
Journal:  PLoS One       Date:  2017-06-14       Impact factor: 3.240

7.  Parietofrontal network upregulation after motor stroke.

Authors:  M Bönstrup; R Schulz; G Schön; B Cheng; J Feldheim; G Thomalla; C Gerloff
Journal:  Neuroimage Clin       Date:  2018-03-07       Impact factor: 4.881

8.  Abnormal functional corticomuscular coupling after stroke.

Authors:  Xiaoling Chen; Ping Xie; Yuanyuan Zhang; Yuling Chen; Shengcui Cheng; Litai Zhang
Journal:  Neuroimage Clin       Date:  2018-04-04       Impact factor: 4.881

9.  Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation.

Authors:  Nikunj A Bhagat; Nuray Yozbatiran; Jennifer L Sullivan; Ruta Paranjape; Colin Losey; Zachary Hernandez; Zafer Keser; Robert Grossman; Gerard E Francisco; Marcia K O'Malley; Jose L Contreras-Vidal
Journal:  Neuroimage Clin       Date:  2020-11-19       Impact factor: 4.881

10.  Coherent neural oscillations inform early stroke motor recovery.

Authors:  Jessica M Cassidy; Anirudh Wodeyar; Ramesh Srinivasan; Steven C Cramer
Journal:  Hum Brain Mapp       Date:  2021-08-26       Impact factor: 5.038

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