Takashi Hoshino1,2, Kazuyo Oguchi1, Kenji Inoue3, Aiko Hoshino2, Minoru Hoshiyama2. 1. Department of Rehabilitation, Kariya Toyota General Hospital, Kariya, Japan. 2. Department of Rehabilitation Sciences, Graduate School of Medicine, Nagoya University, Nagoya, Japan. 3. Department of Clinical Laboratory, Kariya Toyota General Hospital, Kariya, Japan.
Abstract
Backgrounds: Neural biomarkers to predict motor recovery have been used in the field of rehabilitation. Functional connectivity (FC) among the brain regions recorded by functional magnetic resonance imaging systems have been reported, but convenient method to estimate FC for clinical situation has not been established. Objectives: This observational study investigated the relationship between neural functional connectivity obtained by electroencephalography (EEG) and the upper limb function in patients during recovery stage after stroke. Methods: Twenty-four patients in the recovery stage between 4 and 8 weeks after the onset of stroke (mean age: 62 ± 12 (SD)) were enrolled. The EEG signals were obtained by five electrodes placed on the motor-related areas (C3, C4, FC3, FC4, and FCz in the International 10-20 system) for 60 sec at rest and during finger movement on the affected side, and amplitude envelope correlations as measures of FC among the areas were calculated. Fugl-Meyer Assessment (FMA) was used to assess upper limb motor function. Results: The FMA scores evaluated at 4W (33 ± 24 (SD)) were improved by 8W (42 ± 23) (p < .001). The FCs in α and β bands calculated between the electrodes in the ipsi-lesional hemisphere were correlated negatively with the FMA score at 4W after stroke. The FCs obtained at 4W could be used to predict the FMA score at 8W after stroke.Conclusions: The FCs recorded at rest, as well as during the finger motor task, by the five electrodes placed on motor-related areas could be used to predict the motor function and recovery of the upper limb affected by stroke. The results indicate the possibility of using FCs recorded by conventional EEG with electrodes as biomarkers to predict motor recovery after stroke.
Backgrounds: Neural biomarkers to predict motor recovery have been used in the field of rehabilitation. Functional connectivity (FC) among the brain regions recorded by functional magnetic resonance imaging systems have been reported, but convenient method to estimate FC for clinical situation has not been established. Objectives: This observational study investigated the relationship between neural functional connectivity obtained by electroencephalography (EEG) and the upper limb function in patients during recovery stage after stroke. Methods: Twenty-four patients in the recovery stage between 4 and 8 weeks after the onset of stroke (mean age: 62 ± 12 (SD)) were enrolled. The EEG signals were obtained by five electrodes placed on the motor-related areas (C3, C4, FC3, FC4, and FCz in the International 10-20 system) for 60 sec at rest and during finger movement on the affected side, and amplitude envelope correlations as measures of FC among the areas were calculated. Fugl-Meyer Assessment (FMA) was used to assess upper limb motor function. Results: The FMA scores evaluated at 4W (33 ± 24 (SD)) were improved by 8W (42 ± 23) (p < .001). The FCs in α and β bands calculated between the electrodes in the ipsi-lesional hemisphere were correlated negatively with the FMA score at 4W after stroke. The FCs obtained at 4W could be used to predict the FMA score at 8W after stroke.Conclusions: The FCs recorded at rest, as well as during the finger motor task, by the five electrodes placed on motor-related areas could be used to predict the motor function and recovery of the upper limb affected by stroke. The results indicate the possibility of using FCs recorded by conventional EEG with electrodes as biomarkers to predict motor recovery after stroke.
Authors: Amanda A Vatinno; Annie Simpson; Viswanathan Ramakrishnan; Heather S Bonilha; Leonardo Bonilha; Na Jin Seo Journal: Neurorehabil Neural Repair Date: 2022-03-20 Impact factor: 3.919
Authors: Zafer Keser; Samuel C Buchl; Nathan A Seven; Matej Markota; Heather M Clark; David T Jones; Giuseppe Lanzino; Robert D Brown; Gregory A Worrell; Brian N Lundstrom Journal: Front Neurol Date: 2022-02-22 Impact factor: 4.003