Phase Synchrony Measurement in Motor Cortex for Classifying Single-trial EEG during Motor Imagery

2006 ◽  
Author(s):  
Yijun Wang ◽  
Bo Hong ◽  
Xiaorong Gao ◽  
Shangkai Gao
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Phase Synchrony ◽  
Single Trial

Feature combination for classifying single-trial ECoG during motor imagery of different sessions

2007 ◽  
Vol 17 (7) ◽  
pp. 851-858 ◽  
Author(s):  
Wei Quigguo ◽  
Meng Fei ◽  
Wang Yijun ◽  
Gao Xiaorong ◽  
Goa Shangkai
Keyword(s):  
Motor Imagery ◽  
Feature Combination ◽  
Single Trial

scholarly journals 2190 Longitudinal changes in EEG power envelope connectivity are proportional to motor recovery in chronic stroke patients

2018 ◽  
Vol 2 (S1) ◽  
pp. 17-17
Author(s):  
Joseph B. Humphries ◽  
David T. Bundy ◽  
Eric C. Leuthardt ◽  
Thy N. Huskey
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Stroke Rehabilitation ◽  
Brain Computer Interface ◽  
Chronic Stroke ◽  
Motor Recovery ◽  
Stroke Recovery ◽  
Computer Interface ◽  
Beta Band ◽  
Stroke Patients

OBJECTIVES/SPECIFIC AIMS: The objective of this study is to determine the degree to which the use of a contralesionally-controlled brain-computer interface for stroke rehabilitation drives change in interhemispheric motor cortical activity. METHODS/STUDY POPULATION: Ten chronic stroke patients were trained in the use of a brain-computer interface device for stroke recovery. Patients perform motor imagery to control the opening and closing of a motorized hand orthosis. This device was sent home with patients for 12 weeks, and patients were asked to use the device 1 hour per day, 5 days per week. The Action Research Arm Test (ARAT) was performed at 2-week intervals to assess motor function improvement. Before the active motor imagery task, patients were asked to quietly rest for 90 seconds before the task to calibrate recording equipment. EEG signals were acquired from 2 electrodes—one each centered over left and right primary motor cortex. Signals were preprocessed with a 60 Hz notch filter for environmental noise and referenced to the common average. Power envelopes for 1 Hz frequency bands (1–30 Hz) were calculated through Gabor wavelet convolution. Correlations between electrodes were then calculated for each frequency envelope on the first and last 5 runs, thus generating one correlation value per subject, per run. The chosen runs approximately correspond to the first and last week of device usage. These correlations were Fisher Z-transformed for comparison. The first and last 5 run correlations were averaged separately to estimate baseline and final correlation values. A difference was then calculated between these averages to determine correlation change for each frequency. The relationship between beta-band correlation changes (13–30 Hz) and the change in ARAT score was determined by calculating a Pearson correlation. RESULTS/ANTICIPATED RESULTS: Beta-band inter-electrode correlations tended to decrease more in patients achieving greater motor recovery (Pearson’s r=−0.68, p=0.031). A similar but less dramatic effect was observed with alpha-band (8–12 Hz) correlation changes (Pearson’s r=−0.42, p=0.22). DISCUSSION/SIGNIFICANCE OF IMPACT: The negative correlation between inter-electrode power envelope correlations in the beta frequency band and motor recovery indicates that activity in the motor cortex on each hemisphere may become more independent during recovery. The role of the unaffected hemisphere in stroke recovery is currently under debate; there is conflicting evidence regarding whether it supports or inhibits the lesioned hemisphere. These findings may support the notion of interhemispheric inhibition, as we observe less in common between activity in the 2 hemispheres in patients successfully achieving recovery. Future neuroimaging studies with greater spatial resolution than available with EEG will shed further light on changes in interhemispheric communication that occur during stroke rehabilitation.

scholarly journals An Optimal Transport Based Transferable System for Detection of Erroneous Somato-Sensory Feedback from Neural Signals

2021 ◽  
Vol 11 (11) ◽  
pp. 1393
Author(s):  
Saugat Bhattacharyya ◽  
Mitsuhiro Hayashibe
Keyword(s):  
Motor Imagery ◽  
Error Detection ◽  
Error Control ◽  
Transport Theory ◽  
Optimal Transport ◽  
Detection System ◽  
Single Trial ◽  
Neural Signals ◽  
Error Control Mechanism ◽  
Bci System

 This study is aimed at the detection of single-trial feedback, perceived as erroneous by the user, using a transferable classification system while conducting a motor imagery brain–computer interfacing (BCI) task. The feedback received by the users are relayed from a functional electrical stimulation (FES) device and hence are somato-sensory in nature. The BCI system designed for this study activates an electrical stimulator placed on the left hand, right hand, left foot, and right foot of the user. Trials containing erroneous feedback can be detected from the neural signals in form of the error related potential (ErrP). The inclusion of neuro-feedback during the experiments indicated the possibility that ErrP signals can be evoked when the participant perceives an error from the feedback. Hence, to detect such feedback using ErrP, a transferable (offline) decoder based on optimal transport theory is introduced herein. The offline system detects single-trial erroneous trials from the feedback period of an online neuro-feedback BCI system. The results of the FES-based feedback BCI system were compared to a similar visual-based (VIS) feedback system. Using our framework, the error detector systems for both the FES and VIS feedback paradigms achieved an F1-score of 92.66% and 83.10%, respectively, and are significantly superior to a comparative system where an optimal transport was not used. It is expected that this form of transferable and automated error detection system compounded with a motor imagery system will augment the performance of a BCI and provide a better BCI-based neuro-rehabilitation protocol that has an error control mechanism embedded into it. 

scholarly journals The BOLD response in primary motor cortex and supplementary motor area during kinesthetic motor imagery based graded fMRI neurofeedback

NeuroImage ◽  
2019 ◽  
Vol 184 ◽  
pp. 36-44 ◽  
Author(s):  
David M.A. Mehler ◽  
Angharad N. Williams ◽  
Florian Krause ◽  
Michael Lührs ◽  
Richard G. Wise ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Primary Motor Cortex ◽  
Supplementary Motor Area ◽  
Motor Area ◽  
Bold Response

Recognizing single-trial motor imagery EEG based on interpretable clustering method

2021 ◽  
Vol 63 ◽  
pp. 102171
Author(s):  
Rongrong Fu ◽  
Weishuai Li ◽  
Junxiang Chen ◽  
Mengmeng Han
Keyword(s):  
Motor Imagery ◽  
Single Trial ◽  
Clustering Method

scholarly journals Anodal tDCS over the primary motor cortex improves motor imagery benefits on postural control: A pilot study

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Elodie Saruco ◽  
Franck Di Rienzo ◽  
Susana Nunez-Nagy ◽  
Miguel A. Rubio-Gonzalez ◽  
Philip L. Jackson ◽  
...  
Keyword(s):  
Pilot Study ◽  
Motor Cortex ◽  
Postural Control ◽  
Motor Imagery ◽  
Primary Motor Cortex ◽  
Anodal Tdcs
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