Modulation of Functional Connectivity Evaluated by Surface EEG in Alpha and Beta Band During a Motor-Imagery Based BCI Task

Hands motor imagery (MI) has been reported to alter synchronization patterns amongst neurons, yielding variations in the mu and beta bands’ power spectral density (PSD) of the electroencephalography (EEG) signal. These alterations have been used in the field of brain-computer interfaces (BCI), in an attempt to assign distinct MI tasks to commands of such a system. Recent studies have highlighted that information may be missing if knowledge about brain functional connectivity is not considered. In this work, we modeled the brain as a graph in which each EEG electrode represents a node. Our goal was to understand if there exists any linear correlation between variations in the synchronization patterns—that is, variations in the PSD of mu and beta bands—induced by MI and alterations in the corresponding functional networks. Moreover, we (1) explored the feasibility of using functional connectivity parameters as features for a classifier in the context of an MI-BCI; (2) investigated three different types of feature selection (FS) techniques; and (3) compared our approach to a more traditional method using the signal PSD as classifier inputs. Ten healthy subjects participated in this study. We observed significant correlations (p < 0.05) with values ranging from 0.4 to 0.9 between PSD variations and functional network alterations for some electrodes, prominently in the beta band. The PSD method performed better for data classification, with mean accuracies of (90 ± 8)% and (87 ± 7)% for the mu and beta band, respectively, versus (83 ± 8)% and (83 ± 7)% for the same bands for the graph method. Moreover, the number of features for the graph method was considerably larger. However, results for both methods were relatively close, and even overlapped when the uncertainties of the accuracy rates were considered. Further investigation regarding a careful exploration of other graph metrics may provide better alternatives.

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Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor Imagery Protocols

Advances in Human-Computer Interaction ◽

10.1155/2012/127627 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 15

Author(s):

Alkinoos Athanasiou ◽

Chrysa Lithari ◽

Konstantina Kalogianni ◽

Manousos A. Klados ◽

Panagiotis D. Bamidis

Keyword(s):

Functional Connectivity ◽

Motor Imagery ◽

Sensorimotor Cortex ◽

Mu Rhythm ◽

Source Detection ◽

Motor Execution ◽

Motor Tasks ◽

Computer Interfaces ◽

Preliminary Study ◽

Real Hand

Introduction. Sensorimotor cortex is activated similarly during motor execution and motor imagery. The study of functional connectivity networks (FCNs) aims at successfully modeling the dynamics of information flow between cortical areas.Materials and Methods. Seven healthy subjects performed 4 motor tasks (real foot, imaginary foot, real hand, and imaginary hand movements), while electroencephalography was recorded over the sensorimotor cortex. Event-Related Desynchronization/Synchronization (ERD/ERS) of the mu-rhythm was used to evaluate MI performance. Source detection and FCNs were studied with eConnectome.Results and Discussion. Four subjects produced similar ERD/ERS patterns between motor execution and imagery during both hand and foot tasks, 2 subjects only during hand tasks, and 1 subject only during foot tasks. All subjects showed the expected brain activation in well-performed MI tasks, facilitating cortical source estimation. Preliminary functional connectivity analysis shows formation of networks on the sensorimotor cortex during motor imagery and execution.Conclusions. Cortex activation maps depict sensorimotor cortex activation, while similar functional connectivity networks are formed in the sensorimotor cortex both during actual and imaginary movements. eConnectome is demonstrated as an effective tool for the study of cortex activation and FCN. The implementation of FCN in motor imagery could induce promising advancements in Brain Computer Interfaces.

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Functional Brain Connectivity during Multiple Motor Imagery Tasks in Spinal Cord Injury

Neural Plasticity ◽

10.1155/2018/9354207 ◽

2018 ◽

Vol 2018 ◽

pp. 1-20 ◽

Cited By ~ 2

Author(s):

Alkinoos Athanasiou ◽

Nikos Terzopoulos ◽

Niki Pandria ◽

Ioannis Xygonakis ◽

Nicolas Foroglou ◽

...

Keyword(s):

Spinal Cord ◽

Spinal Cord Injury ◽

Functional Connectivity ◽

Motor Imagery ◽

Healthy Subjects ◽

Brain Connectivity ◽

Descending Pathways ◽

Brain Organization ◽

Sensorimotor Network ◽

Cord Injury

Reciprocal communication of the central and peripheral nervous systems is compromised during spinal cord injury due to neurotrauma of ascending and descending pathways. Changes in brain organization after spinal cord injury have been associated with differences in prognosis. Changes in functional connectivity may also serve as injury biomarkers. Most studies on functional connectivity have focused on chronic complete injury or resting-state condition. In our study, ten right-handed patients with incomplete spinal cord injury and ten age- and gender-matched healthy controls performed multiple visual motor imagery tasks of upper extremities and walking under high-resolution electroencephalography recording. Directed transfer function was used to study connectivity at the cortical source space between sensorimotor nodes. Chronic disruption of reciprocal communication in incomplete injury could result in permanent significant decrease of connectivity in a subset of the sensorimotor network, regardless of positive or negative neurological outcome. Cingulate motor areas consistently contributed the larger outflow (right) and received the higher inflow (left) among all nodes, across all motor imagery categories, in both groups. Injured subjects had higher outflow from left cingulate than healthy subjects and higher inflow in right cingulate than healthy subjects. Alpha networks were less dense, showing less integration and more segregation than beta networks. Spinal cord injury patients showed signs of increased local processing as adaptive mechanism. This trial is registered with NCT02443558.

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

Journal of Clinical and Translational Science ◽

10.1017/cts.2018.92 ◽

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.

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Altered beta-band functional connectivity may be related to ‘performance slowing’ in good outcome aneurysmal subarachnoid patients

Neuroscience Letters ◽

10.1016/j.neulet.2019.01.053 ◽

2019 ◽

Vol 699 ◽

pp. 64-70 ◽

Cited By ~ 1

Author(s):

Priyanka P. Shah-Basak ◽

Benjamin T. Dunkley ◽

Annette X. Ye ◽

Simeon Wong ◽

Leodante da Costa ◽

...

Keyword(s):

Functional Connectivity ◽

Beta Band ◽

Good Outcome

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Electroencephalographic Functional Connectivity With the Tacit Learning System Prosthetic Hand: A Case Series Using Motor Imagery

Frontiers in Synaptic Neuroscience ◽

10.3389/fnsyn.2020.00007 ◽

2020 ◽

Vol 12 ◽

Cited By ~ 2

Author(s):

Katsuyuki Iwatsuki ◽

Minoru Hoshiyama ◽

Shintaro Oyama ◽

Hidemasa Yoneda ◽

Shingo Shimoda ◽

...

Keyword(s):

Functional Connectivity ◽

Motor Imagery ◽

Case Series ◽

Learning System ◽

Prosthetic Hand ◽

Tacit Learning

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Reduced Brain Electric Activity and Functional Connectivity in Bipolar Euthymia: An sLORETA Source Localization Study

Clinical EEG and Neuroscience ◽

10.1177/1550059419893472 ◽

2019 ◽

Vol 51 (3) ◽

pp. 155-166

Author(s):

Annamaria Painold ◽

Pascal L. Faber ◽

Eva Z. Reininghaus ◽

Sabrina Mörkl ◽

Anna K. Holl ◽

...

Keyword(s):

Functional Connectivity ◽

Large Scale ◽

Time Course ◽

Temporal Cortex ◽

Electric Activity ◽

Brain Regions ◽

Frequency Bands ◽

Head Surface ◽

Density Values ◽

Surface Eeg

Bipolar disorder (BD) is a chronic illness with a relapsing and remitting time course. Relapses are manic or depressive in nature and intermitted by euthymic states. During euthymic states, patients lack the criteria for a manic or depressive diagnosis, but still suffer from impaired cognitive functioning as indicated by difficulties in executive and language-related processing. The present study investigated whether these deficits are reflected by altered intracortical activity in or functional connectivity between brain regions involved in these processes such as the prefrontal and the temporal cortices. Vigilance-controlled resting state EEG of 13 euthymic BD patients and 13 healthy age- and sex-matched controls was analyzed. Head-surface EEG was recomputed into intracortical current density values in 8 frequency bands using standardized low-resolution electromagnetic tomography. Intracortical current densities were averaged in 19 evenly distributed regions of interest (ROIs). Lagged coherences were computed between each pair of ROIs. Source activity and coherence measures between patients and controls were compared (paired t tests). Reductions in temporal cortex activity and in large-scale functional connectivity in patients compared to controls were observed. Activity reductions affected all 8 EEG frequency bands. Functional connectivity reductions affected the delta, theta, alpha-2, beta-2, and gamma band and involved but were not limited to prefrontal and temporal ROIs. The findings show reduced activation of the temporal cortex and reduced coordination between many brain regions in BD euthymia. These activation and connectivity changes may disturb the continuous frontotemporal information flow required for executive and language-related processing, which is impaired in euthymic BD patients.

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