A study on the primary motor cortex performing motor imagery task for the development of a brain-computer interface

2007 ◽  
Author(s):  
Yoshikazu Ishii ◽  
Toshiharu Mukai ◽  
Tohru Yagi
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Primary Motor Cortex ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Imagery Task

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 Increased motor cortex excitability during motor imagery in brain-computer interface trained subjects

2013 ◽  
Vol 7 ◽  
Author(s):  
Olesya A. Mokienko ◽  
Alexander V. Chervyakov ◽  
Sofia N. Kulikova ◽  
Pavel D. Bobrov ◽  
Liudmila A. Chernikova ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Trained Subjects ◽  
Motor Cortex Excitability

scholarly journals Primary motor cortex has independent representations for ipsilateral and contralateral arm movements but correlated representations for grasping

2019 ◽  
Author(s):  
John E Downey ◽  
Kristin M Quick ◽  
Nathaniel Schwed ◽  
Jeffrey M Weiss ◽  
George F Wittenberg ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Human Subjects ◽  
Brain Computer Interface ◽  
Hand Movement ◽  
Arm Movement ◽  
Computer Interface ◽  
Contralateral Movement ◽  
Contralateral Motor ◽  
Continuous Movements

AbstractMotor commands for the arms and hands generally originate in contralateral motor cortex anatomically. However, ipsilateral primary motor cortex shows activity related to arm movement despite the lack of direct connections. The extent to which the activity related to ipsilateral movement is independent from that related to contralateral movement is unclear based on conflicting conclusions in prior work. Here we present the results of bilateral arm and hand movement tasks completed by two human subjects with intracortical microelectrode arrays implanted in left primary motor cortex for a clinical brain-computer interface study. Neural activity was recorded while they attempted to perform arm and hand movements in a virtual environment. This enabled us to quantify the strength and independence of motor cortical activity related to continuous movements of each arm. We also investigated the subjects’ ability to control both arms through a brain-computer interface system. Through a number of experiments, we found that ipsilateral arm movement was represented independently of, but more weakly than, contralateral arm movement. However, the representation of grasping was correlated between the two hands. This difference between hand and arm representation was unexpected, and poses new questions about the different ways primary motor cortex controls hands and arms.

Event-related desynchronization reflects downregulation of intracortical inhibition in human primary motor cortex

2013 ◽  
Vol 110 (5) ◽  
pp. 1158-1166 ◽  
Author(s):  
Mitsuaki Takemi ◽  
Yoshihisa Masakado ◽  
Meigen Liu ◽  
Junichi Ushiba
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Sensorimotor Cortex ◽  
Primary Motor Cortex ◽  
Motor Evoked Potentials ◽  
Short Interval ◽  
Hand Movement ◽  
Intracortical Inhibition ◽  
Imagery Task ◽  
Event Related Desynchronization

There is increasing interest in electroencephalogram (EEG)-based brain-computer interface (BCI) as a tool for rehabilitation of upper limb motor functions in hemiplegic stroke patients. This type of BCI often exploits mu and beta oscillations in EEG recorded over the sensorimotor areas, and their event-related desynchronization (ERD) following motor imagery is believed to represent increased sensorimotor cortex excitability. However, it remains unclear whether the sensorimotor cortex excitability is actually correlated with ERD. Thus we assessed the association of ERD with primary motor cortex (M1) excitability during motor imagery of right wrist movement. M1 excitability was tested by motor evoked potentials (MEPs), short-interval intracortical inhibition (SICI), and intracortical facilitation (ICF) with transcranial magnetic stimulation (TMS). Twenty healthy participants were recruited. The participants performed 7 s of rest followed by 5 s of motor imagery and received online visual feedback of the ERD magnitude of the contralateral hand M1 while performing the motor imagery task. TMS was applied to the right hand M1 when ERD exceeded predetermined thresholds during motor imagery. MEP amplitudes, SICI, and ICF were recorded from the agonist muscle of the imagined hand movement. Results showed that the large ERD during wrist motor imagery was associated with significantly increased MEP amplitudes and reduced SICI but no significant changes in ICF. Thus ERD magnitude during wrist motor imagery represents M1 excitability. This study provides electrophysiological evidence that a motor imagery task involving ERD may induce changes in corticospinal excitability similar to changes accompanying actual movements.

scholarly journals Microscale recording from human motor cortex: implications for minimally invasive electrocorticographic brain-computer interfaces

2009 ◽  
Vol 27 (1) ◽  
pp. E10 ◽  
Author(s):  
Eric C. Leuthardt ◽  
Zac Freudenberg ◽  
David Bundy ◽  
Jarod Roland
Keyword(s):  
Motor Cortex ◽  
Minimally Invasive ◽  
Primary Motor Cortex ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Future Application ◽  
Electrode Spacing ◽  
Sufficient Information ◽  
Invasive Monitoring ◽  
Seizure Localization

Object There is a growing interest in the use of recording from the surface of the brain, known as electrocorticography (ECoG), as a practical signal platform for brain-computer interface application. The signal has a combination of high signal quality and long-term stability that may be the ideal intermediate modality for future application. The research paradigm for studying ECoG signals uses patients requiring invasive monitoring for seizure localization. The implanted arrays span cortex areas on the order of centimeters. Currently, it is unknown what level of motor information can be discerned from small regions of human cortex with microscale ECoG recording. Methods In this study, a patient requiring invasive monitoring for seizure localization underwent concurrent implantation with a 16-microwire array (1-mm electrode spacing) placed over primary motor cortex. Microscale activity was recorded while the patient performed simple contra- and ipsilateral wrist movements that were monitored in parallel with electromyography. Using various statistical methods, linear and nonlinear relationships between these microcortical changes and recorded electromyography activity were defined. Results Small regions of primary motor cortex (< 5 mm) carry sufficient information to separate multiple aspects of motor movements (that is, wrist flexion/extension and ipsilateral/contralateral movements). Conclusions These findings support the conclusion that small regions of cortex investigated by ECoG recording may provide sufficient information about motor intentions to support brain-computer interface operations in the future. Given the small scale of the cortical region required, the requisite implanted array would be minimally invasive in terms of surgical placement of the electrode array.

scholarly journals Multiclass Informative Instance Transfer Learning Framework for Motor Imagery-Based Brain-Computer Interface

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ibrahim Hossain ◽  
Abbas Khosravi ◽  
Imali Hettiarachchi ◽  
Saeid Nahavandi
Keyword(s):  
Transfer Learning ◽  
Motor Imagery ◽  
Brain Computer Interface ◽  
Training Session ◽  
Training Data ◽  
Superior Performance ◽  
Computer Interface ◽  
Imagery Task ◽  
Learning Framework ◽  
Optimal Ensemble

A widely discussed paradigm for brain-computer interface (BCI) is the motor imagery task using noninvasive electroencephalography (EEG) modality. It often requires long training session for collecting a large amount of EEG data which makes user exhausted. One of the approaches to shorten this session is utilizing the instances from past users to train the learner for the novel user. In this work, direct transferring from past users is investigated and applied to multiclass motor imagery BCI. Then, active learning (AL) driven informative instance transfer learning has been attempted for multiclass BCI. Informative instance transfer shows better performance than direct instance transfer which reaches the benchmark using a reduced amount of training data (49% less) in cases of 6 out of 9 subjects. However, none of these methods has superior performance for all subjects in general. To get a generic transfer learning framework for BCI, an optimal ensemble of informative and direct transfer methods is designed and applied. The optimized ensemble outperforms both direct and informative transfer method for all subjects except one in BCI competition IV multiclass motor imagery dataset. It achieves the benchmark performance for 8 out of 9 subjects using average 75% less training data. Thus, the requirement of large training data for the new user is reduced to a significant amount.

scholarly journals Rapid acquisition of novel interface control by small ensembles of arbitrarily selected primary motor cortex neurons

2014 ◽  
Vol 112 (6) ◽  
pp. 1528-1548 ◽  
Author(s):  
Andrew J. Law ◽  
Gil Rivlis ◽  
Marc H. Schieber
Keyword(s):  
Motor Cortex ◽  
Degrees Of Freedom ◽  
Primary Motor Cortex ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Rapid Acquisition ◽  
Interface Control ◽  
Large Ensembles ◽  
Performance Patterns ◽  
The Individual

Pioneering studies demonstrated that novel degrees of freedom could be controlled individually by directly encoding the firing rate of single motor cortex neurons, without regard to each neuron's role in controlling movement of the native limb. In contrast, recent brain-computer interface work has emphasized decoding outputs from large ensembles that include substantially more neurons than the number of degrees of freedom being controlled. To bridge the gap between direct encoding by single neurons and decoding output from large ensembles, we studied monkeys controlling one degree of freedom by comodulating up to four arbitrarily selected motor cortex neurons. Performance typically exceeded random quite early in single sessions and then continued to improve to different degrees in different sessions. We therefore examined factors that might affect performance. Performance improved with larger ensembles. In contrast, other factors that might have reflected preexisting synaptic architecture—such as the similarity of preferred directions—had little if any effect on performance. Patterns of comodulation among ensemble neurons became more consistent across trials as performance improved over single sessions. Compared with the ensemble neurons, other simultaneously recorded neurons showed less modulation. Patterns of voluntarily comodulated firing among small numbers of arbitrarily selected primary motor cortex (M1) neurons thus can be found and improved rapidly, with little constraint based on the normal relationships of the individual neurons to native limb movement. This rapid flexibility in relationships among M1 neurons may in part underlie our ability to learn new movements and improve motor skill.

scholarly journals Neural Topography and Content of Movement Representations

2005 ◽  
Vol 17 (1) ◽  
pp. 97-112 ◽  
Author(s):  
Floris P. de Lange ◽  
Peter Hagoort ◽  
Ivan Toni
Keyword(s):  
Motor Cortex ◽  
Mental Rotation ◽  
Motor Imagery ◽  
Parietal Cortex ◽  
Visual Imagery ◽  
Primary Motor Cortex ◽  
Premotor Cortex ◽  
Imagery Task ◽  
Hand Laterality ◽  
Posterior Parietal

We have used implicit motor imagery to investigate the neural correlates of motor planning independently from actual movements. Subjects were presented with drawings of left or right hands and asked to judge the hand laterality, regardless of the stimulus rotation from its upright orientation. We paired this task with a visual imagery control task, in which subjects were presented with typographical characters and asked to report whether they saw a canonical letter or its mirror image, regardless of its rotation. We measured neurovascular activity with fast event-related fMRI, distinguishing responses parametrically related to motor imagery from responses evoked by visual imagery and other task-related phenomena. By quantifying behavioral and neurovascular correlates of imagery on a trial-by-trial basis, we could discriminate between stimulus-related, mental rotation-related, and response-related neural activity. We found that specific portions of the posterior parietal and precentral cortex increased their activity as a function of mental rotation only during the motor imagery task. Within these regions, the parietal cortex was visually responsive, whereas the dorsal precentral cortex was not. Response- but not rotation-related activity was found around the left central sulcus (putative primary motor cortex) during both imagery tasks. Our study provides novel evidence on the topography and content of movement representations in the human brain. During intended action, the posterior parietal cortex combines somatosensory and visuomotor information, whereas the dorsal premotor cortex generates the actual motor plan, and the primary motor cortex deals with movement execution. We discuss the relevance of these results in the context of current models of action planning.

Free Virtual Navigation Using Motor Imagery Through an Asynchronous Brain–Computer Interface

2010 ◽  
Vol 19 (1) ◽  
pp. 71-81 ◽  
Author(s):  
Francisco Velasco-Álvarez ◽  
Ricardo Ron-Angevin ◽  
Maria José Blanca-Mena
Keyword(s):  
Virtual Environments ◽  
Motor Imagery ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Imagery Task ◽  
Virtual Navigation ◽  
Intentional Control ◽  
Feedback Training ◽  
Control Interface ◽  
Fixed Path

In this paper, an asynchronous brain–computer interface is presented that enables the control of a wheelchair in virtual environments using only one motor imagery task. The control is achieved through a graphical intentional control interface with three navigation commands (move forward, turn right, and turn left) which are displayed surrounding a circle. A bar is rotating in the center of the circle, so it points successively to the three possible commands. The user can, by motor imagery, extend this bar length to select the command at which the bar is pointing. Once a command is selected, the virtual wheelchair moves in a continuous way, so the user controls the length of the advance or the amplitude of the turns. Users can voluntarily switch from this interface to a noncontrol interface (and vice versa) when they do not want to generate any command. After performing a cue-based feedback training, three subjects carried out an experiment in which they had to navigate through the same fixed path to reach an objective. The results obtained support the viability of the system.

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