scholarly journals Detection of Error Correlates in the Motor Cortex in a Long Term Clinical Trial of ECoG based Brain Computer Interface

2021 ◽  
Author(s):  
Vincent Rouanne ◽  
Maciej Śliwowski ◽  
Thomas Costecalde ◽  
Alim Benabid ◽  
Tetiana Aksenova
Keyword(s):  
Clinical Trial ◽  
Motor Cortex ◽  
Brain Computer Interface ◽  
Computer Interface

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 EEG-based brain-computer interface in chronic tetraplegics to actuate a robotic arm device as assistive technology - clinical survey and long term post trial follow-up

BIOPHILIA ◽  
2011 ◽  
Vol 1 (4) ◽  
pp. 4_28-4_28
Author(s):  
Gelu Onose ◽  
Cristian Grozea ◽  
Aurelian Anghelescu ◽  
Cristina Daia ◽  
Crina Julieta Sinescu ◽  
...  
Keyword(s):  
Assistive Technology ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Robotic Arm ◽  
Clinical Survey ◽  
Post Trial

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.

scholarly journals Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot

2021 ◽  
Vol 15 ◽  
Author(s):  
Neethu Robinson ◽  
Tushar Chouhan ◽  
Ernest Mihelj ◽  
Paulina Kratka ◽  
Frédéric Debraine ◽  
...  
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Brain Computer Interface ◽  
Brain Activation ◽  
Classification Performance ◽  
Open Loop ◽  
Computer Interface ◽  
Single Subject ◽  
User Engagement

Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms (p = 0.0008). We also observe that stronger and more localized brain activation patterns are elicited in the closed-loop paradigm in which the experiment interface closely resembled the end application. Thus, based on this longitudinal evaluation of single-subject data, we demonstrate that BCI-based calibration paradigms with active user-engagement, such as with real-time feedback, could help in achieving better user acceptability and performance.

Pleasure detection from the facial motor cortex by the brain-computer interface

2009 ◽  
Author(s):  
Zia Mohy Ud-Din ◽  
Sang Hyo Woo ◽  
Wei Qun ◽  
Jee Hyun Kim ◽  
Hwan Soo Jang ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
The Brain

An Improved Stimuli System for Brain-Computer Interface Applications

2013 ◽  
Vol 1 (4) ◽  
pp. 1-8 ◽  
Author(s):  
Irina-Emilia Nicolae
Keyword(s):  
Reaction Time ◽  
Motor Cortex ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Auditory Stimuli ◽  
Synchronous Systems ◽  
Spectral Perturbation

When developing a motion synchronous Brain-Computer Interface, it is very important to have effective stimuli. This research tests and proposes an improved brain computer interface stimulus system, based on event related spectral perturbation. In order to investigate the reaction of the motor cortex to stimuli, the influence of the human senses has to be investigated. Considering the limitations of human senses, the article proposes effective visual and auditory stimuli in two similar tasks, to gain accuracy and better reaction time (RT) for real movements in Brain-Computer Interface synchronous systems.

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.

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