Non-invasive Brain-computer Interfaces for Control of Assistive Devices
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Motor Disorders
- Sponsor
- University of Texas at Austin
- Enrollment
- 100
- Locations
- 1
- Primary Endpoint
- Change in the BCI command delivery performance
- Status
- Recruiting
- Last Updated
- last year
Overview
Brief Summary
Injuries affecting the central nervous system may disrupt the cortical pathways to muscles causing loss of motor control. Nevertheless, the brain still exhibits sensorimotor rhythms (SMRs) during movement intents or motor imagery (MI), which is the mental rehearsal of the kinesthetics of a movement without actually performing it. Brain-computer interfaces (BCIs) can decode SMRs to control assistive devices and promote functional recovery. Despite rapid advancements in non-invasive BCI systems based on EEG, two persistent challenges remain: First, the instability of SMR patterns due to the non-stationarity of neural signals, which may significantly degrade BCI performance over days and hamper the effectiveness of BCI-based rehabilitation. Second, differentiating MI patterns corresponding to fine hand movements of the same limb is still difficult due to the low spatial resolution of EEG. To address the first challenge, subjects usually learn to elicit reliable SMR and improve BCI control through longitudinal training, so a fundamental question is how to accelerate subject training building upon the SMR neurophysiology. In this study, the investigators hypothesize that conditioning the brain with transcutaneous electrical spinal stimulation, which reportedly induces cortical inhibition, would constrain the neural dynamics and promote focal and strong SMR modulations in subsequent MI-based BCI training sessions - leading to accelerated BCI training. To address the second challenge, the investigators hypothesize that neuromuscular electrical stimulation (NMES) applied contingent to the voluntary activation of the primary motor cortex through MI can help differentiate patterns of activity associated with different hand movements of the same limb by consistently recruiting the separate neural pathways associated with each of the movements within a closed-loop BCI setup. The investigators study the neuroplastic changes associated with training with the two stimulation modalities.
Investigators
Jose del R. Millan
Professor
University of Texas at Austin
Eligibility Criteria
Inclusion Criteria
- •Able-bodied participants:
- •good general health
- •normal or corrected vision
- •no history of neurological/psychiatric disease
- •ability to read and understand English (Research Personnel do not speak Spanish)
- •Subjects with motor disabilities
- •motor deficits due to: unilateral and bilateral stroke / spinal cord injury / motor neuron diseases (i.e. amyotrophic lateral sclerosis, spino-cerebellar ataxia, multiple sclerosis) / muscular diseases (i.e. myopathy) / traumatic or neurological pain / movement disorders (i.e. cerebral palsy) / orthopedic / traumatic brain injury / brain tumors
- •normal or corrected vision
- •ability to read and understand English
- •ability to provide informed consent
Exclusion Criteria
- •Subjects with motor disabilities
- •short attentional spans or cognitive deficits that prevent the subject from concentrating during the whole experimental session
- •heavy medication affecting the central nervous system (including vigilance)
- •concomitant serious illness (e.g., metabolic disorders)
- •All participants
- •factors hindering EEG/EMG acquisition and the delivery of non-invasive electrical stimulation (e.g., skin infection, wounds, dermatitis, metal implants under electrodes)
- •criteria identified in safety guidelines for MRI and TMS, in particular metallic implants
Outcomes
Primary Outcomes
Change in the BCI command delivery performance
Time Frame: immediately after each intervention session and up to one week after all sessions
The command delivery accuracy reflects the level of control of the subject when using the BCI. It measures the percentage of trials in which the subject-specific classifier that is used to differentiate the different imagined movements could accumulate enough evidence to support the presence of EEG patterns specifically associated with the imagined movement in those trials. The score is 0-100, and the higher the value, the better the outcome.
Change in the focality and Strength of SMR Modulation
Time Frame: immediately after each intervention session and up to one week after all sessions
The focality of sensorimotor rhythm modulation is assessed from EEG using event-related desynchorinzation (ERD) and synchronization (ERS) over the motor area. Continuous measure, the higher the better
Secondary Outcomes
- Separability of Motor Imagery features(immediately after each intervention session and one-day after all sessions)
- Changes in motor-evoked potential amplitude(immediately after each intervention session and one-day after all sessions)
- Change in focality of fMRI activation for different imagined movements(immediately after each intervention session and one-day after all sessions)
- More discriminable fMRI activations for different imagined movements(immediately after each intervention session and one-day after all sessions)
- Stability of Motor Imagery features(immediately after each intervention session and one-day after all sessions)
- Changes in electroencephalography functional connectivity(immediately after each intervention session and one-day after all sessions)