A5032110460- EEG and Brain-Computer Interfaces
- Neuroscience and Neural Engineering
- Muscle activation and electromyography studies
- Neural dynamics and brain function
- Advanced Memory and Neural Computing
- Gaze Tracking and Assistive Technology
- Stroke Rehabilitation and Recovery
- Traumatic Brain Injury Research
- Functional Brain Connectivity Studies
- Neurological disorders and treatments
- Traumatic Brain Injury and Neurovascular Disturbances
- Botulinum Toxin and Related Neurological Disorders
- Acute Ischemic Stroke Management
- Cardiac Arrest and Resuscitation
- Neuroscience and Neuropharmacology Research
- Vagus Nerve Stimulation Research
- Epilepsy research and treatment
- Family and Patient Care in Intensive Care Units
- Blind Source Separation Techniques
- Photoreceptor and optogenetics research
- Cerebrovascular and Carotid Artery Diseases
- Tactile and Sensory Interactions
- Cerebral Palsy and Movement Disorders
- Assistive Technology in Communication and Mobility
- Intensive Care Unit Cognitive Disorders
Providence VA Medical Center
2015-2025
Harvard University
2016-2025
Massachusetts General Hospital
2016-2025
Allen Institute for Brain Science
2015-2025
Center for Neuro-Oncology
2017-2025
Brown University
2016-2025
Neurotech (United States)
2013-2025
University of California, Davis
2024
Neurological Surgery
2024
Rehabilitation Research and Development Service
2015-2024
Brain-computer interfaces (BCIs) have the potential to restore communication for people with tetraplegia and anarthria by translating neural activity into control signals assistive devices. While previous pre-clinical clinical studies demonstrated promising proofs-of-concept (Serruya et al., 2002; Simeral 2011; Bacher 2015; Nuyujukian Aflalo Gilja Jarosiewicz Wolpaw 1998; Hwang 2012; Spüler Leuthardt 2004; Taylor Schalk 2008; Moran, 2010; Brunner Wang 2013; Townsend Platsko, 2016;...
The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess feasibility using activity obtained from a small-scale, chronically implanted, intracortical microelectrode array provide control signals for prosthesis system. Critical questions include how long implanted microelectrodes will record useful signals, reliably those can be acquired and decoded, effectively they used various assistive technologies such as computers robotic devices, or enable...
Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that tetraplegic was able obtain continuous two-dimensional control computer cursor using activity recorded from his cortex. This control, however, not sufficiently accurate for reliable use many common tasks. Here, we studied several central...
The neurophysiological mechanisms by which anesthetic drugs cause loss of consciousness are poorly understood. Anesthetic actions at the molecular, cellular, and systems levels have been studied in detail steady states deep general anesthesia. However, little is known about how anesthetics alter neural activity during transition into unconsciousness. We recorded simultaneous multiscale from human cortex, including ensembles single neurons, local field potentials, intracranial...
See Schiff (doi:10.1093/awx209) for a scientific commentary on this article. Patients with acute severe traumatic brain injury may recover consciousness before self-expression. Without behavioural evidence of at the bedside, clinicians render an inaccurate prognosis, increasing likelihood withholding life-sustaining therapies or denying rehabilitative services. Task-based functional magnetic resonance imaging and electroencephalography techniques have revealed covert in chronic setting, but...
Brain-computer interfaces (BCIs) promise to restore independence for people with severe motor disabilities by translating decoded neural activity directly into the control of a computer. However, recorded signals are not stationary (that is, can change over time), degrading quality decoding. Requiring users pause what they doing whenever perform decoder recalibration routines is time-consuming and impractical everyday use BCIs. We demonstrate that signal nonstationarity in an intracortical...
Speech brain-computer interfaces (BCIs) have the potential to restore rapid communication people with paralysis by decoding neural activity evoked attempted speech into text
Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements such recordings have been extended to include unit activity ensemble neurons. However, detailed functional characterization excitatory and inhibitory cells has not attempted human neocortex, particularly during the sleep state. Here, we report that feature discrimination possible from high-density neocortex by using 2D multielectrode arrays....
Motor neural interface systems (NIS) aim to convert signals into motor prosthetic or assistive device control, allowing people with paralysis regain movement control over their immediate environment. Effector can degrade if the relationship between recorded and intended behavior changes. Therefore, characterizing both biological technological sources of signal variability is important for a reliable NIS. To address frequency causes in spike-based NIS, we analyzed within-day fluctuations...
Background Implantable brain–computer interfaces (BCIs), functioning as motor neuroprostheses, have the potential to restore voluntary impulses control digital devices and improve functional independence in patients with severe paralysis due brain, spinal cord, peripheral nerve or muscle dysfunction. However, reports date had limited clinical translation. Methods Two participants amyotrophic lateral sclerosis (ALS) underwent implant a single-arm, open-label, prospective, early feasibility...
Individuals with neurological disease or injury such as amyotrophic lateral sclerosis, spinal cord stroke may become tetraplegic, unable to speak even locked-in. For people these conditions, current assistive technologies are often ineffective. Brain-computer interfaces being developed enhance independence and restore communication in the absence of physical movement. Over past decade, individuals tetraplegia have achieved rapid on-screen typing point-and-click control tablet apps using...
BackgroundBrain–computer interfaces can enable communication for people with paralysis by transforming cortical activity associated attempted speech into text on a computer screen. Communication brain–computer has been restricted extensive training requirements and limited accuracy.MethodsA 45-year-old man amyotrophic lateral sclerosis (ALS) tetraparesis severe dysarthria underwent surgical implantation of four microelectrode arrays his left ventral precentral gyrus 5 years after the onset...
Brain-computer interfaces have so far focused largely on enabling the control of a single effector, for example computer cursor or robotic arm. Restoring multi-effector motion could unlock greater functionality people with paralysis (e.g., bimanual movement). However, it may prove challenging to decode simultaneous multiple effectors, as we recently found that compositional neural code links movements across all limbs and tuning changes nonlinearly during dual-effector motion. Here,...
Abstract People with paralysis express unmet needs for peer support, leisure activities and sporting activities. Many within the general population rely on social media massively multiplayer video games to address these needs. We developed a high-performance, finger-based brain–computer-interface system allowing continuous control of three independent finger groups, which thumb can be controlled in two dimensions, yielding total four degrees freedom. The was tested human research participant...
The relationship between spiking activities in motor cortex and movement kinematics has been well studied neurologically intact nonhuman primates. We examined the primary (M1) intended (position velocity) using 96-microelectrode arrays chronically implanted two humans with tetraplegia. Study participants were asked to perform different tasks: imagined pursuit tracking of a cursor moving on computer screen “neural center-out” task which position was controlled by participant's neural...