Heitmann S.,University of Pittsburgh |
Rule M.,Brown University |
Truccolo W.,Brown University |
Truccolo W.,Center for Neurorestoration and Neurotechnology |
Ermentrout B.,University of Pittsburgh
PLoS Computational Biology | Year: 2017
Constant optogenetic stimulation targeting both pyramidal cells and inhibitory interneurons has recently been shown to elicit propagating waves of gamma-band (40–80 Hz) oscillations in the local field potential of non-human primate motor cortex. The oscillations emerge with non-zero frequency and small amplitude—the hallmark of a type II excitable medium—yet they also propagate far beyond the stimulation site in the manner of a type I excitable medium. How can neural tissue exhibit both type I and type II excitability? We investigated the apparent contradiction by modeling the cortex as a Wilson-Cowan neural field in which optogenetic stimulation was represented by an external current source. In the absence of any external current, the model operated as a type I excitable medium that supported propagating waves of gamma oscillations similar to those observed in vivo. Applying an external current to the population of inhibitory neurons transformed the model into a type II excitable medium. The findings suggest that cortical tissue normally operates as a type I excitable medium but it is locally transformed into a type II medium by optogenetic stimulation which predominantly targets inhibitory neurons. The proposed mechanism accounts for the graded emergence of gamma oscillations at the stimulation site while retaining propagating waves of gamma oscillations in the non-stimulated tissue. It also predicts that gamma waves can be emitted on every second cycle of a 100 Hz oscillation. That prediction was subsequently confirmed by re-analysis of the neurophysiological data. The model thus offers a theoretical account of how optogenetic stimulation alters the excitability of cortical neural fields. © 2017 Public Library of Science. All Rights Reserved.
Yin M.,Brown University |
Borton D.A.,Brown University |
Borton D.A.,Ecole Polytechnique Federale de Lausanne |
Komar J.,Brown University |
And 15 more authors.
Neuron | Year: 2014
Brain recordings in large animal models and humans typically rely on a tethered connection, which has restricted the spectrum of accessible experimental and clinical applications. To overcome this limitation, we have engineered a compact, lightweight, high data rate wireless neurosensor capable of recording the full spectrum of electrophysiological signals fromthe cortex of mobile subjects. The wireless communication system exploits a spatially distributed network of synchronized receivers that is scalable to hundreds of channels and vast environments. To demonstrate the versatility of our wireless neurosensor, we monitored cortical neuron populations in freely behaving nonhuman primates during natural locomotion and sleep-wake transitions in ecologically equivalent settings. The interface is electrically safe and compatible with the majority of existing neural probes, which may support previously inaccessible experimental and clinical research. © 2014 Elsevier Inc.
Shaikhouni A.,Brown University |
Donoghue J.P.,Brown University |
Donoghue J.P.,Center for Neurorestoration and Neurotechnology |
Hochberg L.R.,Brown University |
And 2 more authors.
Journal of Neurophysiology | Year: 2013
Somatic sensory signals provide a major source of feedback to motor cortex. Changes in somatosensory systems after stroke or injury could profoundly influence brain computer interfaces (BCI) being developed to create new output signals from motor cortex activity patterns. We had the unique opportunity to study the responses of hand/arm area neurons in primary motor cortex to passive joint manipulation in a person with a long-standing brain stem stroke but intact sensory pathways. Neurons responded to passive manipulation of the contralateral shoulder, elbow, or wrist as predicted from prior studies of intact primates. Thus fundamental properties and organization were preserved despite arm/hand paralysis and damage to cortical outputs. The same neurons were engaged by attempted arm actions. These results indicate that intact sensory pathways retain the potential to influence primary motor cortex firing rates years after cortical outputs are interrupted and may contribute to online decoding of motor intentions for BCI applications. © 2013 the American Physiological Society.
Homer M.L.,Brown University |
Nurmikko A.V.,Brown University |
Donoghue J.P.,Brown University |
Donoghue J.P.,Center for Neurorestoration and Neurotechnology |
And 3 more authors.
Annual Review of Biomedical Engineering | Year: 2013
Intracortical brain computer interfaces (iBCIs) are being developed to enable people to drive an output device, such as a computer cursor, directly from their neural activity. One goal of the technology is to help people with severe paralysis or limb loss. Key elements of an iBCI are the implanted sensor that records the neural signals and the software that decodes the user's intended movement from those signals. Here, we focus on recent advances in these two areas, placing special attention on contributions that are or may soon be adopted by the iBCI research community. We discuss how these innovations increase the technology's capability, accuracy, and longevity, all important steps that are expanding the range of possible future clinical applications. Copyright © 2013 by Annual Reviews.
Aghagolzadeh M.,Brown University |
Truccolo W.,Brown University |
Truccolo W.,Center for Neurorestoration and Neurotechnology
IEEE Transactions on Neural Systems and Rehabilitation Engineering | Year: 2016
Motor cortex neuronal ensemble spiking activity exhibits strong low-dimensional collective dynamics (i.e., coordinated modes of activity) during behavior. Here, we demonstrate that these low-dimensional dynamics, revealed by unsupervised latent state-space models, can provide as accurate or better reconstruction of movement kinematics as direct decoding from the entire recorded ensemble. Ensembles of single neurons were recorded with triple microelectrode arrays (MEAs) implanted in ventral and dorsal premotor (PMv, PMd) and primary motor (M1) cortices while nonhuman primates performed 3-D reach-to-grasp actions. Low-dimensional dynamics were estimated via various types of latent state-space models including, for example, Poisson linear dynamic system (PLDS) models. Decoding from low-dimensional dynamics was implemented via point process and Kalman filters coupled in series. We also examined decoding based on a predictive subsampling of the recorded population. In this case, a supervised greedy procedure selected neuronal subsets that optimized decoding performance. When comparing decoding based on predictive subsampling and latent state-space models, the size of the neuronal subset was set to the same number of latent state dimensions. Overall, our findings suggest that information about naturalistic reach kinematics present in the recorded population is preserved in the inferred low-dimensional motor cortex dynamics. Furthermore, decoding based on unsupervised PLDS models may also outperform previous approaches based on direct decoding from the recorded population or on predictive subsampling. © 2001-2011 IEEE.
Cash S.S.,Harvard University |
Hochberg L.R.,Harvard University |
Hochberg L.R.,Brown University |
Hochberg L.R.,Center for Neurorestoration and Neurotechnology
Neuron | Year: 2015
Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the CNS trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this Perspective, we focus on single-neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics. © 2015 Elsevier Inc.
Philip N.S.,Center for Neurorestoration and Neurotechnology |
Ridout S.J.,Brown University |
Albright S.E.,Center for Neurorestoration and Neurotechnology |
Sanchez G.,Center for Neurorestoration and Neurotechnology |
Carpenter L.L.,Brown University
Journal of Traumatic Stress | Year: 2016
Current treatment options for posttraumatic stress disorder (PTSD) offer modest benefits, underscoring the need for new treatments. Repetitive transcranial magnetic stimulation (rTMS) depolarizes neurons in a targeted brain region with magnetic fields typically pulsed at low (1 Hz) or high (10 Hz) frequency to relieve major depressive disorder (MDD). Prior work suggests an intermediate pulse frequency, 5 Hz, is also efficacious for treating comorbid depressive and anxiety symptoms. In this chart review study, we systematically examined the clinical and safety outcomes in 10 patients with comorbid MDD and PTSD syndromes who received 5-Hz rTMS therapy at the Providence VA Medical Center Neuromodulation Clinic. Self-report scales measured illness severity prior to treatment, after every 5 treatments, and upon completion of treatment. Results showed significant reduction in symptoms of PTSD (p = .003, effect size = 1.12, 8/10 with reliable change) and MDD (p = .005, effect size = 1.09, 6/10 with reliable change). Stimulation was well tolerated and there were no serious adverse events. These data indicate 5-Hz rTMS may be a useful option to treat these comorbid disorders. Larger, controlled trials are needed to confirm the benefits of 5-Hz protocols observed in this pilot study. © 2016 International Society for Traumatic Stress Studies.
Bedard P.,Brown University |
Sanes J.N.,Brown University |
Sanes J.N.,Center for Neurorestoration and Neurotechnology
NeuroImage | Year: 2014
Humans readily learn and remember new motor skills, a process that likely underlies adaptation to changing environments. During adaptation, the brain develops new sensory-motor relationships, and if consolidation occurs, a memory of the adaptation can be retained for extended periods. Considerable evidence exists that multiple brain circuits participate in acquiring new sensory-motor memories, though the networks engaged in recalling these and whether the same brain circuits participate in their formation and recall have less clarity. To address these issues, we assessed brain activation with functional MRI while young healthy adults learned and recalled new sensory-motor skills by adapting to world-view rotations of visual feedback that guided hand movements. We found cerebellar activation related to adaptation rate, likely reflecting changes related to overall adjustments to the visual rotation. A set of parietal and frontal regions, including inferior and superior parietal lobules, premotor area, supplementary motor area and primary somatosensory cortex, exhibited non-linear learning-related activation that peaked in the middle of the adaptation phase. Activation in some of these areas, including the inferior parietal lobule, intra-parietal sulcus and somatosensory cortex, likely reflected actual learning, since the activation correlated with learning after-effects. Lastly, we identified several structures having recall-related activation, including the anterior cingulate and the posterior putamen, since the activation correlated with recall efficacy. These findings demonstrate dynamic aspects of brain activation patterns related to formation and recall of a sensory-motor skill, such that non-overlapping brain regions participate in distinctive behavioral events. © 2014.
Fasoli S.E.,Center for Neurorestoration and Neurotechnology |
Fasoli S.E.,Brown University |
Chen C.C.,Columbia University
Archives of Physical Medicine and Rehabilitation | Year: 2014
Clinician feedback and thought processes about treatment classification and description will aid development of the rehabilitation treatment taxonomy (RTT) presented in this supplement. Here, we discuss comparisons between the proposed RTT and an inductive practice-based evidence (PBE) model used to describe rehabilitation treatments. Interviews with clinicians well versed with PBE highlight the complexity of rehabilitation treatments, and bring to light potential advantages and challenges of a deductive, theory-driven classification to uncover the black box of rehabilitation. © 2014 by the American Congress of Rehabilitation Medicine.
Barrese J.C.,UMDNJ New Jersey Medical School |
Barrese J.C.,Brown University |
Barrese J.C.,Center for Neurorestoration and Neurotechnology |
Rao N.,Brown University |
And 6 more authors.
Journal of Neural Engineering | Year: 2013
Objective. Brain-computer interfaces (BCIs) using chronically implanted intracortical microelectrode arrays (MEAs) have the potential to restore lost function to people with disabilities if they work reliably for years. Current sensors fail to provide reliably useful signals over extended periods of time for reasons that are not clear. This study reports a comprehensive retrospective analysis from a large set of implants of a single type of intracortical MEA in a single species, with a common set of measures in order to evaluate failure modes. Approach. Since 1996, 78 silicon MEAs were implanted in 27 monkeys (Macaca mulatta). We used two approaches to find reasons for sensor failure. First, we classified the time course leading up to complete recording failure as acute (abrupt) or chronic (progressive). Second, we evaluated the quality of electrode recordings over time based on signal features and electrode impedance. Failure modes were divided into four categories: biological, material, mechanical, and unknown. Main results. Recording duration ranged from 0 to 2104 days (5.75 years), with a mean of 387 days and a median of 182 days (n = 78). Sixty-two arrays failed completely with a mean time to failure of 332 days (median = 133 days) while nine array experiments were electively terminated for experimental reasons (mean = 486 days). Seven remained active at the close of this study (mean = 753 days). Most failures (56%) occurred within a year of implantation, with acute mechanical failures the most common class (48%), largely because of connector issues (83%). Among grossly observable biological failures (24%), a progressive meningeal reaction that separated the array from the parenchyma was most prevalent (14.5%). In the absence of acute interruptions, electrode recordings showed a slow progressive decline in spike amplitude, noise amplitude, and number of viable channels that predicts complete signal loss by about eight years. Impedance measurements showed systematic early increases, which did not appear to affect recording quality, followed by a slow decline over years. The combination of slowly falling impedance and signal quality in these arrays indicates that insulating material failure is the most significant factor. Significance. This is the first long-term failure mode analysis of an emerging BCI technology in a large series of non-human primates. The classification system introduced here may be used to standardize how neuroprosthetic failure modes are evaluated. The results demonstrate the potential for these arrays to record for many years, but achieving reliable sensors will require replacing connectors with implantable wireless systems, controlling the meningeal reaction, and improving insulation materials. These results will focus future research in order to create clinical neuroprosthetic sensors, as well as valuable research tools, that are able to safely provide reliable neural signals for over a decade. © 2013 IOP Publishing Ltd.