Marc W. Slutzky - US grants

[unreadable] DESCRIPTION (provided by applicant): [unreadable] [unreadable] Over 600,000 Americans have severely impaired motor function from disorders including spinal cord injury, amyotrophic lateral sclerosis, pontine stroke, and cerebral palsy. A brain-machine interface (BMI) could enable locked-in or tetraplegic patients to communicate and interact with their environment. Two crucial decisions in designing a BMI are (1) what type of brain signals to use as inputs to a controller and (2) what methods to use to decode those signals. Most BMIs have used either noninvasive scalp EEG recordings or invasive intracortical recordings of single- or multi-neuron spikes as control inputs. A few have used subdural or intracortical local field potentials (LFPs). However, no group has yet systematically compared these signals in motor cortex for use in BMI applications. This proposal's first goal is to assess the relative performance of spikes and field potentials (both intracortical and epidural) as control inputs for a variety of movement-related outputs. Epidural field potentials (EFPs) are intermediate in invasiveness, signal quality, stability and spatial resolution compared with existing scalp, subdural, and intracortical recordings, and thus represent an unexplored middle ground. This proposal's second goal is to evaluate linear and nonlinear techniques-including several novel to BMI applications-for both decoding data and reducing the inherently large dimensionality of data from multiple neural signals. The primary hypotheses of the proposed project are (1) that spikes will perform better in decoding more complex movement-related outputs, but that field potentials may perform similarly on decoding simpler outputs, and (2) that nonlinear decoders and dimensionality-reduction techniques may provide improved accuracy over linear methods. The specific aims to address these hypotheses are 1) to evaluate single neuron spikes as inputs to decoders of movement- related outputs, 2) to develop a novel epidural multi-electrode recording technique in the macaque monkey, and 3) to evaluate field potential signals as inputs to decoders of movement-related outputs. Aims 1 and 3 will involve application of dimensionality-reduction algorithms (e.g., independent components analysis, Isomap) and decoding algorithms (system identification, neural networks, support vector machines) to both spikes and field potentials. Aim 2 will entail using a computer model and spatial spectral analysis to optimize the epidural electrode array design. This project will provide the first comparison of spikes, LFPs and EFPs as inputs for identical BMI output applications. The supervision of Drs. Lee Miller and W. Zev Rymer, with additional guidance from Drs. Simon Levine, Jonathan Wolpaw and Nicholas Hatsopoulos, will provide the principal investigator with expertise in recording and processing both spikes and field potentials for BMI applications using a variety of state-of-the- art techniques. A comprehensive career development plan including clinical and research mentoring, seminars, and courses, will foster the candidate's transition into an independent physician-scientist. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Stroke remains the leading cause of chronic disability in the U.S., and more than half of stroke survivors have persistent impairment of arm function despite receiving conventional therapy. In these stroke survivors, a significant cause of impaired arm movement is abnormal co-activation between muscles that normally do not activate together. The long-term goal of this research is to develop a new therapy for stroke using an inexpensive, easily portable device to improve motor function by decoupling abnormally co-activating muscles. This therapy, a myoelectric computer interface (MCI), maps electrical muscle activity onto movements of a cursor in a computer game. This provides direct, detailed feedback about the co-activation of a pair of muscles to the user. Our preliminary results suggest that training with the MCI allows stroke survivors to greatly reduce abnormal co-activation in the targeted arm muscle pair and may also improve function. The objective of this proposal is to determine how to optimize translation of the decoupled muscle activations into functional improvement. We seek to improve motor function in chronic stroke survivors by even more than in our preliminary studies, which assessed isometric MCI training of a single muscle pair. We will test the effects of two different doses of training on motor function. We will also assess the extent to which individual muscles can be decoupled during movement, which is a more functionally relevant condition than isometric activation. The specific aims of the proposal are to 1) determine the extent to which isometric MCI training of multiple muscle pairs improves function, and 2) determine the extent to which movement-based MCI training of multiple muscle pairs improves function. The proposed research is innovative because it applies fundamental insight about abnormal co-activation after stroke to develop a novel treatment modality that will be inexpensive and portable. In addition, it tests the fundamental ability of an injured central nervous system to regain precise control over specific pairs of muscles. The ability to regain precise control of individual muscles is important because it should improve the ability to transfer the learned behavior to functional tasks. This therapy will broadly impact the field sinc it can enable use by a wide range of stroke survivors. This includes those with severe motor impairments, who are those most in need of new therapies. Achieving our objective will be significant because we expect it to lead to development of an effective treatment for impaired movement after stroke and set the stage for initial clinical trials of the therapy. We estimate tht this therapy could benefit at least 1 million stroke survivors in the U.S. alone.

? DESCRIPTION (provided by applicant): Many survivors of brain injury have persistent impairment of hand function despite receiving conventional therapy. The long-term goal of this research project is to augment and direct the brain's inherent plasticity to improve motor function for survivors of traumatic or ischemic brain injury. Functional improvement after brain injury correlates with an enlarged area of cerebral cortex corresponding to the improved movement (motor map), but it is unclear if the enlarged map causes improved function. This question is of fundamental importance to our understanding of recovery from brain injuries. Brain machine interfaces (BMIs), which enable subjects to use their brain signals to directly control external devices, can induce plastic changes in the brain's activity. Thus, a BMI could provide a powerful tool to drive plasticity in injured brains and also test the effects of map enlargement on function. However, important gaps in our knowledge remain about what aspects of BMI training are critical to enhancing cortical plasticity, including 1) the types and features of neural signals used to control the BMI, 2) the temporal precision with which somatosensory (haptic) feedback must be synchronized with motor intent, and 3) the spatial precision of movement intent (e.g., individual finger vs. whole hand) used to control the BMI. The objectives of this proposal are to determine the aspects of BMIs most important to changing motor maps, and the extent to which motor map expansion driven by BMIs improves function. By expanding the map, the control of muscles that have by paralyzed by brain injury can be moved to areas of cortex that still retain intact descending connections, thus restoring function. The central hypothesis of this proposal is that optimally driving plasticity and motor map changes is critically dependent on simultaneously activating motor intent and haptic feedback. We propose that high-frequency signals will enable much greater spatiotemporal precision than the low frequencies used in BMIs for rehabilitation to date. We will test this hypothesis in subjects who have had hemicraniectomies for traumatic brain injury via these specific aims: 1) Determine the extent to which high-frequency based BMI training drives motor map enlargement and improves hand function, and 2) Determine the role of synchrony between motor intent and haptic feedback in driving changes in map size and hand function. This proposal's innovative use of scalp signals over the hemicraniectomy will enable us to record high-resolution, high-bandwidth signals non-invasively and test our hypothesis. Achieving our objectives will be significant because it will improve the design of BMI training paradigms by identifying spectral, temporal, and spatial features that are critical to plasticity enhancement. We expect this proposal to define the ability of BMIs to create changes in motor maps. We also expect it to help define the relationship between motor map changes and functional recovery. Finally, it will demonstrate the potential for functional improvement in future studies using minimally-invasive, epidural-based BMIs after brain injury.

Hemiparesis from stroke is the leading cause of disability in the world. Arm impairment after stroke is due not only to weakness, but also to impaired muscle coordination?abnormal co-activation?during attempted movement. This is especially true in the most severely-impaired patients, who are most in need of new treatments. We have developed a myoelectric computer interface (MCI) paradigm to remedy this co-activation. The long term goal of this research is to develop an affordable, wearable MCI device that will improve motor function in stroke survivors. However, to date we have studied MCI use only in chronic stroke survivors in the laboratory, using cumbersome and expensive equipment. Little information exists as to how soon after stroke abnormal co-activation starts to impede arm function, but it seems likely that averting it would be easier in the acute stage, when the brain exhibits greater plasticity. Moreover, as healthcare resources become ever scarcer, it is important to design new therapies that are portable and affordable to enable extensive use in the community. The objective of this proposal is to advance the MCI paradigm by 1) creating a wearable MCI device that can be used outside the laboratory, 2) enhancing the training regimen, and 3) testing the MCI in stroke survivors in both the acute and chronic stages of recovery. The central hypothesis of this proposal is that making MCI therapy more intense, more similar to everyday movements, and starting training early in stroke recovery, will result in even greater functional improvement. We will design a wearable device and test this hypothesis in stroke survivors in both early and late stages after stroke via these specific aims: 1) To design and implement a wearable MCI device that controls therapeutic, tablet-based games, 2) To develop and enhance home-based MCI training in chronic stroke survivors, and 3) To assess the effect of acute-phase MCI training on stroke survivors' movement and function. This proposal's innovative development of a wearable device paradigm to reduce abnormal co-activation will enable us to study the benefits of MCI training both early and late after stroke. Achieving our objectives will be significant because it will address unmet needs to develop new treatments for stroke that are inexpensive and wearable to enable widespread use. We expect MCI training will help people with severe arm impairment as well as those with moderate impairment, since the severely-impaired have more abnormal co-activation and since the MCI only requires some residual myoelectric activity, not overt movements. We also expect this proposal to provide an unprecedented characterization of the temporal development of abnormal co-activation early after stroke. This will impact our overall understanding of the process of recovery from stroke. We expect that the MCI paradigm will be synergistic with other therapies, since it has a novel mechanism of action (reducing co-activation using EMGs). Finally, we anticipate that this proposal will provide critical results that will position us to translate this research into clinical trials.

Brain-computer interfaces (BCIs) have the potential to revolutionize communication and environmental interaction abilities for people with extensive paralysis. Successful translation of BCIs to actual clinical use by such people depends on close and productive multidisciplinary interactions, and requires recognition of and attention to a set of crucial issues. The International BCI Meeting Series (1999, 2002, 2005, 2010, 2013 and 2016) convened a wide range of research groups and disciplines vital to BCI research and triggered many productive interactions and collaborations. This proposal, for the Seventh International BCI Meeting: ?BCIs: Not Getting Lost in Translation,? will be organized under the leadership of a Program Committee appointed by the BCI Society. The meeting will encourage and facilitate the development and translation of BCIs into clinically- viable devices through the following specific aims: 1) Convene and foster productive interactions among all the disciplines and constituencies whose cooperation is crucial to successful BCI research and development. No other venue brings them all together. 2) Present a concise and comprehensive update of the current state of BCI research and development. 3) Address in focused workshops the major topics critical for continued progress in BCI research and development. Additional topics of broad interest will be chosen based on workshop proposals and abstracts submitted by participants. 4) Promote the education and development of new researchers through the participation of many graduate students and postdoctoral fellows. Networking events will encourage interactions between new and established researchers and particularly target underrepresented groups of researchers. 5) Convene the new BCI Society and encourage the involvement of young scientists in the society. This is crucial to generating new and fresh ideas in addition to translating state-of-the-art BCIs to clinical use. 6) Maximize the immediate and long-term Meeting impact through publication by the journal Brain Computer Interfaces of a special issue of peer-reviewed primary articles and focused reviews derived from the meeting. In summary, this meeting will assemble scientists, engineers, clinicians and policymakers involved in BCI research and clinical use, review the present state of the field, address key issues critical to further progress, and promote the education and participation of young researchers. This meeting and the resulting comprehensive publications should, like its predecessors, contribute greatly to BCI research and development.

Stroke is the largest cause of major disability. This disability most often results from persistent arm impairment. A significant portion of arm impairment is caused not by weakness or spasticity, but by abnormal co-activation among arm muscles. This coordination dysfunction is pervasive in the most severely impaired patients, who are most in need of new therapies. To treat abnormal muscle co-activation, we developed a myoelectric-computer interface (MyoCI). In addition, we pioneered the use of targeted memory reactivation (TMR) to enhance memory consolidation during sleep. The long-term goal of this research is to develop an affordable, non- invasive, and easy-to-use combination of MyoCI and TMR that improves control of arm movements by reducing abnormal co-activation. Our preliminary studies show that TMR enhances consolidation of MyoCI learning in a single nap in a group of healthy individuals, and across several nights in three stroke survivors. Accordingly, we propose to determine whether this training-plus-sleep combination will generalize to improve motor function over an extended training protocol in stroke survivors. The objectives of this proposal are 1) to determine whether TMR can augment motor learning after stroke, and 2) to determine optimal parameters for the MyoCI+TMR paradigm to enhance motor function in stroke survivors. Our central hypothesis is that supplementing MyoCI training with TMR will augment learning considerably and thereby improve arm movement. We will test this hypothesis via the following specific aims: 1) Test the extent to which TMR during SWS enhances MyoCI learning after stroke, 2) Assess the ability of TMR across all sleep stages to enhance MyoCI learning after stroke, and 3) Assess the influence of TMR dose and stroke location on MyoCI learning. This proposal?s innovative combination of wearable, inexpensive, and noninvasive MyoCI+TMR will enable us to test the effects of TMR on motor learning after stroke. Achieving our objectives will be significant because it will facilitate the development of an enhanced rehabilitative therapy to improve function after stroke that could be used widely and could help the most severely impaired stroke survivors. We expect that the paradigm will be synergistic with other therapies, given its novel mechanism of action (reducing co-activation using myoelectric signals). The research will also provide basic information about what brain areas are critical for consolidating motor learning. We further expect that TMR could be applied to other types of stroke rehabilitation in addition to MyoCI. Finally, this project will provide critical information needed to plan larger clinical trials to assess efficacy of this and related approaches.