103 research outputs found

    Doctor of Philosophy

    Get PDF
    dissertationRecording the neural activity of human subjects is indispensable for fundamental neuroscience research and clinical applications. Human studies range from examining the neural activity of large regions of the cortex using electroencephalography (EEG) or electrocorticography (ECoG) to single neurons or small populations of neurons using microelectrode arrays. In this dissertation, microscale recordings in the human cortex were analyzed during administration of propofol anesthesia and articulate movements such as speech, finger flexion, and arm reach. Recordings were performed on epilepsy patients who required long-term electrocorticographic monitoring and were implanted with penetrating or surface microelectrode arrays. We used penetrating microelectrode arrays to investigate the effects of propofol anesthesia on action potentials (APs) and local field potentials (LFPs). Increased propofol concentration correlated with decreased high-frequency power in LFP spectra and decreased AP firing rates, as well as the generation of large amplitude spike-like LFP activity; however, the temporal relationship between APs and LFPs remained relatively consistent at all levels of propofol anesthesia. The propofol-induced suppression of neocortical network activity allowed LFPs to be dominated by low-frequency spike-like activity, and correlated with sedation and unconsciousness. As the low-frequency spike-like activity increased, and the AP-LFP relationship became more predictable, firing rate encoding capacity was impaired. This suggests a mechanism for decreased information processing in the neocortex that accounts for propofol-induced unconsciousness. We also demonstrated that speech, finger, and arm movements can be decoded from LFPs recorded with dense grids of microelectrodes placed on the surface of human cerebral cortex for brain computer interface (BCI) applications using LFPs recorded over face-motor area, vocalized articulations of ten different words and silence were classified on a trial-by-trial basis with 82.4% accuracy. Using LFPs recorded over the hand area of motor cortex, three individual finger movements and rest were classified on a trial-by-trial basis with 62% accuracy. LFPs recorded over the arm area of motor cortex were used to continuously decode the arm trajectory with a maximum correlation coefficient of 0.82 in the x-direction and 0.76 in the y-direction. These findings demonstrate that LFPs recorded by micro-ECoG grids from the surface of the cerebral cortex contain sufficient information to provide rapid and intuitive control a BCI communication or motor prosthesis

    The future of upper extremity rehabilitation robotics: research and practice

    Full text link
    The loss of upper limb motor function can have a devastating effect on people’s lives. To restore upper limb control and functionality, researchers and clinicians have developed interfaces to interact directly with the human body’s motor system. In this invited review, we aim to provide details on the peripheral nerve interfaces and brain‐machine interfaces that have been developed in the past 30 years for upper extremity control, and we highlight the challenges that still remain to transition the technology into the clinical market. The findings show that peripheral nerve interfaces and brain‐machine interfaces have many similar characteristics that enable them to be concurrently developed. Decoding neural information from both interfaces may lead to novel physiological models that may one day fully restore upper limb motor function for a growing patient population.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155489/1/mus26860_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155489/2/mus26860.pd

    Oscillatory Activity in Mouse Lemur Primary Motor Cortex During Natural Locomotor Behavior

    Get PDF
    In arboreal environments, substrate orientation determines the biomechanical strategy for postural maintenance and locomotion. In this study, we investigated possible neuronal correlates of these mechanisms in an ancestral primate model, the gray mouse lemur. We conducted telemetric recordings of electrocorticographic activity in left primary motor cortex of two mouse lemurs moving on a branch-like small-diameter pole, fixed horizontally, or vertically. Analysis of cortical oscillations in high ÎČ (25–35 Hz) and low Îł (35–50 Hz) bands showed stronger resting power on horizontal than vertical substrate, potentially illustrating sensorimotor processes for postural maintenance. Locomotion on horizontal substrate was associated with stronger event-related desynchronization than vertical substrate, which could relate to locomotor adjustments and/or derive from differences in baseline activity. Spectrograms of cortical activity showed modulation throughout individual locomotor cycles, with higher values in the first than second half cycle. However, substrate orientation did not significantly influence these variations. Overall, these results confirm that specific cortical mechanisms are solicited during arboreal locomotion, whereby mouse lemurs adjust cortical activity to substrate orientation during static posture and locomotion, and modulate this activity throughout locomotor cycles

    VALIDATION OF A MODEL OF SENSORIMOTOR INTEGRATION WITH CLINICAL BENEFITS

    Get PDF
    Healthy sensorimotor integration – or how our touch influences our movements – is critical to efficiently interact with our environment. Yet, many aspects of this process are still poorly understood. Importantly, several movement disorders are often considered as originating from purely motor impairments, while a sensory origin could also lead to a similar set of symptoms. To alleviate these issues, we hereby propose a novel biologically-based model of the sensorimotor loop, known as the SMILE model. After describing both the functional, and the corresponding neuroanatomical versions of the SMILE, we tested several aspects of its motor component through functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS). Both experimental studies resulted in coherent outcomes with respect to the SMILE predictions, but they also provided novel scientific outcomes about such broad topics as the sub-phases of motor imagery, the neural processing of bodily representations, or the extend of the role of the extrastriate body area. In the final sections of this manuscript, we describe some potential clinical application of the SMILE. The first one presents the identification of plausible neuroanatomical origins for focal hand dystonia, a yet poorly understood sensorimotor disorder. The last chapter then covers possible improvements on brain-machine interfaces, driven by a better understanding of the sensorimotor system. -- La façon dont votre sens du toucher et vos mouvements interagissent est connue sous le nom d’intĂ©gration sensorimotrice. Ce procĂ©dĂ© est essentiel pour une interaction normale avec tout ce qui nous entoure. Cependant, plusieurs aspects de ce processus sont encore mĂ©connus. Plus important encore, l’origine de certaines dĂ©ficiences motrices encore trop peu comprises sont parfois considĂ©rĂ©es comme purement motrice, alors qu’une origine sensorielle pourrait mener Ă  un mĂȘme ensemble de symptĂŽmes. Afin d’amĂ©liorer cette situation, nous proposons ici un nouveau modĂšle d’intĂ©gration sensorimotrice, dĂ©nommĂ© « SMILE », basĂ© sur les connaissances de neurobiologie actuelles. Dans ce manuscrit, nous commençons par dĂ©crire les caractĂ©ristiques fonctionnelles et neuroanatomiques du SMILE. Plusieurs expĂ©riences sont ensuite effectuĂ©es, via l’imagerie par rĂ©sonance magnĂ©tique fonctionnelle (IRMf), et la stimulation magnĂ©tique transcranienne (SMT), afin de tester diffĂ©rents aspects de la composante motrice du SMILE. Si les rĂ©sultats de ces expĂ©riences corroborent les prĂ©dictions du SMILE, elles ont aussi mis en Ă©vidences d’autres rĂ©sultats scientifiques intĂ©ressants et novateurs, dans des domaines aussi divers que les sous-phases de l’imagination motrice, les processus cĂ©rĂ©braux liĂ©s aux reprĂ©sentations corporelles, ou encore l’extension du rĂŽle de l’extrastriate body area. Dans les derniĂšres parties de ce manuscrit, nous dĂ©voilons quelques applications cliniques potentielles de notre modĂšle. Nous utilisons le SMILE afin de proposer deux origines cĂ©rĂ©brales plausibles de la dystonie focale de la main. Le dernier chapitre prĂ©sente comment certaines technologies existantes, telles que les interfaces cerveaux-machines, pourraient bĂ©nĂ©ficier d’une meilleure comprĂ©hension du systĂšme sensorimoteur

    Mapping Sensorimotor Function and Controlling Upper Limb Neuroprosthetics with Electrocorticography

    Get PDF
    Electrocorticography (ECoG) occupies a unique intermediate niche between microelectrode recordings of single neurons and recordings of whole brain activity via functional magnetic resonance imaging (fMRI). ECoG’s combination of high temporal resolution and wide area coverage make it an ideal modality for both functional brain mapping and brain-machine interface (BMI) for control of prosthetic devices. This thesis demonstrates the utility of ECoG, particularly in high gamma frequencies (70-120 Hz), for passive online mapping of language and motor behaviors, online control of reaching and grasping of an advanced robotic upper limb, and mapping somatosensory digit representations in the postcentral gyrus. The dissertation begins with a brief discussion of the framework for neuroprosthetic control developed by the collaboration between Johns Hopkins and JHU Applied Physics Laboratory (JHU/APL). Second, the methodology behind an online spatial-temporal functional mapping (STFM) system is described. Trial-averaged spatiotemporal maps of high gamma activity were computed during a visual naming and a word reading task. The system output is subsequently shown and compared to stimulation mapping. Third, simultaneous and independent ECoG-based control of reaching and grasping is demonstrated with the Modular Prosthetic Limb (MPL). The STFM system was used to identify channels whose high gamma power significantly and selectively increases during either reaching or grasping. Using this technique, two patients were able to rapidly achieve naturalistic control over simple movements by the MPL. Next, high-density ECoG (hdECoG) was used to map the cortical responses to mechanical vibration of the fingertips. High gamma responses exhibited a strong yet overlapping somatotopy that was not well replicated in other frequency bands. These responses are strong enough to be detected in single trials and used to classify the finger being stimulated with over 98% accuracy. Finally, the role of ECoG is discussed for functional mapping and BMI applications. ECoG occupies a unique role among neural recording modalities as a tool for functional mapping, but must prove its value relative to stimulation mapping. For BMI, ECoG lags microelectrode arrays but hdECoG may provide a more robust long-term interface with optimal spacing for sampling relevant cortical representations

    Human Ipsilateral Motor Physiology and Neuroprosthetic Applications in Chronic Stroke

    Get PDF
    Improving the recovery of lost motor function in hemiplegic chronic stroke survivors is a critical need to improve the lives of these patients. Over the last several decades, neuroprosthetic systems have emerged as novel tools with the potential to restore function in a variety of patient populations. While traditional neuroprosthetics have focused on using neural activity contralateral to a moving limb for device control, an alternative control signal may be necessary to develop brain-computer interface (BCI) systems in stroke survivors that suffer damage to the cortical hemisphere contralateral to the affected limb. While movement-related neural activity also occurs in the hemisphere ipsilateral to a moving limb, it is uncertain if these signals can be used within BCI systems. This dissertation examines the motor activity ipsilateral to a moving limb and the potential use of these signals for neuroprosthetic applications in chronic stroke survivors. Patients performed three-dimensional (3D) reaching movements with the arm ipsilateral to an electrocorticography (ECoG) array in order to assess the extent of kinematic information that can be decoded from the cortex ipsilateral to a moving limb. Additionally, patients performed the same task with the arm contralateral to the same ECoG arrays, allowing us to compare the neural representations of contralateral and ipsilateral limb movements. While spectral power changes related to ipsilateral arm movements begin later and are lower in amplitude than power changes related to contralateral arm movements, 3D kinematics from both contralateral and ipsilateral arm trajectories can be decoded with similar accuracies. The ability to decode movement kinematics from the ipsilateral cortical hemisphere demonstrates the potential to use these signals within BCI applications for controlling multiple degrees of freedom. Next we examined the relationship between electrode invasiveness and signal quality. The ability to decode movement kinematics from neural activity was significantly decreased in simulated electroencephalography (EEG) signals relative to ECoG signals, indicating that invasive signals would be necessary to implement BCI systems with multiple degrees of freedom. For ECoG signals, the human dura also causes a significant decrease in signal quality when electrodes with small spatial sizes are used. This tradeoff between signal quality and electrode invasiveness should therefore be taken into account when designing ECoG BCI systems. Finally, chronic stroke survivors used activity associated with affected hand motor intentions, recorded from their unaffected hemisphere using EEG, to control simple BCI systems. This demonstrates that motor signals from the ipsilateral hemisphere are viable for BCI applications, not only in motor-intact patients, but also in chronic stroke survivors. Taken together, these experiments provide initial demonstrations that it is possible to develop BCI systems using the unaffected hemisphere in stroke survivors with multiple degrees of freedom. Further development of these BCI systems may eventually lead to improving function for a significant population of patients

    Evaluation and Advancement of Electrocorticographic Brain-Machine Interfaces for Individuals with Upper-Limb Paralysis

    Get PDF
    Brain-machine interface (BMI) technology aims to provide individuals with movement paralysis a natural and intuitive means for the restoration of function. Electrocorticography (ECoG), in which disc electrodes are placed on either the surface of the dura or the cortex to record field potential activity, has been proposed as a viable neural recording modality for BMI systems, potentially providing stable, long-term recordings of cortical activity with high spatial and temporal resolution. Previous demonstrations of BMI control using ECoG have consisted of short-term periods of control by able-bodied subjects utilizing basic processing and decoding techniques. This dissertation presents work seeking to advance the current state of ECoG BMIs through an assessment of the ability of individuals with movement paralysis to control an ECoG BMI, an investigation into adaptation during BMI skill acquisition, an evaluation of chronic implantation of an ECoG electrode grid, and improved extraction of BMI command signals from ECoG recordings. Two individuals with upper-limb paralysis were implanted with high-density ECoG electrode grids over sensorimotor cortical areas for up to 30 days, with both subjects found to be capable of voluntarily modulating their cortical activity to control movement of a computer cursor with up to three degrees of freedom. Analysis of control signal angular error and the tuning characteristics of ECoG spectral features during the acquisition of brain control revealed that both decoder calibration and fixed-decoder training could facilitate performance improvements. In addition, to better understand the capability of ECoG to provide robust, long-term recordings, work was conducted assessing the effects of chronic implantation of an ECoG electrode grid in a non-human primate, demonstrating that movement-related modulation could be recorded from electrode nearly two years post-implantation despite the presence of substantial fibrotic encapsulation. Finally, it was found that the extraction of command signals from ECoG recordings could be improved through the use of a decoding method incorporating weight-space priors accounting for the expected correlation structure of electrical field potentials. Combined, this work both demonstrates the feasibility of ECoG-based BMI systems as well as addresses some of key challenges that must be overcome before such systems are translated to the clinical realm

    ECoG correlates of visuomotor transformation, neural plasticity, and application to a force-based brain computer interface

    Get PDF
    Electrocorticography: ECoG) has gained increased notoriety over the past decade as a possible recording modality for Brain-Computer Interface: BCI) applications that offers a balance of minimal invasiveness to the patient in addition to robust spectral information over time. More recently, the scale of ECoG devices has begun to shrink to the order of micrometer diameter contacts and millimeter spacings with the intent of extracting more independent signals for BCI control within less cortical real-estate. However, most control signals to date, whether within the field of ECoG or any of the more seasoned recording techniques, have translated their control signals to kinematic control parameters: i.e. position or velocity of an object) which may not be practical for certain BCI applications such as functional neuromuscular stimulation: FNS). Thus, the purpose of this dissertation was to present a novel application of ECoG signals to a force-based control algorithm and address its feasibility for such a BCI system. Micro-ECoG arrays constructed from thin-film polyimide were implanted epidurally over areas spanning premotor, primary motor, and parietal cortical areas of two monkeys: three hemispheres, three arrays). Monkeys first learned to perform a classic center-out task using a brain signal-to-velocity mapping for control of a computer cursor. The BCI algorithm utilized day-to-day adaptation of the decoding model to match the task intention of the monkeys with no need for pre-screeening of movement-related ECoG signals. Using this strategy, subjects showed notable 2-D task profiency and increased task-related modulation of ECoG features within five training sessions. After fixing the last model trained for velocity control of the cursor, the monkeys then utilized this decoding model to control the acceleration of the cursor in the same center-out task. Cursor movement profiles under this mapping paralleled those demonstrated using velocity control, and neural control signal profiles revealed the monkeys actively accelerated and decelerated the cursor within a limited time window: 1-1.5 seconds). The fixed BCI decoding model was recast once again to control the force on a virtual cursor in a novel mass-grab task. This task required targets not only to reach to peripheral targets but also account for an additional virtual mass as they grabbed each target and moved it to a second target location in the presence of the external force of gravity. Examination of the ensemble control signals showed neural adaptation to variations in the perceived mass of the target as well as the presence or absence of gravity. Finally, short rest periods were interleaved within blocks of each task type to elucidate differences between active BCI intention and rest. Using a post-hoc state-decoder model, periods of active BCI task control could be distinguished from periods of rest with a very high degree of accuracy: ~99%). Taken together, the results from these experiments present a first step toward the design of a dynamics-based BCI system suitable for FNS applications as well as a framework for implementation of an asyncrhonous ECoG BCI
    • 

    corecore