Mapping Sensorimotor Function and Controlling Upper Limb Neuroprosthetics with Electrocorticography

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

Nonuniform Power Changes and Spatial, Temporal and Spectral Diversity in High Gamma Band (\u3e60 Hz) Signals in Human Electrocorticography

High-gamma band: \u3e60Hz) power changes in cortical electrophysiology are a reliable indicator of focal, event-related cortical activity. In spite of discoveries of oscillatory subthreshold and synchronous suprathreshold activity at the cellular level, there is an increasingly popular view that high-gamma band amplitude changes recorded from cellular ensembles are the result of asynchronous firing activity that yields wideband and uniform power increases. Others have demonstrated independence of power changes in the low- and high-gamma bands, but to date, no studies have shown evidence of any such independence above 60Hz. Based on non-uniformities in time-frequency analyses of electrocorticographic: ECoG) signals, we hypothesized that induced high-gamma band: 60-500Hz) power changes are more heterogeneous than currently understood. We quantified this spectral non-uniformity with two different approaches using single-word repetition tasks in human subjects. First, we showed that the functional responsiveness of different ECoG high-gamma sub-bands can discriminate cognitive tasks: e.g., hearing, reading, speaking) and cortical locations. Power changes in these sub-bands of the high-gamma range are consistently present within single trials and have statistically different time courses within the trial structure. Moreover, when consolidated across all subjects within three task-relevant anatomic regions: sensorimotor, Broca\u27s area, and superior temporal gyrus), these behavior- and location- dependent power changes evidenced nonuniform trends across the population of subjects. Second, we studied the dynamics of multiple frequency bands in order to quantify the diversity present in the ECoG signals. Using a matched filter construct and receiver operating characteristic: ROC) analysis we show that power modulations correlated with phonemic content in spoken and heard words are represented diffusely in space, time and frequency. Correlating power modulation in multiple frequency bands above 60 Hz over broad cortical areas, with time varying envelopes significantly improved performed area under the ROC curve scores in phoneme prediction experiments. Finally we show preliminary evidence supporting our hypothesis in microarray ECoG data. Taken together, the nonuniformity of high frequency power changes and the information content captured in the spatio-temporal dynamics of those frequencies suggests that a new approach to evaluating high-gamma band cortical activity is necessary. These findings show that in addition to time and location, frequency is another fundamental dimension of high-gamma dynamics

Reading Your Own Mind: Dynamic Visualization of Real-Time Neural Signals

Brain Computer Interfaces: BCI) systems which allow humans to control external devices directly from brain activity, are becoming increasingly popular due to dramatic advances in the ability to both capture and interpret brain signals. Further advancing BCI systems is a compelling goal both because of the neurophysiology insights gained from deriving a control signal from brain activity and because of the potential for direct brain control of external devices in applications such as brain injury recovery, human prosthetics, and robotics. The dynamic and adaptive nature of the brain makes it difficult to create classifiers or control systems that will remain effective over time. However it is precisely these qualities that offer the potential to use feedback to build on simple features and create complex control features that are robust over time. This dissertation presents work that addresses these opportunities for the specific case of Electrocorticography: ECoG) recordings from clinical epilepsy patients. First, queued patient tasks were used to explore the predictive nature of both local and global features of the ECoG signal. Second, an algorithm was developed and tested for estimating the most informative features from naive observations of ECoG signal. Third, a software system was built and tested that facilitates real-time visualizations of ECoG signal patients and allows ECoG epilepsy patients to engage in an interactive BCI control feature screening process

The mirror illusion induces high gamma oscillations in the absence of movement

We tested whether mirror visual feedback (MVF) from a moving hand induced high gamma oscillation (HGO) response in the hemisphere contralateral to the mirror and ipsilateral to the self-paced movement. MEG was recorded in 14 subjects under three conditions: bilateral synchronous movements of both index fingers (BILATERAL), movements of the right hand index finger while observing the immobile left index finger (NOMIRROR), and movements of the right hand index finger while observing its mirror reflection (MIRROR). The right hemispheric spatiospectral regions of interests (ROIs) in the sensor space, sensitive to bilateral movements, were found by statistical comparison of the BILATERAL spectral responses to baseline. For these ROIs, the post-movement HGO responses were compared between the MIRROR and NOMIRROR conditions. We found that MVF from the moving hand, similarly to the real movements of the opposite hand, induced HGO (55–85 Hz) in the sensorimotor cortex. This MVF effect was frequency-specific and did not spread to oscillations in other frequency bands. This is the first study demonstrating movement-related HGO induced by MVF from the moving hand in the absence of proprioceptive feedback signaling. Our findings support the hypothesis that MVF can trigger the feedback-based control processes specifically associated with perception of one's own movements

Neural synchrony within the motor system: what have we learned so far?

Synchronization of neural activity is considered essential for information processing in the nervous system. Both local and inter-regional synchronization are omnipresent in different frequency regimes and relate to a variety of behavioral and cognitive functions. Over the years, many studies have sought to elucidate the question how alpha/mu, beta, and gamma synchronization contribute to motor control. Here, we review these studies with the purpose to delineate what they have added to our understanding of the neural control of movement. We highlight important findings regarding oscillations in primary motor cortex, synchronization between cortex and spinal cord, synchronization between cortical regions, as well as abnormal synchronization patterns in a selection of motor dysfunctions. The interpretation of synchronization patterns benefits from combining results of invasive and non-invasive recordings, different data analysis tools, and modeling work. Importantly, although synchronization is deemed to play a vital role, it is not the only mechanism for neural communication. Spike timing and rate coding act together during motor control and should therefore both be accounted for when interpreting movement-related activity

Gamma oscillatory amplitude encodes stimulus intensity in primary somatosensory cortex

Gamma oscillations have previously been linked to pain perception and it has been hypothesised that they may have a potential role in encoding pain intensity. Stimulus response experiments have reported an increase in activity in the primary somatosensory cortex (SI) with increasing stimulus intensity, but the specific role of oscillatory dynamics in this change in activation remains unclear. In this study, Magnetoencephalography (MEG) was used to investigate the changes in cortical oscillations during 4 different intensities of a train of electrical stimuli to the right index finger, ranging from low sensation to strong pain. In those participants showing changes in evoked oscillatory gamma in SI during stimulation, the strength of the gamma power was found to increase with increasing stimulus intensity at both pain and sub-pain thresholds. These results suggest that evoked gamma oscillations in SI are not specific to pain but may have a role in encoding somatosensory stimulus intensity. © 2013 Rossiter, Worthen, Witton, Hall and Furlong

Beyond language: The unspoken sensory-motor representation of the tongue in non-primates, non-human and human primates

The English idiom “on the tip of my tongue” commonly acknowledges that something is known, but it cannot be immediately brought to mind. This phrase accurately describes sensorimotor functions of the tongue, which are fundamental for many tongue-related behaviors (e.g., speech), but often neglected by scientific research. Here, we review a wide range of studies conducted on non-primates, non-human and human primates with the aim of providing a comprehensive description of the cortical representation of the tongue's somatosensory inputs and motor outputs across different phylogenetic domains. First, we summarize how the properties of passive non-noxious mechanical stimuli are encoded in the putative somatosensory tongue area, which has a conserved location in the ventral portion of the somatosensory cortex across mammals. Second, we review how complex self-generated actions involving the tongue are represented in more anterior regions of the putative somato-motor tongue area. Finally, we describe multisensory response properties of the primate and non-primate tongue area by also defining how the cytoarchitecture of this area is affected by experience and deafferentation

Characterization of High-Gamma Activity in Electrocorticographic Signals

IntroductionElectrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information.MethodsTo address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA.ResultsThe high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks.DiscussionThis study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies

A Quest for Meaning in Spontaneous Brain Activity - From fMRI to Electrophysiology to Complexity Science

The brain is not a silent, complex input/output system waiting to be driven by external stimuli; instead, it is a closed, self-referential system operating on its own with sensory information modulating rather than determining its activity. Ongoing spontaneous brain activity costs the majority of the brain\u27s energy budget, maintains the brain\u27s functional architecture, and makes predictions about the environment and the future. I have completed three separate studies on the functional significance and the organization of spontaneous brain activity. The first study showed that strokes disrupt large-scale network coherence in the spontaneous functional magnetic resonance imaging: fMRI) signals, and that the degree of such disruption predicts the behavioral impairment of the patient. This study established the functional significance of coherent patterns in the spontaneous fMRI signals. In the second study, by combining fMRI and electrophysiology in neurosurgical patients, I identified the neurophysiological signal underlying the coherent patterns in the spontaneous fMRI signal, the slow cortical potential: SCP). The SCP is a novel neural correlate of the fMRI signal, most likely underlying both spontaneous fMRI signal fluctuations and task-evoked fMRI responses. Some theoretical considerations have led me to propose a hypothesis on the involvement of the neural activity indexed by the SCP in the emergence of consciousness. In the last study I investigated the temporal organization across a wide range of frequencies in the spontaneous electrical field potentials recorded from the human brain. This study demonstrated that the arrhythmic, scale-free brain activity often discarded in human and animal electrophysiology studies in fact contains rich, complex structures, and further provided evidence supporting the functional significance of such activity