Rapid motor learning and epidural stimulation in primate cortex

Understanding how the nervous system explores and then finds optimal solutions during the process of motor learning is fundamental for rational electrotherapy design. Plasticity in the motor cortex has been implicated in motor learning across a variety of tasks and model organisms. Translational approaches to modulating motor cortical activity have also demonstrated great potential for restoring or relearning motor tasks following brain injury. In this thesis, I begin in Chapter 1 by summarizing the modern understanding of the motor learning network, outlining how the primary motor cortex is uniquely positioned to regulate rapid adaptations to task demands. Then, I provide a historical perspective on brain stimulation methods used in humans for clinical and research applications, including the strengths and limitations and current approaches. In Chapter 2, I present a novel, translatable electrical brain stimulation technique – the ringtrode – which allows for the flexible and precise modulation of the primate cortex. In Chapter 3, I characterize the neural dynamics in motor cortex that underly rapid motor learning during brief breaks. Then, I apply the ringtrode to manipulate these dynamics and assess whether they are causal for motor learning. Finally, I present a model for how stimulation delivered via the ringtrode interacts with motor learning processes in the brain to explore why stimulation-induced effects on motor learning may depend on stimulation frequency

Medial Orbitofrontal Cortex, Dorsolateral Prefrontal Cortex, and Hippocampus Differentially Represent the Event Saliency

Two primary functions attributed to the hippocampus and prefrontal cortex (PFC) network are retaining the temporal and spatial associations of events and detecting deviant events. It is unclear, however, how these two functions converge into one mechanism. Here, we tested whether increased activity with perceiving salient events is a deviant detection signal or contains information about the event associations by reflecting the magnitude of deviance (i.e., event saliency). We also tested how the deviant detection signal is affected by the degree of anticipation. We studied regional neural activity when people watched a movie that had varying saliency of a novel or an anticipated flow of salient events. Using intracranial electroencephalography from 10 patients, we observed that high-frequency activity (50-150 Hz) in the hippocampus, dorsolateral PFC, and medial OFC tracked event saliency. We also observed that medial OFC activity was stronger when the salient events were anticipated than when they were novel. These results suggest that dorsolateral PFC and medial OFC, as well as the hippocampus, signify the saliency magnitude of events, reflecting the hierarchical structure of event associations

Spatial integration during active tactile sensation drives orientation perception

Active haptic sensation is critical for object identification, but its neural circuit basis is poorly understood. We combined optogenetics, two-photon imaging, and high-speed behavioral tracking in mice solving a whisker-based object orientation discrimination task. We found that orientation discrimination required animals to summate input from multiple whiskers specifically along the whisker arc. Animals discriminated the orientation of the stimulus per se as their performance was invariant to the location of the presented stimulus. Populations of barrel cortex neurons summated across whiskers to encode each orientation. Finally, acute optogenetic inactivation of the barrel cortex and cell-type-specific optogenetic suppression of layer 4 excitatory neurons degraded performance, implying that infragranular layers alone are not sufficient to solve the task. These data suggest that spatial summation over an active haptic array generates representations of an object's orientation, which may facilitate encoding of complex three-dimensional objects during active exploration

Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes

Recent advances in dry electrodes technology have facilitated the recording of EEG in situations not previously possible, thanks to the relatively swift electrode preparation and avoidance of applying gel to subject's hair. However, to become a true alternative, these systems should be compared to state-of-the-art wet EEG systems commonly used in clinical or research applications. In our study, we conducted a systematic comparison of electrodes application speed, subject comfort, and most critically electrophysiological signal quality between the conventional and wired Biosemi EEG system using wet active electrodes and the compact and wireless F1 EEG system consisting of dry passive electrodes. All subjects (n = 27) participated in two recording sessions on separate days, one with the wet EEG system and one with the dry EEG system, in which the session order was counterbalanced across subjects. In each session, we recorded their EEG during separate rest periods with eyes open and closed followed by two versions of a serial visual presentation target detection task. Each task component allows for a neural measure reflecting different characteristics of the data, including spectral power in canonical low frequency bands, event-related potential components (specifically, the P3b), and single trial classification based on machine learning. The performance across the two systems was similar in most measures, including the P3b amplitude and topography, as well as low frequency (theta, alpha, and beta) spectral power at rest. Both EEG systems performed well above chance in the classification analysis, with a marginal advantage of the wet system over the dry. Critically, all aforementioned electrophysiological metrics showed significant positive correlations (r = 0.54-0.89) between the two EEG systems. This multitude of measures provides a comprehensive comparison that captures different aspects of EEG data, including temporal precision, frequency domain as well as multivariate patterns of activity. Taken together, our results indicate that the dry EEG system used in this experiment can effectively record electrophysiological measures commonly used across the research and clinical contexts with comparable quality to the conventional wet EEG system

Integrated analysis of anatomical and electrophysiological human intracranial data

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