Modulating Low-Frequency Cortical Population Dynamics to Augment Motor Function After Stroke

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PROJECT SUMMARY Stroke is the leading cause of motor disability in the United States, with approximately 700,000 new cases per year. Impaired hand and finger control are a leading cause of such disability. Despite advances in task- specific training for the upper limb, a large number of stroke patients do not regain full function of their hand; novel treatment methods are urgently required. We propose to use a systems neuroscience and `neural engineering' framework that captures the dynamic interactions between neurons and the distributed motor network to both characterize and develop novel neurophysiological based neuromodulation approaches to enhance motor function. Studies in healthy animals support a framework for dynamic interactions between local and distant areas through transient oscillations. Oscillations are defined by a frequency bandwidth, e.g. motor areas are known to have task-related low-frequency oscillations (0.5-4 Hz). How the recovery process affects neural activity and oscillatory dynamics in primates preforming dexterous tasks remains unknown? Our recent studies in rats (Ramanathan et al., Nature Medicine 2018; Lemke et al., Nature Neuroscience, 2019) demonstrated that population dynamics linked to low-frequency oscillatory activity (0.5-4Hz “LFO”) are essential for movement control, track spontaneous recovery and can serve as a target for modulation using electrical stimulation. More specifically, cortical stimulation was found to both boost LFO power and augment motor function. Essential translational steps involve testing whether this approach also works for gyrated brains during the performance of dexterous tasks. This proposal aims to use in vivo electrophysiological methods to model the network dynamics of recovery. The underlying hypothesis is that synchronous LFO spike-field interactions in the perilesional cortex are important for recovery and its modulation can augment dexterous motor function. Importantly, our preliminary data provides strong support for our proposed research goals; we have found that low-frequency oscillatory dynamics drive coordination of sensory and motor areas during recovery and that artificial low-frequency electrical stimulation can boost dexterous function during recovery. Completion of these aims will provide critical information for designing therapeutic approaches that specifically target perilesional oscillatory activity with low frequency electrical stimulation. Focusing on targeted neuromodulation of such dynamic network interactions represents a new direction that could transform our ability to augment upper extremity function following stroke.