Systems, methods, and devices for brain stimulation and monitoring
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Publication Number
US-10898706-B2
Publication Date
2021-01-26
Expiration Date
Abstract
Provided are systems, methods, and devices for brain stimulation and monitoring. Brain stimulation may be provided to enhance slow wave and spindle synchrony. Such stimulation may provide increased memory consolidation. Furthermore, brain stimulation modalities may provide enhanced sleep and awakening. For example, transcranial direct current stimulation of the brain stimulation may enhance sleep quality. Moreover, one or more markers characterizing unconsciousness are may be identified based on changes in measured power densities or spectra. Further still, the above described modalities of brain stimulation may be implemented in an open-loop or closed loop manner. Brain state parameters may be generated for building models of the brain based on determined synchrony patterns between slow waves and spindles. The models may be used to determine a mediation procedure for adjusting the intensity of slow wave oscillations to enhance slow wave and spindle synchrony.
Core Innovation
The invention measures slow wave oscillations and sleep spindles from a brain of a user via an interface. It generates a plurality of brain state parameters characterizing one or more features of at least one brain state, including an assessment of a temporal directionality of interactions between slow wave oscillations and sleep spindles and an amount of temporal deviation between slow wave oscillation peaks and sleep spindle peaks.
A machine learning model of the brain of the user is generated based, at least in part, on the plurality of measurements and the synchrony pattern. Using the machine learning model together with training data comprising one or more mediation data points, the invention determines a procedure for mediation specifying at least an amplitude or a duration of stimuli to be applied to the brain to adjust a power of slow wave oscillations.
The interface generates one or more stimuli based on the control signals, and the one or more stimuli are applied to cortical tissue of the brain. The stimuli are configured to enhance synchrony of slow wave oscillations and sleep spindles such that sleep spindle peaks occur closer to slow wave oscillation peaks. Dependent embodiments further include subsequent brain measurements after applying stimuli to update a mediation procedure and adjust a machine learning model using changes in brain state parameters, and may specify the brain state as an unconscious state corresponding to non-rapid-eye-movement sleep.
Claims Coverage
The partial content includes three independent claims (method, system, and non-transitory computer readable medium). Across these independent claims, the inventive core comprises measuring slow wave oscillations and sleep spindles, computing synchrony pattern parameters including temporal directionality and temporal deviation, training a machine learning model with mediation data points to determine a mediation procedure for stimulus parameters to adjust slow wave power, and generating control signals to apply cortical stimuli that enhance SO–spindle synchrony so that spindle peaks occur closer to slow wave peaks.
Measuring synchrony pattern with temporal directionality and peak deviation
Obtaining a plurality of measurements from a brain of a user via an interface, where the plurality of measurements includes indications of slow wave oscillations and sleep spindles, and generating brain state parameters characterizing features including an assessment of temporal directionality of interactions between the measured slow wave oscillations and sleep spindles and an amount of temporal deviation between slow wave oscillation peaks and sleep spindle peaks.
Machine learning model for determining a mediation procedure from mediation data points
Generating a machine learning model of the brain of the user based, at least in part, on the plurality of measurements and the synchrony pattern, and determining, using the machine learning model and training data comprising one or more mediation data points, a procedure for mediation specifying at least an amplitude or a duration of stimuli to be applied to the brain to adjust a power of slow wave oscillations.
Controller-generated control signals to drive cortical stimuli that enhance synchrony
Generating one or more control signals, via a controller, based on the procedure for mediation, transmitting the one or more control signals to the interface, and generating via the interface one or more stimuli based on the one or more control signals, where the stimuli are applied to cortical tissue of the brain and configured to enhance synchrony of slow wave oscillations and sleep spindles such that sleep spindle peaks occur closer to slow wave oscillation peaks.
Together, the independent claims cover a closed-loop style architecture (method/system/medium) that measures slow wave oscillations and sleep spindles, computes synchrony pattern brain state parameters including temporal directionality and temporal deviation, trains a machine learning model with mediation data points to determine a mediation procedure for stimulus amplitude or duration to adjust slow wave power, and applies cortical stimuli driven by control signals to enhance SO–spindle synchrony so spindle peaks occur closer to slow wave peaks.
Stated Advantages
Enhances synchrony of slow wave oscillations and sleep spindles such that sleep spindle peaks occur closer to slow wave oscillation peaks.
Documented Applications
Enhancing synchrony of slow wave oscillations and sleep spindles in a non-rapid-eye-movement (NREM) unconscious state.
Improving sleep and related memory consolidation outcomes by enhancing slow wave–sleep spindle timing during sleep.
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