A system and method is provided for imaging and monitoring a tissue, such as a cerebral cortex, of a subject. Access to imaging a tissue, such as cerebral cortex, may be provided by removing a portion of a bone, such as a portion of a skull of the subject. A prosthesis, such as an optically transparent prosthesis, may be used to replace the portion of the skull removed and may be conformed to the same 3D contour of the bone that was removed. A data acquisition system, such as an imaging system, may then be affixed to the skull prosthesis and may be used to acquire image data of the tissue of the subject at high spatial and temporal resolution and without interference from intervening bone material.

A system performs concurrent detection and early detection of epileptic seizure episodes, based on scalp electroencephalogram (EEG) of a patient collected through a data acquisition device in the course of the patient's normal daily activities. An early detection model, which is trained and retrained applying machine learning techniques at predetermined intervals on the collected data, enables issuing of an early warning of an upcoming seizure episode to allow the patient to take necessary preparatory actions (e.g., seeking a safe location for the episode to happen and alerting care-givers).

A method includes obtaining a first imaging scan and a second imaging scan of a single subject brain. The first imaging scan is converted to a first dataset, and the second imaging scan is converted to a second dataset. A sequence-adaptive multimodal segmentation algorithm is applied to the first dataset and the second dataset. The sequence-adaptive multimodal segmentation algorithm performs automatic intensity-based tissue classification to generate a first labelled dataset and a second labeled dataset. The first labeled dataset and the second labeled dataset are automatically co-registered to each other to generate a transformation matrix based on the first labeled dataset and the second labeled dataset. The transformation matrix is applied to align the first dataset and the second dataset.

A brain-machine interface system configured to decode neural signals to control a target device includes a sensor to sample the neural signals, and a computer-readable storage medium having software instructions, which, when executed by a processor, cause the processor to transform the neural signals into a common representational space stored in the system, provide the common representational space as a state representation to inform an Actor recurrent neural network policy of the system, generate and evaluate, utilizing a deep recurrent neural network of the system having a generative sequence decoder, predictive sequences of control signals, supply a control signal to the target device to achieve an output of the target device, determine an intrinsic biometric-based reward signal, from the common representational space, based on an expectation of the output of the target device, and supply the intrinsic biometric-based reward signal to a Critic model of the system.

The present disclosure provides a system for analyzing electrical activities of at least one brain. The system comprises a visual output module for rendering a visual output space according to analyzed data sets generated by an analysis module, and displaying a visual output. The visual output comprises a first axis representing FM, a second axis representing AM, and a plurality of visual elements defined by the first axis and the second axis. Each of the visual elements comprises an accumulated signal strength and the analyzed data sets. Each of the analyzed data sets comprises a plurality of analyzed data units collected over a time period.

The present disclosure provides a system for analyzing electrical activities of at least one brain. The system comprises a visual output module for rendering a visual output space according to analyzed data sets generated by an analysis module, and displaying a visual output. The visual output comprises a first axis representing FM, a second axis representing AM, and a plurality of visual elements defined by the first axis and the second axis. Each of the visual elements comprises an accumulated signal strength and the analyzed data sets. Each of the analyzed data sets comprises a plurality of analyzed data units collected over a time period.

A system and method for determining a vector of action based on a psychological state and a contextual state of a user are provided. The system utilizes signals generated by biological processes to determine a user's psychological state and utilizes environmental conditions to determine a user's contextual state. The signals are detected by at least one user sensor within a wearable device, and the environmental conditions are detected by at least one context sensor of the system. The contextual state and psychological state are analyzed to create a vector of action for the user. A vector of action instructs the system to provide the user with an interface action based on the contextual state modified by the psychological state. Because the system continuously determines a user's psychological and contextual states, the system may continuously provide the user with interface actions relevant to the user's current emotional state and environment.

A system and method for determining a vector of action based on a psychological state and a contextual state of a user are provided. The system utilizes signals generated by biological processes to determine a user's psychological state and utilizes environmental conditions to determine a user's contextual state. The signals are detected by at least one user sensor within a wearable device, and the environmental conditions are detected by at least one context sensor of the system. The contextual state and psychological state are analyzed to create a vector of action for the user. A vector of action instructs the system to provide the user with an interface action based on the contextual state modified by the psychological state. Because the system continuously determines a user's psychological and contextual states, the system may continuously provide the user with interface actions relevant to the user's current emotional state and environment.

In accordance with some embodiments of the disclosed subject matter, mechanisms (which can, for example, include systems, methods, and media) for detecting an effortful mental state providing real-time deep brain stimulation to enhance performance of effortful mental tasks are provided. In some embodiments, system for detecting and facilitating effortful mental states is provided, the system comprising: monitoring sensors to capture neural activity from a subject's brain; an implanted stimulator to provide electrical stimulation to the subject's brain; a hardware processor programmed to: correlate activity in a first and second region of the subject brain during task performance; correlate activity in the first and second regions during task non performance; train a support vector machine (SVM) using the correlations as first and second class examples; and provide stimulation to augment brain function when the SVM indicates, based on activity in the first and second regions, the subject is in the mental state.

In accordance with some embodiments of the disclosed subject matter, mechanisms (which can, for example, include systems, methods, and media) for detecting an effortful mental state providing real-time deep brain stimulation to enhance performance of effortful mental tasks are provided. In some embodiments, system for detecting and facilitating effortful mental states is provided, the system comprising: monitoring sensors to capture neural activity from a subject's brain; an implanted stimulator to provide electrical stimulation to the subject's brain; a hardware processor programmed to: correlate activity in a first and second region of the subject brain during task performance; correlate activity in the first and second regions during task non performance; train a support vector machine (SVM) using the correlations as first and second class examples; and provide stimulation to augment brain function when the SVM indicates, based on activity in the first and second regions, the subject is in the mental state.