An apparatus for providing information about a user's brain resources is provided. The apparatus includes at least sensor interface circuitry and processing circuitry coupled to the sensor interface circuitry. In a calibration mode, the sensor interface circuitry is configured to receive first sensor data from an electroencephalography sensor. The first sensor data are indicative of an electroencephalogram of the user. Further, the sensor interface circuitry is configured to receive second sensor data from a physiological sensor in the calibration mode. The second sensor data are indicative of a physiological property of the user. In the calibration mode, the processing circuitry is configured to train a brain-physiological model for the user based on the first sensor data and the second sensor data.

Systems and methods of the present disclosure are directed to neural stimulation via non-invasive sensory stimuli. The non-invasive sensory stimuli can reduce neuroinflammation, improving synaptic plasticity and stimulating neural networking, and improving microglial-mediated clearance of cerebral insults, which would otherwise contribute to the progression of brain atrophy, by inducing synchronized gamma oscillations in at least one region of a brain in a subject. Stimulations can adjust, control or otherwise manage the frequency of the neural oscillations to provide beneficial effects to one or more cognitive states or cognitive functions of the brain, while mitigating or preventing adverse consequences on a cognitive state or cognitive function that stem from progression of brain atrophy.

A system and method comprising several hardware and software components that work together to achieve the goal of performance prediction. The hardware components include neuroimaging collection hardware and a computing system. The neuroimaging hardware obtains the brain signals and sends this first set of data to a computational resource for further analysis. A second sent of data is the task performance scores of the participants. This second set is also set to the computational resource. The inventive system can predict a learning rate of target tasks for an individual from just a few minutes of off-task, resting-state neuroimaging data.

A system and method comprising several hardware and software components that work together to achieve the goal of performance prediction. The hardware components include neuroimaging collection hardware and a computing system. The neuroimaging hardware obtains the brain signals and sends this first set of data to a computational resource for further analysis. A second sent of data is the task performance scores of the participants. This second set is also set to the computational resource. The inventive system can predict a learning rate of target tasks for an individual from just a few minutes of off-task, resting-state neuroimaging data.

Provided is a system for estimating a subjective evaluation by an estimation subject. This system for estimating a subjective evaluation by an estimation subject comprises: a reception means that receives feature data of a biosignal acquired from the estimation subject; a storage means that stores a plurality of feature templates extracted from a plurality of biosignals acquired from a plurality of subjects to be modeled including a first subject to be modeled and a second subject to be modeled, or that stores a plurality of models trained using said feature templates; and an estimation means that estimates a subjective evaluation by the estimation subject on the basis of the feature data and the plurality of feature templates or the plurality of models.

The present disclosure relates to establishing bidirectional communication between a brain wave processing device and a vehicle to control at least one vehicle component of the vehicle. For this purpose, a brain-computer communication channel is provided between the brain wave processing device and the respective vehicle component. Subsequently, a control signal is determined as a function of a brain wave of the operator of the brain wave processing device and transmitted via the brain-computer communication channel to adapt at least one operating parameter of the respective vehicle component. This causes a change in the operating state of the respective vehicle component. Depending on this, an output signal is generated and is assigned to the change in the operating state of the vehicle component. This output signal is transmitted back to the brain wave processing device via the brain-computer communication channel and is output to the operator by means of an output unit of the brain wave processing device.

Described herein are systems and methods for the detection and monitoring of delirium in a subject. Other neurological conditions may also be detected and monitored. The systems may include a data module configured to obtain a plurality of electroencephalography (EEG) signals collected from a subject. The systems may also include a processing module in communication with the data module. The processing module may be configured to process the data to detect and monitor delirium and/or one or more other neurological conditions that the subject is experiencing or likely to experience. The processing module may also generate indications or assessments for delirium and/or for each neurological condition at an individual level, or optionally, between two or more related neurological conditions.

Described herein are systems and methods for the detection and monitoring of delirium in a subject. Other neurological conditions may also be detected and monitored. The systems may include a data module configured to obtain a plurality of electroencephalography (EEG) signals collected from a subject. The systems may also include a processing module in communication with the data module. The processing module may be configured to process the data to detect and monitor delirium and/or one or more other neurological conditions that the subject is experiencing or likely to experience. The processing module may also generate indications or assessments for delirium and/or for each neurological condition at an individual level, or optionally, between two or more related neurological conditions.

A method and system for generating an optimal audio stimulus for achieving a target brain state value for a brain state. The method and system can be used to generate one or more brain state models which can decode brain activity signals to predict brain state values. The brain state models can be applied to brain activity signals captured while users are performing tasks with an audio stimulus. Audio features of the audio stimulus can be extracted. An audio-brain model can be trained on the predicted brain state values and the audio features. From the trained audio-brain model, the optimal audio stimulus can be generated.

A method and system for generating an optimal audio stimulus for achieving a target brain state value for a brain state. The method and system can be used to generate one or more brain state models which can decode brain activity signals to predict brain state values. The brain state models can be applied to brain activity signals captured while users are performing tasks with an audio stimulus. Audio features of the audio stimulus can be extracted. An audio-brain model can be trained on the predicted brain state values and the audio features. From the trained audio-brain model, the optimal audio stimulus can be generated.