131 results about "Cerebral activity" patented technology

Methods for determining whether the brain activity of a human subject in response to a stimulus of interest or question of interest is characteristic of a state of interest, such as a deceptive state or a truthful state, are disclosed. Some methods include the use of control questions, including truthful control questions and deceptive control questions, to provide bases for comparison for responses to stimuli of interest or questions of interest. In some methods, brain maps are generated and compared. Also disclosed are systems for detecting deception by measuring brain activity.

Decoding and reconstructing a subjective perceptual or cognitive experience is described. A first set of brain activity data produced in response to a first brain activity stimulus is acquired from a subject using a brain imaging device and converted into a corresponding set of predicted response values. A second set of brain activity data produced in response to a second brain activity stimulus is acquired from a the subject and decoded using a decoding distribution and the probability the second set of brain activity data corresponds to said predicted response values is determined. The second set of brain activity stimuli is then reconstructed based on the probability of correspondence between the second set of brain activity data and the predicted response values.

Methods for determining whether the brain activity of a human subject in response to a stimulus of interest or question of interest is characteristic of a state of interest, such as a deceptive state or a truthful state, are disclosed. Some methods include the use of control questions, including truthful control questions and deceptive control questions, to provide bases for comparison for responses to stimuli of interest or questions of interest. Some methods include the use of differences between two states, such as a deceptive state and a truthful state. In some methods, brain maps are generated and compared. Also disclosed are systems for detecting deception by measuring brain activity.

A mental state awareness system comprises a non-invasive brain interface assembly configured for detecting brain activity of a user, a processor configured for determining a mental state of a user based on the detected brain activity, and a biofeedback device configured for automatically providing biofeedback to the user indicative of the determined mental state of the user.

Subdural arrays transmit electrocorticogram recordings wirelessly, across the patient's skull, allowing the craniotomy used for surgical placement of the arrays to be completely closed. In various embodiments, the arrays also respond to commands, applying signal patterns to the patient's brain for diagnostic and treatment purposes.

The invention provides a method of estimating cerebral sources of electrical activity from a small subset of EEG channels utilizing existing methods to provide a 3-dimensional, discrete, distributed, linear solution to the inverse problem using inputs consisting of a small number of EEG channels (e.g., 4 channels) augmented with synthetic EEG data for the other channels. The resultant image of cerebral electrical activity in the region of the EEG channels from which data is recorded is of comparable spatial resolution in the corresponding region to images of cerebral electrical activity obtained using a complete set of EEG channels (e.g., using 24 channels).

The present invention differentiates objective disease labels for depression symptoms relative to brain activity states. As one means to address the problem to be addressed thereby, the present invention provides a differentiation device that is for helping to determine whether a subject has depression symptoms. The differentiation device comprises a storage device that is for storing informationthat specifies a classifier that has been generated by classifier generation processing from signals obtained by using a brain activity detection device to chronologically premeasure signals that indicate brain activity in a plurality of prescribed regions of the resting brains of each of a plurality of participants that include healthy and depressive patients. The classifier: is generated on thebasis of a weighted sum of a plurality of functional connectivities that, from among functional connectivities between the plurality of prescribed regions, have, by means of machine learning, been selected by feature selection as being related to disease labels for depression symptoms; and is generated to differentiate the disease labels for depression symptoms. The differentiation device also comprises a computing device. Using the classifier, the computing device executes differentiation processing that generates classification results for the depression symptoms of the subject.