Abstract: A method of configuring a local brain stimulation tool is disclosed. The method comprises: obtaining a reference brain network activity (BNA) pattern, and a BNA pattern describing a neurophysiological state of the subject, each of the BNA patterns having a plurality of nodes and each node representing a brain location and at least one brain wave frequency. The method further comprises comparing the BNA patterns; and configuring the local brain stimulation tool to apply local brain stimulation at a frequency selected based on the comparison.

Abstract: A method of managing pain using neurophysiological data acquired from the brain of a subject is disclosed. The method comprises: identifying activity-related features in the data; parceling the data according to the activity-related features to define a plurality of capsules, each representing a spatiotemporal activity region in the brain; comparing at least some of the defined capsules to at least one reference capsule; and assessing the likelihood that the subject is experiencing pain responsively to the comparison.

Abstract: A method of managing pain using neurophysiological data acquired from the brain of a subject is disclosed. The method comprises: identifying activity-related features in the data; parceling the data according to the activity-related features to define a plurality of capsules, each representing a spatiotemporal activity region in the brain; comparing at least some of the defined capsules to at least one reference capsule; and assessing the likelihood that the subject is experiencing pain responsively to the comparison.

Abstract: Systems and method for classifying EEG signals of a human subject generated responsive to a series of images containing target images and non-target images. The EEG signals are in a spatio-temporal representation. The time points are classified independently, using a linear discriminant classifier, to compute spatio-temporal discriminating weights that are used to amplify the spatio-temporal representation, to create a spatially-weighted representation. Principal Component Analysis is used on a temporal domain for dimensionality reduction, separately for each spatial channel of the signals, to create a projection, which is applied to the spatially-weighted representation onto a first plurality of principal components, to create a temporally approximated spatially weighted representation.

Abstract: A method of analyzing neurophysiological data recorded from a subject is disclosed. The method comprises identifying activity-related features in the data, and parceling the data according to the activity-related features to define a plurality of capsules, each representing a spatiotemporal activity region in the brain. The method further comprises comparing at least some of the defined capsules to at least one reference capsule, and estimating a brain function of the subject based on the comparison.

Abstract: Systems and methods for identifying and analyzing neuropsychological flow patterns, include creating a knowledge base of neuropsychological flow patterns. The knowledge base is formed by obtaining signals from multiple research groups for particular behavioral processes, localizing sources of activity participating in the particular behavioral processes, identifying sets of patterns of brain activity for the behavioral processes and neuropsychologically analyzing the localized sources and the identified patterns for each of the research groups. The neuropsychological analysis includes identifying all possible pathways for the identified sets of patterns, ranking the possible pathways based on likelihood for the particular behavioral process and reducing the number of ranked possible pathways based on additional constraints. A system for comparison of obtained signals from an individual to the created knowledge base is provided.

Abstract: Systems and methods for identifying and analyzing neuropsychological flow patterns, include creating a knowledge base of neuropsychological flow patterns. The knowledge base is formed by obtaining signals from multiple research groups for particular behavioral processes, localizing sources of activity participating in the particular behavioral processes, identifying sets of patterns of brain activity for the behavioral processes and neuropsychologically analyzing the localized sources and the identified patterns for each of the research groups. The neuropsychological analysis includes identifying all possible pathways for the identified sets of patterns, ranking the possible pathways based on likelihood for the particular behavioral process and reducing the number of ranked possible pathways based on additional constraints. A system for comparison of obtained signals from an individual to the created knowledge base is provided.

Abstract: A method for functional analysis of neurophysiological data by decomposing neurophysiological data and EEG signal to form a plurality of signal features. The signal features may then optionally be analyzed to determined one or more patterns.

Abstract: Systems and methods for constructing a neural model, wherein the system and method comprises analyzing neuropsychological data to obtain the model and modeling functional plasticity.

Abstract: A method of estimating the likelihood of brain concussion from neurophysiological data acquired from the brain of the subject is disclosed. The method comprises: identifying activity-related features in the data; constructing a subject-specific brain network activity (BNA) pattern having a plurality of nodes, wherein each node represents a feature of the activity-related features, and each pair of nodes is assigned with a connectivity weight; calculating a BNA pattern similarity describing a comparison between the constructed BNA pattern and a baseline BNA pattern being specific to the subject; and assessing the likelihood of brain concussion responsively to the BNA pattern similarity.

Abstract: A method for functional analysis of neurophysiological data by decomposing neurophysiological data and EEG signal to form a plurality of signal features. The signal features may then optionally be analyzed to determined one or more patterns.

Abstract: Systems and methods for identifying and analyzing neuropsychological flow patterns, include creating a knowledge base of neuropsychological flow patterns. The knowledge base is formed by obtaining signals from multiple research groups for particular behavioral processes, localizing sources of activity participating in the particular behavioral processes, identifying sets of patterns of brain activity for the behavioral processes and neuropsychologically analyzing the localized sources and the identified patterns for each of the research groups. The neuropsychological analysis includes identifying all possible pathways for the identified sets of patterns, ranking the possible pathways based on likelihood for the particular behavioral process and reducing the number of ranked possible pathways based on additional constraints. A system for comparison of obtained signals from an individual to the created knowledge base is provided.

Abstract: A method of analyzing neurophysiological data is disclosed. The method comprises: identifying activity-related features in the data, constructing a brain network activity (BNA) pattern having a plurality of nodes, each representing a feature of the activity-related features, and assigning a connectivity weight to each pair of nodes in the BNA pattern.

Abstract: Systems and methods for constructing a neural model, wherein the system and method comprises analyzing neuropsychological data to obtain the model and modeling functional plasticity.

Abstract: A method for functional analysis of neurophysiological data by decomposing neurophysiological data and EEG signal to form a plurality of signal features. The signal features may then optionally be analyzed to determined one or more patterns.

Abstract: A method for functional analysis of neurophysiological data by decomposing neurophysiological data and EEG signal to form a plurality of signal features. The signal features may then optionally be analyzed to determined one or more patterns.

Abstract: Systems and methods for identifying and analyzing neuropsychological flow patterns, include creating a knowledge base of neuropsychological flow patterns. The knowledge base is formed by obtaining signals from multiple research groups for particular behavioral processes, localizing sources of activity participating in the particular behavioral processes, identifying sets of patterns of brain activity for the behavioral processes and neuropsychologically analyzing the localized sources and the identified patterns for each of the research groups. The neuropsychological analysis includes identifying all possible pathways for the identified sets of patterns, ranking the possible pathways based on likelihood for the particular behavioral process and reducing the number of ranked possible pathways based on additional constraints. A system for comparison of obtained signals from an individual to the created knowledge base is provided.

Abstract: A method for diagnosis includes acquiring a physiological signal from a patient (22) during a period of sleep, and segmenting the signal to define a time sequence of quasi-stationary segments, each of the segments having a respective frequency spectrum. Respective levels of membership of the segments in a plurality of frequency states are computed responsively to the respective frequency spectrum. Based on the respective levels of membership, a sleep quality indicator is determined and displayed, responsively to a statistical characteristic of the segments.