Abstract: System and methods are adapted to extract client attention/engagement/effort barrier electrophysiological signal during practice, to combine the attention/engagement/effort barrier with level of success of the client in performing practice task, in order to provide practice recommendation during the current session or following it.

Abstract: A method for stroke evaluation, including: recording electrical signals from a first anterior location and from a second anterior location on a subject head, wherein each of the first anterior location and the second anterior location are above different brain hemispheres; estimating synchronization of brain activity based on a correlation between the recorded electrical signals; evaluating stroke or at least one parameter of stroke in the subject based on the estimated synchronization.

Abstract: Systems and methods are disclosed for management of anesthetized patients. The systems and methods can enable determination of whether the patient risks an anesthetic complication, an intraoperative stroke, or awareness during anesthesia. The disclosed systems and methods can involve receiving a signal from EEG electrodes on the head of a patient during presentation of a stimuli to the patient. This signal can be used to generate segment posteriorization index values and/or synchronization values. Based on synchronization values anesthesia depth of the patient can be reduced or a surgical intervention performed. Based on segment posteriorization index values anesthesia depth of the patient can be increased.

Abstract: Computer-implemented systems and methods are provided for determining indications of a mental state of a subject. A computing system may receive at least one electrophysiological signal from at least one pair of electrodes on a head of a subject. The system may store at least one threshold bio-electrical value, and compare a plurality of portions of the at least one electrophysiological signal with the stored value. The system may determine, based on the comparing, identities of portions of the at least one electrophysiological signal that surpass the stored at least one threshold bio-electrical value. The system may also determine the existence of a portion sequence among the portions of the at least one electrophysiological signal that surpass the stored at least one threshold bio-electrical value. And the system may output an indication of a mental state of the subject when it is determined that the portion sequence exists.

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: 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: 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 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 system for detecting a neurological deterioration in a patient, the system constituted of: an analyzing module; and at least one input port arranged to receive a plurality of first samples of electroencephalographic (EEG) activity of the patient and a plurality of second samples of EEG activity of the patient and further arranged to output the received samples to the analyzing module, wherein the analyzing module is arranged to: compare a function of the received first EEG samples to a function of the received second EEG samples; determine the difference between the outcome of the comparison and a baseline value; and output a neurological deterioration signal responsive to the determined difference.

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 of training a biological neural network using a controller, comprising: applying a cycle comprising: stimulating a neural network by said controller applying at least an input signal to the network; detecting an output response of the network by said controller; and modifying said stimulation by said controller for at least a period of time if said response matches a desired at least approximate response; and repeating said cycle of stimulation, detection and modification at least one more time until said neural network is trained to generate a desired output response for said input signal.