CLINICAL APPLICATIONS OF NEUROPSYCHOLOGICAL PATTERN ANALYSIS AND MODELING

• US 20110004412A1
• Filed: 11/30/2008
• Published: 01/06/2011
• Est. Priority Date: 11/29/2007
• Status: Abandoned Application

• Current Assignee: ElMindA, Ltd.
• Original Assignee: ElMindA, Ltd.
• Inventors: Kanter, Ayelet, Ben-Bassat, Guy, Shahaf, Goded, Reches, Amit, Gordon, Urit, Geva, Amir B., Pinchuk, Noga
• Application Number:
  US12/745,559
• Publication Number:
  US 20110004412A1
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 5/375 using biofeedback
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

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.

Claims

1-18. -18. (canceled)

19. A method of assessing a neurological state of a subject, comprising:

obtaining neurophysiological data from the subject;

identifying flow patterns in said data and utilizing said patterns for comparison of said data to at least one neural model; and

assessing the neurological state of the subject based on said comparison.

20. The method according to claim 19, further comprising determining brain network activity (BNA) based on said flow patterns, wherein said at least one neural model comprises information pertaining to BNA and wherein said determined BNA are compared to said BNA of said at least one neural model.

21. The method according to claim 19, further comprising repeating said assessment for a plurality of subjects and classifying each subjects according to the respective state.

22. The method according to claim 21, further comprising performing a clinical trial according to said classification.

23. The method according to claim 19, wherein said identification of flow patterns comprises identification of causally related features in said data.

24. The method according to claim 19, wherein said neurophysiological data comprises data acquired while the subject is performing a task.

25. The method according to claim 19, wherein said neurophysiological data comprises data acquired while the subject is conceptualizing a task, but does not perform said task.

26. The method according to claim 25, wherein the subject is incapable of performing one or more voluntary actions.

27. The method according to claim 19, wherein said neurophysiological data comprises data acquired before a treatment and data acquired during and/or after a treatment;

and wherein the method further comprises assessing the effect of said treatment.

28. The method according to claim 27, wherein said treatment comprises a pharmacological treatment.

29. The method according to claim 27, wherein said treatment comprises a surgical intervention.

30. The method according to claim 27, wherein said treatment comprises a rehabilitative treatment.

31. The method according to claim 27, wherein said treatment comprises at least one treatment selected from the group consisting of neural feedback, EMG biofeedback, EEG neurofeedback, transcranial magnetic stimulation (TMS) and direct electrode stimulation.

32. The method according to claim 19, wherein said assessing the neurological state comprises assessing level of operation of a sensory network in the brain.

33. The method according to claim 19, wherein said assessing the neurological state comprises assessing level of operation of a visual network in the brain.

34. The method according to claim 19, wherein said assessing the neurological state comprises assessing level of synchronization between a sensory network and a visual in the brain.

35. The method according to claim 19, wherein said assessing the neurological state comprises identifying functional plasticity in the brain.

36. The method according to claim 19, further comprising predicting an effect of a treatment based on said comparison.

37. The method according to claim 19, wherein said neurophysiological data comprises at least one data type selected from the group consisting of EEG data, CT data, PET data, MRI data, fMRI data, ultrasound data, and SPECT data.

38. The method according to claim 19, wherein said neurophysiological data is EEG data.

39. A method of determining the effect of a treatment, comprising:

obtaining EEG data from the subject before and after the treatment;

identifying patterns of causally related features in said data; and

utilizing said patterns for determining the effect of the treatment.

40. A method of predicting an effect of a treatment, comprising:

obtaining EEG data from the subject;

identifying patterns of causally related features in said data; and

utilizing said patterns for predicting an effect of a treatment.

41. A computer software product, comprising a computer-readable medium in which program instructions are stored, which instructions, when read by a computer, cause the computer to obtain neurophysiological data from the subject, identify flow patterns in said data, utilize said patterns for comparison of said data to at least one neural model, and assess the neurological state of the subject based on said comparison.