Functional analysis of neurophysiological data
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.
1. A method of determining a brain activity pattern, the method comprising:
using an EEG or brain imaging tool for obtaining neurophysiological data from a subject, while or after said subject is performing a task;
using a data processor communicating with said EEG or brain imaging tool for:
decomposing the data into a plurality of waveforms;
identifying within said waveforms three-dimensional data patterns according to latency, amplitude and frequency of peaks of said waveforms; and
determining brain activity patterns based on said data patterns; and
displaying a graphic presentation of said activity patterns, said graphic presentation presenting brain regions that are active while or after said subject is performing said task.
2. The method according to claim 1 , further comprising decomposing the data into a plurality of peaks.
3. The method according to claim 1 , wherein the data are decomposed to a plurality of overlapping sets of waveforms.
4. The method according to claim 1 , further comprising comparing said data patterns to a previously determined pattern.
5. The method according to claim 1 , further comprising searching through a database of previously determined data patterns and selecting from said database a pattern closest to at least one of said identified data patterns.
6. The method according to claim 1 , further comprising obtaining neurophysiological data also from at least one additional subject for a particular behavioral process, and associating said brain activity patterns with said behavioral process.
7. The method according to claim 1 , wherein said neurophysiological data comprise data pertaining to a spontaneous brain activity.
8. The method according to claim 1 , further comprising clustering said waveforms according to at least one of said latency, said amplitude and said frequency of peaks of said waveforms, to provide a plurality of clusters.
9. The method according to claim 1 , further comprising determining a causality relation among data pattern components, and utilizing said relation to determine an activity network among said data patterns.
10. The method according to claim 9 , further comprising determining a brain network activity (BNA) correlation to said activity network.
11. The method according to claim 10 , wherein said determination of said BNA correlation comprises determining synchronization, or lack thereof, between a plurality of areas of the brain.
12. The method according to claim 10 , wherein said identifying said data patterns comprises identifying source localizations for said BNA.
13. The method according to claim 12 , further comprising comparing said data patterns to a previously determined pattern and correcting said source localizations based on said comparison.
14. The method according to claim 1 , wherein said neurophysiological data comprises EEG signals.
15. The method according to claim 1 , wherein said decomposing the data is effected by a wavelet transform.
16. The method according to claim 1 , wherein said task is a conceptual task.