Surgery – Diagnostic testing – Detecting brain electric signal
Reexamination Certificate
2002-09-05
2004-12-14
Nasser, Robert L. (Department: 3736)
Surgery
Diagnostic testing
Detecting brain electric signal
Reexamination Certificate
active
06832110
ABSTRACT:
FIELD AND BACKGROUND OF THE INVENTION
The present invention relates to the field of measurement and analysis of brain function and, more particularly, to a method of analysis of EEG and evoked potential (EP) generated data which allows differentiation between ongoing cortical neuro-electric activity and evoked cortical neuro-electric activity of a subject.
The conventional analysis of EPs is based on averaged data due to the small signal (response) to noise (background EEG) ratio. Thus, data concerning individual trials and the variation of the evoked responses from trial to trial are lost and the nature of the individual response is unclear. For example, a typical goal in EP analysis in clinical cases is to elucidate the reason for the attenuation of particular EP components: is it due to variations in latency of the components across trials or to lower amplitudes of that component in several individual trials? Therefore, many studies have searched for a technique which could possibly provide single trial analysis of the evoked responses
An alternative approach is based on the assumption that the waveform of the conventionally averaged EP is similar to that of the single response so that the averaged response can be used as a criteria (template) for the selection of the appropriate trials for single trial analysis. Thus, only the components of EP which are obtained after averaging can then be used in this approach. However, it is known that some single trial components can be distorted, highly decreased in amplitude or even lost as a result of the averaging, leading to a loss of possibly important information needed for such a study of single trial responses.
The frequency analysis technique has also been suggested to study the evoked potentials in single trials. Thus the evoked potentials can be considered to result from a reorganization of the phases of the ongoing EEG or from selective amplification of EEG in specific frequency bands. However, these spectral (frequency domain) methods do not relate to the local time properties of the responses (e.g. latencies of the particular EP components), and the methods do not allow study of the local time variations of the EP.
Recent studies have shown that background activity and single trial responses are integrated with each other. Consequently it would be advantageous to use the same method for processing and analyzing both aspects (responses and background) of the recorded activity. However, the problem of differentiation of single trial evoked responses from the background EEG activity has yet to be solved, and reliable methods for the analysis of EP and background variability are needed.
There is thus a widely recognized need for a method of EEG and EP data analysis that is devoid of the above described limitations and that facilitates the differentiation of the ongoing cortical neuro-electric activity and the evoked cortical neuro-electric activity of the brain of a subject.
SUMMARY OF THE INVENTION
Accordingly, it is an object of the present invention to provide a method of EEG and EP data analysis that facilitates the differentiation of the ongoing cortical neuro-electric activity and the evoked cortical neuro-electric activity of the brain of a subject.
It is a further object of the present invention to provide a method that may identify responses to single stimuli evoking neuro-electrical activity.
It is a further object of the present invention to provide a method that may be actuated by an algorithm.
It is a further object of the present invention to provide a method that employs an algorithm that is computer programmable.
It is a further object of the present invention to provide a method that employs an algorithm that may be modified to provide for analysis of differing EEG and EP data.
The present invention describes a novel method for the analysis of both the neural electrical activity initiated in response to a series of sensory stimuli and of ongoing neural electrical activity. The positive and negative deflections in the EEG activity are detected and the time distributions and the amplitude as a function of time distributions of these deflections are obtained. This provides a statistical description of the appearance of positive and negative deflections or fluctuations in the ongoing EEG before, during and after a series of sensory stimuli. An algorithm based upon the statistical description is used to quantify the differentiation between the neural electrical activity evoked by the stimuli and the background EEG, both with respect to the number of these deflections and with respect to their amplitude. This differentiation provides insights into the possible relations between evoked and background EEG activity, leading to a better understanding of how evoked potentials are generated.
Accordingly, there is provided a method of analyzing EEG and EP data in order to differentiate between ongoing neuro-electric activity of the brain of a subject and evoked neuro-electric activity of the brain of the subject, the analysis being based upon the frequency and the amplitude of deflections from the base line of the EEG and EP data, the method comprising a. recording by EEG measurement the ongoing neuro-electric activity; b. administering a series of sensory stimuli to the subject; c. recording by EEG and EP measurement neuro-electric activity evoked in response to the stimuli; d. marking the time of occurrence, polarity and amplitude of each of the deflections recorded; e. generating a histogram of time periods of the deflections for a defined duration prior to, during and subsequent to each of the single stimuli, the histogram reflecting the deflections within the time periods, generating a deflection time distribution based upon data from the histogram, generating an amplitude profile of the deflections; and f using the deflection time distribution and the amplitude profile to statistically analyze and evaluate the ongoing and evoked neuro-electric activity; such that the differentiation between the ongoing and the evoked neuro-electric activity may be quantified.
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Goodman Craig
Rodionov Vladimir
Sohmer Haim
Nasser Robert L.
Scully Scott Murphy & Presser
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