Brain electrical activity mapping

Abstract

Apparatus for generating a topographic display of information on brain electrical activity based on responses of electrical-activity transducers placed on the skull. In different aspects, the brain is stimulated at pseudorandom intervals to produce ep responses; matrices corresponding to the electrical responses are processed to generate a statistical comparison matrix and the corresponding display map is grid sector analyzed; a series of tests is administered some of which put the brain in a simple resting state, others putting the brain in nonresting states of varying activity level; statistical comparison matrixes are generated representing the statistical difference between normal and abnormal groups at different skull locations with respect to different brain activities; significance probability maps are generated each representing the statistical difference between a patient and the normal population with respect to different brain activities; and an epileptic spike is caused, a sufficient number of data matrices is generated to capture onset of the spike, and the frame rate of display of the corresponding topographic maps is selectably changed for observing the onset.

Description

The invention described herein was made in the course of work under a grant or award from the Department of Health and Human Services.

BACKGROUND OF THE INVENTION

This invention relates to analysis of brain electrical activity and diagnosis of brain disorders.

Traditional electro-encephalographic (EEG) techniques of analyzing brain electrical activity to diagnose brain dysfunction require the skilled neurophysiologist to observe and distinguish time and frequency related characteristics of many channels of voltage waveforms derived from an individual's brain and to determine, largely from memory, differences between that individual's waveforms and waveforms characteristic of a normalized population. The process necessarily fails to take account of many subtle but potentially useful pieces of information contained in the analyzed data.

Signal averaged sensory evoked potential (EP) transient responses have also been used as a source for brain electrical activity analysis, but large amounts of useful information contained in such transient system. Twenty electrodes 5 (e.g., Grass gold cup) are attached to subject's skull 4 in a conventional international 10-20 format. Twenty leads 6 from electrodes 5 are connected through switch 7 to conventional 24-channel polygraph 10 (e.g., Grass 8- 24D), which contains parallel variable grain differential amplifiers and strip chart recorders. Calibration signal source 8, an A.C. generator, is also connected through switch 7 to polygraph 10. Stimulus A 2 (e.g., Grass Model PS1 strobe light) and stimulus B 3 (e.g., click generator) present stimuli to the subject under the control of pseudorandom stimulus controller 9, which also provides pre-stimulus and stimulus trial marker signals (5 volt spikes) of opposite polarity to one of the input channels to 24-channel FM analog tape recorder 11 (e.g., Honeywell 5600E). In other embodiments, recorder 11 is eliminated and polygraph 10 is connected directly to filter 12 for real-time loading of data. The 21 active outputs of recorder 11 are connected to the inputs of 21 parallel variable band pass filters 12 (e.g., Butterworth filters; EEG Associates Mark 4×24) having variable gain controls. The 21 outputs of filters 12 are connected to 21 of the input terminal of two 16-channel, 12-bit analog-to-digital converters 15, 16 (Digital Equipment Corporation AA-11K), which comprise part of digital computer 13 (Digital Equipment Corporation PDP 11/60). Analog-to-digital converters 15, 16 are attached to data bus 14 (Digital Equipment Corporation Unibus). Also attached to data bus 14 are 4-channel, 12-bit digital-to-analog converter 17 (Digital Equipment Corporation AD-11K) whose three outputs control black and white television monitor 18 (Digital Equipment Corporation VR 17) for waveform displays; color display control 19 (Digital Equipment Corporation VSV 01) whose three outputs control 12" color television monitor 20 (CONRAC) for topographic displays; 8 serial line controller 24 (Digital Equipment Corporation DZ 11) two outputs of which control interactive keyboard and video character display terminal 22 (Digital Equipment Corporation VT 100) and printer 23 (Digital Equipment Corporation LA 120); 256K byte memory 24 containing operating system software 27 (Digital Equipment Corporation RSX 11/M); BEAM software 28 (Agrippa Data Systems), and analytic software 29 (TICAS; University of Arizona); floating point processor 25 (Digital Equipment Corporation FPP-11); central processing unit 26 (Digital Equipment Corporation PDP 11/60); and disk controller 27 controlling at least one disk drive 28.

Software Description

In general, the brain electrical activity mapping system creates color topographic displays reflecting brain electrical activity using, as input, continuous electrical waveforms recorded from a number of points on the skull. The color topographic displays consist of discrete matrices of a large number of display points (also called pixels), each of which has a color or intensity of other visible characteristic which indicates a certain value or values at the location of that point analogous to a point on the skull. In order to generate discrete topographic display matrices having many thousands of display points from continuous analog waveforms at a limited, e.g. 20, number of points on the skull, the brain electrical activity mapping system, as illustrated in FIG. 2, converts the data to digital form and generates discrete sample frames 40, each sample or frame initially comprising 20 recorded values 41 from 20 channels of information. The system treats related groups of samples 40 as segments 42. In the case of EP data, for example, a segment would consist of a series of frames or samples, each 4 milliseconds in length, the series together representing one transient response sequence from the beginning of a pre-stimulus period to the end of the post-stimulus transient response. In the case of steady-state EEG data, a segment would consist of 2 seconds of data divided into 256 samples. A spectral analysis of the EEG data then produces 256 samples, each of which reflects the energy level in a small, e.g. 1/2 Hz, energy band and a segment consists of the entire series of 256 spectral samples. For signal averaging purposes, the system considers a set of segments together, e.g., 500 segments each representing a transient response to a given stimulus. The 500 segments taken together are known as an ensemble 43. Frames of data can be raw data or data which has been processed or transformed by the system. In any case, as illustrated in FIG. 3, when a frame 40 is to be displayed it is expanded into a matrix 45 consisting of a large number of display points 46 which are determined by an interpolation process from the original frame data points 47. Each point of the matrix is then converted to a visual display point 47 which forms part of the final topographic display 48.

FIG. 4 illustrates the organization of the operations which comprise brain electrical activity mapping software 28 and TICAS analytic software 29. Raw and processed data is stored in disk files 51. Operations 52-65 and 67-69 use data stored in files 51 to perform data manipulation, data display and data storage functions. Operations 54 and 55 also process data from the outputs of converters 15, 16.

FIG. 5 illustrates the function of define protocols operation 53. Protocol files 73 are generated and edited by program `SETPAR` 71 based on control information 70 provided by the operator through terminal 22, the results of the operation being displayed (block 72) on terminal 22 to the operator. Each protocol file 73 contains information which governs the manner in which other operations are performed on a particular type of data file (e.g., one protocol might apply to the processing of EP transient response data from strobe light stimuli). The protocol information may include the number and identity of input channels, the labeling of the output channels to correspond to specific points on the final display, the identity of the trial marker channel, the voltage level above which to search for the trial markers, the rate in samples per second of sampling of the data, the number of samples in a segment, the number of segments Us. Pat. No. 4,417,591)or of hypo- or hyperactive cortex that become visible on the brain electrical activity mapping images. For example, tumors show decrease in activity early, excessive activities later, and reduced activity at the vertex. Brain electrical activity mapping greatly adds to the information obtained by radiographic scanning as it is sensitive to the functional disturbances produced by these lesions which usually extend beyond the anatomical limits of the lesion.

To pinpoint abnormalities the technique of significance probability mapping (SPM) should be used. Furthermore, quantification of a lesion by grid sector analysis (GSA) is often useful.

Beam Brain electrical activity mapping is most useful when tests must be applied to a large population for screening purposes or repeatedly to a single person. Such uses would include screening for tumor and stroke, determining whether a lesion is increasing or decreasing, and assessing the effects of treatment on a lesion. Beam Brain electrical activity mapping is completely non-invasive, and not dangerous as radiographic techniques would be in such circumstances. There is also evidence that many lesions produce electrical (functional) disturbances before they can be detected by radiographic means.

Suspected Learning Disabilities

Beam electrical activity mapping studies are most useful in the elucidation of regional abnormalities of brain activity found in dyslexia, hyperactivity, dyscalculia, and combinations of the above. For example, dyslexia reveals abnormalities not just in the classic left temporal lobe speech areas but in the medial frontal lobe bilaterally. To demonstrate these abnormalities, one needs to perform the full test battery which includes: right hemispheric activiting tests (the Kimura Figures task and listening to music as described elsewhere); left hemispheric activating (listening to speech and reading Grey Oral passages as described elsewhere); and bi-hemispherical tests (Paired Associates test and the Tight-Tyke evoked potential phenomic discrimination test as described elsewhere).

Automated classification tests to discriminate among these clinical entities can be developed.

Emotional Dysfunction

Many forms of emotional disorder can be caused by the lesions mentioned above. Beam Brain electrical activity mapping can be more useful in the recognition of covert pathology in this patient population than radiographic techniques. In addition, certain forms of psychopathology have recognizable brain electrical activity mapping signatures. For example sociopathic behavior is associated with lack of synchrony between the frontal lobes; e.g., the VER may show different electrical polarity between the right and left frontal lobes. Schizophrenia shows markedly increased EEG slow activity overlying the frontal regions. In this group of subjects, the eyes open and eyes closed EEG and VER studies are most useful.

Infant Competence

Discrimination between babies at risk for future learning and emotional problems is a frequent clinical request. Brain electrical activity mapping has proven useful in accomplishing such discrimination. In addition to studying the EEG and VER in stages 1 and 2 sleep, the EEG should be studied while the babies are brought into the alert state and maintained there as discussed elsewhere. Less competent babies, for example, show paradoxical increases in frontal delta slowing as they are alerted.

Suspected Dementia

Senile and pre-senile dementia represent a major problem for gerontologists and neurologists. Radiographic evidence of brain abnormality may not be found until the clinical symptom complex is well established. On the other hand, brain electrical activity mapping studies demonstrate early abnormalities is a non-invasive manner. The best battery of tests is similar to those described above for suspected learning disabilities, but generally the tight-tyke EP is replaced by another EP where the subject must discriminate between frequently and infrequently heard tone pips of differing frequency. A different EP between the response to the two different tone pips is produced. The topographic display of the difference EP shows a marked reduction in dementia and may be used to follow the course of dementia and the response of dementia to pharmacotherapies.

Headache

Headache may be caused by many factors. Brain electrical activity mapping is very useful to screen out serious lesions of the types described as supratentorial lesions above. The specific syndrome of migraine headache has a frequently seen pattern on brain electrical activity mapping of excessive 8-11 Hz occipital oscillations and excessive occipital activity, it is best to use the EO and EC EEG and VER for headache. Occasionally the BSEP is useful.

Comparison of Individual to Group

As described above, the brain electrical activity mapping system is generally able to compare an individual statistically to a group and display the result topographically. In a clinical setting, the individual in question, who may have displayed a normal CT scan, is compared to an age matched/sex matched group of normals, and abnormalities are then displayed in color-mapped form, wherein bright colors show high abnormality and dull colors show insignificant abnormality. This technique provides an effective diagnostic tool.

Comparisons of Groups; Automatic Diagnosis Rules

The result of a group comparison under the system is a topographic display of statistical difference expressed as t-statistics, which when coupled with the number of degrees of freedom available in the calculation, produce a probability level of significant difference between two groups at a particular brain state. For instance, a group of normals could be compared to a group of schizophrenics by the creation of t-statistic displays with respect to a variety of brain states and stimuli. The user looks for displays which exhibit high degrees of coherence and statistical difference. This is normally shown on a screen in color. The larger statistical differences appear as brighter colors. The degree to which the differences are focused at particular points or diffused over the skull is also apparent. Smoothness in the lines dividing areas of different brightness suggests focused differences, while diffuse differences are suggested by ragged edges betwen dim and bright areas. It is possible for the researcher, upon selection of a particular map that shows something interesting, to save the matrix for later analysis. Such a saved matrix of t-statistics can be used to non-linearly weight the underlying data frames to create features which can be analyzed using TICAS. Once a set of saved frames representing group difference information is accumulated, he then converts all of the saved information, representing features which tend to distinguish the two groups into a file format which is suitable for analysis by TICAS, which is a multi-variate classification systen, publicly available from the University of Arizona, courtesy of Dr. Peter H. Bartell.

TICAS is designed to sift through all of the features saved in the course of the inter-group analysis and pick those which prove to be the most discerning mathematically to produce a set of features which succinctly allows automatic diagnosis of a patient.

This procedure has been used to successfully discriminate between normal subjects and those with dyslexia, to discriminate between normal subjects and those with supertentorial brain tumor, and to discriminate between subjects with exposure to organophosphate compounds and nonexposed controls.

Dyslexia Analysis

An article, Dyslexia Regional Differences in Brain Electrical Activity by Topographic Mapping, Duffy et al. (Annals of Neurology, Vol. 7, No. 5, May, 1980), hereby incorporated by reference, describes the use of the brain electrical activity mapping system to identify the parts of the brain whose electrical activity differs for individuals suffering from reading disability (dyslexia) as compared with normal individuals, and to establish objective standards for diagnosing dyslexia. The previously described battery of brain state tests were administered to a dyslexic group and a control group. Visual and auditory stimuli were repeatedly presented to both groups and recorded with the appropriate trial markers. The stimuli were offered in pseudorandom fashion. Using the brain electrical activity mapping system, topographic displays of the alpha (8 to 11.75 Hz) and theta (4 to 7.75 Hz) activity at each electrode for each tested brain state for each subject were produced. Similar cartoons of 128 frames (4 milliseconds each) were prepared for each type of EP response for each subject. The resulting brain state frames and EP response frames for the dyslexic group and the control group were then averaged to form mean frames of each group for each state and stimulus. The two groups of mean images were then compared using the t-statistic function. A further transformation produced a matrix of percentile index values (PI) whose value is related inversely to t-values. The PI values permit a graphic localization of regions of maximum difference between the dyslexic group and the control group. By topographically displaying the PI matrices for alpha and theta for each brain state and for each EP stimulus, it was possible to identify the brain regions which differed between the dyslexics and the controls. As a final step, a new display matrix was formed which summarized the differences reflected in all of the PI matrices as indicated by the occurrence of a certain PI level on at least one of the underlying PI matrices. The map of PI differences having a value of at least 2 identified four brain areas related to dyslexia: (1) bilateral medical frontal, (2) left anteriolateral frontal, (3) left mid-temporal and (4) left posterolateral quadrant. Classic concepts of dyslexia had not suggested the involvement of all of these brain areas in dyslexics. The study also indicated that alpha brain activity was involved in dyslexia as well as the theta activity which has previously been viewed as of primary importance.

In Dyslexia: Automated Diagnosis by Computerized Classification of Brain Electrical Activity, Duffy et al. (Annals of Neurology, Vol. 7, No. 5, May, 1980) hereby incorporated by reference, specific highly effective diagnostic rules for identifying dyslexics were developed by a rule selection process applying TICAS software to the brain wave data derived in the study described immediately above. Working from displays of brain electrical activity, 183 features were identified for particular regions and brain states in which the strongest differences between the dyslexic group and the normal group occurred. Two of the 183 features were identified as capable of classifying unknown subjects as dyslexic or normal with a success of 80-90%.

Localization of Tumor

In Brain Electrical Activity Mapping (B.E.A.M.); A Method for Extending the Clinical Utility of EEG and Evoked Potential Data, Duffy, et al (Annals of Neurology, Vol. 5, No. 4, April, 1979), hereby incorporated by reference, the use of brain electrical activity mapping system topographic displays to identify the location of a brain tumor was discussed. Spectral EEG data in the four classic bands (delta, theta, alpha, and beta) was recorded for various tested brain states. Average EP response data for strobe light stimuli comprising 128 time frames of 4 milliseconds each was also recorded. After three-point linear interpolation to expand the matrix, displays of spectral EEG data, and cartooned EP data were obtained. FIG. 5 of the article illustrates the spectral EEG displays in the four classic bands of brain activity for a patient with a known tumor, which had been located by CT scanning. The assymetries in the spectral displays also identify the area of the tumor, although the suggested lesion size was larger than indicated by CT scanning. Analysis of 7 tumor patients, whose classic EEG's were normal or non-localizing, showed that brain electrical activity mapping studies were able to define the lesions almost as effectively as CT scan.

Use of Significance Probability Mapping with B.E.A.M. to Compare Groups and Compare Individuals to Groups

In Significant Probability Mapping: An Aid in the Topographic Analysis of Brain Electrical Activity, Duffy et al., accepted for publication (hereby incorporated by filing a copy thereof as an Appendix) the authors describe the use of topographic displays of statistical transformations of data. In one application, EP response data was obtained from a group of subjects with brain tumors and a second control group of subjects. The data was broken into sequential frames of 4 milliseconds each. For the control group, new matrices of mean and variance of each electrode over all members of the group were prepared. A z-statistic matrix was formed for each tumor subject to illustrate his deviation from the normal population. Using the z-statistic display a clinical neurophysiologist was able to identify 11 of 12 tumor subjects.

In a second application, discussed in the same article, EEG steady-state signals were recorded for three different brain states (resting but alert with no external stimulation, listening to a tape recording of speech, and listening to a tape recording of music) for individuals in a group of dyslexics and individuals in a group of normal readers. Matrices of alpha band activity were produced for each individual, and mean and variance matrices for each state were prepared for each of the two groups. For each group t-statistic matrices were formed to compare the resting and listening to speech states and the resting and listening to music states. By examining the t-statistic displays for the two groups it was possible to infer the differences in speech-induced and music-induced brain activity between the dyslexics and the normal readers. Those determinations could not have been made from an analysis of the underlying EEG alpha matrices.

Use of Grid Sector Analysis of B.E.A.M. SPM Data to Determine Degree of Focal or Global Deviation From Normal

In an unpublished article, "Quantification of Focal Abnormalities in BEAM Data by Grid Sector Analysis: Automated discrimination Between Normal Subjects and Patients with Supratentorial Brain Tumor", Duffy, et al., (hereby incorporated by filing a copy thereof as an Appendix) describes uses of grid sector analysis as part of the brain electrical activity mapping system for the purpose of automated neutophysiological diagnosis of brain tumor. In this application, EEG and visual EP data were recorded from a group of patients with confirmed supratentarial brain tumor and from a control group. SPM matrices were prepared comparing the tumor subjects to a normal group and comparing the control group to the tumor group. Four 96 millisecond time periods of EP data were analyzed. Grid sector analyses on the data resulted in a set of 1096 combined global and focal features from the combined EEG and EP data. By a process of features selection and rule development and testing, two features were identified as most useful in distinguishing the tumor subjects from the control subjects. When classification rules developed on the initial group of 30 subjects were applied to a new group of 10 subjects, containing 5 normals and 5 subjects with brain tumor, all ten were correctly classified.

Other Embodiments

Other embodiments of the invention are within the following claims. For exaple, the input data may be obtained from any type of transducer capable of measuring brain electrical activity, and

topographic displays can be prepared from the signals taken from the skull, without interpolation of additional points to form a display matrix.

Related Applications

This application is related to the following applications, each of which is hereby incorporated by reference:

(1) Frank H. Duffy and Norman David Culver, Brain Electrical Activity Mapping (BEAM), U.S. Pat. No. 4,408,616

(2) Norman David Culver, Brain Electrical Activity Mapping (BEAM), U.S. Pat. No. 4,407,299

(3) Norman David Culver, Analysis of Brain Electrical Activity, U.S. Ser. No. 263,931 (abandoned)

(4) Norman David Culver, Apparatus and Method for Topographic Display of Multichannel EEG Data, U.S. Ser. No. 221,830 U.S. Pat. No. 4,417,591

Claims

1. Apparatus for generating a topographic display of information on the electrical activity of the brain, said apparatus comprising

a plurality of electrical-activity transducers adapted for placement at spaced apart locations on the skull of a patient,

stimulus means for repeatedly generating a sensory stimulus for the brain to produce at said transducers repeated segments of data each associated with one ep response, said stimulus means including

pseudorandom timing means for triggering successive said stimuli at times spaced apart by pseudorandom time intervals, and for determining each said pseudorandom time interval as a combination of a subinterval of fixed length and a subinterval of pseudorandomly determined length, each said fixed length subinterval comprising a pre-stimulus subinterval of predetermined length and a post-stimulus subinterval of predetermined length,

averaging means connected to be responsive to said transducers for averaging said repeated segments to generate average segments for each transducer,

processing means connected to be responsive to said averaging means for processing said average segments to generate one or more matrices, each element said one or more matrices representing information on the electrical activity of the brain at one location on the skull,

display means connected to be responsive to said processing means for displaying said one or more matrices as topographic maps of the skull, each said matrix element forming a discrete point of said maps.

2. The apparatus of claim 1 wherein said pseudorandomly determined subinterval includes a subinterval that varies pseudorandomly from zero to a period longer than the post-stimulus response time, whereby interference due to contigent contingent negative variation is reduced.

3. The apparatus of claim 1 wherein said pseudorandomly determined subinterval includes a subinterval that varies pseudorandomly from zero to a period longer than the wavelength of a prominent of frequency of steady-state brain activity, whereby interference due to such steady-state brain activity is reduced.

4. The apparatus of claim 3 wherein said prominent frequency is 10 Hz and said subinterval varies from zero to 100 milliseconds.

5. The apparatus of claim 1 wherein said pseudorandom timing means includes

a clock for generating timing pulses,

a sequential counter connected to be responsive to said clock for counting said pulses,

a comparator connected to be responsive to said counter for comparing the contents of said counter to a stored number, and signalling the end of one said subinterval when said count equals said stored number,

a memory for storing a sequence of pseudorandom numbers, and

means for replacing said stored number with a different one of said pseudorandom numbers for each succeeding stimulus.

6. The apparatus of claim 1 further comprising means connected to influence said stimulus means, for temporarily delaying triggering of said stimuli in response to a signal from the operator of said apparatus.

7. The apparatus of claim 1 wherein said stimulus means comprises means for generating a repeated sequence of plural stimuli.

8. The apparatus of claim 7 wherein said plural stimuli are of different types.

9. The apparatus of claim 8 wherein said different types include light stimuli and sound stimuli.

10. The apparatus of claim 1 wherein said stimulus is repeated at least 100 times.

11. The apparatus of claim 1 wherein said stimuli are any one of the following: a single flash, a single click, a visual pattern reversal, and a somatosensory stimulus.

12. The apparatus of claim 7 wherein said stimulus consists of an auditory or visual event that is infrequently of a first type and more frequently of a second type.

13. The apparatus of claim 12 wherein said first and second events are spoken words that are similar in sound.

14. Apparatus for generating a topographic display of information on the electrical activity of the brain, said apparatus comprising

a plurality of electrical-activity transducers adapted for placement at spaced apart locations on the skull of a patient,

processing means connected to be responsive to said transducers for processing electrical response responses measured at said transducers to produce one or more matrices, each matrix containing a plurality of elements, said elements representing information on the electrical activity of the brain at particular skull locations,

statistical processing means connected to be responsive to said processing means for processing at least two said matrices to generate a statistical comparison matrix, said statistical comparison matrix having elements each of which is representative of a statistical difference between the corresponding elements in said two matrices,

display means connected to be responsive to said statistical processing means for displaying said statistical comparison matrix as a topographic map of the skull, said matrix elements forming discrete points of said map, and

grid sector analysis means connected to be responsive to said display means including means for assigning points of said map to sectors of a grid and means for determining the mean of said statistical comparison elements in each said sector.

15. The apparatus of claim 14 wherein said grid sector analysis means further comprises

means connected to be responsive to said grid sector analysis means for changing the sector size in said grid and repeating the determination of the means mean for the new sector size,

means for determining a histogram for each of the grid sector sizes, each said histogram constituting numbers of grid sectors having mean values falling within selected mean value ranges.

16. The apparatus of claim 15 wherein said means for changing the sector size includes means for forming grids with from 2 to 4000 sectors.

17. The apparatus of claim 16 wherein said means for changing the sector size includes means for forming grids with either 16, 64, or 4000 sectors.

18. A method of extracting clinically useful information on the electrical activity of a patient's brain, comprising the steps of:

applying electrical-activity transducers at spaced apart locations on the skull of the patient,

administering a series of tests to the patient while processing responses measured by said transducers, one or more of said tests being selected to put the brain in a simple resting steady state and

a plurality of other tests being selected to put the brain in nonresting steady states corresponding respectively to different levels of activity, and

processing resulting responses measured during each said state to generate one or more matrices of display elements, each display element representing information on the electrical activity of the brain at one location on the skull, and

displaying said one or more display matrices in the form of topographic maps, with each display element forming a discrete point on the maps.

19. The method of claim 18 wherein said processing is done intermittently at times while the brain is in a single state and not while the brain is changing between states and not while there exists a condition in the patient's activity that would generate an artifact in the response.

20. The method of claim 18 wherein said tests for putting the brain in a simple resting steady state are selected from the following:

(1) patient relaxes and remains still with eyes closed,

(2) patient relaxes and remains still with eyes open,

(3) patient hyperventilates, and

(4) patient becomes drowsy. 21. The method of claim 18 A method of extracting clinically useful information on the electrical activity of a patient's brain, comprising the steps of:

applying electrical activity transducers at spaced apart locations on the skull of the patient,

administering a series of tests to the patient while processing responses measured by said transducers, one or more of said tests being selected to put the brain in a simple resting steady state and

a plurality of other tests being selected to put the brain in non-resting steady states corresponding respectively to different levels of activity, and

processing resulting responses measured during each said state to generate one or more matrices of display elements, each display element representing information on the electrical activity of the brain at one location on the skull, and

displaying said one or more display matrices in the form of topographic maps, with each display element forming a discrete point on the maps, wherein said plurality of tests for putting the brain in nonresting steady states of varying activity levels are selected from the following:

(1) patient listens carefully to a story and answers simple questions about its content when completed,

(2) patient listens to music,

(3) patient remembers a set of abstract figures presented by the examiner,

(4) patient selects the previously presented figures from a larger set of figures by verbally indicating yes or no,

(5) patient associates abstract figures with particular artificial names spoken by the examiner,

(6) patient names each of the abstract figures when tested by the examiner,

(7) patient reads silently three previously unread paragraphs in preparation to answer questions subsequently,

(8) patient identifies whether sentences presented by the examiner were previously included in the three paragraphs, and

(9) patient reads text upside down.

22. The method of claim 18 wherein the total time of the responses for each test in said series is in the

range from 20 seconds to 3 minutes. 23. The method of claim 18 A method of extracting clinically useful information on the electrical activity of a patient's brain, comprising the steps of:

applying electrical activity transducers at spaced apart locations on the skull of the patient,

administering a series of tests to the patient while processing responses measured by said transducers, one or more of said tests being selected to put the brain in a simple resting steady state and

a plurality of other tests being selected to put the brain in non-resting steady states corresponding respectively to different levels of activity, and

processing resulting responses measured during eash said state to generate one or more matrices of display elements, each display element representing information on the electrical activity of the brain at one location on the skull, and

displaying said one or more display matrices in the form of topographic maps, with each display element forming a discrete point on the maps, wherein said patient is an infant and said tests for putting the brain in a simple resting steady state are selected from the following:

(1) infant is sleeping and

(2) infant is drowsy. 24. The method of claim 18 A method of extracting clinically useful information on the electrical activity of a patient's brain, comprising the steps of:

applying electrical activity transducers at spaced apart locations on the skull of the patient,

administering a series of tests to the patient while processing responses measured by said transducers, one or more of said tests being selected to put the brain in a simple resting steady state and

a plurality of other tests being selected to put the brain in non-resting steady states corresponding respectively to different levels of activity, and

processing resulting responses measured during each said state to generate one or more matrices of display elements, each display element representing information on the electrical activity of the brain at one location of the skull, and

displaying said one or more display matrices in the form of topographic maps, with each display element forming a discrete point on the maps, wherein said patient is an infant and said tests for putting said brain in said non-resting steady states are:

(1) infant is stimulated by face-to-face visual contact and

(2) infant is alert but not attending to visual and auditory information.

. A method of using topographic maps of brain electrical activity to determine brain regions with different electrical activity for normal and abnormal groups, comprising the steps of

applying electrical-activity transducers at spaced apart locations on the skulls of a group of normal patients and a group of abnormal patients,

administering to the patients a series of tests that cause selected brain electrical activity while simultaneously storing portions of responses measured by the transducers,

processing the stored responses to generate one or more matrices for each selected brain activity and each patient, the one or more matrices having elements representing brain electrical activity at different skull locations,

processing the one or more matrices to generate a statistical comparison matrix for each selected brain activity, each statistical comparison matrix having elements representing the statistical difference between the normal and abnormal groups at different skull locations,

displaying each statistical comparison matrix as a topographic map of the skull, with each element defining a discrete point of the map, and

identifying map regions in which normal and abnormal population groups have statistically significant differences in brain electrical activity.

A method of using topographic maps of brain electrical activity to aid diagnosis of a selected brain abnormality in a patient, comprising the steps of

applying electrical-activity transducers at spaced apart locations on the skull of the patient,

administering to the patient one or more tests that cause selected brain electrical activity while simultaneously storing portions of responses measured by the transducers,

processing the stored responses to generate one or more matrices for each selected brain activity, the one or more matrices having elements representing brain electrical activity at different skull locations,

processing the one or more matrices to generate a significance probability map for each selected brain activity, each statistical probability map having elements representing the statistical difference between the patient and the normal population,

displaying said one or more matrices as topographic maps of the skull, said matrix elements forming discrete points of the said maps, and

assessing selected regions of said one or more maps to identify differences in those regions between the patient and the normal population.

27. The method of claim 26 wherein said assessing step comprises the steps of

processing the elements within said selected regions to generate one or more quantitative measures of the statistical difference between the patient and the normal population,

comparing said one or more measures against predetermined values to provide diagnostic information on the likelihood that the individual has said

selected abnormality. 28. The method of claim 27 A method of using topographic maps of brain electrical activity to aid diagnosis of a selected brain abnormality in a patient comprising the steps of:

applying electrical activity transducers at spaced apart locations on the skull of the patient, administering to the patient one or more tests that cause selected electrical activity while simultaneously storing portions of responses measured by the transducers,

processing the stored responses to generate one or more matrices for each selected brain activity, the one or more matrices having elements representing brain activity at different skull locations,

processing the one or more matrices to generate a significant probability map for each selected brain activity, each statistical probability map having elements representing the statistical difference between the patient and the normal population,

displaying said one or more matrices as topographic maps of the skull, said one or more matrices having discrete points of the said maps, and assessing selected regions of said maps to identify differences in those regions between the patient and the normal population,

processing the elements within said selected regions to generate one or more quantitative measures of the statistical difference between the patient and the normal population,

comparing said one or more measures against predetermined values to provide diagnostic information on the likelihood that the individual has said selected abnormalities, wherein said abnormality is a migraine headache, said tests include causing the patient to assume a resting eyes-open state and a resting eyes-closed state, and providing repeated visual stimuli to produce repeated ep responses, said processing includes producing spectral energy matrices for the 8-11 H_z frequency band from the background data taken during the resting states and producing a time-sequence of matrices from the ep responses, and wherein said assessing step includes assessing from said matrices the presence of

increased occipital activity. 29. The method of claim 28 wherein said tests further include providing repeated bilateral somatosensory stimuli

to generate repeated ep responses. 30. The method of claim 26 A method of using topographic maps of brain electrical activity to aid diagnosis of a selected brain abnormality in a patient, comprising the steps of:

applying electric activity transducers at spaced apart locations on the skull of the patient,

administering to the patient one or more tests the cause brain electrical activity while simultaneously storing portions of the responses measured by the transducers,

processing the stored responses to generate one or more matrices for each selected brain activity, the one or more matrices having elements representing brain electrical activity at different skull locations,

processing the one or more matrices to generate a significance probability map for each selected brain activity, each statistical probability map having elements representing the statistical difference between the patient and the normal population,

displaying said one or more matrices as topographic maps of the skull, said one or more matrices having discrete points of the said maps and assessing selected regions of said maps to identify difference in those regions between the patient and the normal population, wherein said abnormality is an emotional dysfunction, said regions include the frontal lobes, and said assessing steps includes assessing the lack of synchrony

between said frontal lobes. 31. The method of claim 30 wherein said tests include repeated visual stimuli to generate repeated ep responses, and said assessing includes assessing the difference in electrical polarity

between the right and left frontal lobes. 32. The method of claim 30 wherein said emotional dysfunction is schizophrenia and said tests include causing the patient to assume resting eyes-open and resting eyes-closed states and providing a repeated visual stimulus to generate repeated ep responses, said processing includes producing spectral-energy matrices from the background activity stored during the eyes-open and eyes-closed tests and producing a time-sequence of matrices from the ep responses, and said assessing includes assessing the presence of increased activity

overlying the frontal regions. 33. The method of claim 26 A method of using topographic maps of brain electrical activity to aid diagnosis of a selected brain abnormality in a patient comprising the steps of:

applying electrical activity transducers at spaced apart locations on the skull of the patient,

administering to the patient one or more tests that cause selected electrical activity while simultaneously storing portions of responses measured by the transducers,

processing the stored responses to generate one or more matrices for each selected brain activity, the one or more matrices having elements representing brain activity at different skull locations,

processing the one or more matrices to generate a significant probability map for each selected brain activity, each statistical probability map having elements representing the statistical difference between the patient and the normal population,

displaying said one or more matrices as topographic maps of the skull, said one or more matrices having discrete points of the said maps, and assessing selected regions of said maps to identify differences in those regions between the patient and the normal population, wherein said abnormality is learning and emotional problems in an infant, said tests include sleeping, providing repeated visual stimuli during sleep, causing the baby to become alert from a sleeping state, said processing includes producing spectral energy matrices from the background activity stored during the sleeping and the alert states and a time-sequence of matrices from the ep responses to the visual stimuli and wherein said assessing step includes assessing increased activity in the frontal regions of the delta spectral-energy matrices for data taken as the infant

is being alerted. 34. The method of claim 26 A method of using topographic maps of brain electrical activity to aid diagnosis of a selected brain abnormality in a patient comprising the steps of:

applying electrical activity transducers at spaced apart locations on the skull of the patient,

administering to the patient one or more tests that cause selected electrical activity while simultaneously storing portions of responses measured by the transducers,

processing the stored responses to generate one or more matrices for each selected brain activity, the one or more matrices having elements representing brain activity at different skull locations,

processing the one or more matrices to generate a significant probability map for each selected brain activity, each statistical probability map having elements representing the statistical difference between the patient and the normal population,

displaying said one or more matrices as topographic maps of the skull, said one or more matrices having discrete points of the said maps, and assessing selected regions of said maps to identify differences in those regions between the patient and the normal population, wherein said abnormality is senile or pre-senile dementia, said tests include requiring the patient to repeatedly discriminate between frequently and infrequently heard tone pips of differing frequency, said processing includes producing a time-sequence of matrices representing the difference

between the ep responses to the two different tone pips.

35. The method of claim 26 wherein said abnormality is epilepsy,

said tests include causing the patient to assume a resting state with eyes closed and causing the patient to assume a resting state with eyes open,

said processing includes determining the Fourier transforms of the stored responses and determining from the transforms, for each transducer, the spectral energy contained in selected frequency bands, and processing the output of said spectral processing means to generate, for each selected activity, a plurality of matrices, one of said matrices for each selected frequency band, the elements of said matrices representing the spectral energy within the respective frequency band at one location on the skull, and

said assessing step includes assessing from said maps whether, as compared to the normal population, there are focal increases of activity in the selected frequency bands.

36. The method of claim 26 wherein said abnormality is epilepsy and wherein

said tests include providing a repeated visual stimulus to the patient to generate repeated ep responses,

said processing includes averaging the repeated responses to produce an average response for each transducer, zeroing each average response using a baseline determined from the pre-stimulus portion of each average response, and processing the zeroed average responses to generate one or more matrices, each element of which represents information on the ep response at one location on the skull, and

said assessing step includes assessing from said maps whether, as compared to the normal population, there are focal increases of activity.

37. The method of claim 26 wherein said abnormality is a supratentorial lesion and wherein

said tests include causing the patient to assume a resting state with eyes closed and causing the patient to assume a resting state with eyes open,

said processing includes determining the Fourier transforms of the stored responses and determining from the transforms, for each transducer, the spectral energy contained in selected frequency bands, and processing the output of said spectral processing means to generate, for each selected activity, a plurality of matrices, one of said matrices for each selected frequency band, the elements of said matrices representing the spectral energy within the respective frequency band at one location on the skull, and

said assessing step includes assessing from said maps whether, as compared to the normal population, there exists a pattern of hypo- or hyperactive

cortex. 38. The method of claim 26 wherein said abnormality is a supratentorial lesion and wherein

said tests include providing a repeated visual stimulus to the patient to generate repeated ep responses,

said processing includes averaging the repeated responses to produce an average response for each transducer, zeroing each average response using a baseline determined from the pre-stimulus portion of each average response, and processing the zeroed average responses to generate one or more matrices, each element of which represents information on the ep response at one location on the skull, and

said assessing step includes assessing from said maps whether, as compared to the normal population, there are focal increases of activity.

39. The method of claim 26 further comprising the step of selecting one or more features each corresponding to one or more predetermined regions of said maps and to one or more predetermined said tests, said features being indicative of said abnormality, and wherein said selected regions include

said predetermined regions. 40. The method of claim 39 A method of using topographic maps of brain electrical activity to aid diagnosis of a selected brain abnormality in a patient, comprising the steps of:

applying electric activity transducers at spaced apart locations on the skull of the patient,

administering to the patient one or more tests that cause brain electrical activity while simultaneously storing portions of the responses measured by the transducers,

processing the stored responses to generate one or more matrices for each selected brain activity, the one or more matrices having elements representing brain electrical activity at different skull locations,

processing the one or more matrices to generate a significant probability map for each selected brain activity, each statistical probability map having elements representing the statistical difference between the patient and the normal population,

displaying said one or more matrices as topographic maps of the skull, said one or more matrices having discrete points of the said maps, and assessing selected regions of said maps to identify differences in those regions between the patient and the normal population,

selecting one or more features each corresponding to one or more predetermined regions of said maps and to one or more predetermined said tests, said features being indicative of said abnormality, and wherein said selected regions include said predetermined regions, wherein said abnormality is dyslexia, and

one said feature corresponds to a region in the right occipital portion of the skull and to a tight-tyke auditory evoked potential test, and another said feature corresponds to a region in the left rear quadrant of the top

of the skull, and to an auditory (click) evoked potential test. 41. A method for assessing the brain regions in which an epileptic spike originates, comprising the steps of:

applying a plurality of electrical-activity transducers at spaced apart locations on the skull,

causing an epileptic spike to occur while storing responses of said transducers,

processing the responses of said transducers to generate a time sequence of matrices, each said matrix having elements representing the instantaneous amplitudes of said responses at various locations on the skull and there being a sufficient number of said matrices for a selected time period of actual brain activity for capturing onset of the epileptic spike,

displaying said matrices as a time sequence of topographic maps of the skull at a variable frame rate, said matrices having elements defining discrete points of said maps,

selectably slowing the frame rate at which said topographic maps are displayed so as to permit observation of onset of said spike, and

assessing from said display the brain region or regions in which an

epileptic spike originates. 42. A method for generating a topographic display of information on the electrical activity of the brain, said method comprising the steps of

placing a plurality of electrical-activity transducers at spaced apart locations on the skull of a patient,

repeatedly generating a sensory stimulus for the brain to produce at said transducers repeated segments of data each associated with one ep response, said stimulus step including

triggering successive said stimuli at time spaced apart by pseudorandom time intervals, and determining each said pseudorandom time interval as a combination of a subinterval of fixed length and a subinterval of pseudorandomly determined length, each said fixed length subinterval comprising a pre-stimulus subinterval of predetermined length and a post-stimulus subinterval of predetermined length,

averaging said repeated segments to generate average segments for each transducer,

processing said average segments to generate one or more matrices, said one or more matrices having elements,

each of which represents information on the electrical activity of the brain at one location on the skull, and

displaying said matrices as topographic maps of the skull, said matrices

having elements forming discrete points of said maps. 43. A method for generating a topographic display of information on the electrical activity of the brain, said method comprising the steps of

placing a plurality of electrical-activity transducers for placement at spaced apart locations on the skull of a patient,

processing electrical responses measured at said transducers to produce one or more matrices, each of said matrices containing a plurality of elements, said elements representing information on the electrical activity of the brain at particular skull locations,

statistically processing at least two said matrices to generate a statistical comparison matrix, said matrix having elements, each of which is representative of a statistical difference between the corresponding elements in said two matrices,

displaying said statistical comparison matrix as a topographic map of the skull, said matrix elements forming discrete points of said map,

assigning points of said map to sectors of a grid, and

determining the mean of said statistical comparison elements in each said

sector. 44. The apparatus of claim 1 wherein said display means further comprising a scaled color means connected to be responsive to said processing means for producing scaled coloring of said topographic maps of the skull, each said point of said maps having a discrete scaled color. 45. The apparatus of claim 14 wherein said display means further comprising a scaled color means connected to be responsive to said statistical processing means for producing scaled coloring of said topographic maps of the skull, each said point of said maps having a discrete scaled color. 46. The method of claim 25 further comprising the step of processing each matrix element to produce scaled coloring of said topographic maps of the skull, each said point of said

maps having a dicrete scaled color. 47. The method of claim 41 further comprising the step of processing each matrix element to produce scaled coloring of said topographic maps of the skull, each said point of said maps having a discrete scaled color. 48. The method of claim 42 further comprising the step of processing each matrix element to produce scaled coloring of said topographic maps of the skull, each said point of said maps having a discrete scaled color. 49. The method of claim 43 further comprising the step of processing each statistical comparison matrix element to produce scaled coloring of said topographic maps of the skull, each said point of said maps having a discrete scaled color.