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Mohammed T. Abou-Saleh

Mohammed T. Abou-Saleh

Mohammed T. Abou-Saleh

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EEG 347the EEG predicts survival time while the extent of cortical activitydoes not 22 .THE APPLICATION OF QUANTITATIVEELECTROENCEPHALOGRAPHYRecent computerized EEG (CEEG) investigations have usedfrequency spectral analyses of the background activity and havegenerally replicated the earlier reports obtained by visualinspection of the EEG tracings. An overall slowing in meanEEG frequency is an invariable finding, with relative powerincreases in the slower frequencies (theta/delta) and decreases inthe fast (beta) frequencies. The degree of frequency slowingcorrelates reasonably well with clinical ratings of dementiaseverity, e.g. Mini-Mental State and Clinical Dementia ratingscales.Is there a Relationship to Clinical Severity?Alterations in the distribution of power across the variousfrequency bands seem to relate to the severity of the dementingprocess. In less severe cases, the main changes are increases intheta and reductions in beta power. When the disease is advanced,the respective amounts of delta and alpha power are also affected,the former being increased and the latter reduced. Theseassociations have been observed during cross-sectional studies,there being a paucity of longitudinal investigations.What <strong>Abou</strong>t Early Cases?Much of the work has been on populations of patients withestablished AD being cared for in hospital. A number of recentstudies have examined mild probable AD patients (clinicaldementia ratings of 1) compared to age-matched controls. Thesehave replicated the earlier findings of frequency spectral slowingwhich have a specificity of virtually 100% 23 . However, thesensitivity is only 20%. This means that only one in five of earlycases of AD will have CEEG findings that deviate three standarddeviations from the mean and therefore fall into the AD range.The Potential Role of Brain MappingA new development in EEG technology has been brain electricalactivity mapping (BEAM). This involves sampling the corticalelectrical activity from multiple scalp electrodes and calculatingthe distribution of voltage across the whole of the scalp using amathematical interpolation method. The patterns of scalp voltagedistribution are displayed as colour-coded contour maps. Thistechnique investigates the patterns of electrical activity generatedat the same time by different areas of cerebral cortex. It can beused to detect regional differences and promises to be a useful toolin the investigation of the dementias. Several investigators haveused multichannel or BEAM recordings to demonstrate localizedleft temporal lobe delta power abnormalities, which may in ADpatients be an early manifestation of the disease 24–27 . Hence,BEAM may prove especially useful in the early detection ofdementia.Does the CEEG Change as the Dementia Progresses?The few longitudinal CEEG studies that have been carried outover several years give conflicting results. Some report significantdecreases in mean frequency over time, with increases in delta/theta power and reduced alpha and beta activity 28–29 , but othershave found either statistically insignificant trends in the directionof frequency slowing or that only about half of AD patients showprogressive EEG changes over 12 months 30–31 . It is noteworthythat the negative reports deal with relatively short time scales; 18months or less. This may not be long enough to establishsignificant progression. There is also some evidence that frontallobe quantitative changes may precede more generalized slowing31 .Differences between AD and MIDFew CEEG investigations have investigated the question ofquantitative differences between AD and MID patients. Arecently completed study in my laboratory reveals significantlygreater amounts of delta power and less alpha power in thetemporal and parieto-occipital areas of both hemispheres in ADpatients, compared to those with a clinical diagnosis of multiinfarctdementia. As well as having less alpha power, the peakalpha frequency is slower in AD patients with mean values of 7 Hzand 8 Hz in AD and MID subjects, respectively, and significantasymmetry between the hemispheres in the MID patients 31 .The degrees of synchrony between different areas of cortexwithin each cerebral hemisphere and between homologous areasof the right and left hemisphere can be assessed by coherencespectral analyses, which measures the similarity between pairs ofEEG signals generated by different cortical areas. The coherencefunction is essentially a frequency correlation coefficient andmeasures the correlation at each frequency. It varies from 0(signals quite different) to +1.0 (signals identical).The main coherence differences between the AD and MIDpatient are seen in the temporal and parieto-occipital areas ofboth hemispheres. Compared to the MID patients, the withinhemispherealpha and beta synchrony is lower in AD subjects.The pattern of between-hemisphere synchrony is different, beinghigher in AD patients for theta components between the temporalareas and lower for the alpha and beta frequencies between theparieto-occipital areas 31 .Do Elderly Patients with ‘‘Non-organic’’ Psychiatric IllnessDeviate from Normals?In my laboratory we have also investigated age-matched controlsand elderly patients with major depressive illness. Compared tothe normals, the depressive patients had significantly more thetapower and less alpha power, such changes being maximal in thetemporal regions. Indeed, the mean spectral values of the threepatient groups could be ranked roughly according to degree ofdeviation from the healthy controls. The AD patients were themost deviant, then those with MID, and finally the depressedpatients. The deviation of the elderly depressives from the healthycontrols raises the issue of the contribution of organic braindisease to the genesis of affective disorder in old age, as suggestedby current CT and single photon emission computed tomography(SPECT) scan work 32,33 .EVENT-RELATED POTENTIALS IN DEMENTIAWhat is an Event-related Potential?Event-related or evoked potentials (ERPs or EPs) consist oftransient voltage changes that occur in response to a sensorystimulus. These take the form of a series of negative and positive

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