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OBJECTIVE: EEG coherence is decreased in Alzheimer's disease (AD), suggesting decreased interaction between brain areas. Nonlinear EEG analysis in AD points to decreased complexity of brain dynamics, implicating increased interaction. To clarify these apparently paradoxical findings from linear and nonlinear analysis, we calculated global coherence and global correlation dimension (D2), a nonlinear measure, in the EEG of patients with probable AD and controls. Our hypothesis is that these measures are related to each other when calculated in a comparable way. METHODS: From 15 patients with probable AD (mean age 63.1 years; SD 6.3) and 21 age-matched controls with subjective memory complaints (mean age 62.8; SD 12.0), band filtered EEG data were analysed in six frequency bands. For each frequency band average coherence and multichannel D2 were determined. RESULTS: ANOVA for repeated measures showed for D2 an interaction between band and group, but not for coherence. In the beta band and upper alpha band, D2 was higher in patients with probable AD compared to controls, while global coherence tended to be lower in these frequency bands in patients with probable AD. In the frequency range from theta to beta, coherence and D2 were inversely correlated without group differences. CONCLUSIONS: When calculated in comparable ways, global correlation dimension and coherence are related measures. In AD, these measures change especially in the higher frequency ranges, both pointing to decreased functional cortical connectivity. SIGNIFICANCE: Both global coherence and global correlation dimension seem to measure global connectivity, but nonlinear measures may be more sensitive. In AD, connectivity measures are not equally impaired in all frequency ranges, possibly reflecting differentiated affection of the dynamical processes responsible for the different frequency bands.

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We present three patients with a clinical course and cerebrospinal fluid findings consistent with a diagnosis of primary progressive multiple sclerosis (PPMS). Extensive and repeated magnetic resonance imaging (MRI) examinations showed only diffuse abnormality in brain and spinal cord, but no focal lesions. We propose that these cases represent the most pure form of PPMS, even though according to currently applied criteria this diagnosis can not be made in the absence of focal lesions on MRI.

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OBJECTIVE: To validate the newly developed Multiple Sclerosis Impact Scale (MSIS-29) in a large, well characterized, independent group of MS patients by investigating the relation between the MSIS-29 and the Guy's Neurological Disability Scale (GNDS), the Expanded Disability Status Scale (EDSS) and the MS Functional Composite (MSFC). METHODS: Two hundred MS patients were recruited at our outpatient department. At the same visit GNDS, EDSS, MSFC and MSIS-29 were assessed. Data obtained from GNDS, EDSS and MSFC assessment were compared to both physical and psychological impact scores of the MSIS-29. In addition the contribution of GNDS subcategories, EDSS functional systems and MSFC components to the physical and psychological impact scores of the MSIS-29 was studied. RESULTS: Median scores were 37.5 for the physical and 22.2 for the psychological impact score of the MSIS-29, 13.0 for GNDS and 4.0 for EDSS. Mean MSFC was 0.07. The physical impact score showed good correlations with both GNDS (0.79) and EDSS (0.68) and a moderate correlation with the MSFC (-0.53). The psychological impact score showed weak correlations with EDSS (0.22) and MSFC (-0.30) and a moderately strong correlation with the GNDS (0.58). In 50 (25%) patients, scores on physical and psychological impact scales diverted, i.e., a relative high score on one scale combined with a relative low score on the other scale. This was related to the clinical disease course. CONCLUSION: Our study supports the use of the MSIS-29 as a measure for the assessment of physical impact of MS on normal daily life. In addition, our data provides a deeper understanding of the factors that determine both physical and psychological disease impact. Discrepancies between the latter two aspects deserve further attention.

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OBJECTIVE: To analyse the value of the INTERMED, a screening instrument to assess case complexity, compared with the Expanded Disability Status Scale (EDSS) and the Guy's Neurological Disability Scale (GNDS) to identify multiple sclerosis (MS) patients in need of multidisciplinary treatment. METHODS: One hundred MS patients underwent INTERMED, EDSS, and GNDS examinations. Patient care needs were assessed by a multidisciplinary team and a goal oriented treatment plan was defined. Correlations between INTERMED, individual INTERMED domains, EDSS, GNDS sum score, and total number of proposed disciplines involved in the treatment plan were studied. RESULTS: Mean (SD) age was 40.6 (10.1) years. Median scores were 14.0 for the INTERMED, 4.0 for the EDSS, and 13.5 for the GNDS sum score. Moderate correlations were found between the INTERMED sum score and EDSS (r=0.59) and GNDS sum score (r=0.60). The number of disciplines as proposed by the multidisciplinary team showed the highest statistically significant correlation with the INTERMED sum score (r=0.41) compared with EDSS (r=0.32) and GNDS sum score (r=0.34). No significant or only weak correlations were found between the psychological domain of the INTERMED and EDSS or GNDS. CONCLUSION: The findings in this study show that there is an additional value of the INTERMED compared with the EDSS and GNDS in identifying MS patients in need of multidisciplinary treatment. The INTERMED domains show the area of the patient's vulnerability and care needs: especially the INTERMED's psychological and social domains may guide the clinician to deal with specific problems that complicate healthcare delivery.

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OBJECTIVES: To determine the quality of life (QoL) of MS patients during the initial 6 months of treatment with interferon-beta (IFN-beta). Furthermore, to determine whether changes in QoL relate to disability, emotional state, therapeutic expectations or side effect profile. BACKGROUND: IFN-beta has been shown to have beneficial effects on the course of MS. Since the aim of IFN-beta treatment is not to cure but to slow down the disease it is important to know how this treatment affects QoL. Surprisingly, the impact of treatment with IFN-beta on QoL measures has not been extensively studied so far. METHODS: Case report documentation, including EDSS, SF-36 and MADRAS scores, of 51 relapsing-remitting MS patients treated with IFN-beta was obtained at baseline and at months 1, 3 and 6. Patients also filled in a form about their expectations of therapy and a questionnaire on side effects. RESULTS: During treatment there was a significant linear trend indicating improvement in the role-physical functioning (RPF) scale of the SF-36 (F(1,50)=4.9, P=0.032). A transient decrease at month 1 was found in the scale for bodily pain, indicating more experienced pain (F(1,50)=19.8, P<0.001). Subgroup analysis showed that patients with most depressive symptoms on the MADRAS at baseline contributed most to the increase in RPF scores over time (F(1,24)=5,6 P=0.026). Furthermore, we found associations between adverse event scores and several domains of QoL. CONCLUSIONS: Our findings suggest that IFN-beta therapy has an impact on QoL of MS patients in that it improves role-physical functioning and transiently worsens experienced bodily pain. QoL during treatment with IFN-beta is influenced by depressive symptoms at baseline as well as by treatment-associated side-effects. Multiple Sclerosis (2000) 6 338 - 342

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Nonlinear EEG analysis attempts to characterize the dynamics of neural networks in the brain. Abnormalities in nonlinear EEG measures have been found repeatedly in Alzheimer's disease (AD). The present study was undertaken to investigate whether these abnormalities could already be found in the early stage of AD. In a representative sample of 49 community-dwelling elderly, Alzheimer's disease was diagnosed in 7 subjects. Correlation dimension (D2) and nonlinear prediction were measured at 16 electrodes and in two different activational states. Also, 10 surrogate data sets were generated for each EEG epoch in order to investigate the presence of nonlinear dynamics. Differences between nonlinear statistics derived from original and from surrogate data sets were expressed as Z-scores. We found lower D2 and higher predictability in the demented subjects compared to the normal subjects. The results obtained with the Z-scores pointed to changed nonlinear dynamics in frontal and temporal areas in demented subjects. However, the major differences between demented and healthy subjects are not due to nonlinearity. From this it appears that linear dynamics change first in the course of AD, followed by changes in nonlinear dynamics.

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OBJECTIVE: Non-linear EEG analysis can provide information about the functioning of neural networks that cannot be obtained with linear analysis. The correlation dimension (D2) is considered to be a reflection of the complexity of the cortical dynamics underlying the EEG signal. The presence of non-linear dynamics can be determined by comparing the D2 calculated from original EEG data with the D2 from phase-randomized surrogate data. METHODS: In a prospective study, we used this method in order to investigate non-linear structure in the EEG of Alzheimer patients and controls. Twenty-four patients (mean age 75.6 years) with 'probable Alzheimer's disease' (NINCDS-ADRDA criteria) and 22 controls (mean age 70.3 years) were examined. D2 was calculated from original and surrogate data at 16 electrodes and in three conditions: with eyes open, eyes closed and during mental arithmetic. RESULTS: D2 was significantly lower in the Alzheimer patients compared to controls (P = 0.023). The difference between original and surrogate data was significant in both groups, implicating that non-linear dynamics play a role in the D2 value. Moreover, this difference between original and surrogate data was smaller in the patient group. D2 increased with activation, but not significantly more in controls than in patients. CONCLUSIONS: In conclusion, we found decreased dimensional complexity in the EEG of Alzheimer patients. This decrease seems to be attributable at least partially to different non-linear EEG dynamics. Because of this, non-linear EEG analysis could be a useful tool to increase our insight into brain dysfunction in Alzheimer's disease.

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The sensitivity of the EEG in early AD is somewhat limited. In this respect spectral analysis is little better than visual assessment. In this study we address the question whether a new type of EEG analysis derived from chaos theory can improve the sensitivity of the EEG. EEGs were recorded in 15 control subjects and 15 patients with mild AD. The EEG recorded at 02 and 01 during eyes closed and eyes open conditions was subjected to spectral analysis (relative power) and nonlinear analysis (calculation of the correlation dimension D2). AD patients had more relative theta power and impaired reactivity in alpha, delta and theta bands. Also, reactivity of the D2 was impaired in AD subjects. For a specificity of 100%, relative theta power had the highest sensitivity (46.7%). Alpha band reactivity at O1 had a sensitivity of 40% and D2 reactivity at O1 had a sensitivity of 33.3%. Combining theta power with alpha reactivity resulted in a sensitivity of 53.3%; combining theta with D2 reactivity resulted in a sensitivity of 60%. Used in isolation, linear analysis was superior in differentiating AD patients from controls. The best results were obtained by combining linear with nonlinear measures. This approach does not seem practical yet, but deserves further study.

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Many recent studies based on the surrogate data method failed to identify significant non-linearity in the EEG. In this study we examine whether the use of a different embedding method (spatial instead of time delay), and calculation of Kolmogorov entropy (K2) and the largest Lyapunov exponent (L1) in addition to the correlation dimension (D2), can distinguish the EEG form linearly filtered noise. We have calculated D2, L1 and K2 of original EEG epochs and surrogate (phase randomized) data in 9 control subjects, 9 demented patients and 13 Parkinson patients. The correlation dimension D2 and the largest Lyapunov exponent L1 could distinguish between the EEG tracings and the surrogate data. Demented patients had significantly lower D2 and L1 compared to controls. L1 was higher in Parkinson patients than in demented patients. Contrary to other studies that have used the Theiler surrogate data method, we find evidence for non-linearity in normal and abnormal EEG during the awake/eyes closed state. Apparently it is the spatial structure in the EEG that exhibits much of the non-linear structure. Furthermore, non-linear EEG measures show more or less specific patterns of dysfunction in dementia and Parkinson's disease.

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Acceleration spectrum entropy (ASE) was used to quantify EEG desynchronization, which is related to cortical activation. We investigated the ASE in control and patient groups with dementia (AD) and Parkinson's disease (PD). Both patient groups had significantly lower ASE scores corresponding with less desynchronization in all cortical regions. In the AD group, the ASE was significantly lower in the parietal region. ASE was found to be a sensitive and specific measure for differentiating patient groups with AD and PD from controls and from each other.

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The irregular, aperiodic character of the EEG is usually explained by a stochastic model. In this view the EEG is linearly filtered noise. According to chaos theory such irregular signals can also result from low dimensional deterministic chaos. In this case the underlying dynamics is nonlinear, and has only few effective degrees of freedom. In contrast, stochastic models are less efficient, because they require in principle infinite degrees of freedom. Chaotic dynamics in the EEG can be studied by calculating the correlation dimension (D2). Although it has become clear that D2 calculations alone cannot prove chaos, the D2 has potential value as an EEG diagnostic. In this study we investigated whether D2 could be used to discriminate EEGs from normal controls, demented patients and Parkinson patients. We have analyzed epochs (20 channels; 2.5 s) from 52 EEGs (20 controls; 15 patients with dementia; 17 patients with Parkinson's disease). Controls had a mean D2 of 6.5 (0.9); demented patients of 4.4 (1.5), and Parkinson patients of 5.3 (0.9). Both groups were significantly different from controls (p < 0.001). There was a significant positive correlation between D2 and relative power in the beta band (r = 0.81) and a significant negative correlation between D2 and power in the delta (r = -0.60) and theta band (r = -0.37). These results suggest the possible usefulness of multichannel D2 estimation in a clinical setting.

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