Vesna Jelic

Mild cognitive impairment : beyond controversies, towards a consensus : report of the International Working Group on Mild Cognitive Impairment

The First Key Symposium was held in Stockholm, Sweden, 2–5 September 2003. The aim of the symposium was to integrate clinical and epidemiological perspectives on the topic of Mild Cognitive Impairment (MCI). A multidisciplinary, international group of experts discussed the current status and future directions of MCI, with regard to clinical presentation, cognitive and functional assessment, and the role of neuroimaging, biomarkers and genetics. Agreement on new perspectives, as well as recommendations for management and future research were discussed by the international working group. The specific recommendations for the general MCI criteria include the following: (i) the person is neither normal nor demented; (ii) there is evidence of cognitive deterioration shown by either objectively measured decline over time and/or subjective report of decline by self and/or informant in conjunction with objective cognitive deficits; and (iii) activities of daily living are preserved and complex instrumental functions are either intact or minimally impaired.

Quantitative electroencephalography in mild cognitive impairment: longitudinal changes and possible prediction of Alzheimer's disease

The present study evaluated the clinical course of patients with mild cognitive impairment (MCI), the pattern of electroencephalography (EEG) changes following cognitive deterioration, as well as the potential of neurophysiological measures in predicting dementia. Twenty-seven subjects with MCI were followed for a mean follow up period of 21 months. Fourteen subjects (52%) progressed (P MCI) to clinically manifest Alzheimers disease (AD), and 13 (48%) remained stable (S MCI). The two MCI subgroups did not differ in baseline EEG measures between each other and the healthy controls (n = 16), but had significantly lower theta relative power at left temporal, temporo-occipital, centro-parietal, and right temporo-occipital derivation when compared to the reference AD group (n = 15). The P MCI baseline alpha band temporo-parietal coherence, alpha relative power values at left temporal and temporo-occipital derivations, theta relative power values at frontal derivations, and the mean frequency at centro-parietal and temporo-occipital derivations overlapped with those for AD and control groups. After the follow-up, the P MCI patients had significantly higher theta relative power and lower beta relative power and mean frequency at the temporal and temporo-occipital derivations. A logistic regression model of baseline EEG values adjusted for baseline Mini-Mental Test Examination showed that the important predictors were alpha and theta relative power and mean frequency from left temporo-occipital derivation (T5-O1), which classified 85% of MCI subjects correctly.

Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study

OBJECTIVES The spatial aspects of brain electrical activity can be assessed by equivalent EEG frequency band generators. We aimed to describe alterations of these EEG generators in Alzheimers disease (AD) and healthy aging and whether they could serve as predictive markers of AD in subjects at risk. METHODS The amplitude and 3-dimensional localization of equivalent EEG sources were evaluated using FFT dipole approximation in 38 mild AD patients, 31 subjects with mild cognitive impairment (MCI) and 24 healthy control subjects. RESULTS AD patients showed an increase of delta and theta global field power (GFP), which corresponds to the generalized EEG amplitude, as well as a reduction of alpha GFP when compared to the controls. A decrease of alpha and beta GFP was found in AD patients, as compared to the MCI subjects. With respect to topography in the antero-posterior direction, sources of alpha and beta activity shifted more anteriorly in AD patients compared to both the controls and MCI subjects. No significant difference was found between MCI and controls. Combined alpha and theta GFP were the best discriminating variables between AD patients and controls (84% correct classification) and AD and MCI subjects (78% correctly classified). MCI subjects were followed longitudinally (25 months on average) in order to compare differences in baseline EEG variables between MCI subjects who progressed to AD (PMCI) and those who remained stable (SMCI). Compared to SMCI, PMCI had decreased alpha GFP and a more anterior localization of sources of theta, alpha and beta frequency. In a linear discriminant analysis applied on baseline values of the two MCI subgroups, the best predictor of future development of AD was found to be antero-posterior localization of alpha frequency. CONCLUSIONS FFT dipole approximation and frequency analysis performed by conventional FFT showed comparable classification accuracy between the studied groups. We conclude that localization and amplitude of equivalent EEG sources could be promising markers of early AD.

Mild cognitive impairment: a concept in evolution

The construct of mild cognitive impairment (MCI) has evolved over the past 10 years since the publication of the new MCI definition at the Key Symposium in 2003, but the core criteria have remained unchanged. The construct has been extensively used worldwide, both in clinical and in research settings, to define the grey area between intact cognitive functioning and clinical dementia. A rich set of data regarding occurrence, risk factors and progression of MCI has been generated. Discrepancies between studies can be mostly explained by differences in the operationalization of the criteria, differences in the setting where the criteria have been applied, selection of subjects and length of follow‐up in longitudinal studies. Major controversial issues that remain to be further explored are algorithmic versus clinical classification, reliability of clinical judgment, temporal changes in cognitive performances and predictivity of putative biomarkers. Some suggestions to further develop the MCI construct include the tailoring of the clinical criteria to specific populations and to specific contexts. The addition of biomarkers to the clinical phenotypes is promising but requires deeper investigation. Translation of findings from the specialty clinic to the population setting, although challenging, will enhance uniformity of outcomes. More longitudinal population‐based studies on cognitive ageing and MCI need to be performed to clarify all these issues.

Impaired cerebral glucose metabolism and cognitive functioning predict deterioration in mild cognitive impairment

The objective of this study was to assess whether reduced glucose metabolism (rCMRGlu) and cognitive functioning could predict development of Alzheimers disease (AD) in subjects with mild cognitive impairment (MCI). Twenty MCI patients underwent baseline and follow-up investigations of rCMRGlu, as measured by PET, and cognitive function measured by neuropsychological test assessments. Subjects were clinically followed up with an average interval of 36.5 months. Two groups were obtained after the second clinical assessment. Nine patients were diagnosed as AD and classified as progressive MCI (P-MCI), whereas 11 patients remained clinically stable and were classified as stable MCI (S-MCI). There were no differences in demographic variables or baseline MMSE between the two subgroups. Logistic regression indicated the two variables that most effectively predicted future development of AD were rCMRGlu from the left temporoparietal area and performance on the block design. These combined measures gave an optimal 90% correct classification rate, whereas only rCMRGlu or neuropsychology alone gave 75% and 65% correct classification, respectively. Measures of temporoparietal cerebral metabolism and visuospatial function may aid in predicting the evolution to AD for patients with MCI.

Decreased EEG synchronization in Alzheimer's disease and mild cognitive impairment.

The hypothesis of a functional disconnection of neuro-cognitive networks in patients with mild cognitive impairment (MCI) and Alzheimer Dementia was investigated using baseline resting EEG data. EEG databases from New York (264 subjects) and Stockholm (155 subjects), including healthy controls and patients with varying degrees of cognitive decline or Alzheimer Dementia were analyzed using Global Field Synchronization (GFS), a novel measure of global EEG synchronization. GFS reflects the global amount of phase-locked activity at a given frequency by a single number; it is independent of the recording reference and of implicit source models. Patients showed decreased GFS values in Alpha, Beta, and Gamma frequency bands, and increased GFS values in the Delta band, confirming the hypothesized disconnection syndrome. The results are discussed within the framework of current knowledge about the functional significance of the affected frequency bands.

Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer's disease

BACKGROUND Since the measurement of human cerebral glucose metabolism (GluM) by positron emission tomography (PET) and that of human cerebral electrical activity by EEG reflect synaptic activity, both methods should be related in their cerebral spatial distribution. Healthy subjects do indeed demonstrate similar metabolic and neuroelectric spatial patterns. OBJECTIVE The aim of the study was to show that this similarity of GluM and EEG spatial patterns holds true in a population with a high variability of glucose metabolism. METHODS We investigated healthy control subjects and patients with varying degrees of cognitive dysfunction and varying GluM patterns by applying [18F]FDG PET and EEG. RESULTS We demonstrated that the localization of intracerebral generators of EEG correlates with spatial indices of GluM. CONCLUSION These results indicates that EEG provides similar spatial information about brain function as GluM-PET. Since EEG is a non-invasive technique, which is more widely available and can be repeated more often than PET, this may have important implications both for neuropsychiatric research and for clinical diagnosis. However, further studies are required to determine whether equivalent EEG dipole generators can yield a diagnostic specificity and sensitivity similar to that of GluM-PET.

A critical discussion of the role of neuroimaging in mild cognitive impairment

Objective – In this paper, the current neuroimaging literature is reviewed with regard to characteristic findings in mild cognitive impairment (MCI). Particular attention is drawn to the possible value of neuroimaging modalities in the prediction and early diagnosis of Alzheimers disease (AD).

Quantitative Electroencephalography Power and Coherence in Alzheimer's Disease and Mild Cognitive Impairment

In this study the best combination of quantitative electroencephalographic variables (qEEG) for the discrimination of groups with mild to moderate Alzheimers disease (AD), mild cognitive impairment and healthy subjects was defined and related to neuropsychological performance. The study population included 18 patients with mild to moderate probable AD, 19 subjects with objective memory disturbance, 17 subjects with subjective memory complaints who did not have clinical evidence of memory disturbance, and 16 healthy controls. AD patients had significantly increased theta and decreased alpha relative power, mean frequency, and temporoparietal coherence. There was no significant difference in the mean frequency in the left temporal region between AD patients and subjects with objective memory disturbances. Temporoparietal coherence appeared as a discriminant variable together with alpha and theta relative power only between AD patients and controls giving 77.8% sensitivity and 100% specificity. Significant correlations between regional changes in qEEG variables and cognitive functions were found.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimers disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.