EEG abnormalities have been reported for both dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). Although it has been suggested that variations in mean EEG frequency are greater in the former, the existence of meaningful differences remains controversial. No evidence is as yet available for Parkinson's disease with dementia (PDD). The aim of this study was to evaluate whether EEG abnormalities can discriminate between DLB, AD and PDD in the earliest stages of dementia and to do this 50 DLB, 50 AD and 40 PDD patients with slight cognitive impairment at first visit (MMSE > or = 20) were studied. To improve clinical diagnostic accuracy, special emphasis was placed on identifying cognitive fluctuations and REM-sleep behaviour disorder. EEG variability was assessed by mean frequency analysis and compressed spectral arrays (CSA) in order to detect changes over time from different scalp derivations. Patients' initial diagnoses were revised at a 2-year follow-up visit with neuroimaging evaluation. Initial diagnoses were confirmed in 36 DLB, 40 AD and 35 PDD patients. The most relevant group differences were observed between the AD and DLB patients in EEGs from posterior derivations (P<0.001). Dominant frequencies were 8.3 +/- 0.6 Hz for the AD group and 7.4 +/- 1.6 Hz for the DLB group, in which most of the patients (88%) exhibited a frequency band of 5.6-7.9 Hz. Dominant frequency variability also differed between the AD (1.1 +/- 0.4 Hz) and DLB groups (1.8 +/- 1.2 Hz, P<0.001). Of note, less than a half (46%) of the patients with PDD exhibited the EEG abnormalities seen in those with DLB. Graded according to the presence of alpha activity, five different patterns were identified on EEG CSA from posterior derivations. A pattern with dominant alpha bands was observed in patients with AD alone while, in those with DLB and PDD, the degree to which residual alpha and 5.6-7.9 bands appeared was related to the presence and severity of cognitive fluctuations. At follow-up, EEG abnormalities from posterior leads were seen in all subjects with DLB and in three-quarters of those with PDD. Of interest, in four patients initially labelled as having AD, in whom the occurrence of fluctuations and/or REM-sleep behaviour disorder during the 2-year follow-up had made the diagnosis of AD questionable, the initial EEG was characterized by the features observed in the DLB group. If revised consensus criteria for DLB diagnosis are properly applied (i.e. emphasizing the diagnostic weight of fluctuations and REM sleep behaviour disorder), EEG recording may act to support discrimination between AD and DLB at the earliest stages of dementia, since characteristic abnormalities may even precede the appearance of distinctive clinical features.

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Mild cognitive impairment (MCI) as a precursor of dementia with Lewy bodies (DLB) is the focus of recent research, trying to explore the early mechanisms and possible biomarkers of DLB. Quantitative electroencephalogram (QEEG) methods are able to differentiate early DLB from Alzheimer's disease (AD). The aim of the present study was to assess whether QEEG abnormalities, characterized by dominant frequency <8 Hz and dominant frequency variability >1.5 Hz, typical of early DLB, are already present at the stage of MCI and to evaluate whether EEG abnormalities can predict the development of DLB. Forty-seven MCI subjects were followed for 3 years. EEG recordings were obtained at admission and at the end of the study. At the end of follow-up, 20 subjects had developed probable DLB (MCI-DLB), 14 had probable AD (MCI-AD), 8 did not convert to dementia, 5 developed a non-AD/DLB dementia. One hundred percent of MCI-DLB showed EEG abnormalities at admission. Ninety three percent of MCI-AD maintained a normal EEG throughout the study. QEEG may represent a powerful tool to predict the progression from MCI to DLB with a sensitivity and specificity close to 100%.

.2010. In this study, we characterized the patterns and timing of cortical activation of visually guided movements in a task with critical temporal demands. In particular, we investigated the neural correlates of motor planning and on-line adjustments of reaching movements in a choice-reaction time task. High-density electroencephalograohy (EEG, 256 electrodes) was recorded in 13 subjects performing reaching movements. The topography of the movement-related spectral perturbation was established across five 250-ms temporal windows (from prestimulus to postmovement) and five frequency bands (from theta to beta). Nine regions of interest were then identified on the scalp, and their activity was correlated with specific behavioral outcomes reflecting motor planning and on-line adjustments. Phase coherence analysis was performed between selected sites. We found that motor planning and on-line adjustments share similar topography in a fronto-parietal network, involving mostly low frequency bands. In addition, activities in the high and low frequency ranges have differential function in the modulation of attention with the former reflecting the prestimulus, top-down processes needed to promote timely responses, and the latter the planning and control of sensory-motor processes.

Default mode network activity and connectivity was higher in PD with visual hallucinations and reduced in multiple system atrophy and PD without visual hallucinations. Cortical thickness comparisons suggest that functional, rather than structural, changes underlie the activity and connectivity differences.

BackgroundThe relationship between apathy, depression and cognitive impairment in Parkinson's disease (PD) is still controversial. The objective of this study is to investigate whether apathy and depression are associated with inefficient cognitive strategies in PD.MethodsIn this prospective clinical cohort study conducted in a university-based clinical and research movement disorders center we studied 48 PD patients. Based on clinical evaluation, they were classified in two groups: PD with apathy (PD-A group, n = 23) and PD without apathy (PD-NA group, n = 25). Patients received clinical and neuropsychological evaluations. The clinical evaluation included: Apathy Evaluation Scale-patient version, Hamilton Depression Rating Scale-17 items, the Unified Parkinson's Disease Rating Scale and the Hoehn and Yahr staging system; the neuropsychological evaluation explored speed information processing, attention, working memory, executive function, learning abilities and memory, which included several measures of recall (immediate free, short delay free, long delay free and cued, and total recall).FindingsPD-A and PD-NA groups did not differ in age, disease duration, treatment, and motor condition, but differed in recall (p<0.001) and executive tasks (p<0.001). Immediate free recall had the highest predictive value for apathy (F =  10.94; p = 0.002). Depression and apathy had a weak correlation (Pearson index  = 0.3; p<0.07), with three items of the depression scale correlating with apathy (Pearson index between .3 and.4; p<0.04). The depressed and non-depressed PD patients within the non-apathetic group did not differ.ConclusionApathy, but not depression, is associated with deficit in implementing efficient cognitive strategies. As the implementation of efficient strategies relies on the fronto-striatal circuit, we conclude that apathy, unlike depression, is an early expression of executive impairment in PD.

The formation of new motor memories, which is fundamental for efficient performance during adaptation to a visuo-motor rotation, occurs when accurate planning is achieved mostly with feedforward mechanisms. The dynamics of brain activity underlying the switch from feedback to feedforward control is still matter of debate. Based upon the results of studies in declarative learning, it is likely that phase synchronization of low and high frequencies as well as their temporal modulation in power amplitude underlie the formation of new motor memories during visuo-motor adaptation. High density-EEG (256 electrodes) was recorded in 17 normal human subjects during adaptation to a visuo-motor rotation of 60° in four incremental steps of 15°. We found that initial learning is associated with enhancement of gamma power in a right parietal region during movement execution as well as gamma/theta phase coherence during movement planning. Late stages of learning are instead accompanied by an increase of theta power over that same right parietal region during movement planning, which is correlated with the degree of learning and retention. Altogether, these results suggest that the formation of new motor memories and thus, the switch from feedback to feedforward control, is associated with the modulation of gamma and theta spectral activities, with respect to their amplitude and phase, during movement planning and execution. Specifically, we propose that gamma/theta phase coupling plays a pivotal role in the integration of a new representation into motor memories.

Fluid intelligence (gf) refers to abstract reasoning and problem solving abilities. It is considered a human higher cognitive factor central to general intelligence (g). The regions of the cortex supporting gf have been revealed by recent bioimaging studies and valuable hypothesis on the neural correlates of individual differences have been proposed. However, little is known about the interaction between individual variability in gf and variation in cortical activity following task complexity increase. To further investigate this, two samples of participants (high-IQ, N = 8; low-IQ, N = 10) with significant differences in gf underwent two reasoning (moderate and complex) tasks and a control task adapted from the Raven progressive matrices. Functional magnetic resonance was used and the recorded signal analyzed between and within the groups. The present study revealed two opposite patterns of neural activity variation which were probably a reflection of the overall differences in cognitive resource modulation: when complexity increased, high-IQ subjects showed a signal enhancement in some frontal and parietal regions, whereas low-IQ subjects revealed a decreased activity in the same areas. Moreover, a direct comparison between the groups' activation patterns revealed a greater neural activity in the low-IQ sample when conducting moderate task, with a strong involvement of medial and lateral frontal regions thus suggesting that the recruitment of executive functioning might be different between the groups. This study provides evidence for neural differences in facing reasoning complexity among subjects with different gf level that are mediated by specific patterns of activation of the underlying fronto-parietal network.