J.L.W. Bosboom

Cognitive dysfunction and dementia in Parkinson’s disease

Summary.Parkinson’s disease (PD) is a slowly progressive neurodegenerative disorder mainly characterized by degeneration of dopaminergic neurons in the substantia nigra and the ventral tegmental area, in combination with a varying loss of central noradrenergic (locus coeruleus), cholinergic (nucleus basalis of Meynert) and serotonergic (dorsal raphe nuclei) integrity, leading to a multitude of motor and non-motor behavioral disturbances.Apart from the clinical motor hallmarks, in the early stages of disease, subtle cognitive dysfunction might be seen comprising mainly executive dysfunction, with secondary visuospatial and mnemonic disturbances. In about 20–40% of patients, these problems may eventually proceed to dementia, which constitutes an important risk factor for caregiver distress, decreased quality of life and nursing home placement. Dementia in PD is typically characterized by a progressive dysexecutive syndrome with attentional deficits and fluctuating cognition, often accompanied by psychotic symptoms. It is thought to be the result of a combination of both subcortical and cortical changes. PD-related dopaminergic deficiency in the nucleus caudatus and mesocortical areas (due to degeneration of projections from the substantia nigra and ventral tegmental area) and cholinergic deficiency in the cortex (due to degeneration of ascending projections from the nucleus basalis of Meynert), combined with additional Alzheimer-pathology and cortical Lewy bodies, may greatly contribute to dementia.Current treatment of dementia in PD is based on compensation of the profound cholinergic deficiency. Recent studies with the cholinesterase inhibitors galantamine, donepezil and rivastigmine show promising results in improving cognition and ameliorating psychotic symptoms, which must further be confirmed in randomized controlled trials.

Frequency-dependent functional connectivity within resting-state networks: An atlas-based MEG beamformer solution

The brain consists of functional units with more-or-less specific information processing capabilities, yet cognitive functions require the co-ordinated activity of these spatially separated units. Magnetoencephalography (MEG) has the temporal resolution to capture these frequency-dependent interactions, although, due to volume conduction and field spread, spurious estimates may be obtained when functional connectivity is estimated on the basis of the extra-cranial recordings directly. Connectivity estimates on the basis of reconstructed sources may similarly be affected by biases introduced by the source reconstruction approach. Here we propose an analysis framework to reliably determine functional connectivity that is based around two main ideas: (i) functional connectivity is computed for a set of atlas-based ROIs in anatomical space that covers almost the entire brain, aiding the interpretation of MEG functional connectivity/network studies, as well as the comparison with other modalities; (ii) volume conduction and similar bias effects are removed by using a functional connectivity estimator that is insensitive to these effects, namely the Phase Lag Index (PLI). Our analysis approach was applied to eyes-closed resting-state MEG data for thirteen healthy participants. We first demonstrate that functional connectivity estimates based on phase coherence, even at the source-level, are biased due to the effects of volume conduction and field spread. In contrast, functional connectivity estimates based on PLI are not affected by these biases. We then looked at mean PLI, or weighted degree, over areas and subjects and found significant mean connectivity in three (alpha, beta, gamma) of the five (including theta and delta) classical frequency bands tested. These frequency-band dependent patterns of resting-state functional connectivity were distinctive; with the alpha and beta band connectivity confined to posterior and sensorimotor areas respectively, and with a generally more dispersed pattern for the gamma band. Generally, these patterns corresponded closely to patterns of relative source power, suggesting that the most active brain regions are also the ones that are most-densely connected. Our results reveal for the first time, using an analysis framework that enables the reliable characterisation of resting-state dynamics in the human brain, how resting-state networks of functionally connected regions vary in a frequency-dependent manner across the cortex.

Resting state oscillatory brain dynamics in Parkinson's disease: an MEG study.

OBJECTIVE The pathophysiological mechanisms of cognitive dysfunction and dementia in Parkinsons disease (PD) are still poorly understood. Altered resting state oscillatory brain activity may reflect underlying neuropathological changes. The present study using magneto encephalography (MEG) was set up to study differences in the pattern of resting state oscillatory brain activity in groups of demented and non-demented PD patients and healthy, elderly controls. METHODS The pattern of MEG background oscillatory activity was studied in 13 demented PD patients, 13 non-demented PD patients and 13 healthy controls. Whole head MEG recordings were obtained in the morning in an eyes closed and an eyes open, resting state condition. Relative spectral power was calculated using Fast Fourier Transformation in delta, theta, alpha, beta and gamma frequency bands. RESULTS In the non-demented PD patients, relative theta power was diffusely increased and beta power concomitantly decreased relative to controls. gamma Power was decreased in central and parietal channels. In the demented PD patients, a diffuse increase in relative delta and to lesser extent theta power and a decrease in relative alpha, beta and to lesser extent gamma power were found in comparison to the non-demented PD group. In addition, reactivity to eye opening was much reduced in the demented PD group. CONCLUSIONS Parkinsons disease is characterized by a slowing of resting state brain activity involving theta, beta and gamma frequency bands. Dementia in PD is associated with a further slowing of resting state brain activity, additionally involving delta and alpha bands, as well as a reduction in reactivity to eye-opening. SIGNIFICANCE The differential patterns of slowing of resting state brain activity in demented and non-demented PD patients suggests that, in conjunction with a progression of the pathological changes already present in non-demented patients, additional mechanisms are involved in the development of dementia in PD.

MEG resting state functional connectivity in Parkinson's disease related dementia

Parkinson’s disease (PD) related dementia (PDD) develops in up to 60% of patients, but the pathophysiology is far from being elucidated. Abnormalities of resting state functional connectivity have been reported in Alzheimer’s disease (AD). The present study was performed to determine whether PDD is likewise characterized by changes in resting state functional connectivity. MEG recordings were obtained in 13 demented and 13 non-demented PD patients. The synchronization likelihood (SL) was calculated within and between cortical areas in six frequency bands. Compared to non-demented PD, PDD was characterized by lower fronto-temporal SL in the alpha range, lower intertemporal SL in delta, theta and alpha1 bands as well as decreased centro-parietal gamma band synchronization. In addition, higher parieto-occipital synchronization in the alpha2 and beta bands was found in PDD. The observed changes in functional connectivity are reminiscent of changes in AD, and may reflect reduced cholinergic activity and/or loss of cortico-cortical anatomical connections in PDD.

Cholinergic modulation of MEG resting-state oscillatory activity in Parkinson’s disease related dementia

OBJECTIVE EEG and MEG studies in Parkinsons disease (PD) related dementia (PDD) have shown a slowing of resting-state, oscillatory activity compared to non demented PD. Aim of the present MEG study was to determine whether treatment with the cholinesterase inhibitor rivastigmine would reverse this slowing of resting-state activity in PDD patients. METHODS In eight PDD patients, whole head MEG was recorded in a resting-state condition before and after treatment with rivastigmine. Relative spectral power was calculated in the delta, theta, alpha, beta and gamma frequency bands in fronto-central, parieto-occipital and temporal regions. RESULTS After treatment with rivastigmine, PDD patients demonstrated an increase in relative power in the alpha range in parieto-occipital and temporal regions together with a diffuse increase in beta power. Furthermore, a decrease of delta power in fronto-central and parieto-occipital regions was found. CONCLUSIONS Treatment with the cholinesterase inhibitor rivastigmine at least partly counteracts the slowing of resting-state brain activity that is known to occur in PD related dementia. SIGNIFICANCE Our observations emphasize the prominent role of degeneration of the cholinergic system in the pathophysiology of dementia in PD. In the future, MEG might contribute to the selection of PD patients who may optimally benefit from cholinergic treatment.