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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. ► Introducing a framework for reliable estimation of interactions in anatomical space. ► Choice of connectivity estimator (PLI) removes biases caused by volume conduction. ► Use of atlas-based ROIs aides interpretation and comparison with other modalities. ► Cortical profiles of resting-state power and connectivity are frequency-specific. ► Highly active brain regions are also the ones that are most-densely connected.

Parkinson's disease (PD) is often associated with cognitive deficits, although their severity varies considerably between patients. Recently, we used voxel-based morphometry (VBM) to show that individual differences in gray matter (GM) volume relate to cognitive heterogeneity in PD. VBM does, however, not differentiate between cortical thickness (CTh) and surface area (SA), which might be independently affected in PD. We therefore re-analyzed our cohort using the surface-based method FreeSurfer, and investigated (i) CTh, SA, and (sub)cortical GM volume differences between 93 PD patients and 45 matched controls, and (ii) the relation between these structural measures and cognitive performance on six neuropsychological tasks within the PD group. We found cortical thinning in PD patients in the left pericalcarine gyrus, extending to cuneus, precuneus and lingual areas and left inferior parietal cortex, bilateral rostral middle frontal cortex, and right cuneus, and increased cortical surface area in the left pars triangularis. Within the PD group, we found negative correlations between (i) CTh of occipital areas and performance on a verbal memory task, (ii) SA and volume of the frontal cortex and visuospatial memory performance, and, (iii) volume of the right thalamus and scores on two verbal fluency tasks. Our primary findings illustrate that i) CTh and SA are differentially affected in PD, and ii) VBM and FreeSurfer yield non-overlapping results in an identical dataset. We argue that this discrepancy is due to technical differences and the subtlety of the PD-related structural changes.

Background Despite decades of intensive research, to date, there is no accepted diagnosis for Parkinson’s disease (PD) based on biochemical analysis of blood or CSF. However, neurodegeneration in the brains of PD patients begins several years before the manifestation of the clinical symptoms, pointing to serious flaw/limitations in this approach. Results To explore the potential use of alpha-synuclein (α-syn) species as candidate biomarkers for PD, we generated specific antibodies directed against wide array of α-syn species, namely total-, oligomeric- and phosphorylated-Ser129-α-syn (t-, o- and p-S129-α-syn). Next we sought to employ our antibodies to develop highly specific ELISA assays to quantify α-syn species in biological samples. Finally we verified the usefulness of our assays in CSF samples from 46 PD patients and 48 age-matched healthy controls. We also assessed the discriminating power of combining multiple CSF α-syn species with classical Alzheimer’s disease biomarkers. The combination of CSF o-/t-α-syn, p-S129-α-syn and p-tau provided the best fitting predictive model for discriminating PD patients from controls. Moreover, CSF o-α-syn levels correlated significantly with the severity of PD motor symptoms ( r  = -0.37). Conclusion Our new ELISA assays can serve as research tools to address the unmet need for reliable CSF biomarkers for PD and related disorders.

In Parkinson’s disease (PD), α-synuclein aggregation in striatal synapses is hypothesised to trigger a cascade of events leading to synaptic loss and cortical Lewy body (LB) pathology. Using multiplex immunofluorescence and confocal microscopy on 69 brains spanning Braak stages 0–6—including controls, incidental LB disease (iLBD), and PD—we show that phosphorylated (pSer129) α-synuclein is enriched in putaminal dopaminergic synapses already in early disease stages, and associates with dopaminergic terminal loss. C-terminally truncated (CTT122) α-synuclein shows a similar trend in later stages. Enrichment of pSer129 and CTT122 α-synuclein in cortical glutamatergic synapses in the putamen occurs prior to LB appearance in cortical regions, supporting the theory of α-synuclein retrograde transport from synapse to cell body. Using AlphaLISA, we confirm that isolated PD putaminal synaptosomes contain higher pSer129 α-synuclein protein levels compared to controls. These findings suggest that synaptic enrichment of pSer129 α-synuclein occurs in early PD, possibly contributing to dopaminergic denervation and cortical LB pathology. α-Synuclein accumulation in putaminal synapses is hypothesised to drive Parkinson’s disease progression. This study demonstrates synaptic pSer129 α-synuclein enrichment in early-stage Parkinson’s disease, and its link with dopaminergic denervation and cortical Lewy body pathology.

Longitudinal analyses of magnetoencephalography (MEG) data are essential for a full understanding of the pathophysiology of brain diseases and the development of brain activity over time. However, time-dependent factors, such as the recording environment and the type of MEG recording system may affect such longitudinal analyses. We hypothesized that, using source-space analysis, hardware and software differences between two recordings systems may be overcome, with the aim of finding consistent neurophysiological results. We studied eight healthy subjects who underwent three consecutive MEG recordings over 7 years, using two different MEG recordings systems; a 151-channel VSM-CTF system for the first two time points and a 306-channel Elekta Vectorview system for the third time point. We assessed the within (longitudinal) and between-subject (cross-sectional) consistency of power spectra and functional connectivity matrices. Consistency of within-subject spectral power and functional connectivity matrices was good and was not significantly different when using different MEG recording systems as compared to using the same system. Importantly, we confirmed that within-subject consistency values were higher than between-subject values. We demonstrated consistent neurophysiological findings in healthy subjects over a time span of seven years, despite using data recorded on different MEG systems and different implementations of the analysis pipeline.

Cognitive training (CT) is an increasingly popular, non-pharmacological intervention for improving cognitive functioning in neurodegenerative diseases and healthy aging. Although meta-analyses support the efficacy of CT in improving cognitive functioning, the neural mechanisms underlying the effects of CT are still unclear. We performed a systematic review of literature in the PubMed, Embase and PsycINFO databases on controlled CT trials (N > 20) in aging and neurodegenerative diseases with pre- and post-training functional MRI outcomes up to November 23rd 2018 (PROSPERO registration number CRD42019103662). Twenty articles were eligible for our systematic review. We distinguished between multi-domain and single-domain CT. CT induced both increases and decreases in task-related functional activation, possibly indicative of an inverted U-shaped curve association between regional brain activity and task performance. Functional connectivity within ‘cognitive’ brain networks was consistently reported to increase after CT while a minority of studies additionally reported increased segregation of frontoparietal and default mode brain networks. Although we acknowledge the large heterogeneity in type of CT, imaging methodology, in-scanner task paradigm and analysis methods between studies, we propose a working model of the effects of CT on brain activity and connectivity in the context of current knowledge on compensatory mechanisms that are associated with aging and neurodegenerative diseases.

Autonomic dysfunction is a common non-motor symptom in Parkinson’s disease (PD). Dopamine and serotonin are known to play a role in autonomic regulation, and, therefore, PD-related degeneration of serotonergic and dopaminergic neurons in these regions may be associated with autonomic dysfunction. We sought to clarify the association between extrastriatal serotonergic and striatal dopaminergic degeneration and the severity of autonomic symptoms, including gastrointestinal, pupillomotor, thermoregulatory, cardiovascular, and urinary dysfunction. We performed hierarchical multiple regression analyses to determine the relationships between (extra)striatal serotonergic and dopaminergic degeneration and autonomic dysfunction in 310 patients with PD. We used [ 123 I]FP-CIT SPECT binding to presynaptic serotonin (SERT) and dopamine (DAT) transporters as a measure of the integrity of these neurotransmitter systems, and the SCOPA-AUT (Scales for Outcomes in Parkinson’s Disease—Autonomic) questionnaire to evaluate the perceived severity of autonomic dysfunction. Motor symptom severity, medication status, and sex were added to the model as covariates. Additional analyses were also performed using five subdomains of the SCOPA-AUT: cardiovascular, gastrointestinal, urinary, thermoregulatory, and pupillomotor symptoms. We found that autonomic symptoms were most significantly related to lower [ 123 I]FP-CIT binding ratios in the right caudate nucleus and were mainly driven by gastrointestinal and cardiovascular dysfunction. These results provide a first look into the modest role of dopaminergic projections towards the caudate nucleus in the pathophysiology of autonomic dysfunction in PD, but the underlying mechanism warrants further investigation.

BackgroundAnxiety is a common neuropsychiatric symptom in Parkinson’s disease (PD), yet the neural mechanisms have been scarcely investigated. Disturbances in dopaminergic and serotonergic signalling may play a role in its pathophysiology. 123I-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane (123I-FP-CIT) is a single-photon emission CT radiotracer, and its binding in striatal and extrastriatal subcortical brain areas represents predominant binding to the presynaptic dopamine transporter (DAT) and the serotonin transporter (SERT), respectively. Availability of DAT and SERT may thus provide an in vivo measure for the integrity of both dopamine and serotonin neurons.MethodsWe studied the association between anxiety symptoms, measured with an affective subscale of the Beck Anxiety Inventory, and (extra)striatal 123I-FP-CIT binding in 127 non-demented patients with PD with a median disease duration of 2.55 (IQR 2.90) years. We conducted the analyses on patients currently on or not on dopamine replacement therapy (DRT).ResultsSeverity of anxiety symptoms showed a significant negative association with 123I-FP-CIT binding ratios in the right thalamus (β=−0.203, p=0.019; ΔR2=0.040) (multiple testing pcorr <0.020). In the subgroup of patients not on DRT (n=81), we found a significant negative association between anxiety and thalamic 123I-FP-CIT binding ratios bilaterally (right: β=−0.349, p=0.001, ΔR2=0.119; left: β=−0.269, p=0.017, ΔR2=0.071) (pcorr <0.020).ConclusionThis study shows that higher levels of anxiety in patients with PD are associated with lower thalamic 123I-FP-CIT binding, pointing towards a contribution of serotonergic degeneration to anxiety symptoms in PD.

Background Asymptomatic carriers of leucine-rich repeat kinase 2 ( LRRK2 ) gene mutations constitute an ideal population for discovering prodromal biomarkers of Parkinson’s disease (PD). In this study, we aim to identify CSF candidate risk biomarkers of PD in individuals with LRRK2 mutation carriers. Methods We measured the levels of CSF total- (t-), oligomeric (o-) and phosphorylated S129 (pS129-) α-syn, total-tau (tTau), phosphorylated threonine 181 tau (pTau), amyloid-beta 40 (Aβ-40), amyloid-beta-42 (Aβ-42) and 40 inflammatory chemokines in symptomatic ( n  = 23) and asymptomatic ( n  = 51) LRRK2 mutation carriers, subjects with a clinical diagnosis of PD ( n  = 60) and age-matched healthy controls ( n  = 34). General linear models corrected for age and gender were performed to assess differences in CSF biomarkers between the groups. Markers that varied significantly between the groups were then analyzed using backward-elimination logistic regression analysis to identify an ideal biomarkers panel of prodromal PD. Results Discriminant function analysis revealed low levels of CSF t-α-syn, high levels of CSF o-α-syn and TNF-α best discriminated asymptomatic LRRK2 mutation carriers from both symptomatic PD and healthy controls. Assessing the discriminative power using receiver operating curve analysis, an area under the curve > 0.80 was generated. Conclusions The current study suggests that CSF t-, o-α-syn and TNF-α are candidate risk biomarkers for the detection of PD at the prodromal stage. Our findings also highlight the dynamic interrelationships between CSF proteins and the importance of using a biomarkers’ panel approach for an accurate and timely diagnosis of PD.