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• Regional metabolism correlations of CSF proteins may reflect specific pathophysiology. • CSF neurogranin and α-synuclein express PC/PCC deafferentation and hypometabolism. • CSF β-synuclein reflects the progression of synaptopathy in left temporal lobe. • CSF NfL mirrors axonal injury in still normometabolic right temporal regions. • Metabolic changes due to neuronal, synaptic, or axonal damage have distinct topography. We explored the brain metabolism correlates of emergent cerebrospinal fluid (CSF) biomarkers in a group of 26 patients with prodromal Alzheimer's disease (AD). Distinct volumes of interest (VOIs) expressed the sites of correlation between CSF biomarkers and brain metabolism as determined on [18F]FDG-PET images, as well as of significant hypometabolism in patients compared to healthy controls. Neurogranin- and α-synuclein-VOIs included left precuneus and/or posterior cingulate cortex (PC and/or PCC) and partially overlapped hypometabolism at those sites. β-synuclein- and neurofilament light chain (NfL)-VOIs regarded either left or right lateral temporal areas, respectively, with partial overlap with hypometabolism only for the β-synuclein-VOI, whereas the NfL-VOI did not include hypometabolic regions. We speculate that CSF neurogranin and α-synuclein express an already established hippocampal damage leading to PC and/or PCC deafferentation and hypometabolism. β-synuclein may represent the progression of synaptopathy in the temporal lobe, while NfL the axonal injury in right temporal regions where neuronal loss is not yet evident. [ABSTRACT FROM AUTHOR]

Background: Patients with amnesic mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show a "slowing" of cortical resting-state eyes-closed electroencephalographic (rsEEG) rhythms. Some of them also show subclinical, non-convulsive, and epileptiform EEG activity (EEA) with an unclear relationship with that "slowing."Objective: Here we tested the hypothesis that the "slowing" of rsEEG rhythms is related to EEA in ADMCI patients.Methods: Clinical and instrumental datasets in 62 ADMCI patients and 38 normal elderly (Nold) subjects were available in a national archive. No participant had received a clinical diagnosis of epilepsy. The eLORETA freeware estimated rsEEG cortical sources. The area under the receiver operating characteristic curve (AUROCC) indexed the accuracy of eLORETA solutions in the classification between ADMCI-EEA and ADMCI-noEEA individuals.Results: EEA was observed in 15% (N = 8) of the ADMCI patients. The ADMCI-EEA group showed: 1) more abnormal Aβ42 levels in the cerebrospinal fluid as compared to the ADMCI-noEEA group and 2) higher temporal and occipital delta (<4 Hz) rsEEG source activities as compared to the ADMCI-noEEA and Nold groups. Those source activities showed moderate accuracy (AUROCC = 0.70-0.75) in the discrimination between ADMCI-noEEA versus ADMCI-EEA individuals.Conclusion: It can be speculated that in ADMCI-EEA patients, AD-related amyloid neuropathology may be related to an over-excitation in neurophysiological low-frequency (delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance. [ABSTRACT FROM AUTHOR]

• Nold, ADD and DLB subjects show a reduction in the posterior rsEEG alpha activities at the eyes-opening. • Compared to Nold, ADD and DLB subjects show less reactivity of the posterior alpha source. • Compared to ADD, DLB subjects show less reactivity of the posterior alpha source. Please modify the Abstract as follows:Here we tested if the reactivity of posterior resting-state electroencephalographic (rsEEG) alpha rhythms from the eye-closed to the eyes-open condition may differ in patients with dementia due to Lewy Bodies (DLB) and Alzheimer's disease (ADD) as a functional probe of the dominant neural synchronization mechanisms regulating the vigilance in posterior visual systems.We used clinical, demographical, and rsEEG datasets in 28 older adults (Healthy), 42 DLB, and 48 ADD participants. The eLORETA freeware was used to estimate cortical rsEEG sources.Results showed a substantial (> -10%) reduction in the posterior alpha activities during the eyes-open condition in 24 Healthy, 26 ADD, and 22 DLB subjects. There were lower reductions in the posterior alpha activities in the ADD and DLB groups than in the Healthy group. That reduction in the occipital region was lower in the DLB than in the ADD group.These results suggest that DLB patients may suffer from a greater alteration in the neural synchronization mechanisms regulating vigilance in occipital cortical systems compared to ADD patients. [ABSTRACT FROM AUTHOR]

Purpose: Hyposmia is a common feature of COVID-19 and Parkinson's disease (PD). As parkinsonism has been reported after COVID-19, a link has been hypothesized between SARS-CoV2 infection and PD. We aimed to evaluate brain metabolic correlates of isolated persistent hyposmia after mild-to-moderate COVID-19 and to compare them with metabolic signature of hyposmia in drug-naïve PD patients. Methods: Forty-four patients who experienced hyposmia after SARS-COV2 infection underwent brain [18F]-FDG PET in the first 6 months after recovery. Olfaction was assessed by means of the 16-item "Sniffin' Sticks" test and patients were classified as with or without persistent hyposmia (COVID-hyposmia and COVID-no-hyposmia respectively). Brain [18F]-FDG PET of post-COVID subgroups were compared in SPM12. COVID-hyposmia patients were also compared with eighty-two drug-naïve PD patients with hyposmia. Multiple regression analysis was used to identify correlations between olfactory test scores and brain metabolism in patients' subgroups. Results: COVID-hyposmia patients (n = 21) exhibited significant hypometabolism in the bilateral gyrus rectus and orbitofrontal cortex with respect to COVID-non-hyposmia (n = 23) (p < 0.002) and in middle and superior temporal gyri, medial/middle frontal gyri, and right insula with respect to PD-hyposmia (p < 0.012). With respect to COVID-hyposmia, PD-hyposmia patients showed hypometabolism in inferior/middle occipital gyri and cuneus bilaterally. Olfactory test scores were directly correlated with metabolism in bilateral rectus and medial frontal gyri and in the right middle temporal and anterior cingulate gyri in COVID-hyposmia patients (p < 0.006) and with bilateral cuneus/precuneus and left lateral occipital cortex in PD-hyposmia patients (p < 0.004). Conclusion: Metabolic signature of persistent hyposmia after COVID-19 encompasses cortical regions involved in olfactory perception and does not overlap metabolic correlates of hyposmia in PD. [ABSTRACT FROM AUTHOR]

Background: Sleep disturbances are common non-motor symptoms of Parkinson's Disease (PD). Methods: The aim of this study was to investigate the polysomnographic correlates of sleep changes, as investigated by the Parkinson's Disease Sleep Scale-2 (PDSS-2), in a cohort of sixty-two consecutive de novo, drug naïve PD patients (71.40 ± 7.84 y/o). Results: PDSS-2 total score showed a direct correlation with stage shifts (p = 0.008). Fragmented sleep showed an inverse correlation with sleep efficiency (p = 0.012). Insomnia symptoms showed an inverse correlation with wake after sleep onset (p = 0.005) and direct correlation with periodic leg movements (p = 0.006) and stage shift indices (p = 0.003). Motor Symptoms showed a direct correlation with Apnoea-Hypopnoea (AHI; p = 0.02) and awakenings indices (p = 0.003). Dream distressing showed a direct correlation with REM without atonia (RWA, p = 0.042) and an inverse correlation with AHI (p = 0.012). Sleep quality showed an inverse correlation with RWA (p = 0.008). Conclusion: PDSS-2 features are significantly correlated with polysomnography objective findings, thus further supporting its reliability to investigate sleep disturbances in PD patients. [ABSTRACT FROM AUTHOR]

Purpose: FDG-PET is an established supportive biomarker in dementia with Lewy bodies (DLB), but its diagnostic accuracy is unknown at the mild cognitive impairment (MCI-LB) stage when the typical metabolic pattern may be difficultly recognized at the individual level. Semiquantitative analysis of scans could enhance accuracy especially in less skilled readers, but its added role with respect to visual assessment in MCI-LB is still unknown. Methods: We assessed the diagnostic accuracy of visual assessment of FDG-PET by six expert readers, blind to diagnosis, in discriminating two matched groups of patients (40 with prodromal AD (MCI-AD) and 39 with MCI-LB), both confirmed by in vivo biomarkers. Readers were provided in a stepwise fashion with (i) maps obtained by the univariate single-subject voxel-based analysis (VBA) with respect to a control group of 40 age- and sex-matched healthy subjects, and (ii) individual odds ratio (OR) plots obtained by the volumetric regions of interest (VROI) semiquantitative analysis of the two main hypometabolic clusters deriving from the comparison of MCI-AD and MCI-LB groups in the two directions, respectively. Results: Mean diagnostic accuracy of visual assessment was 76.8 ± 5.0% and did not significantly benefit from adding the univariate VBA map reading (77.4 ± 8.3%) whereas VROI-derived OR plot reading significantly increased both accuracy (89.7 ± 2.3%) and inter-rater reliability (ICC 0.97 [0.96–0.98]), regardless of the readers' expertise. Conclusion: Conventional visual reading of FDG-PET is moderately accurate in distinguishing between MCI-LB and MCI-AD, and is not significantly improved by univariate single-subject VBA but by a VROI analysis built on macro-regions, allowing for high accuracy independent of reader skills. [ABSTRACT FROM AUTHOR]

Cortical network modularity underpins cognitive functions, so we hypothesized its progressive derangement along the course of frontotemporal (FTD) and Alzheimer's (AD) dementing diseases. EEG was recorded in 18 FTD, 18 AD, and 20 healthy control s (HC). In the FTD and AD patients, the EEG recordings were performed at the prodromal stage of dementia, at the onset of dementia, and three years after the onset of dementia. HC underwent three EEG recordings at 2–3-year time interval. Information flows underlying EEG activity recorded at electrode pairs were estimated by means of Mutual Information (MI) analysis. The functional organization of the cortical network was modelled by means of the Graph theory analysis on MI adjacency matrices. Graph theory analysis showed that the main hub of HC (Parietal area) was lost in FTD patients at onset of dementia, substituted by provincial hubs in frontal leads. No changes in global network organization were found in AD. Despite a progressive cognitive impairment during the FTD and AD progression, only the FTD patients showed a derangement in the cortical network modularity, possibly due to dysfunctions in frontal functional connectivity. [ABSTRACT FROM AUTHOR]

Patients with isolated rapid-eye-movement sleep behaviour disorder (RBD) are commonly regarded as being in the early stages of a progressive neurodegenerative disease involving α-synuclein pathology, such as Parkinson's disease, dementia with Lewy bodies, or multiple system atrophy. Abnormal α-synuclein deposition occurs early in the neurodegenerative process across the central and peripheral nervous systems and might precede the appearance of motor symptoms and cognitive decline by several decades. These findings provide the rationale to develop reliable biomarkers that can better predict conversion to clinically manifest α-synucleinopathies. In addition, biomarkers of disease progression will be essential to monitor treatment response once disease-modifying therapies become available, and biomarkers of disease subtype will be essential to enable prediction of which subtype of α-synucleinopathy patients with isolated RBD might develop. [ABSTRACT FROM AUTHOR]

Purpose: To investigate brain functional correlates of mild cognitive impairment (MCI) in idiopathic REM sleep behavior disorder (iRBD). Methods: Thirty-nine consecutive iRBD patients, 17 with (RBD-MCI, 73.6±6.5 years), and 22 without (RBD-NC, 69.6±6.1 years) MCI underwent neuropsychological assessment, 18F-FDG-PET, and 123I-FP-CIT-SPECT as a marker of nigro-striatal dopaminergic function. Forty-two healthy subjects (69.6±8.5 years) were used as control for 18F-FDG-PET analysis. Brain metabolism was compared between the three groups by univariate analysis of variance. Post hoc comparison between RBD-MCI and RBD-NC was performed to investigate the presence of an MCI-related volume of interest (MCI-VOI). Brain functional connectivity was explored by interregional correlation analysis (IRCA), using the whole-brain normalized MCI-VOI uptake as the independent variable. Moreover, the MCI-VOI uptake was correlated with 123I-FP-CIT-SPECT specific-to-non displaceable binding ratios (SBR) and neuropsychological variables. Finally, the MCI-VOI white matter structural connectivity was analyzed by using a MRI-derived human atlas. Results: The MCI-VOI was characterized by a relative hypometabolism involving precuneus and cuneus (height threshold p<0.0001). IRCA (height threshold p<0.0001) revealed a brain functional network involving regions in frontal, temporal, parietal, and occipital lobes, thalamus, caudate, and red nuclei in iRBD patients. In controls, the network was smaller and involved temporal, occipital, cingulate cortex, and cerebellum. Moreover, MCI-VOI metabolism was correlated with verbal memory (p=0.01), executive functions (p=0.0001), and nigro-putaminal SBR (p=0.005). Finally, MCI-VOI was involved in a white matter network including cingulate fasciculus and corpus callosum. Conclusion: Our data suggest that cuneus/precuneus is a hub of a large functional network subserving cognitive function in iRBD. [ABSTRACT FROM AUTHOR]

Study Objectives: To evaluate neurophysiological alterations of visual function in idiopathic REM sleep Behavior Disorder (iRBD) both as markers and predictors of neurodegenerative disorders.Methods: In a longitudinal follow-up study of 46 consecutive iRBD patients (follow-up duration 8.4 ± 3.4 years), the baseline parameters in luminance-contrast pattern (VEPp), red-green color (VEPc) and motion-onset (VEPm) Visual Evoked Potentials in iRBD were compared to early (ePD) and advanced (aPD) Parkinson's Disease subjects. Parameters of latency and amplitude of iRBD converters to neurodegenerative disease were compared with those of the non-converters.Results: The VEP P100 mean latency values for both eyes and for both stimulation checks (30' and 15') were significantly longer in all the three groups of patients as compared to controls; moreover latencies were longer in aPD than in the iRBD group who did not differ from the ePD group. The same held true when we analyzed the number of abnormal subjects belonging to each diagnostic group with a higher number of abnormal subjects in the aPD group compared to both the ePD and in iRBD groups. Chromatic and motion potentials were not different from controls and did not differ in the 3 diagnostic groups. The iRBD subjects who converted to a neurodegenerative disorder showed longer P100 latencies and a higher occurrence of VEPp abnormalities than those who did not convert. Again chromatic and motion VEPs were not different depending on conversion.Conclusions: In iRBD patients the detection of an abnormal VEPp should be considered as a red flag for possible synnucleinopathy, eventually contributing in stratifying the risk of phenoconversion. [ABSTRACT FROM AUTHOR]

Extending Başar's theory of event-related EEG oscillations, here we hypothesize that even in quiet wakefulness, transient increases in delta rhythms may enhance global cortical arousal as revealed by the desynchronization of alpha rhythms in normal (Nold) seniors with some derangement in Alzheimer's disease dementia (ADD). Clinical and EEG datasets in 100 ADD and 100 Nold individuals matched as demography, education, and gender were taken from an international archive. Standard delta (< 4 Hz) and alpha1 (8–10.5 Hz) bands were used for the main analysis, while alpha2 (10.5–13 Hz), theta (4–8 Hz), beta1 (13–20 Hz), beta2 (20–35 Hz), and gamma (35–40 Hz) served as controls. In the interpretation, the higher the alpha1 power (density), the lower that arousal. As expected, when compared to the Nold group, the ADD group showed higher global (scalp) power density at the delta-theta band and lower global power density at the alpha-beta bands. As novel findings, we observed that: (1) in the Nold group, the global delta and alpha1–2 power were negatively and linearly correlated; (2) in the ADD group, this correlation was just marginal; and (3) in both Nold and AD groups, the EEG epochs with the highest delta power (median value for stratification) were associated with the lowest global alpha1 power. This effect was related to eLORETA freeware solutions showing maximum alpha1 source activations in posterior cortical regions. These results suggest that even in quiet wakefulness, delta and alpha rhythms are related to each other, and ADD partially affects this cross-band neurophysiological mechanism. • Resting EEG rhythms differ in Alzheimer's and healthy seniors (group level). • Alzheimers' seniors show abnormally high delta and low alpha rhythms. • Delta and alpha power densities are negatively correlated in healthy seniors. • Above correlation is mitigated by Alzheimer's disease (dementia). [ABSTRACT FROM AUTHOR]

From previous studies in healthy volunteers the prefrontal regions are deeply involved in prospective memory (PM), although little is known about the functional neural basis of PM in prodromal Alzheimer's disease (AD). To this end, we retrospectively recruited 18 patients with mild cognitive impairment caused by AD and 23 matched healthy control subjects who had undergone 18F-fluorodeoxyglucose positron emission tomography and the PM-specific paradigm test. Brain metabolism was correlated with the PM score in the 2 groups separately to find those brain areas correlated with PM performance, which were then used as a hub for an inter-regional metabolic connectivity analyses (inter-regional correlation analysis). Of note, in mild cognitive impairment caused by AD, but not in healthy control subjects, PM score positively correlated with metabolic levels in the right anterior prefrontal cortex (middle and inferior frontal gyri), which disclosed a loss of interhemispheric connectivity in the inter-regional correlation analysis. According to our findings, the functioning of the right anterior prefrontal cortex and its interhemispheric metabolic connectivity is crucial in early AD to sustain PM performance, which deteriorates along with progressive metabolic failure of the interconnected areas. • Prospective memory (PM) is frequently impaired in early Alzheimer's disease (AD). • In healthy subjects the anterior prefrontal cortex (aPFC) has a crucial role in PM. • Metabolism in right aPFC positively correlates with PM performance also in MCI-AD. • The right aPFC acts as a point of resilience of the network sustaining PM in MCI-AD. • PM impairment may be underpinned by a severe connectivity failure in early AD. [ABSTRACT FROM AUTHOR]

• Patients with prodromal-overt dementia with Lewy bodies (DLB) and visual hallucinations show highest parietal delta rhythms. • DLB patients with the greatest cognitive deficits show highest posterior alpha rhythms. • EEG rhythms are related to clinical manifestations in DLB patients. Here we tested if cortical sources of resting state electroencephalographic (rsEEG) rhythms may differ in sub-groups of patients with prodromal and overt dementia with Lewy bodies (DLB) as a function of relevant clinical symptoms. We extracted clinical, demographic and rsEEG datasets in matched DLB patients (N = 60) and control Alzheimer's disease (AD, N = 60) and healthy elderly (Nold, N = 60) seniors from our international database. The eLORETA freeware was used to estimate cortical rsEEG sources. As compared to the Nold group, the DLB and AD groups generally exhibited greater spatially distributed delta source activities (DLB > AD) and lower alpha source activities posteriorly (AD > DLB). As compared to the DLB "controls", the DLB patients with (1) rapid eye movement (REM) sleep behavior disorders showed lower central alpha source activities (p < 0.005); (2) greater cognitive deficits exhibited higher parietal and central theta source activities as well as higher central, parietal, and occipital alpha source activities (p < 0.01); (3) visual hallucinations pointed to greater parietal delta source activities (p < 0.005). Relevant clinical features were associated with abnormalities in spatial and frequency features of rsEEG source activities in DLB patients. Those features may be used as neurophysiological surrogate endpoints of clinical symptoms in DLB patients in future cross-validation prospective studies. [ABSTRACT FROM AUTHOR]

Background: Sleep disorders and cognitive impairment are frequently reported in Parkinson's disease (PD) as non-motor disabling symptoms. While it is known that REM sleep Behaviour Disorder (RBD) in PD is associated with motor and cognitive decline, little is known about the neurobiological significance of NREM sleep arousal-related disorders.Objectives: to evaluate the cognitive and clinical correlates of arousal-related disorders in PD.Methods: Clinical data and video-polysomnography were analysed from one hundred-seventy consecutive subjects with PD. Based on the neuropsychological assessment, the subjects were divided into three groups: no cognitive impairment (PD; n = 58), mild cognitive impairment (PD-MCI; n = 58) and overt dementia (PDD; n = 54).Results: Arousal-related disorders by history were reported in 32.9% of the subjects: 10.3% PD, 31.6% PD-MCI and 59.3% PDD (p = 0.001). Video-PSG captured arousal-related disorders in 1.7% PD, 21.2% MCI-PD and 35.6% PDD (p = 0.001). Arousal-related disorders and RBD were recorded in the same night in 7.7% PD, 9.8% MCI-PD and 15.6% PDD (p = 0.04). Patients with arousal-related disorders captured at V-PSG have a longer disease duration (p = 0.003), higher UPDRS score (p = 0.039), longer duration of treatment with levodopa (p = 0.017) and dopamine agonists (p = 0.018), worse H&Y staging (p = 0.001), lower MMSE score (p = 0.019) and more frequently hallucinations (p = 0.004). In multivariate analysis, cognitive impairment significantly increases the risk of arousal-related disorders (OR 3.387-95% CI 1.395-8.220, p = 0.007).Conclusion: Arousal-related disorders appear to be a marker of cognitive decline in PD. Recognizing arousal-related disorders should make clinicians aware of a possible cognitive decline in PD and eventually modify the therapeutic approach. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) slowing with prealpha dominant frequency (DF) in posterior derivations is a biomarker for dementia with Lewy bodies (DLB) diagnosis, in contrast with Alzheimer's disease (AD). However, an intrasubject re-evaluation of the original data, which contributed to the identification of EEG DLB biomarker, showed that DF was slower in anterior than posterior derivations. We suppose this anterior-posterior gradient of DF slowing could arise in DLB from a thalamocortical dysrhythmia, differently involving the anterior and posterior cortical areas, and correlating with cognitive impairment (Mini-Mental State Examination). EEG was recorded in 144 DLB, 116 AD, and 65 controls from 7 Centers of the European DLB Consortium. Spectra were divided into delta, theta, prealpha, alpha frequency bands. In DLB, mean DF was prealpha both anteriorly and posteriorly, but lower anteriorly (p < 0.001). In 14% of DLB, DF was prealpha anteriorly, whereas alpha posteriorly. In AD and controls, DF was constantly alpha. EEG slowing in DLB correlated with cognitive impairment. Thalamocortical dysrhythmia gives rise to prealpha rhythm with an anterior-posterior gradient and correlates with impaired cognition. • Electroencephalography dominant frequency recorded in anterior was slower than in posterior derivations. • In patients with dementia with Lewy bodies, electroencephalography abnormalities were more prominent in anterior derivations. • In dementia with Lewy bodies, the prealpha rhythm is dominant in anterior leads, whereas alpha prevails behind. [ABSTRACT FROM AUTHOR]

Compared with Alzheimer's disease (AD), Parkinson's disease (PD) shows peculiar clinical manifestations related to vigilance (i.e., executive cognitive deficits and visual hallucinations) that may be reflected in resting-state electroencephalographic rhythms. To test this hypothesis, clinical and resting-state electroencephalographic rhythms in age-, sex-, and education-matched PD patients (N = 136) and Alzheimer's disease patients (AD, N = 85), and healthy older participants (Nold, N = 65), were available from an international archive. Electroencephalographic sources were estimated by eLORETA software. The results are as follows: (1) compared to the Nold participants, the AD and PD patients showed higher widespread delta source activities (PD > AD) and lower posterior alpha source activities (AD > PD); (2) the PD patients with the most pronounced motor deficits exhibited very low alpha source activities in widespread cortical regions; (3) the PD patients with the strongest cognitive deficits showed higher alpha source activities in widespread cortical regions; and (4) compared to the PD patients without visual hallucinations, those with visual hallucinations were characterized by higher posterior alpha sources activities. These results suggest that in PD patients resting in quiet wakefulness, abnormalities in cortical neural synchronization at alpha frequencies are differently related to cognitive, motor, and visual hallucinations. Interestingly, parallel PD neuropathological processes may have opposite effects on cortical neural synchronization mechanisms generating cortical alpha rhythms in quiet wakefulness. • In Parkinson's disease patients, resting-state delta and alpha electroencephalographic source activities were abnormal. • Those abnormalities were differently related to cognitive, motor, and perceptual deficits. • Those source activities may reflect the effect of Parkinson's disease on cognitive, motor, and perceptual systems. [ABSTRACT FROM AUTHOR]

Introduction: The reduction of background activity and the increase of low-frequency powers on electroencephalogram (EEG) correlate with cognitive impairment and have been suggested to be underpinned by cholinergic deficit. We aimed to investigate the ratio between α and θ band power (α/θ ratio), as a synoptic index of quantitative EEG (qEEG) slowing-down, in a peculiar group of patients with mild cognitive impairment (MCI) due to an early-stage Lewy body disease (MCI-LBD), as compared to de novo PD patients without cognitive impairment (PD-MOT), to patients with MCI due to Alzheimer's disease (MCI-AD), and to healthy controls (HC).Methods: Twelve patients with MCI-LBD (8 males; mean age 74.8 ± 3.6), 11 PD-MOT, 11 MCI-AD and 24 HC subjects undergoing qEEG were matched for gender, age, and education. Following logarithmic transformation, the α/θ ratio was compared among groups and brain regions by repeated measures ANOVA, also exploring group*regions interactions.Results: A significant effect of group (p = 0.0003), regions (p = 0.0001), and group*regions interaction (p = 0.0001) on the α/θ ratio was observed. At post-hoc analysis, α/θ ratio was significantly lower in MCI-LBD (p = 0.001) and in PD-MOT (p = 0.02) compared to HC, and in MCI-LBD than MCI-AD (p = 0.05). No significant differences were found between MCI-AD and HC, as well as between MCI-LBD and PD-MOT.Conclusion: The α/θ power ratio as a synoptic index of EEG background slowing-down could be a simple and easy-to-use qEEG index which might indirectly mirror a cholinergic failure, useful to pick-up those MCI patients at higher risk of developing a Lewy-body disease. [ABSTRACT FROM AUTHOR]

Rationale: In Parkinson's disease (PD), spatial covariance analysis of 18F-FDG PET data has consistently revealed a characteristic PD-related brain pattern (PDRP). By quantifying PDRP expression on a scan-by-scan basis, this technique allows objective assessment of disease activity in individual subjects. We provide a further validation of the PDRP by applying spatial covariance analysis to PD cohorts from the Netherlands (NL), Italy (IT), and Spain (SP). Methods: The PDRPNL was previously identified (17 controls, 19 PD) and its expression was determined in 19 healthy controls and 20 PD patients from the Netherlands. The PDRPIT was identified in 20 controls and 20 "de-novo" PD patients from an Italian cohort. A further 24 controls and 18 "de-novo" Italian patients were used for validation. The PDRPSP was identified in 19 controls and 19 PD patients from a Spanish cohort with late-stage PD. Thirty Spanish PD patients were used for validation. Patterns of the three centers were visually compared and then cross-validated. Furthermore, PDRP expression was determined in 8 patients with multiple system atrophy. Results: A PDRP could be identified in each cohort. Each PDRP was characterized by relative hypermetabolism in the thalamus, putamen/pallidum, pons, cerebellum, and motor cortex. These changes co-varied with variable degrees of hypometabolism in posterior parietal, occipital, and frontal cortices. Frontal hypometabolism was less pronounced in "de-novo" PD subjects (Italian cohort). Occipital hypometabolism was more pronounced in late-stage PD subjects (Spanish cohort). PDRPIT, PDRPNL, and PDRPSP were significantly expressed in PD patients compared with controls in validation cohorts from the same center (P < 0.0001), and maintained significance on cross-validation (P < 0.005). PDRP expression was absent in MSA. Conclusion: The PDRP is a reproducible disease characteristic across PD populations and scanning platforms globally. Further study is needed to identify the topography of specific PD subtypes, and to identify and correct for center-specific effects. [ABSTRACT FROM AUTHOR]

In machine learning, data often comes from different sources, but combining them can introduce extraneous variation that affects both generalization and interpretability. For example, we investigate the classification of neurodegenerative diseases using FDG-PET data collected from multiple neuroimaging centers. However, data collected at different centers introduces unwanted variation due to differences in scanners, scanning protocols, and processing methods. To address this issue, we propose a two-step approach to limit the influence of center-dependent variation on the classification of healthy controls and early vs. late-stage Parkinson's disease patients. First, we train a Generalized Matrix Learning Vector Quantization (GMLVQ) model on healthy control data to identify a "relevance space" that distinguishes between centers. Second, we use this space to construct a correction matrix that restricts a second GMLVQ system's training on the diagnostic problem. We evaluate the effectiveness of this approach on the real-world multi-center datasets and simulated artificial dataset. Our results demonstrate that the approach produces machine learning systems with reduced bias - being more specific due to eliminating information related to center differences during the training process - and more informative relevance profiles that can be interpreted by medical experts. This method can be adapted to similar problems outside the neuroimaging domain, as long as an appropriate "relevance space" can be identified to construct the correction matrix. • Learning Vector Quantization approach to improve the early diagnosis of neurodegenerative diseases, where center-specific bias is present in the data. • The novel subspace correction method finds and removes class specific variance, where the correction can be transferred onto a subsequent learning problem. • The subspace correction method provides a solution by reducing center specific differences in FDG-PET scans. [ABSTRACT FROM AUTHOR]

In Dementia with Lewy bodies (DLB), rapid cognitive decline and seizures seldom complicate the typical clinical course. Nevertheless, concurrent, treatable conditions may be responsible. We report a case of DLB with superimposed anti-LGI1 encephalitis, emphasizing the importance of thorough diagnostic reasoning beyond the simplest explanation amid distinct clinical cues. [Display omitted] • Rapid cognitive decline and seizures are rare in Dementia with Lewy bodies (DLB). • Autoimmune encephalitis can seldom mimic or overlap neurodegenerative disorders. • Co-occurrence of LGI1-encephalitis may disrupt the typical DLB course. [ABSTRACT FROM AUTHOR]

Previous evidence has shown different resting-state eyes-closed electroencephalographic delta (<4 Hz) and alpha (8–10.5 Hz) source connectivity in subjects with dementia due to Alzheimer's (ADD) and Lewy body (DLB) diseases. The present study tested if the same differences may be observed in the prodromal stages of mild cognitive impairment (MCI). Here, clinical and resting-state eyes-closed electroencephalographic data in age-, gender-, and education-matched 30 ADMCI, 23 DLBMCI, and 30 healthy elderly (Nold) subjects were available in our international archive. Mini-Mental State Evaluation (MMSE) score was matched in the ADMCI and DLBMCI groups. The eLORETA freeware estimated delta and alpha source connectivity by the tool called lagged linear connectivity (LLC). Area under receiver operating characteristic curve (AUROCC) indexed the classification accuracy among individuals. Results showed that widespread interhemispheric and intrahemispheric LLC solutions in alpha sources were abnormally lower in both MCI groups compared with the Nold group, but with no differences were found between the 2 MCI groups. AUROCCs of LLC solutions in alpha sources exhibited significant accuracies (0.72–0.75) in the discrimination of Nold versus ADMCI-DLBMCI individuals, but not between the 2 MCI groups. These findings disclose similar abnormalities in ADMCI and DLBMCI patients as revealed by alpha source connectivity. It can be speculated that source connectivity mostly reflects common cholinergic impairment in prodromal state of both AD and DLB, before a substantial dopaminergic derangement in the dementia stage of DLB. • We evaluated the abnormalities in functional cortical connectivity computed in rsEEG sources in subjects with Mild Cognitive Impairment due to Alzheimer's and Lewy Body disease. • At the group level, EEG markers of functional cortical connectivity were abnormally lower in in Alzheimer's Disease (ADD) and Lewy Body Disease (DLB) patients compared to healthy elderly subjects (Nold). • At the group level, EEG markers of functional cortical connectivity were similar between in ADD and DLB patients compared to Nold subjects. • At the individual level, EEG marker of functional cortical connectivity exhibited better classification accuracies for the discrimination of ADD versus Nold, and DLB versus Nold, but not between ADD and DLB. [ABSTRACT FROM AUTHOR]

Abstract We hypothesized that dopamine neuromodulation might affect cortical excitability in Parkinson's disease (PD) patients set in quiet wakefulness, as revealed by resting state eyes-closed electroencephalographic (rsEEG) rhythms at alpha frequencies (8–12 Hz). Clinical and rsEEG rhythms in PD with dementia (N = 35), PD with mild cognitive impairment (N = 50), PD with normal cognition (N = 35), and normal (N = 50) older adults were available from an international archive. Cortical rsEEG sources were estimated by exact low-resolution brain electromagnetic tomography. Compared with the normal older group, the PD groups showed reduced occipital alpha sources and increased widespread delta (<4 Hz) sources. Widespread frontal and temporal alpha sources exhibited an increase in PD with dementia compared with PD with mild cognitive impairment and PD with normal cognition groups, as function of dopamine depletion severity, typically greater in the former than the latter groups. A daily dose of levodopa induced a widespread reduction in cortical delta and alpha sources in a subgroup of 13 PD patients under standard chronic dopaminergic regimen. In PD patients in quiet wakefulness, alpha cortical source activations may reflect an excitatory effect of dopamine neuromodulation. [ABSTRACT FROM AUTHOR]

Pisa syndrome (PS) is a trunk postural abnormality in Parkinson's disease (PD). Its pathophysiology is still debated: peripheral and central mechanisms have been hypothesized. To investigate the role of nigrostriatal dopaminergic deafferentation and of brain metabolism impairment in the onset PS in PD patients. We retrospectively selected 34 PD patients who developed PS (PS+) and who had previously undergone dopamine transporter (DaT)-SPECT and/or brain F-18 fluorodeoxyglucose PET (FDG-PET). PS + patients were divided considering leaning body side in left ((l)PS+) or right ((r)PS+). DaT-SPECT specific-to-non-displaceable binding ratio (SBR) of striatal regions (BasGan V2 software) were compared between 30 PS+ and 60 PD patients without PS (PS-) as well as between 16 (l)PS+ and 14 (r)PS + patients. Voxel-based analysis (SPM12) was used to compare FDG-PET among 22 PS+, 22 PS- and 42 healthy controls (HC) and between 9 (r)PS+ and 13 (l)PS+. No significant DaT-SPECT SBR differences were found between PS+ and PS- groups or between (r)PD+ and (l)PS + subgroups. Compared to HC, significant hypometabolism in PS+ was found in bilateral temporal-parietal regions, mainly in the right hemisphere, whereas the right Brodmann area 39 (BA39) was relatively hypometabolic both in the (r)PS+ and in the (l)PS+. BA39 and bilateral posterior cingulate cortex were significantly hypometabolic in PS + than in PS- group. As a hub of the network supervising the body schema perception, the involvement of the right posterior hypometabolism supports the hypothesis PS is a result of a somatosensory perceptive deficit rather than a nigrostriatal dopaminergic unbalance. • No clinical differences were found between patients with and without Pisa syndrome. • No DAT-SPECT differences were found between patients with and without Pisa syndrome. • Metabolism of right angular gyrus is reduced in Pisa syndrome. [ABSTRACT FROM AUTHOR]

• We evaluated iron deposition in N1 in HC and patients with early PD (ePD) and iRBD. • N1 aspect was pathological in T2*-w images in 45% of iRBD patients and in most ePD. • ePD N1 χ was higher than iRBD and HC χ but had no correlation with disease duration. • N1 χ in iRBD was similar to HC but increased with disease duration. • N1 χ may be a presymptomatic biomarker for neurodegeneration in prodromal PD. Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies, such as Parkinson's disease (PD), which are characterized by the loss of dopaminergic neurons in substantia nigra, associated with abnormal iron load. The assessment of presymptomatic biomarkers predicting the onset of neurodegenerative disorders is critical for monitoring early signs, screening patients for neuroprotective clinical trials and understanding the causal relationship between iron accumulation processes and disease development. Here, we used Quantitative Susceptibility Mapping (QSM) and 7T MRI to quantify iron deposition in Nigrosome 1 (N1) in early PD (ePD) patients, iRBD patients and healthy controls and investigated group differences and correlation with disease progression. We evaluated the radiological appearance of N1 and analyzed its iron content in 35 ePD, 30 iRBD patients and 14 healthy controls via T2*-weighted sequences and susceptibility (χ) maps. N1 regions of interest (ROIs) were manually drawn on control subjects and warped onto a study-specific template to obtain probabilistic N1 ROIs. For each subject the N1 with the highest mean χ was considered for statistical analysis. The appearance of N1 was rated pathological in 45% of iRBD patients. ePD patients showed increased N1 χ compared to iRBD patients and HC but no correlation with disease duration, indicating that iron load remains stable during the early stages of disease progression. Although no difference was reported in iron content between iRBD and HC, N1 χ in the iRBD group increases as the disease evolves. QSM can reveal temporal changes in N1 iron content and its quantification may represent a valuable presymptomatic biomarker to assess neurodegeneration in the prodromal stages of PD. [Display omitted]. [ABSTRACT FROM AUTHOR]

• Visualizing prototypical activity profiles of Parkinson's disease patients. • Generalized matrix learning vector quantization used as diagnostic visualization tool. • Towards explainable machine learning models in neuroradiology. Background and objective: Neurodegenerative diseases like Parkinson's disease often take several years before they can be diagnosed reliably based on clinical grounds. Imaging techniques such as MRI are used to detect anatomical (structural) pathological changes. However, these kinds of changes are usually seen only late in the development. The measurement of functional brain activity by means of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) can provide useful information, but its interpretation is more difficult. The scaled sub-profile model principal component analysis (SSM/PCA) was shown to provide more useful information than other statistical techniques. Our objective is to improve the performance further by combining SSM/PCA and prototype-based generalized matrix learning vector quantization (GMLVQ). Methods: We apply a combination of SSM/PCA and GMLVQ as a classifier. In order to demonstrate the combination's validity, we analyze FDG-PET data of Parkinson's disease (PD) patients collected at three different neuroimaging centers in Europe. We determine the diagnostic performance by performing a ten times repeated ten fold cross validation. Additionally, discriminant visualizations of the data are included. The prototypes and relevance of GMLVQ are transformed back to the original voxel space by exploiting the linearity of SSM/PCA. The resulting prototypes and relevance profiles have then been assessed by three neurologists. Results: One important finding is that discriminative visualization can help to identify disease-related properties as well as differences which are due to center-specific factors. Secondly, the neurologist assessed the interpretability of the method and confirmed that prototypes are similar to known activity profiles of PD patients. Conclusion: We have shown that the presented combination of SSM/PCA and GMLVQ can provide useful means to assess and better understand characteristic differences in FDG-PET data from PD patients and HCs. Based on the assessments by medical experts and the results of our computational analysis we conclude that the first steps towards a diagnostic support system have been taken successfully. [ABSTRACT FROM AUTHOR]

Background: Magnetic resonance imaging (MRI) has recently enabled to identify four distinct Alzheimer's disease (AD) subtypes: hippocampal sparing (HpSp), typical AD (tAD), limbic predominant (Lp), and minimal atrophy (MinAtr). To date, however, the natural history of these subtypes, especially regarding the presence of subjects switching to other MRI patterns and their clinical and biological differences, remains poorly understood., Objective: To investigate the clinical and biological underpinnings of longitudinal atrophy pattern progression in AD., Methods: 251 AD patients (16 with significant memory concern, 66 with early mild cognitive impairment (MCI), 125 with late MCI, and 44 with AD dementia) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were assigned to their baseline MRI atrophy subtype using Freesurfer-derived cortical:hippocampal volumes ratio. Switching to other MRI patterns was investigated on longitudinal scans, and patients were accordingly classified as " switching " and " stable ". Logistic regression models were applied to identify predictors of switching to other MRI patterns., Results: 40% of Lp, 26% of HpSp, and 35% of MinAtr cases switched to other MRI patterns, with tAD representing the destination subtype of all switching HpSp and Lp, and the majority of MinAtr. At baseline significant clinical, cognitive and biomarkers differences were observed across the four subtypes. Only clinical and cognitive variables, however, were significantly associated with switch to other MRI patterns., Conclusions: Our results suggest convergent directions of disease progression across atypical and typical AD forms, at least in a subset of AD subjects, and highlight the importance of deep-phenotyping approaches to understand AD heterogeneity., Competing Interests: Declaration of conflicting interestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Federico Massa is an Editorial Board Member of this journal but was not involved in the peer-review process of this article nor had access to any information regarding its peer-review. The remaining authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The phenoconversion trajectory from idiopathic/isolated Rapid eye movement (REM) sleep behavior disorder (iRBD) towards either Parkinson's Disease (PD) or Dementia with Lewy Bodies (DLB) is currently uncertain. We investigated the capability of baseline brain [ 18 F]FDG-PET in differentiating between iRBD patients eventually phenoconverting to PD or DLB, by deriving the denovoPDRBD-related pattern (denovoPDRBD-RP) from 32 de novo PD patients; and the denovoDLBRBD-RP from 30 de novo DLB patients, both with evidence of RBD at diagnosis. To explore [ 18 F]FDG-PET phenoconversion trajectories prediction power, we applied these two patterns on a group of 115 iRBD patients followed longitudinally. At follow-up (25.6 ± 17.2 months), 42 iRBD patients progressed through overt alpha-synucleinopathy (21 iRBD-PD and 21 iRBD-DLB converters), while 73 patients remained stable at the last follow-up visit (43.2 ± 27.6 months). At survival analysis, both patterns were significantly associated with the phenoconversion trajectories. Brain [ 18 F]FDG-PET is a promising biomarker to study progression trajectories in the alpha-synucleinopathy continuum., (© 2024. The Author(s).)

Background: Cognitive reserve (CR) is an expression of brain resilience in response to damage. Education, occupational experience and leisure activities are thought to increase CR and have beneficial effects on global cognition and cognitive decline in Parkinson's disease (PD). We aimed to disclose brain metabolic and dopaminergic correlates of CR in de-novo PD patients., Methods: Sixty-two drug-naïve de-novo PD patients underwent [ 18 F]FDG-PET and DAT-SPECT. CR was quantified through the Cognitive-Reserve-Index questionnaire including total-CR and 3 subscores (educational-CR, occupational-CR, leisure-CR). Specific binding ratios (SBRs) and Z-scores in basal ganglia were obtained with 'BasGan-V2'. Z-scores were used as dependent variables in general linear models to assess the interaction between dopaminergic function and CR. Voxel-based correlation between brain metabolism and CR-scores and between SBR and [ 18 F]FDG-PET was evaluated using SPM12 (P<0.05 FWE-corrected at peak and cluster level considered significant)., Results: Dopaminergic deficit in the most affected hemisphere (MAH) putamen was significantly less marked in higher CR patients (Z-score -1.7±0.1 highly-educated versus -2.1±0.1 poorly-educated, P<0.02). Total and leisure-related-CR resulted correlated directly with z-scores of the MAH putamen (P<0.018 and P<0.003) and inversely with brain metabolism in both cerebellar hemispheres (P<0.001). MAH-putamen SBR correlated directly with metabolism in occipital and parietal cortex (P<0.003) and inversely in cerebellar hemispheres (P<0.02)., Conclusions: CR proxies demonstrated to correlate directly with dopaminergic function and inversely with metabolism in cerebellar hemispheres in de-novo PD patients. The present multi-modal approach including both metabolic and dopaminergic correlates of CR allowed to identify possible compensation mechanisms, highlighting a potential role of the cerebellum that deserves further investigation.

Background: High-grade glioma (HGG) patients post-radiotherapy often face challenges distinguishing true tumor progression (TTP) from pseudoprogression (PsP). This study evaluates the effectiveness of systemic inflammatory markers and volume of enhancing tissue on post-contrast T1 weighted (T1WCE) MRI images for this differentiation within the first six months after treatment., Material and Methods: We conducted a retrospective analysis on a cohort of HGG patients from 2015 to 2021, categorized per WHO 2016 and 2021 criteria. We analyzed treatment responses using modified RANO criteria and conducted volumetry on T1WCE and T2W/FLAIR images.Blood parameters assessed included neutrophil/lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI). We employed Chi-square, Fisher's exact test, and Mann-Whitney U test for statistical analyses, using log-transformed predictors due to multicollinearity. A Cox regression analysis assessed the impact of PsP- and TTP-related factors on overall survival (OS)., Results: The cohort consisted of 39 patients, where 16 exhibited PsP and 23 showed TTP. Univariate analysis revealed significantly higher NLR and SII in the TTP group [NLR: 4.1 vs 7.3, p = 0.002; SII 546.5 vs 890.5p = 0.009]. T1WCE volume distinctly differentiated PsP from TTP [2.2 vs 11.7, p < 0.001]. In multivariate regression, significant predictors included NLR and T1WCE volume in the "NLR Model," and T1WCE volume and SII in the "SII Model." The study also found a significantly lower OS rate in TTP patients compared to those with PsP [HR 3.97, CI 1.59 to 9.93, p = 0.003]., Conclusion: Elevated both, SII and NLR, and increased T1WCE volume were effective in differentiating TTP from PsP in HGG patients post-radiotherapy. These results suggest the potential utility of incorporating these markers into clinical practice, though further research is necessary to confirm these findings in larger patient cohorts., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V. on behalf of European Society for Radiotherapy and Oncology.)

Alpha-synucleinopathies are prevalent neurological disorders that cause significant disability, leading to progressive clinical deterioration that is currently managed solely through symptomatic treatment. Efforts to evaluate disease-modifying therapies during the established stage of the disease have not yielded positive outcomes in terms of clinical or imaging efficacy endpoints. However, alpha-synucleinopathies have a long prodromal phase that presents a promising opportunity for intervention with disease-modifying therapies. The presence of polysomnography-confirmed REM sleep behavior disorder (RBD) is the most reliable risk factor for identifying individuals in the prodromal stage of alpha-synucleinopathy. This paper discusses the rationale behind targeting idiopathic/isolated RBD in disease-modifying trials and outlines possible study designs, including strategies for patient stratification, selection of biomarkers to assess disease progression and patient eligibility, as well as the identification of suitable endpoints. Additionally, the potential targets for disease-modifying treatment in alpha-synucleinopathies are summarized., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dario Arnaldi reports financial support was provided by Italian ministry of health. Dario Arnaldi reports financial support was provided by Italian ministry of university and research. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB)., Methods: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion., Results: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters., Interpretation: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024;95:1178-1192., (© 2024 The Authors. Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Study Objectives: Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies and eventually phenoconverts to overt neurodegenerative diseases including Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Associations of baseline resting-state electroencephalography (EEG) with phenoconversion have been reported. In this study, we aimed to develop machine learning models to predict phenoconversion time and subtype using baseline EEG features in patients with iRBD., Methods: At baseline, resting-state EEG and neurological assessments were performed on patients with iRBD. Calculated EEG features included spectral power, weighted phase lag index, and Shannon entropy. Three models were used for survival prediction, and four models were used for α-synucleinopathy subtype prediction. The models were externally validated using data from a different institution., Results: A total of 236 iRBD patients were followed up for up to 8 years (mean 3.5 years), and 31 patients converted to α-synucleinopathies (16 PD, 9 DLB, 6 MSA). The best model for survival prediction was the random survival forest model with an integrated Brier score of 0.114 and a concordance index of 0.775. The K-nearest neighbor model was the best model for subtype prediction with an area under the receiver operating characteristic curve of 0.901. Slowing of the EEG was an important feature for both models., Conclusions: Machine learning models using baseline EEG features can be used to predict phenoconversion time and its subtype in patients with iRBD. Further research including large sample data from many countries is needed to make a more robust model., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Goal: REM Sleep Behavior Disorder (RBD) is a REM parasomnia that is associated to high risk of developing α-synucleinopathies, as Parkinson's disease (PD) or dementia with Lewy bodies, over time. This study aims at investigating the presence of autonomic dysfunctions in RBD subjects, with and without PD, by assessing their sleep structure and autonomous nervous system activity along the different sleep stages. Methods: To this aim, an innovative framework combining a sleep transition model, by Markov chains, with an instantaneous assessment of autonomic state dynamics by statistical modeling of heart rate variability (HRV) dynamics through a point-process approach, was introduced. Results: In general, RBD groups showed lower HRV than controls across all sleep stages, as well as higher probabilities of transitioning towards lighter sleep stages. Subjects also affected by PD present an even lower HRV, but better sleep continuity. Conclusions: RBD patients suffer from sleep fragmentation and overall autonomic dysfunction, mainly due to lower autonomic activation across all sleep stages. Coexistence of PD seems to improve sleep quality, possibly due to a sleep-related relief of their symptoms., Competing Interests: The authors declare that they have no conflict of interest., (© 2024 The Authors.)

Background: SOMI (Stages of Objective Memory Impairment) is a novel classification that identifies six stages of memory decline in Alzheimer's Disease (AD) using the Free and Cued Selective Reminding Test (FCSRT). However, the relationship between SOMI stages and brain metabolism remains unexplored. This study aims to investigate the metabolic correlates of SOMI stages using FDG-PET in Mild Cognitive Impairment due to AD (MCI-AD) and early AD patients., Methods: One hundred twenty-nine-patients (99 aMCI-AD and 30 AD), and 42 healthy controls (HCs) (MMSE = 29.2 ± .8; age:69.1 ± 8.6 years; education:10.7 ± 3.8 years) who underwent an extensive neuropsychological battery including FCSRT and brain FDG-PET were enrolled. According to their clinical relevance and available sample sizes, SOMI-4 (N = 24 subjects; MMSE score:26.6 ± 2.6: age:75.4 ± 3.2; education:9.9 ± 4.5) and SOMI-5 groups (N = 97; MMSE:25.3 ± 2.6; age:73.9 ± 5.8; education:9.4 ± 4.1) were investigated., Results: Compared to HCs, SOMI-4 showed hypometabolism in the precuneus, medial temporal gyrus bilaterally, right pecuneus and angular gyrus. SOMI-5 exhibited broader hypometabolism, extending to the left posterior cingulate and medial frontal gyrus bilaterally. The conjunction analysis revealed overlapping areas in the precuneus, medial temporal gyrus bilaterally, and in the right angular gyrus and cuneus. The disjunction analysis identified SOMI-5 specific hypometabolism encompassing left inferior temporal gyrus, uncus and parahippocampal gyrus, and medial frontal gyrus bilaterally (p < .001, p-value (FWE) < .05)., Discussion: SOMI-4 relates to posterior hypometabolism, while SOMI-5 to more extensive hypometabolism further encompassing frontal cortices, suggesting SOMI as a biologically relevant classification system of memory decline., Conclusion: Memory decline staged with SOMI is associated with hypometabolism spreading in amnesic MCI-AD/AD, suggesting its usefulness as a clinical marker of increasing neurodegeneration., Competing Interests: Declaration of competing interest Dr. Pardini reports research support from Novartis and Nutricia and speakers fees from GEBiogen and Merk. Dr. Arnaldi reports speakers fee from Fidia. Dr. Morbelli reports speakers fees GE. All other authors do not report significant conflicts of interest., (Copyright © 2023. Published by Elsevier Ltd.)

Introduction: Isolated/idiopathic rapid eye movement sleep behavior disorder (iRBD) is a powerful early predictor of dementia with Lewy bodies (DLB) and Parkinson's disease (PD). This provides an opportunity to directly observe the evolution of prodromal DLB and to identify which cognitive variables are the strongest predictors of evolving dementia., Methods: IRBD participants (n = 754) from 10 centers of the International RBD Study Group underwent annual neuropsychological assessment. Competing risk regression analysis determined optimal predictors of dementia. Linear mixed-effect models determined the annual progression of neuropsychological testing., Results: Reduced attention and executive function, particularly performance on the Trail Making Test Part B, were the strongest identifiers of early DLB. In phenoconverters, the onset of cognitive decline began up to 10 years prior to phenoconversion. Changes in verbal memory best differentiated between DLB and PD subtypes., Discussion: In iRBD, attention and executive dysfunction strongly predict dementia and begin declining several years prior to phenoconversion., Highlights: Cognitive decline in iRBD begins up to 10 years prior to phenoconversion. Attention and executive dysfunction are the strongest predictors of dementia in iRBD. Decline in episodic memory best distinguished dementia-first from parkinsonism-first phenoconversion., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Idiopathic/isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is considered the prodromal stage of alpha-synucleinopathies. Thus, iRBD patients are the ideal target for disease-modifying therapy. The risk FActoRs PREdictive of phenoconversion in iRBD Italian STudy (FARPRESTO) is an ongoing Italian database aimed at identifying risk factors of phenoconversion, and eventually to ease clinical trial enrollment of well-characterized subjects., Methods: Polysomnography-confirmed iRBD patients were retrospectively and prospectively enrolled. Baseline harmonized clinical and nigrostriatal functioning data were collected at baseline. Nigrostriatal functioning was evaluated by dopamine transporter-single-photon emission computed tomography (DaT-SPECT) and categorized with visual semi-quantification. Longitudinal data were evaluated to assess phenoconversion. Cox regressions were applied to calculate hazard ratios., Results: 365 patients were enrolled, and 289 patients with follow-up (age 67.7 ± 7.3 years, 237 males, mean follow-up 40 ± 37 months) were included in this study. At follow-up, 97 iRBD patients (33.6%) phenoconverted to an overt synucleinopathy. Older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression, and visual semi-quantification of nigrostriatal functioning predicted phenoconversion. The remaining 268 patients are in follow-up within the FARPRESTO project., Conclusions: Clinical data (older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression) predicted phenoconversion in this multicenter, longitudinal, observational study. A standardized visual approach for semi-quantification of DaT-SPECT is proposed as a practical risk factor for phenoconversion in iRBD patients. Of note, non-converted and newly diagnosed iRBD patients, who represent a trial-ready cohort for upcoming disease-modification trials, are currently being enrolled and followed in the FARPRESTO study. New data are expected to allow better risk characterization., (© 2023 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Here we tested the hypothesis of a relationship between the cortical default mode network (DMN) structural integrity and the resting-state electroencephalographic (rsEEG) rhythms in patients with Alzheimer's disease with dementia (ADD). Clinical and instrumental datasets in 45 ADD patients and 40 normal elderly (Nold) persons originated from the PDWAVES Consortium (www.pdwaves.eu). Individual rsEEG delta, theta, alpha, and fixed beta and gamma bands were considered. Freeware platforms served to derive (1) the (gray matter) volume of the DMN, dorsal attention (DAN), and sensorimotor (SMN) cortical networks and (2) the rsEEG cortical eLORETA source activities. We found a significant positive association between the DMN gray matter volume, the rsEEG alpha source activity estimated in the posterior DMN nodes (parietal and posterior cingulate cortex), and the global cognitive status in the Nold and ADD participants. Compared with the Nold, the ADD group showed lower DMN gray matter, lower rsEEG alpha source activity in those nodes, and lower global cognitive status. This effect was not observed in the DAN and SMN. These results suggest that the DMN structural integrity and the rsEEG alpha source activities in the DMN posterior hubs may be related and predict the global cognitive status in ADD and Nold persons., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: A brain glucose metabolism pattern related to phenoconversion in patients with idiopathic/isolated REM sleep behaviour disorder (iRBDconvRP) was recently identified. However, the validation of the iRBDconvRP in an external, independent group of iRBD patients is needed to verify the reproducibility of such pattern, so to increase its importance in clinical and research settings. The aim of this work was to validate the iRBDconvRP in an independent group of iRBD patients., Methods: Forty iRBD patients (70 ± 5.59 years, 19 females) underwent brain [ 18 F]FDG-PET in Seoul National University. Thirteen patients phenoconverted at follow-up (7 Parkinson disease, 5 Dementia with Lewy bodies, 1 Multiple system atrophy; follow-up time 35 ± 20.56 months) and 27 patients were still free from parkinsonism/dementia after 62 ± 29.49 months from baseline. We applied the previously identified iRBDconvRP to validate its phenoconversion prediction power., Results: The iRBDconvRP significantly discriminated converters from non-converters iRBD patients (p = 0.016; Area under the Curve 0.74, Sensitivity 0.69, Specificity 0.78), and it significantly predicted phenoconversion (Hazard ratio 4.26, C.I.95%: 1.18-15.39)., Conclusions: The iRBDconvRP confirmed its robustness in predicting phenoconversion in an independent group of iRBD patients, suggesting its potential role as a stratification biomarker for disease-modifying trials., (© 2023. The Author(s).)

Purpose: A cut-off of -2 z-score for striatal or putaminal SBR has been to date arbitrarily used to define an abnormal DaT SPECT in patients with suspected neurodegenerative parkinsonism. We aimed to experimentally identify the most accurate z-score cut-offs for SBR of striatal and substriatal regions to independently discriminate PD and DLB, with respect to essential tremor (ET) and Alzheimer's disease (AD) respectively., Methods: Two-hundred twenty-five patients undergoing DaT SPECT were enrolled (seventy-five de novo PD, eighty ET, fifty DLB, and twenty AD). Semiquantification was computed by means of Datquant® software which returns measures of striatal SBR and z-scores with respect to 118 healthy volunteers belonging to the Parkinson's Progression Markers Initiative (PPMI). ROC analysis was used to identify most accurate cut-offs for z-score for striatum and substriatal regions (clinical diagnosis at follow-up as gold standard)., Results: Posterior putamen of the most affected hemisphere (MAH) with a z-score cut-off of  - 1.27 demonstrated the highest accuracy to differentiate between PD and ET (sensitivity 0.97, specificity 0.94). The whole putamen (z-score cut-off  - 0.96) was the most accurate parameter to support the diagnosis of DLB (sensitivity 0.74, specificity 0.95). Putamen to caudate ratio was accurate to detect PD (especially in early stages) while not DLB patients., Conclusion: We experimentally demonstrated that different substriatal regions and cut-offs for z-score of SBR should be considered to support the diagnosis of either PD or DLB. The identified less conservative cut-offs showed higher sensitivity without a measurable reduction in specificity with respect to the arbitrary  - 2 z-score., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Graph theory models a network by its nodes (the fundamental unit by which graphs are formed) and connections. 'Degree' hubs reflect node centrality (the connection rate), while 'connector' hubs are those linked to several clusters of nodes (mainly long-range connections)., Methods: Here, we compared hubs modeled from measures of interdependencies of between-electrode resting-state eyes-closed electroencephalography (rsEEG) rhythms in normal elderly (Nold) and Alzheimer's disease dementia (ADD) participants. At least 5 min of rsEEG was recorded and analyzed. As ADD is considered a 'network disease' and is typically associated with abnormal rsEEG delta (<4 Hz) and alpha rhythms (8-12 Hz) over associative posterior areas, we tested the hypothesis of abnormal posterior hubs from measures of interdependencies of rsEEG rhythms from delta to gamma bands (2-40 Hz) using eLORETA bivariate and multivariate-directional techniques in ADD participants versus Nold participants. Three different definitions of 'connector' hub were used., Results: Convergent results showed that in both the Nold and ADD groups there were significant parietal 'degree' and 'connector' hubs derived from alpha rhythms. These hubs had a prominent outward 'directionality' in the two groups, but that 'directionality' was lower in ADD participants than in Nold participants., Discussion: In conclusion, independent methodologies and hub definitions suggest that ADD patients may be characterized by low outward 'directionality' of partially preserved parietal 'degree' and 'connector' hubs derived from rsEEG alpha rhythms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lopez, Del Percio, Lizio, Noce, Padovani, Nobili, Arnaldi, Famà, Moretti, Cagnin, Koch, Benussi, Onofrj, Borroni, Soricelli, Ferri, Buttinelli, Giubilei, Güntekin, Yener, Stocchi, Vacca, Bonanni and Babiloni.)

Background: Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents the prodromal stage of α-synucleinopathies. Reliable biomarkers are needed to predict phenoconversion., Objective: The aim was to derive and validate a brain glucose metabolism pattern related to phenoconversion in iRBD (iRBDconvRP) using spatial covariance analysis (Scaled Subprofile Model and Principal Component Analysis [SSM-PCA])., Methods: Seventy-six consecutive iRBD patients (70 ± 6 years, 15 women) were enrolled in two centers and prospectively evaluated to assess phenoconversion (30 converters, 73 ± 6 years, 14 Parkinson's disease and 16 dementia with Lewy bodies, follow-up time: 21 ± 14 months; 46 nonconverters, 69 ± 6 years, follow-up time: 33 ± 19 months). All patients underwent [ 18 F]FDG-PET ( 18 F-fluorodeoxyglucose positron emitting tomography) to investigate brain glucose metabolism at baseline. SSM-PCA was applied to obtain the iRBDconvRP; nonconverter patients were considered as the reference group. Survival analysis and Cox regression were applied to explore prediction power., Results: First, we derived and validated two distinct center-specific iRBDconvRP that were comparable and significantly able to predict phenoconversion. Then, SSM-PCA was applied to the whole set, identifying the iRBDconvRP. The iRBDconvRP included positive voxel weights in cerebellum; brainstem; anterior cingulate cortex; lentiform nucleus; and middle, mesial temporal, and postcentral areas. Negative voxel weights were found in posterior cingulate, precuneus, middle frontal gyrus, and parietal areas. Receiver operating characteristic analysis showed an area under the curve of 0.85 (sensitivity: 87%, specificity: 72%), discriminating converters from nonconverters. The iRBDconvRP significantly predicted phenoconversion (hazard ratio: 7.42, 95% confidence interval: 2.6-21.4)., Conclusions: We derived and validated an iRBDconvRP to efficiently discriminate converter from nonconverter iRBD patients. [ 18 F]FDG-PET pattern analysis has potential as a phenoconversion biomarker in iRBD patients. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)