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Abstract The progression of Parkinson’s disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences. Diffusion-weighted MRI data from 1654 participants diagnosed with PD (age: 20–89 years; 33% female) and 885 controls (age: 19–84 years; 47% female) were analyzed using the ENIGMA-DTI protocol to evaluate white matter microstructure. Skeletonized maps of fractional anisotropy (FA) and mean diffusivity (MD) were compared across Hoehn and Yahr (HY) disease groups and controls to reveal the profile of white matter alterations at different stages. We found an enhanced, more widespread pattern of microstructural alterations with each stage of PD, with eventually lower FA and higher MD in almost all regions of interest: Cohen’s d effect sizes reached d = −1.01 for FA differences in the fornix at PD HY Stage 4/5. The early PD signature in HY stage 1 included higher FA and lower MD across the entire white matter skeleton, in a direction opposite to that typical of other neurodegenerative diseases. FA and MD were associated with motor and non-motor clinical dysfunction. While overridden by degenerative changes in the later stages of PD, early PD is associated with paradoxically higher FA and lower MD in PD, consistent with early compensatory changes associated with the disorder.

Measurement(s) stroke lesion Technology Type(s) manual segmentation in ITK-SNAP Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment brain

Abstract Microstructural alterations in cortico-subcortical connections are thought to be present in obsessive–compulsive disorder (OCD). However, prior studies have yielded inconsistent findings, perhaps because small sample sizes provided insufficient power to detect subtle abnormalities. Here we investigated microstructural white matter alterations and their relation to clinical features in the largest dataset of adult and pediatric OCD to date. We analyzed diffusion tensor imaging metrics from 700 adult patients and 645 adult controls, as well as 174 pediatric patients and 144 pediatric controls across 19 sites participating in the ENIGMA OCD Working Group, in a cross-sectional case-control magnetic resonance study. We extracted measures of fractional anisotropy (FA) as main outcome, and mean diffusivity, radial diffusivity, and axial diffusivity as secondary outcomes for 25 white matter regions. We meta-analyzed patient-control group differences (Cohen’s d) across sites, after adjusting for age and sex, and investigated associations with clinical characteristics. Adult OCD patients showed significant FA reduction in the sagittal stratum (d = −0.21, z = −3.21, p = 0.001) and posterior thalamic radiation (d = −0.26, z = −4.57, p

Background: In the first wave of the COVID-19 pandemic in 2020, many countries made changes to the routine management of patients with non-communicable diseases, including neurocognitive disorders. Therefore, many “so-called” non-urgent elective procedures and outpatient appointments have been canceled or postponed, possibly impacting negatively on health and well-being of patients in the short- and long-term.Aim: Here, we aimed at describing numbers and types of outpatient appointments canceled as a result of government's restrictive measures in our memory clinic.Methods: The scheduled appointments at the memory clinic of the Santa Lucia Foundation IRCCS, Rome, Italy, are recorded in a comprehensive dataset under strict administrative control. Here, we compared appointments (first-time and follow-up) that were canceled from January to April 2020 with those of the corresponding months in 2019.Results: We observed a substantial decrease in appointments during 2020. The majority of scheduled appointments were follow-up, and about a quarter were first-time appointments. We estimated that 66.7% and 77.4% of patients missed out respectively their first and follow-up appointments in our memory clinic due to government's restrictive measures in March–April 2020.Conclusions: A large number of patients with neurocognitive disorders missed crucial appointments due to government's restrictive measures, and many experienced a delay in initial diagnosis and initiation of treatment. This has relevant impact on their treatment and consequently has (is still having and potentially will have) an increase on the healthcare service burden of clinics. Furthermore, as a second wave of COVID-19 affects Europe, and with winter approaching, it is a compelling priority to ensure easy and rapid access to appropriate assessment, care and treatment in the event of a new outbreak and potential subsequent lockdowns, with particular attention to the development of specific healthcare technologies customized to older persons with cognitive impairment.

Background: During the first wave of the COVID-19 pandemic, many non-urgent outpatient services in Italy were closed due to the Government-enforced lockdown period. So far, little is known about what effect the pandemic, quarantine measures, and reductions in medical services had on people with cognitive impairment and their caregivers.Objectives: To develop two versions (i.e., patients and informants/caregivers) of a survey designed to assess the impact of the COVID-19 pandemic during the first Italian lockdown period (11 March −4 May 2020) on Memory Clinic outpatients with Mild Cognitive Impairment (MCI) or dementia, and their caregivers.Design: Psychiatrists, neuropsychologists, and epidemiologists developed two versions: one for patients with Mild Cognitive Impairment and other cognitive disorders, the other for their relatives and/or caregivers. Each version of the survey includes five sections: (a) socio-demographic information and access to technology devices; (b) individual COVID-19 protection methods; (c) knowledge about COVID-19; (d) the effect of COVID-19 on daily life; and (e) the effect of COVID-19 on emotional state.Conclusion: Until an effective vaccine is developed it is likely that future waves of COVID-19 will result in shielding of vulnerable older adults. We believe that this instrument will be useful as a tool to collect information and help clinicians to promptly respond to changes in patients' cognitive, psychiatric, and somatic health needs, and to help for future planning in possible subsequent quarantine periods.

Timing disturbances have being proposed as a key component of schizophrenia pathogenesis. However, the contribution of cognitive impairment to such disorders has not been clarified. Here, we investigated duration estimation and predictive timing in 30 patients with DSM-5 diagnosis of schizophrenia (SZ) compared to 30 healthy controls (HC). Duration estimation was examined in a temporal and colour discrimination task, fully controlled for working memory (WM) and attention requirements, and by more traditional temporal production and temporal bisection tasks. Predictive timing was measured in a temporal and spatial orienting of attention task. Expectations about stimulus onset (temporal condition) or location (spatial condition) were induced by valid and invalid symbolic cues. Results showed that discrimination of temporal and colour stimulus attributes was equally impaired in SZ. This, taken with the positive correlation between temporal bisection performance and neuropsychological measures of WM, indicates that duration estimation impairments in SZ are underpinned by WM dysfunction. Conversely, we found dissociation in temporal and spatial predictive ability in SZ. Unlike controls, patients were selectively unperturbed by events appearing at an unexpected moment in time, though were perturbed by targets appearing at an unexpected location. Moreover, patients were able to generate temporal expectations more implicitly, as their performance was influenced by the predictive nature of the flow of time itself. Our findings shed new light on the debate over the specificity of timing distortions in SZ, providing evidence that predictive timing is a precise marker of SZ, more sensitive than duration estimation, serving as a valid heuristic for studying the pathophysiology of the disorder.

The brain structural correlates of cognitive and psychopathological symptoms within the active phase in severely psychotic schizophrenic inpatients have been rarely investigated. Twenty-eight inpatients with a DSM-5 diagnosis of Schizophrenia (SZ), admitted for acute psychotic decompensation, were assessed through a comprehensive neuropsychological and psychopathological battery. All patients underwent a high-resolution T1-weighted magnetic resonance imaging investigation. Increased psychotic severity was related to reduced grey matter volumes in the medial portion of the right superior frontal cortex, the superior orbitofrontal cortex bilaterally and to white matter volume reduction in the medial portion of the left superior frontal area. Immediate verbal memory performance was related to left insula and inferior parietal cortex volume, while long-term visuo-spatial memory was related to grey matter volume of the right middle temporal cortex, and the right (lobule VII, CRUS1) and left (lobule VI) cerebellum. Moreover, psychotic severity correlated with cognitive inflexibility and negative symptom severity was related to visuo-spatial processing and reasoning disturbances. These findings indicate that a disruption of the cortical-subcortical-cerebellar circuit, and distorted memory function contribute to the development and maintenance of psychotic exacerbation.

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses.Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods.Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models.Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.

The dynamics of the environment where we live in and the interaction with it, predicting events, provided strong evolutionary pressures for the brain functioning to process temporal information and generate timed responses. As a result, the human brain is able to process temporal information and generate temporal patterns. Despite the clear importance of temporal processing to cognition, learning, communication and sensory, motor and emotional processing, the basal mechanisms of how animals differentiate simple intervals or provide timed responses are still under debate. The lesson we learned from the last decade of research in neuroscience is that functional and structural brain connectivity matter. Specifically, it has been accepted that the organization of the brain in interacting segregated networks enables its function. In this paper we delineate the route to a promising approach for investigating timing mechanisms. We illustrate how novel insight into timing mechanisms can come by investigating brain functioning as a multi-layer dynamical network whose clustered dynamics is bound to report the presence of metastable states. We anticipate that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic functioning associated to time perception. This new point of view will help further clarifying mechanisms of neuropsychiatric disorders.

The ability to generate probabilistic expectancies regarding when and where sensory stimuli will occur, is critical to derive timely and accurate inferences about updating contexts. However, the existence of specialized neural networks for inferring predictive relationships between events is still debated. Using graph theoretical analysis applied to structural connectivity data, we tested the extent of brain connectivity properties associated with spatio-temporal predictive performance across 29 healthy subjects. Participants detected visual targets appearing at one out of three locations after one out of three intervals; expectations about stimulus location (spatial condition) or onset (temporal condition) were induced by valid or invalid symbolic cues. Connectivity matrices and centrality/segregation measures, expressing the relative importance of, and the local interactions among specific cerebral areas respect to the behavior under investigation, were calculated from whole-brain tractography and cortico-subcortical parcellation.Results: Response preparedness to cued stimuli relied on different structural connectivity networks for the temporal and spatial domains. Significant covariance was observed between centrality measures of regions within a subcortical-fronto-parietal-occipital network -comprising the left putamen, the right caudate nucleus, the left frontal operculum, the right inferior parietal cortex, the right paracentral lobule and the right superior occipital cortex-, and the ability to respond after a short cue-target delay suggesting that the local connectedness of such nodes plays a central role when the source of temporal expectation is explicit. When the potential for functional segregation was tested, we found highly clustered structural connectivity across the right superior, the left middle inferior frontal gyrus and the left caudate nucleus as related to explicit temporal orienting. Conversely, when the interaction between explicit and implicit temporal orienting processes was considered at the long interval, we found that explicit processes were related to centrality measures of the bilateral inferior parietal lobule. Degree centrality of the same region in the left hemisphere covaried with behavioral measures indexing the process of attentional re-orienting. These results represent a crucial step forward the ordinary predictive processing description, as we identified the patterns of connectivity characterizing the brain organization associated with the ability to generate and update temporal expectancies in case of contextual violations.