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Amnestic mild cognitive impairment (aMCI) is a risk factor for Alzheimer's disease (AD). Multi-domain cognitive training (CT) may slow cognitive decline and delay AD onset. However, most work involves short interventions, targeting single cognitive domains or lacking active controls. We conducted a single-blind randomized controlled trial to investigate the effect of a 6-month, multi-domain CT on Fluid Cognition, functional connectivity in memory and executive functioning networks (primary outcomes), and white matter microstructural properties (secondary outcome) in aMCI. Sixty participants were randomly assigned to either a multi-domain CT or crossword training (CW) group, and thirty-four participants completed the intervention. We found a significant group-by-time interaction in Fluid Cognition (p = 0.007, F (1,28) = 8.26, Cohen's d = 0.38, 95% confidence interval [CI]: 2.45-14.4), with 90% of CT patients showing post-intervention improvements (p < 0.01, Cohen's d = 0.7). The CT group also showed better post-intervention Fluid Cognition than healthy controls (HCs, N = 45, p = 0.045). Functional connectivity analyses showed a significant group-by-time interaction (Cohen's d ≥ 0.8) in the dorsolateral prefrontal cortex (DLPFC) and inferior parietal cortex (IPC) networks. Specifically, CT displayed post-intervention increases whereas CW displayed decreases in functional connectivity. Moreover, increased connectivity strength between the left DLPFC and medial PFC was associated with improved Fluid Cognition. At a microstructural level, we observed a decline in fiber density (FD) for both groups, but the CT group declined less steeply (1.3 vs. 2%). The slower decline in FD for the CT group in several tracts, including the cingulum-hippocampus tract, was associated with better working memory. Finally, we identified regions in cognitive control and memory networks for which baseline functional connectivity and microstructural properties were associated with changes in Fluid Cognition. Long-term, multi-domain CT improves cognitive functioning and functional connectivity and delays structural brain decline in aMCI (ClinicalTrials.gov number: NCT03883308)., (© 2024. The Author(s).)

Background: Tau-PET is a diagnostic tool with high sensitivity and specificity for discriminating Alzheimer's disease (AD) dementia from other neurodegenerative disorders in well-controlled research environments. The role of tau-PET in real-world clinical practice, however, remains to be established. The aim of the TAP-TAU study is therefore to investigate the impact of tau-PET in clinical practice., Methods: TAP-TAU is a prospective, longitudinal multi-center study in 300 patients (≥ 50 years old) with mild cognitive impairment or mild dementia across five Dutch memory clinics. Patients are eligible if diagnostic certainty is < 85% after routine dementia screening and if the differential diagnosis includes AD. More specifically, we will include patients who (i) are suspected of having mixed pathology (e.g., AD and vascular pathology), (ii) have an atypical clinical presentation, and/or (iii) show conflicting or inconclusive outcomes on other tests (e.g., magnetic resonance imaging or cerebrospinal fluid). Participants will undergo a [ 18 F]flortaucipir tau-PET scan, blood-based biomarker sampling, and fill out questionnaires on patient reported outcomes and experiences. The primary outcomes are change (pre- versus post- tau-PET) in diagnosis, diagnostic certainty, patient management and patient anxiety and uncertainty. Secondary outcome measures are head-to-head comparisons between tau-PET and less invasive and lower cost diagnostic tools such as novel blood-based biomarkers and artificial intelligence-based classifiers., Results: TAP-TAU has been approved by the Medical Ethics Committee of the Amsterdam UMC. The first participant is expected to be included in October 2024., Conclusions: In TAP-TAU, we will investigate the added clinical value of tau-PET in a real-world clinical setting, including memory clinic patients with diagnostic uncertainty after routine work-up. Findings of our study may contribute to recommendations regarding which patients would benefit most from assessment with tau-PET. This study is timely in the dawning era of disease modifying treatments as an accurate etiological diagnosis becomes increasingly important., Trial Registration: This trial is registered and authorized on December 21st, 2023 in EU Clinical Trials with registration number 2023-505430-10-00., (© 2024. The Author(s).)

Background: Synaptic degeneration, axonal injury, and white matter disintegration are among the pathological events in Alzheimer's disease (AD), for which growth-associated protein 43 (GAP-43) and diffusion tensor imaging (DTI) could be an indicator. In this study, the cerebrospinal fluid (CSF) GAP-43 clinical trajectories and their association with progression and AD hallmarks with white matter microstructural changes were evaluated., Methods: A total number of 133 participants were enrolled in GAP-43 and DTI values were compared between groups, both cross-sectionally and longitudinally with two and four-year follow-ups. Subsequently, the correlation between GAP-43 levels in the CSF and DTI values was investigated using Spearman's correlation., Results: The CSF level of GAP-43 is negatively correlated with the mean diffusivity measures in Fornix (Cres)/Stria terminals in early and late MCI (r s =-0.478 p = 0.021 and r s =-0.425 p = 0.038). Additionally, the CSF level of GAP-43 is negatively correlated with fractional anisotropy in the cingulum in late MCI (r s =-0.437 p = 0.033). Moreover, the axial diffusivity in superior corona radiate (r s =-0.562 p = 0.005 and r s =-0.484 p = 0.036) and radial diffusivity in superior fronto-occipital fasciculus was negatively correlated with GAP-43 level in the early and mid-MCI participants (r s =-0.520 p = 0.011 and r s =-0.498 p = 0.030)., Conclusions: Presynaptic marker GAP-43 in combination with DTI can be used as a novel biomarker to identify microstructural synaptic degeneration in the early MCI. In addition, it can be used as a biomarker for tracking the progression of AD and monitoring treatment efficacy., (© 2024. The Author(s).)

Convolutional neural networks (CNNs) for extracting structural information from structural magnetic resonance imaging (sMRI), combined with functional magnetic resonance imaging (fMRI) and neuropsychological features, has emerged as a pivotal tool for early diagnosis of Alzheimer's disease (AD). However, the fixed-size convolutional kernels in CNNs have limitations in capturing global features, reducing the effectiveness of AD diagnosis. We introduced a group self-calibrated coordinate attention network (GSCANet) designed for the precise diagnosis of AD using multimodal data, including encompassing Haralick texture features, functional connectivity, and neuropsychological scores. GSCANet utilizes a parallel group self-calibrated module to enhance original spatial features, expanding the field of view and embedding spatial data into channel information through a coordinate attention module, which ensures long-term contextual interaction. In a four-classification comparison (AD vs. early MCI (EMCI) vs. late MCI (LMCI) vs. normal control (NC)), GSCANet demonstrated an accuracy of 78.70%. For the three-classification comparison (AD vs. MCI vs. NC), it achieved an accuracy of 83.33%. Moreover, our method exhibited impressive accuracies in the AD vs. NC (92.81%) and EMCI vs. LMCI (84.67%) classifications. GSCANet improves classification performance at different stages of AD by employing group self-calibrated to expand features receptive field and integrating coordinated attention to facilitate significant interactions among channels and spaces. Providing insights into AD mechanisms and showcasing scalability for various disease predictions., (© 2024. The Author(s).)

Long-term cognitive impairment is common in cardiac arrest survivors. Screening to identify patients at risk is recommended. Functional magnetic resonance brain imaging (fMRI) holds potential to contribute to prediction of cognitive outcomes. In this study, we investigated the possible value of early changes in resting-state networks for predicting short and long-term cognitive functioning of cardiac arrest survivors. We performed a prospective multicenter cohort study in cardiac arrest survivors in three Dutch hospitals. Resting-state fMRI scans were acquired within a month after cardiac arrest. We primarily focused on functional connectivity within the default-mode network (DMN) and salience network (SN), and additionally explored functional connectivity in seven other networks. Cognitive outcome was measured using the Montreal Cognitive Assessment (MoCA) during hospital admission and at 3 and 12 months, and by neuropsychological examination (NPE) at 12 months. We tested mixed effects models to evaluate the value of connectivity within the networks for predicting global cognitive outcomes at the three time points, and long-term cognitive outcomes in the memory, attention, and executive functioning domains. We included 80 patients (age 60 ± 11 years, 72 (90%) male). MoCA scores increased significantly between hospital admission and 3 months (ΔMoCA hospital-3M  = 2.89, p < 0.01), but not between 3 and 12 months (ΔMoCA 3M-12M  = 0.38, p = 0.52). Connectivity within the DMN, SN, and dorsal attention network (DAN) was positively related to global cognitive functioning during hospital admission (β DMN  = 0.85, p = 0.03; β SN  = 1.48, p < 0.01; β DAN  = 0.96, p = 0.01), but not at 3 and 12 months. Network connectivity was also unrelated to long-term memory, attention, or executive functioning. Resting-state functional connectivity in the DMN, SN, and DAN measured in the first month after cardiac arrest is related to short-term global, but not long-term global or domain-specific cognitive performance of survivors. These results do not support the value of functional connectivity within these RSNs for prediction of long-term cognitive performance after cardiac arrest., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Early stages of Alzheimer's disease (AD) are associated with volume reductions in specific subregions of the medial temporal lobe (MTL). Using a manual segmentation method-the Olsen-Amaral-Palombo (OAP) protocol-previous work in healthy older adults showed that reductions in grey matter volumes in MTL subregions were associated with lower scores on the Montreal Cognitive Assessment (MoCA), suggesting atrophy may occur prior to diagnosis of mild cognitive impairment, a condition that often progresses to AD. However, current "gold standard" manual segmentation methods are labour intensive and time consuming. Here, we examined the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) to detect volumetric differences in MTL subregions of healthy older adults who varied in cognitive status as determined by the MoCA. We trained ASHS on the OAP protocol to create the ASHS-OAP atlas and then examined how well automated segmentation replicated manual segmentation. Volumetric measures obtained from the ASHS-OAP atlas were also contrasted against those from the ASHS-PMC atlas, a widely used atlas provided by the ASHS team. The pattern of volumetric results was similar between the ASHS-OAP atlas and manual segmentation for anterolateral entorhinal cortex and perirhinal cortex, suggesting that ASHS-OAP is a viable alternative to current manual segmentation methods for detecting group differences based on cognitive status. Although ASHS-OAP and ASHS-PMC produced varying volumes for most regions of interest, they both identified early signs of neurodegeneration in CA 2 /CA 3 /DG and identified marginal differences in entorhinal cortex. Our findings highlight the utility of automated segmentation methods but still underscore the need for a unified and harmonized MTL segmentation atlas., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Introduction: Atrophy of the nucleus basalis of Meynert (NBM) is an early indicator of Alzheimer's disease (AD). However, reduced integrity of the NBM white matter tracts may be more relevant for cognitive impairment and progression to dementia than NBM volume. Research is needed to compare differences in NBM volume and integrity of the lateral and medial NBM tracts across early and later stages of AD progression., Methods: 187 participants were included in this study who were either healthy controls (HC; n = 50) or had early mild cognitive impairment (EMCI; n = 50), late MCI (LMCI; n = 37), or AD (n = 50). NBM volume was calculated using voxel-based morphometry and mean diffusivity (MD) of the lateral and medial NBM tracts were extracted using probabilistic tractography. Between group differences in NBM volume and tract MD were compared using linear mixed models controlling for age, sex, and either total intracranial volume or MD of a control mask, respectively. Associations between NBM volume and tract MD with executive function, memory, language, and visuospatial function were also analysed., Results: NBM volume was smallest in AD followed by LMCI (p < 0.0001), with no difference between EMCI and HC. AD had highest MD for both tracts compared to all other groups (p < 0.01). Both MCI groups had higher lateral tract MD compared to HC (p < 0.05). Medial tract MD was higher in LMCI (p = 0.008), but not EMCI (p = 0.09) compared to HC. Higher lateral tract MD was associated with executive function (p = 0.001) and language (p = 0.02)., Discussion: Integrity of the lateral NBM tract is most sensitive to the earliest stages of AD and should be considered an important therapeutic target for early detection and intervention., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Arterial stiffness (arteriosclerosis) has been linked to heightened risks for cognitive decline, and ultimately for Alzheimer's disease and other forms of dementia. Importantly, neurovascular outcomes generally vary according to one's biological sex. Here, capitalizing on a large sample of participants with neuroimaging and behavioral data (N = 203, age range = 18-87 years), we aimed to provide support for a hierarchical model of neurocognitive aging, which links age-related declines in cerebrovascular health to the rate of cognitive decline via a series of intervening variables, such as white matter integrity. By applying a novel piecewise regression approach to our cross-sectional sample to support Granger-like temporal inferences, we show that, on average, a precipitous decline in cerebral arterial elasticity (measured with diffuse optical imaging of the cerebral arterial pulse; pulse-DOT) precedes an acceleration in the development of white matter lesions by nearly a decade, with women protected from these deleterious effects until approximately age 50, the average onset of menopause. By employing multiple-mediator path analyses while controlling for sex, we show that age may impair cognition via the sequential indirect effects of arteriosclerosis and white matter atrophy on fluid, but not crystallized, abilities. Importantly, we replicate these results using pulse pressure, an independent index of arterial health, thereby providing converging evidence for the central role of arteriosclerosis as an accelerating factor in normal and pathological aging and identifying robust sex-related differences in the progression of cerebral arteriosclerosis and white matter degradation., Competing Interests: Declaration of competing interest None of the authors of this article has any financial or other conflicts of interest regarding this work., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: In Alzheimer's disease (AD), the associations between tau pathology and brain atrophy and cognitive decline are well established, but imperfect. We investigate whether cerebrospinal fluid (CSF) biomarkers of biological processes (vascular, synaptic, and axonal integrity, neuroinflammation, neurotrophic factors) explain the disconnection between tau pathology and brain atrophy (brain resilience), and tau pathology and cognitive decline (cognitive resilience)., Methods: We included 428 amyloid positive participants (134 cognitively unimpaired (CU), 128 with mild cognitive impairment (MCI), 166 with AD dementia) from the BioFINDER-2 study. At baseline, participants underwent tau positron emission tomography (tau-PET), magnetic resonance imaging (MRI), cognitive testing, and lumbar puncture. Longitudinal data were available for MRI (mean (standard deviation) follow-up 26.4 (10.7) months) and cognition (25.2 (11.4) months). We analysed 18 pre-selected CSF proteins, reflecting vascular, synaptic, and axonal integrity, neuroinflammation, and neurotrophic factors. Stratifying by cognitive status, we performed linear mixed-effects models with cortical thickness (brain resilience) and global cognition (cognitive resilience) as dependent variables to assess whether the CSF biomarkers interacted with tau-PET levels in its effect on cortical atrophy and cognitive decline., Results: Regarding brain resilience, interaction effects were observed in AD dementia, with vascular integrity biomarkers (VEGF-A (β interaction  = -0.009, p FDR  = 0.047) and VEGF-B (β interaction  = -0.010, p FDR  = 0.037)) negatively moderating the association between tau-PET signal and atrophy. In MCI, higher NfL levels were associated with more longitudinal cortical atrophy (β = -0.109, p FDR  = 0.033) and lower baseline cortical thickness (β = -0.708, p FDR  = 0.033) controlling for tau-PET signal. Cognitive resilience analyses in CU revealed interactions with tau-PET signal for inflammatory (GFAP, IL-15; β interaction -0.073--0.069, p FDR 0.001-0.045), vascular (VEGF-A, VEGF-D, PGF; β interaction -0.099--0.063, p FDR  < 0.001-0.046), synaptic (14-3-3ζ/δ; β interaction  = -0.092, p FDR  = 0.041), axonal (NfL; β interaction  = -0.079, p FDR  < 0.001), and neurotrophic (NGF; β interaction  = 0.091, p FDR  < 0.001) biomarkers. In MCI higher NfL levels (β main  = -0.690, p FDR  = 0.025) were associated with faster cognitive decline independent of tau-PET signal., Conclusions: Biomarkers of co-existing pathological processes, in particular vascular pathology and axonal degeneration, interact with levels of tau pathology on its association with the downstream effects of AD pathology (i.e. brain atrophy and cognitive decline). This indicates that vascular pathology and axonal degeneration could impact brain and cognitive resilience., (© 2024. The Author(s).)

Study Objectives: Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network, and central executive network (CEN)., Methods: We selected 320 participants from the ADNI database and divided them by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores., Results: Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterized by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were nonsignificant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD., Conclusions: We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society.)

Background: Early detection of Alzheimer's disease (AD) is essential for timely management and consideration of therapeutic options; therefore, detecting the risk of conversion from mild cognitive impairment (MCI) to AD is crucial during neurodegenerative progression. Existing neuroimaging studies have mostly focused on group differences between individuals with MCI (or AD) and cognitively normal (CN), discarding the temporal information of conversion time. Here, we aimed to develop a prognostic model for AD conversion using functional connectivity (FC) and Cox regression suitable for conversion event modeling., Methods: We developed a prognostic model using a large-scale Alzheimer's Disease Neuroimaging Initiative dataset, and it was validated using external data obtained from the Open Access Series of Imaging Studies. We considered individuals who were initially CN or had MCI but progressed to AD and those with MCI with no progression to AD during the five-year follow-up period. As the exact conversion time to AD is unknown, we inferred this information using imputation approaches. We generated cortex-wide principal FC gradients using manifold learning techniques and computed subcortical-weighted manifold degrees from baseline functional magnetic resonance imaging data. A penalized Cox regression model with an elastic net penalty was adopted to define a risk score predicting the risk of conversion to AD, using FC gradients and clinical factors as regressors., Results: Our prognostic model predicted the conversion risk and confirmed the role of imaging-derived manifolds in the conversion risk. The brain regions that largely contributed to predicting AD conversion were the heteromodal association and visual cortices, as well as the caudate and hippocampus. Our risk score based on Cox regression was consistent with the expected disease trajectories and correlated with positron emission tomography tracer uptake and symptom severity, reinforcing its clinical usefulness. Our findings were validated using an independent dataset. The cross-sectional application of our model showed a higher risk for AD than that for MCI, which correlated with symptom severity scores in the validation dataset., Conclusion: We proposed a prognostic model predicting the risk of conversion to AD. The associated risk score may provide insights for early intervention in individuals at risk of AD conversion., (© 2024. The Author(s).)

White matter microvascular alterations in temporal lobe epilepsy (TLE) may be relevant to acquired neurodegenerative processes and cognitive impairments associated with this condition. We quantified microvascular changes, myelin, axonal, glial and extracellular-matrix labelling in the gyral core and deep temporal lobe white matter regions in surgical resections from 44 TLE patients with or without hippocampal sclerosis. We compared this pathology data with in vivo pre-operative MRI diffusion measurements in co-registered regions and neuropsychological measures of cognitive impairment and decline. In resections, increased arteriolosclerosis was observed in TLE compared to non-epilepsy controls (greater sclerotic index, p < 0.001), independent of age. Microvascular changes included increased vascular densities in some regions but uniformly reduced mean vascular size (quantified with collagen-4, p < 0.05-0.0001), and increased pericyte coverage of small vessels and capillaries particularly in deep white matter (quantified with platelet-derived growth factor receptorβ and smooth muscle actin, p < 0.01) which was more marked the longer the duration of epilepsy (p < 0.05). We noted increased glial numbers (Olig2, Iba1) but reduced myelin (MAG, PLP) in TLE compared to controls, particularly prominent in deep white matter. Gene expression analysis showed a greater reduction of myelination genes in HS than non-HS cases and with age and correlation with diffusion MRI alterations. Glial densities and vascular size were increased with increased MRI diffusivity and vascular density with white matter abnormality quantified using fixel-based analysis. Increased perivascular space was associated with reduced fractional anisotropy as well as age-accelerated cognitive decline prior to surgery (p < 0.05). In summary, likely acquired microangiopathic changes in TLE, including vascular sclerosis, increased pericyte coverage and reduced small vessel size, may indicate a functional alteration in contractility of small vessels and haemodynamics that could impact on tissue perfusion. These morphological features correlate with white matter diffusion MRI alterations and might explain cognitive decline in TLE., (© 2024. The Author(s).)

Background and Objectives: Despite their temporal lobe pathology, a significant subgroup of patients with temporal lobe epilepsy (TLE) is able to maintain normative cognitive functioning. In this study, we identify patients with TLE with intact vs impaired neurocognitive profiles and interrogate for the presence of both normative and highly individual intrinsic connectivity networks (ICNs)-all toward understanding the transition from impaired to intact neurocognitive status., Methods: This retrospective cross-sectional study included patients with TLE and matched healthy controls (HCs) from the Thomas Jefferson Comprehensive Epilepsy Center. Functional MRI data were decomposed using independent component analysis to obtain individualized ICNs. In this article, we calculated the degree of match between individualized ICNs and canonical ICNs (e.g., 17 resting-state networks by Yeo et al.) and divided each participant's ICNs into normative or non-normative status based on the degree of match., Results: 100 patients with TLE (mean age 42.0 [SD: 13.7] years, 47 women) and 92 HCs were included in this study. We found that the individualized networks matched to the canonical networks less well in the cognitively impaired (n = 24) compared with the cognitively intact (n = 63) patients with TLE by 2-way mixed-measures analysis of variance (impaired vs intact mean difference [MD] -0.165 [-0.317, -0.013], p = 0.028). The cognitively impaired patients showed significant abnormalities in the profiles of both normative (impaired vs intact MD -0.537 [-0.998, -0.076], p = 0.017, intact vs HC MD -0.221 [-0.536, 0.924], p = 0.220, and impaired vs HC MD -0.759 [-1.200, -0.319], p < 0.001) and non-normative networks (impaired vs intact MD 0.484 [0.030, 0.937], p = 0.033, intact vs HC MD 0.369 [0.059, 0.678], p = 0.014, and impaired vs HC MD 0.853 [0.419, 1.286], p < 0.001) while the intact patients showed abnormalities only in non-normative networks. At the same time, we found that normative networks held a strong, positive association with the neuropsychological measures, with this association negative in non-normative networks., Discussion: Our data demonstrated that significant cognitive deficits are associated with the status of both canonical and highly individual ICNs, making clear that the transition from intact to impaired cognitive status is not simply the result of disruption to normative brain networks.

Gray matter changes are thought to be closely related to cognitive decline in mild cognitive impairment (MCI) patients. The study aimed to explore cortical and subcortical structural alterations in MCI and their association with cognitive assessment. 24 MCI patients and 22 normal controls (NCs) were included. Voxel-based morphometry (VBM), vertex-based shape analysis and surface-based morphometry (SBM) analysis were applied to explore subcortical nuclei volume, shape and cortical morphology. Correlations between structural changes and cognition were explored using spearman correlation analysis. Support vector machine (SVM) classification evaluated MCI identification accuracy. MCI patients showed significant atrophy in the left thalamus, left hippocampus, left amygdala, right pallidum, right hippocampus, along with inward deformation in the left amygdala. SBM analysis revealed that MCI group exhibited shallower sulci depth in the left hemisphere and increased cortical gyrification index (GI) in the right frontal gyrus. Correlation analysis showed the positive correlation between right hippocampus volume and episodic memory, while negative correlation between the altered GI and memory performance in MCI group. SVM analysis demonstrated superior performance of sulci depth and GI derived from SBM in MCI identification. When combined with cortical and subcortical metrics, SVM achieved a peak accuracy of 89 % in distinguishing MCI from NC. The study reveals significant gray matter structural changes in MCI, suggesting their potential role in underlying functional differences and neural mechanisms behind memory impairment in MCI., Competing Interests: Declaration of Competing Interest 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., (Copyright © 2024. Published by Elsevier Inc.)

We aimed to longitudinally examine the relationship between depression and cognitive function and investigate the mediating effects of imaging indicators in this relationship. 2,251 subjects with longitudinal assessment of geriatric depression scale, Mini-Mental State Examination, Montreal Cognitive Assessment, Clinical Dementia Rating-Sum of Boxes (CDRSB), Alzheimer's Disease Assessment Scale11, Alzheimer's Disease Assessment Scale13 and imaging of 3DT1, diffusion tensor imaging, fluid-attenuated inversion recovery, arterial spin labeling, fluorodeoxyglucose positron emission tomography, 18F-AV45-PET, and 18F-AV1451-PET were included from the Alzheimer's Disease Neuroimaging Initiative database. The multivariate mixed-effects models were employed to analyze the correlation between geriatric depression scale scores, cognitive function, and imaging indicators. The sgmediation software package was utilized to analyze the mediating effects of imaging indicators. The geriatric depression scale was negatively correlated with Mini-Mental State Examination and Montreal Cognitive Assessment, and positively correlated with CDRSB, Alzheimer's Disease Assessment Scale11, and Alzheimer's Disease Assessment Scale13 when the subjects were not grouped. The geriatric depression scale was negatively correlated with Montreal Cognitive Assessment and positively correlated with Alzheimer's Disease Assessment Scal13 in groups with baseline diagnosis of early mild cognitive impairment and late mild cognitive impairment. Furthermore, depression was associated with regional imaging indicators, while cognitive function was linked to broad imaging indicators. Some of these indicators were related to both depression and cognitive function, playing a mediating role in their relationship. Depression was related to cognitive function, especially in subjects with mild cognitive impairment. Some imaging indicators may represent the underlying basis for the association between depression and cognitive function., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Impaired episodic memory is the primary feature of early Alzheimer's disease (AD), but not all memories are equally affected. Patients with AD and amnestic Mild Cognitive Impairment (aMCI) remember pictures better than words, to a greater extent than healthy elderly. We investigated neural mechanisms for visual object recognition in 30 patients (14 AD, 16 aMCI) and 36 cognitively unimpaired healthy (19 in the "preclinical" stage of AD). Event-related brain potentials (ERPs) were recorded while participants performed a visual object recognition task. Hippocampal occupancy (integrity), amyloid (florbetapir) PET, and neuropsychological measures of verbal & visual memory, executive function were also collected. A right-frontal ERP recognition effect (500-700 ms post-stimulus) was seen in cognitively unimpaired participants only, and significantly correlated with memory and executive function abilities. A later right-posterior negative ERP effect (700-900 ms) correlated with visual memory abilities across participants with low verbal memory ability, and may reflect a compensatory mechanism. A correlation of this retrieval-related negativity with right hippocampal occupancy (r = 0.55), implicates the hippocampus in the engagement of compensatory perceptual retrieval mechanisms. Our results suggest that early AD patients are impaired in goal-directed retrieval processing, but may engage compensatory perceptual mechanisms which rely on hippocampal function., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Cognitive impairment is an increasingly recognized comorbidity of diabetes, yet the mechanisms underlying this association remain poorly understood. This knowledge gap has contributed to conflicting findings regarding the impact of diabetes on long-term cognitive outcomes in older adults. The presence of cerebrovascular disease (CeVD) may potentially modify this relationship. However, interactive effect between diabetes and subclinical MRI markers of CeVD on cognitive trajectories and incident dementia remains unexplored., Methods: A total of 654 participants underwent brain MRI at baseline, from whom 614 with at least one follow-up were selected for longitudinal analysis. Cognitive tests were performed annually up to 5 years. CeVD markers of interest were lacunes, white matter hyperintensities (WMHs), cerebral microbleeds (CMBs), cortical microinfarcts (CMIs), intracranial stenosis (ICS), and cortical infarcts. Blood-based Alzheimer biomarkers, including p-tau181 and p-tau181/Aβ42 ratio, were used as indicators of Alzheimer pathology., Results: At baseline, diabetes was associated with lower cognitive performance and higher burden of CeVD, but not p-tau181 or p-tau181/Aβ42 ratio. Longitudinally, we found an interactive effect of diabetes and WMHs, rather than an independent effect of diabetes, on cognitive decline and dementia risk. Subgroup analyses showed association of diabetes with cognitive outcomes was stronger in participants with high WMHs load but non-significant in those with low WMHs load. Moreover, these associations remained unchanged after adjusting for blood-based Alzheimer biomarkers., Conclusions: The effect of diabetes on cognitive decline is contingent upon the presence of WMHs and independent of Alzheimer's pathology. This finding raises the possibility of utilizing WMHs as an imaging biomarker to identify diabetic subgroup at greater risk of developing cognitive impairment. Furthermore, therapeutic interventions targeting WMHs may prevent cognitive deterioration in older adults with diabetes., (© 2024. The Author(s).)

Alzheimer's disease is the most common major neurocognitive disorder. Although currently, no cure exists, understanding the neurobiological substrate underlying Alzheimer's disease progression will facilitate early diagnosis and treatment, slow disease progression, and improve prognosis. In this study, we aimed to understand the morphological changes underlying Alzheimer's disease progression using structural magnetic resonance imaging data from cognitively normal individuals, individuals with mild cognitive impairment, and Alzheimer's disease via a contrastive variational autoencoder model. We used contrastive variational autoencoder to generate synthetic data to boost the downstream classification performance. Due to the ability to parse out the nonclinical factors such as age and gender, contrastive variational autoencoder facilitated a purer comparison between different Alzheimer's disease stages to identify the pathological changes specific to Alzheimer's disease progression. We showed that brain morphological changes across Alzheimer's disease stages were significantly associated with individuals' neurofilament light chain concentration, a potential biomarker for Alzheimer's disease, highlighting the biological plausibility of our results., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Between 2.5% and 28% of people infected with SARS-CoV-2 suffer long COVID or persistence of symptoms for months after acute illness. Many symptoms are neurological, but the brain changes underlying the neuropsychological impairments remain unclear. This study aimed to provide a detailed description of the cognitive profile, the pattern of brain alterations in long COVID and the potential association between them. To address these objectives, 83 patients with persistent neurological symptoms after COVID-19 were recruited, and 22 now healthy control subjects chosen because they had suffered COVID-19 but did not experience persistent neurological symptoms. Patients and controls were matched for age, sex and educational level. All participants were assessed by clinical interview, comprehensive standardized neuropsychological tests and structural MRI. The mean global cognitive function of patients with long COVID assessed by Addenbrooke's Cognitive Examination-III screening test [overall cognitive level (OCLz) = -0.39 ± 0.12] was significantly below the infection recovered-controls (OCLz = +0.32 ± 0.16, P < 0.01). We observed that 48% of patients with long COVID had episodic memory deficit, with 27% also with impaired overall cognitive function, especially attention, working memory, processing speed and verbal fluency. The MRI examination included grey matter morphometry and whole brain structural connectivity analysis. Compared to infection recovered controls, patients had thinner cortex in a specific cluster centred on the left posterior superior temporal gyrus. In addition, lower fractional anisotropy and higher radial diffusivity were observed in widespread areas of the patients' cerebral white matter relative to these controls. Correlations between cognitive status and brain abnormalities revealed a relationship between altered connectivity of white matter regions and impairments of episodic memory, overall cognitive function, attention and verbal fluency. This study shows that patients with neurological long COVID suffer brain changes, especially in several white matter areas, and these are associated with impairments of specific cognitive functions., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. 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.)

Background and Purpose: Resting-state functional MRI (rs-fMRI) can be used to estimate functional connectivity (FC) between different brain regions, which may be of value for identifying cognitive impairment in patients with brain tumors. Unfortunately, neither rs-fMRI nor neurocognitive assessments are routinely assessed clinically, mostly due to limitations in examination time and cost. Since DSC perfusion MRI is often used clinically to assess tumor vascularity and similarly uses a gradient-echo-EPI sequence for T2*-sensitivity, we theorized a "pseudo-rs-fMRI" signal could be derived from DSC perfusion to simultaneously quantify FC and perfusion metrics, and these metrics can be used to estimate cognitive impairment in patients with brain tumors., Materials and Methods: Twenty-four consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, resting-sate functional MRI (rs-fMRI), and neurocognitive assessment. Voxelwise modeling of contrast bolus dynamics during DSC acquisition was performed and then subtracted from the original signal to generate a residual "pseudo-rs-fMRI" signal. Following the preprocessing of pseudo-rs-fMRI, full rs-fMRI, and a truncated version of the full rs-fMRI (first 100 timepoints) data, the default mode, motor, and language network maps were generated with atlas-based ROIs, Dice scores were calculated for the resting-state network maps from pseudo-rs-fMRI and truncated rs-fMRI using the full rs-fMRI maps as reference. Seed-to-voxel and ROI-to-ROI analyses were performed to assess FC differences between cognitively impaired and nonimpaired patients., Results: Dice scores for the group-level and patient-level (mean±SD) default mode, motor, and language network maps using pseudo-rs-fMRI were 0.905/0.689 ± 0.118 (group/patient), 0.973/0.730 ± 0.124, and 0.935/0.665 ± 0.142, respectively. There was no significant difference in Dice scores between pseudo-rs-fMRI and the truncated rs-fMRI default mode ( P = .97) or language networks ( P = .30), but there was a difference in motor networks ( P = .02). A multiple logistic regression classifier applied to ROI-to-ROI FC networks using pseudo-rs-fMRI could identify cognitively impaired patients (sensitivity = 84.6%, specificity = 63.6%, receiver operating characteristic area under the curve (AUC) = 0.7762 ± 0.0954 (standard error), P = .0221) and performance was not significantly different from full rs-fMRI predictions (AUC = 0.8881 ± 0.0733 (standard error), P = .0013, P = .29 compared with pseudo-rs-fMRI)., Conclusions: DSC perfusion MRI-derived pseudo-rs-fMRI data can be used to perform typical rs-fMRI FC analyses that may identify cognitive decline in patients with brain tumors while still simultaneously performing perfusion analyses., (© 2024 by American Journal of Neuroradiology.)

Background: Cholinesterase inhibitors (ChEIs) are prescribed for Alzheimer's disease (AD) and sometimes for mild cognitive impairment (MCI) without knowing underlying pathologies and its effect on cognition. We investigated the frequency of ChEI prescriptions in amyloid-negative MCI and their association with cognitive changes in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort., Methods: We included participants with amyloid positron emission tomography (PET)-negative MCI from the ADNI. We analyzed the associations of ChEI use with cognitive changes, brain volume, and cerebrospinal fluid (CSF) total tau (t-tau), hyperphosphorylated tau 181 (p-tau 181 ), and p-tau 181 /t-tau ratio., Results: ChEIs were prescribed in 27.4% of amyloid PET-negative MCI and were associated with faster cognitive decline, reduced baseline hippocampal volume and entorhinal cortical thickness, and a longitudinal decrease in the frontal lobe cortical thickness., Conclusions: The association between ChEI use and accelerated cognitive decline may stem from underlying pathologies involving reduced hippocampal volume, entorhinal cortical thickness and faster frontal lobe atrophy. We suggest that ChEI use in amyloid PET-negative MCI patients might need further consideration, and studies investigating the causality between ChEI use and cognitive decline are warranted in the future., (© 2024. The Author(s).)

Background: Recent magnetic resonance imaging (MRI) studies have established that brain iron accumulation might accelerate cognitive decline in Alzheimer's disease (AD) patients. Both normal aging and AD are associated with cerebral atrophy in specific regions. However, no studies have investigated aging- and AD-selective iron deposition-related cognitive changes during normal aging. Here, we applied quantitative susceptibility mapping (QSM) to detect iron levels in cortical signature regions and assessed the relationships among iron, atrophy, and cognitive changes in older adults., Methods: In this Taizhou Imaging Study, 770 older adults (mean age 62.0 ± 4.93 years, 57.5% women) underwent brain MRI to measure brain iron and atrophy, of whom 219 underwent neuropsychological tests nearly every 12 months for up to a mean follow-up of 2.68 years. Global cognition was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Domain-specific cognitive scores were obtained from MoCA subscore components. Regional analyses were performed for cortical regions and 2 signature regions where atrophy affected by aging and AD only: Aging (AG) -specific and AD signature meta-ROIs. The QSM and cortical morphometry means of the above ROIs were also computed., Results: Significant associations were found between QSM levels and cognitive scores. In particular, after adjusting for cortical thickness of regions of interest (ROIs), participants in the upper tertile of the cortical and AG-specific signature QSM exhibited worse ZMMSE than did those in the lower tertile [ β = -0.104, p = 0.026; β = -0.118, p = 0.021, respectively]. Longitudinal analysis suggested that QSM values in all ROIs might predict decline in ZMoCA and key domains such as attention and visuospatial function (all p < 0.05). Furthermore, iron levels were negatively correlated with classic MRI markers of cortical atrophy (cortical thickness, gray matter volume, and local gyrification index) in total, AG-specific signature and AD signature regions (all p < 0.05)., Conclusion: AG- and AD-selective iron deposition was associated with atrophy and cognitive decline in elderly people, highlighting its potential as a neuroimaging marker for cognitive aging., (© 2024. The Author(s).)

Objective: This meta-analysis aimed to evaluate the comparative diagnostic performance of amyloid-β positron emission tomography (Aβ PET) and magnetic resonance imaging (MRI) in diagnosing Alzheimer's disease (AD)., Methods: An extensive search was conducted in the PubMed and Embase databases to identify available publications up to December 2023. Head-to-head comparative studies were included if they evaluated the diagnostic performance of Aβ PET and MRI in diagnosing Alzheimer's disease. Sensitivity and specificity were assessed using the DerSimonian and Laird method, followed by transformation via the Freeman-Tukey double inverse sine transformation., Results: Six articles involving 560 patients were included in the meta-analysis. When distinguishing AD from mild cognitive impairment (MCI), both methods showed comparable sensitivity (Aβ PET: 0.71, MRI: 0.62) and specificity (Aβ PET: 0.68, MRI: 0.69), with no statistically significant differences observed (p = 0.34 and 0.99). When identifying AD from normal cognitive control (NC), both Aβ PET and MRI showed similar results, with comparable sensitivity (Aβ PET: 0.93, MRI: 0.85) and specificity (Aβ PET: 0.95, MRI: 0.82), without significant differences (p = 0.38 and 0.19). Similarly, in detecting MCI from NC, both Aβ PET and MRI demonstrated similar sensitivity (Aβ PET: 0.69, MRI: 0.64) and specificity (Aβ PET: 0.75, MRI: 0.76) without significant differences (p = 0.40 and 0.94). However, 18F-FMM seems to have a higher specificity compared to MRI when distinguishing AD from MCI (P = 0.03) and AD from NC (p = 0.04)., Conclusions: Our meta-analysis indicates that Aβ PET demonstrates similar sensitivity and specificity to MRI in diagnosing Alzheimer's disease. However, the limited number of studies may impact the evidence of the current study; further larger sample prospective research is required to confirm these findings., (© 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)

Objective: The pathophysiology behind memory impairment in Parkinson's Disease Mild Cognitive Impairment (PD-MCI) is unclear. This study aims to investigate the hippocampal and cortical atrophy patterns in PD-MCI patients with different types of memory impairments, categorized as Retrieval Failure (RF) and Encoding Failure (EF)., Methods: The study included 16 healthy controls (HC) and 34 PD-MCI patients, divided into RF (N = 18) and EF (N = 16) groups based on their Verbal Memory Processes Test (VMPT) scores, including spontaneous recall, recognition, and Index of Sensitivity to Cueing (ISC). Hippocampal subfields and cortical thicknesses were measured using the FreeSurfer software for automatic segmentation., Results: Compared to the HC group, the EF group exhibited significant atrophy in the left lateral occipital region and the right caudal middle frontal, superior temporal, and inferior temporal regions (p⟨0.05). The RF group displayed significant atrophy in the left lateral occipital, middle temporal, and precentral regions, as well as the right pars orbitalis and superior frontal regions (p⟨0.05). Hippocampal subfield analysis revealed distinct volume differences between HC-EF and RF-EF groups, with significant reductions in the CA1, CA3, and CA4 subregions in the EF group, but no differences between HC and RF groups (p > 0.05)., Conclusion: Gray matter atrophy patterns differ in PD-MCI patients with encoding and retrieval memory impairments. The significant hippocampal atrophy in the EF group, particularly in the CA subregions, highlights its potential role in disease progression and memory decline. Additionally, the convergence of atrophy in the lateral occipital cortex across both RF and EF groups suggests the involvement of the Parietal Memory Network (PMN) in PD-related memory impairment., (© 2024 The Author(s). CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

Patients with congenital heart disease (CHD) demonstrate altered structural brain network connectivity. However, there is large variability between reported results and little information is available to identify those patients at highest risk for brain alterations. Thus, we aimed to investigate if network connectivity measures were associated with the individual patient's cumulative load of clinical risk factors and with family-environmental factors in a cohort of adolescents with CHD. Further, we investigated associations with executive function impairments. In 53 adolescents with CHD who underwent open-heart surgery during infancy, and 75 healthy controls, diffusion magnetic resonance imaging and neuropsychological assessment was conducted at a mean age of 13.2 ± 1.3 years. Structural connectomes were constructed using constrained spherical deconvolution tractography. Graph theory and network-based statistics were applied to investigate network connectivity measures. A cumulative clinical risk (CCR) score was built by summing up binary risk factors (neonatal, cardiac, neurologic) based on clinically relevant thresholds. The role of family-environmental factors (parental education, parental mental health, and family function) was investigated. An age-adjusted executive function summary score was built from nine neuropsychological tests. While network integration and segregation were preserved in adolescents with CHD, they showed lower edge strength in a dense subnetwork. A higher CCR score was associated with lower network segregation, edge strength, and executive function performance. Edge strength was particularly reduced in a subnetwork including inter-frontal and fronto-parietal-thalamic connections. There was no association with family-environmental factors. Poorer executive functioning was associated with lower network integration and segregation. We demonstrated evidence for alterations of network connectivity strength in adolescents with CHD - particularly in those patients who face a cumulative exposure to multiple clinical risk factors over time. Quantifying the cumulative load of risk early in life may help to better predict trajectories of brain development in order to identify and support the most vulnerable patients as early as possible., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Background: Persistent pain is a prominent symptom of knee osteoarthritis (KOA) and has been associated with cognitive decline in individuals with KOA. The amygdala, a complex structure consisting of nine subnuclei, and programmed cell death protein-1 (PD-1) levels play crucial roles in pain regulation and cognitive processing. This study aims to investigate the relationships among amygdala subregion volumes, cognitive function, and PD-1 levels to elucidate the underlying mechanism of cognitive decline in KOA., Methods: In this cross-sectional study, we recruited 36 patients with KOA and 25 age/gender-matched healthy controls for neuropsychological tests, structural magnetic resonance imaging scanning, and measurement of serum PD-1 levels. We used the atlas provided by FreeSurfer software to automatically segment the amygdala subnuclei. Subsequently, we compared the volumes of amygdala subregions between groups and explored their correlation with clinical scores and PD-1 levels., Results: Compared to healthy controls, individuals with KOA exhibited significantly lower scores on global cognition tasks, such as long-delay free recall, short-delay free recall, and immediate recall tasks. Moreover, they displayed decreased volumes in lateral nucleus basal nucleus paralaminar nucleus while showing increased volumes in accessory basal nucleus, central nucleus, medial nucleus, and cortical nucleus. Within the KOA group specifically, paralaminar volume was negatively correlated with immediate recall scores; pain scores were negatively correlated with global cognition; basal volume was negatively correlated with PD-1 levels., Conclusion: Our findings highlight those alterations in amygdala subregion volumes along with changes in serum PD-1 levels may contribute to observe cognitive decline among individuals suffering from KOA., (© 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)

Alzheimer's disease (AD) affects the hippocampus during its progression, but the specific observable changes of hippocampal subfields during disease progression remain poorly understood. In this study, we employed an event-based model (EBM) to determine the sequence of occurrence of hippocampal subfield atrophy in mild cognitive impairment (MCI) and AD cohorts. Subjects (207) were included: 86 MCI, 53 AD, and 68 healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent structural magnetic resonance imaging (MRI) scans to analyse the hippocampal subfields. We assigned each patient to a specific EBM stage, based on the number of their abnormal subfields. A combination of 2-year follow-up MRI scans were applied to demonstrate the longitudinal consistency and utility of the model's staging system. The model estimated that the earliest atrophy occurs in the hippocampal fissure, then spreading to other subregions in both MCI and AD. We identified a marked divergence between the sequences of left and right hippocampal subfields atrophy, so inter-hemispheric asymmetry pattern was further analysed. The sequence of asymmetry index (AI) increases beginning in the molecular and granule cell layers of the dentate gyrus (GC-ML-DG), cornus ammonis (CA) 4, and the molecular layer (ML). Longitudinal analysis confirms the efficacy of the model. In addition, the model stages were significantly correlated with patients' memory scores (p < .05). Collectively, we used a data-driven method to provide new insight into AD hippocampal progression. The present model could aid in understanding of the disease stages, as well as tracking memory decline., (© 2024 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Introduction: Neuroanatomical normative modeling captures individual variability in Alzheimer's disease (AD). Here we used normative modeling to track individuals' disease progression in people with mild cognitive impairment (MCI) and patients with AD., Methods: Cortical and subcortical normative models were generated using healthy controls (n ≈ 58k). These models were used to calculate regional z scores in 3233 T1-weighted magnetic resonance imaging time-series scans from 1181 participants. Regions with z scores < -1.96 were classified as outliers mapped on the brain and summarized by total outlier count (tOC)., Results: tOC increased in AD and in people with MCI who converted to AD and also correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of progression from MCI to AD. Brain outlier maps identified the hippocampus as having the highest rate of change., Discussion: Individual patients' atrophy rates can be tracked by using regional outlier maps and tOC., Highlights: Neuroanatomical normative modeling was applied to serial Alzheimer's disease (AD) magnetic resonance imaging (MRI) data for the first time. Deviation from the norm (outliers) of cortical thickness or brain volume was computed in 3233 scans. The number of brain-structure outliers increased over time in people with AD. Patterns of change in outliers varied markedly between individual patients with AD. People with mild cognitive impairment whose outliers increased over time had a higher risk of progression from AD., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

As an important biomarker of neural aging, the brain age reflects the integrity and health of the human brain. Accurate prediction of brain age could help to understand the underlying mechanism of neural aging. In this study, a cross-stratified ensemble learning algorithm with staking strategy was proposed to obtain brain age and the derived predicted age difference (PAD) using T1-weighted magnetic resonance imaging (MRI) data. The approach was characterized as by implementing two modules: one was three base learners of 3D-DenseNet, 3D-ResNeXt, 3D-Inception-v4; another was 14 secondary learners of liner regressions. To evaluate performance, our method was compared with single base learners, regular ensemble learning algorithms, and state-of-the-art (SOTA) methods. The results demonstrated that our proposed model outperformed others models, with three metrics of mean absolute error (MAE), root mean-squared error (RMSE), and coefficient of determination (R 2 ) of 2.9405 years, 3.9458 years, and 0.9597, respectively. Furthermore, there existed significant differences in PAD among the three groups of normal control (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD), with an increased trend across NC, MCI, and AD. It was concluded that the proposed algorithm could be effectively used in computing brain aging and PAD, and offering potential for early diagnosis and assessment of normal brain aging and AD., Competing Interests: Declaration of competing interest The authors declare no conflicts of interests., (Copyright © 2024. Published by Elsevier Inc.)

Background: As cognitive impairment in multiple sclerosis (MS) is a frequent and disabling symptom, it is particularly important to identify treatments that have proven efficacy in this aspect of the disease. Several disease-modifying therapies for MS have been evaluated and shown to have a potential effect on cognition and its neurobiological correlates, but to date there is very little data on Teriflunomide (TRF). The aim of this study is to explore the influence of TRF on comprehensive cognitive function and its MRI correlations (global and focal brain volume) in relapsing-remitting multiple sclerosis (RRMS) after two years of therapy., Methods: Twenty-four patients with RRMS were evaluated at baseline and after two years of treatment with BCcogSEP, a French translation of the Brief Repeatable Battery (BRB-N) including 3 additional tests. We explored the performance evolution for each test and correlation with MRI data for all patients. We also differentiated MS patients with and without cognitive impairment., Results: After two years of treatment, an improvement is observed at the Selective Reminding Test for mean number of words (p = 0.044), learning (p = 0.018), and delayed recall (p = 0.002) and at GoNoGo task (p = 0.022). At MRI, the corpus callosum volume variation correlates positively with SRT total recall test (p = 0,047). Intergoup analysis shows that the evolution of group performance differs only for the SRT total recall test. The comparison of patients with or without cognitive impairment showed a clear difference in white matter substance volume (p = 0,003) and in the Percentage Brain Volume Change (p = 0,016)., Conclusion: Results suggest that TRF treatment in RRMS has a positive effect in cognitive function, and specifically on long term verbal memory and inhibition. Neuroimaging data suggest a link between cognition and global and focal white matter volume, particularly in the corpus callosum which is involved in anatomical disconnection syndrome and therefore brain plasticity capacities., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier B.V.)

The main objective was to evaluate structural and functional connectivity correlates of fatigue in post-COVID syndrome, and to investigate the relationships with an objective measure of mental fatigue and with subjective cognitive complaints. One-hundred and twenty-nine patients were recruited after 14.79 ± 7.17 months. Patients were evaluated with fatigue, neuropsychological, and subjective cognitive complaints assessments. Structural and functional magnetic resonance imaging were acquired, and functional connectivity, white matter diffusivity and grey matter volume were evaluated. Fatigue was present in 86 % of patients, and was highly correlated to subjective cognitive complaints. Fatigue was associated with structural and functional connectivity mostly in frontal areas but also temporal, and cerebellar areas, showing mental fatigue different pattern of functional connectivity correlates compared to physical fatigue. White matter diffusivity correlates were similar in fatigue and subjective cognitive complaints, located in the forceps minor, anterior corona radiata and anterior cingulum. Findings confirm that fatigue in post-COVID syndrome is related to cerebral connectivity patterns, evidencing its brain substrates. Moreover, results highlight the relationship between fatigue and subjective cognitive complaints. These findings point out the relevance of the multidisciplinary assessment of post-COVID syndrome patients with subjective cognitive complaints, in order to unravel the symptomatology beneath the patient's complaints., Competing Interests: Declaration of competing interest 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., (Copyright © 2024. Published by Elsevier B.V.)

Background: In multiple sclerosis (MS), imaging biomarkers play a crucial role in characterizing the disease at the time of diagnosis. MRI and optical coherence tomography (OCT) provide readily available biomarkers that may help to define the patient's clinical profile. However, the evaluation of cortical and paramagnetic rim lesions (CL, PRL), as well as retinal atrophy, is not routinely performed in clinic., Objective: To identify the most significant MRI and OCT biomarkers associated with early clinical disability in MS., Methods: Brain, spinal cord (SC) MRI, and OCT scans were acquired from 45 patients at MS diagnosis to obtain: brain PRL and non-PRL, CL, SC lesion volumes and counts, brain volumetric metrics, SC C2-C3 cross-sectional area, and retinal layer thickness. Regression models assessed relationships with physical disability (Expanded Disability Status Scale [EDSS]) and cognitive performance (Brief International Cognitive Assessment for Multiple Sclerosis [BICAMS])., Results: In a stepwise regression (R 2  = 0.526), PRL (β = 0.001, p = 0.023) and SC lesion volumes (β = 0.001, p = 0.017) were the most significant predictors of EDSS, while CL volume and age were strongly associated with BICAMS scores. Moreover, in a model where PRL and non-PRL were pooled, only the contribution of SC lesion volume was retained in EDSS prediction. OCT measures did not show associations with disability at the onset., Conclusion: At MS onset, PRL and SC lesions exhibit the strongest association with physical disability, while CL strongly contribute to cognitive performance. Incorporating the evaluation of PRL and CL into the initial MS patient assessment could help define their clinical profile, thus supporting the treatment choice., (© 2024. Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Mild cognitive impairment is a common feature of Parkinson's disease (PD-MCI), even at the earliest disease stages. Growing evidence supports the instability of PD-MCI over time, without a consistent linear evolution to dementia, and in some patients, the potential of reversion to normal cognition. However, which features are associated with reversion from PD-MCI to normal cognition in early PD-MCI are not fully known., Methods: In our longitudinal study of early drug naïve PD patients, 65 of 134 (48 %) patients had PD-MCI at baseline. Study participants underwent comprehensive assessments at baseline and 1-year follow-up. Sixteen (24.6 %) patients with PD-MCI reverted to normal cognition (Reverters), and 49 (75.4 %) had persistent PD-MCI (Non-Reverters) after 1-year follow-up. We performed single- and multiple-variable logistic regression analyses to identify baseline variables predicting reversion of PD-MCI to normal cognition after 1-year. We also compared brain morphometric measures (cortical thickness and volumes) at baseline between the PD-MCI Reverters and Non-Reverters., Results: Higher educational level and better performance on measures of attention and memory at baseline predicted the reversion to normal cognition at 1-year follow-up. Reverters had greater cortical thickness in the left inferior temporal gyrus than Non-Reverters., Conclusions: Our results show PD-MCI with a higher chance of reverting to normal cognition over time have a higher educational level, better frontotemporal-related cognitive function, and increased thickness of the inferior temporal lobe gyrus. These findings may potentially help researchers to select the candidates for clinical trials focusing on the treatment of cognitive impairment in the early stages of PD., Competing Interests: Declaration of competing interest 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., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Cortical cerebral microinfarcts (CMIs) are associated with loss of white matter (WM) integrity and cognitive impairment in cross-sectional studies, while further investigation using longitudinal datasets is required. This study aims to establish the association between cortical CMIs and WM integrity assessed by diffusion-tensor imaging (DTI) measures and to investigate whether DTI measures mediate the relationship between cortical CMIs and cognitive decline. Cortical CMIs were graded on 3T MRI. DTI measures were derived from histogram analysis of mean diffusivity (MD) and fractional anisotropy (FA). Cognitive function was assessed using a neuropsychological test battery. Linear mixed-effect models were employed to examine associations of cortical CMIs with longitudinal changes in DTI measures and cognitive function. Final analysis included 231 patients (71.14 ± 7.60 years). Presence of cortical CMIs at baseline was associated with longitudinal changes in MD median and peak height and FA median and peak height, as well as global cognition (β = -0.50, 95%CI: -0.91, -0.09) and executive function (β = -0.77, 95%CI: -1.25, -0.28). MD median mediated the cross-sectional association between cortical CMIs and global cognition. Further studies are required to investigate whether cortical CMIs and loss of WM integrity are causally related or if they are parallel mechanisms that contribute to cognitive decline., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Individuals diagnosed with schizophrenia (SZ) demonstrate difficulty distinguishing between internally and externally generated stimuli. These aberrations in "source monitoring" have been theorized as contributing to symptoms of the disorder, including hallucinations and delusions. Altered connectivity within the default mode network (DMN) of the brain has been proposed as a mechanism through which discrimination between self-generated and externally generated events is disrupted. Source monitoring abnormalities in SZ have additionally been linked to impairments in selective attention and inhibitory processing, which are reliably observed via the N100 component of the event-related brain potential elicited during an auditory paired-stimulus paradigm. Given overlapping constructs associated with DMN connectivity and N100 in SZ, the present investigation evaluated relationships between these measures of disorder-related dysfunction and sought to clarify the nature of task-based DMN function in SZ. DMN connectivity and N100 measures were assessed using EEG recorded from SZ during their first episode of illness (N = 52) and demographically matched healthy comparison participants (N = 25). SZ demonstrated less evoked theta-band connectivity within DMN following presentation of pairs of identical auditory stimuli than HC. Greater DMN connectivity among SZ was associated with better performance on measures of sustained attention (p = .03) and working memory (p = .09), as well as lower severity of negative symptoms, though it was not predictive of N100 measures. Together, present findings provide EEG evidence of lower task-based connectivity among first-episode SZ, reflecting disruptions of DMN functions that support cognitive processes. Attentional processes captured by N100 appear to be supported by different neural mechanisms., (© 2024 Society for Psychophysiological Research.)

Positron emission tomography (PET) and magnetic resonance spectroscopy ( 1 H-MRS) are complementary techniques that can be applied to study how proteinopathy and neurometabolism relate to cognitive deficits in preclinical stages of Alzheimer's disease (AD)-mild cognitive impairment (MCI) and late-life depression (LLD). We acquired beta-amyloid (Aβ) PET and 7 T 1 H-MRS measures of GABA, glutamate, glutathione, N-acetylaspartate, N-acetylaspartylglutamate, myo-inositol, choline, and lactate in the anterior and posterior cingulate cortices (ACC, PCC) in 13 MCI and 9 LLD patients, and 13 controls. We used linear regression to examine associations between metabolites, Aβ, and cognitive scores, and whether metabolites and Aβ explained cognitive scores better than Aβ alone. In the ACC, higher Aβ was associated with lower GABA in controls but not MCI or LLD patients, but results depended upon MRS data quality control criteria. Greater variance in California Verbal Learning Test scores was better explained by a model that combined ACC glutamate and Aβ deposition than by models that only included one of these variables. These findings identify preliminary associations between Aβ, neurometabolites, and cognition., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The present study aims to investigate the relationship between cerebellar volumes and cognitive reserve in individuals with Mild Cognitive Impairment (MCI). A description of proxies of cerebellar cognitive reserve in terms of different volumes across lobules is also provided. 36 individuals with MCI underwent neuropsychological (MoCA, MMSE, Clock test, CRIq) assessment and neuroimaging acquisition with magnetic resonance imaging at 3 T. Simple linear correlations were applied between cerebellar volumes and cognitive measures. Multiple linear regression models were then used to estimate standardized regression coefficients and 95% confidence intervals. Simple linear correlations between cerebellar lobules volumes and cognitive features highlighted a significant association between CRIq&#95;Working activity and specific motor cerebellar volumes: Left&#95;V (ρ = 0.40, p = 0.02), Right&#95;V (r = 0.42, p = 0.002), Vermis&#95;VIIIb (ρ = 0.47, p = 0.003), Left&#95;X (ρ = -0.46, p = 0.002) and Vermis&#95;X (r = 0.35, p = 0.03). Furthermore, CRIq&#95;Working activity scores correlated with certain cerebellar lobules implicated in cognition: Left&#95;Crus&#95;II, Vermis VIIb, Left&#95;IX. MMSE was associated only with the Right&#95;VIIB volume (r = 0.35, p = 0.02), while Clock Drawing Test scores correlated with both Left&#95;Crus&#95;I and Right&#95;Crus&#95;I (r = -0.42 and r = 0.42, p = 0.02, respectively). This study suggests that a higher cognitive reserve is associated with specific cerebellar lobule volumes and that Working activity may play a predominant role in this association. These findings contribute to the understanding of the relationship between cerebellar volumes and cognitive reserve, highlighting the potential modulatory role of Working activity on cerebellum response to cognitive decline., (© 2024. The Author(s).)

Importance: The lack of an in vivo measure for α-synuclein (α-syn) pathology until recently has limited thorough characterization of its brain atrophy pattern, especially during early disease stages., Objective: To assess the association of state-of-the-art cerebrospinal fluid (CSF) seed amplification assays (SAA) α-syn positivity (SAA α-syn+) with magnetic resonance imaging (MRI) structural measures, across the continuum from clinically unimpaired (CU) to cognitively impaired (CI) individuals, in 3 independent cohorts, and separately in CU and CI individuals, the latter reflecting a memory clinic population., Design, Setting, and Participants: Cross-sectional data were used from the Swedish BioFINDER-2 study (inclusion, 2017-2023) as the discovery cohort and the Swedish BioFINDER-1 study (inclusion, 2007-2015) and Alzheimer's Disease Neuroimaging Initiative (ADNI; inclusion 2005-2022) as replication cohorts. All cohorts are from multicenter studies, but the BioFINDER cohorts used 1 MRI scanner. CU and CI individuals fulfilling inclusion criteria and without missing data points in relevant metrics were included in the study. All analyses were performed from 2023 to 2024., Exposures: Presence of α-syn pathology, estimated by baseline CSF SAA α-syn., Main Outcomes and Measures: The primary outcomes were cross-sectional structural MRI measures either through voxel-based morphometry (VBM) or regions of interest (ROI) including an automated pipeline for cholinergic basal forebrain nuclei CH4/4p (nucleus basalis of Meynert [NBM]) and CH1/2/3. Secondary outcomes were domain-specific cross-sectional cognitive measures. Analyses were adjusted for CSF biomarkers of Alzheimer pathology., Results: A total of 2961 participants were included in this study: 1388 (mean [SD] age, 71 [10] years; 702 female [51%]) from the BioFINDER-2 study, 752 (mean [SD] age, 72 [6] years; 406 female [54%]) from the BioFINDER-1 study, and 821 (mean [SD] age, 75 [8] years; 449 male [55%]) from ADNI. In the BioFINDER-2 study, VBM analyses in the whole cohort revealed a specific association between SAA α-syn+ and the cholinergic NBM, even when adjusting for Alzheimer copathology. ROI-based analyses in the BioFINDER-2 study focused on regions involved in the cholinergic system and confirmed that SAA α-syn+ was indeed independently associated with smaller NBM (β = -0.271; 95% CI, -0.399 to -0.142; P <.001) and CH1/2/3 volumes (β = -0.227; 95% CI, -0.377 to -0.076; P =.02). SAA α-syn+ was also independently associated with smaller NBM volumes in the separate CU (β = -0.360; 95% CI, -0.603 to -0.117; P =.03) and CI (β = -0.251; 95% CI, -0.408 to -0.095; P =.02) groups. Overall, the association between SAA α-syn+ and NBM volume was replicated in the BioFINDER-1 study and ADNI cohort. In CI individuals, NBM volumes partially mediated the association of SAA α-syn+ with attention/executive impairments in all cohorts (BioFINDER-2, β = -0.017; proportion-mediated effect, 7%; P =.04; BioFINDER-1, β = -0.096; proportion-mediated effect, 19%; P =.04; ADNI, β = -0.061; proportion-mediated effect, 20%; P =.007)., Conclusions and Relevance: In this cohort study, SAA α-syn+ was consistently associated with NBM atrophy already during asymptomatic stages. Further, in memory clinic CI populations, SAA α-syn+ was associated with NBM atrophy, which partially mediated α-syn-induced attention/executive impairment.

Background: While patients affected by mild cognitive impairment (MCI) exhibit characteristic voxel-mirrored homotopic connectivity (VMHC) alterations, the ability of such VMHC abnormalities to predict the diagnosis of MCI in these patients remains uncertain. As such, this study was performed to evaluate the potential role of VMHC abnormalities in the diagnosis of MCI., Methods: MCI patients and healthy controls (HCs) were enrolled and subjected to resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological testing. VMHC and support vector machine (SVM) techniques were then used to examine the collected imaging data., Results: Totally, 53 MCI patients and 68 healthy controls were recruited. Compared to HCs, MCI patients presented with an increase in postcentral gyrus VMHC. SVM classification demonstrated the ability of postcentral gyrus VMHC values to classify HCs and MCI patients with accuracy, sensitivity, and specificity values of 63.64 %, 71.69 %, and 89.71 %, respectively., Conclusion: VMHC abnormalities in the postcentral gyrus may be mechanistically involved in the pathophysiological progression of MCI patients, and these abnormal VMHC patterns may also offer utility as a neuroimaging biomarker for MCI patient diagnosis., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose of the Review: In this review, we attempt to summarize the most updated studies that applied resting-state functional magnetic resonance imaging (rs-fMRI) in the field of Parkinsonisms and related dementia., Recent Findings: Over the past decades, increasing interest has emerged on investigating the presence and pathophysiology of cognitive symptoms in Parkinsonisms and their possible role as predictive biomarkers of neurodegenerative brain processes. In recent years, evidence has been provided, applying mainly three methodological approaches (i.e. seed-based, network-based and graph-analysis) on rs-fMRI data, with promising results. Neural correlates of cognitive impairment and dementia have been detected in patients with Parkinsonisms along the diseases course. Interestingly, early functional connectivity signatures were proposed to track and predict future progression of neurodegenerative processes. However, longitudinal studies are still sparce and further investigations are needed to overcome this knowledge gap., (© 2024. The Author(s).)

Study Objectives: We assessed possible brain abnormalities in adult patients with moderate and severe obstructive sleep apnea using the mean kurtosis (MK) from diffusion kurtosis imaging and analyzed the correlation between MK and cognitive function., Methods: A total of 30 patients with moderate or severe obstructive sleep apnea and 30 healthy controls evaluated by the Montreal Cognitive Assessment scale were enrolled. All participants underwent diffusion kurtosis imaging and 3-dimensional T1-weighted imaging on a 3.0T magnetic resonance scanner. The MK values of gray and white matter brain regions were compared. Partial correlation analysis was used to analyze the correlation between respiratory sleep parameters/cognitive score and MK values in different brain regions., Results: Compared with the healthy controls, the MK of 20 brain regions (13 after false discovery rate correction) and cognitive scores in the obstructive sleep apnea group were significantly lower. In the obstructive sleep apnea group, apnea-hypopnea index was negatively correlated with the MK in the white matter of the right occipital lobe; lowest oxygen saturation was positively correlated with the MK in the bilateral parietal, precentral, and right postcentral cortex; total score on the Montreal Cognitive Assessment scale was positively correlated with MK in the left hippocampus; language function was positively correlated with MK in the white matter of the left parietal lobe; and delayed recall was positively correlated with the MK in right insula cortex and bilateral cingulate. After false discovery rate correction, only the correlations of lowest oxygen saturation with right precentral gyrus cortex and bilateral parietal cortex were significant., Conclusions: MK values of diffusion kurtosis imaging may provide valuable information in assessing the neurological impacts of obstructive sleep apnea., Citation: Zhang N, Peng K, Guo J-X, Liu Q, Xiao A-L, Jing H. Microstructural brain abnormalities and associated neurocognitive dysfunction in obstructive sleep apnea: a pilot study with diffusion kurtosis imaging. J Clin Sleep Med. 2024;20(10):1571-1578., (© 2024 American Academy of Sleep Medicine.)

Objective: This study aims to explore the relationship between the burden of cerebral small vessel disease (CSVD) on imaging and cognitive impairment (CI) in patients with chronic obstructive pulmonary disease (COPD)., Methods: The study included 118 COPD patients admitted to Changxing People's Hospital between July 2020 and July 2023. All patients received a 1.5 T MRI of the brain and pulmonary function tests. A cognitive function assessment was conducted via the Montreal Cognitive Assessment (MoCA) scale, and patients were divided into two groups. The relationship between the MoCA and CSVD burden score was analyzed by Pearson correlation, and to identify risk factors, multiple logistic regression analysis was performed., Results: The study showed a negative correlation between the MoCA and CSVD burden score in COPD patients (r=-0.479, P<0.001). Multiple logistic regression analysis found that age (OR=2.264, 95 % CI: 1.426-3.596, P<0.001), COPD grade (OR=3.139, 95 % CI: 2.012-4.898, P<0.001), as well as CSVD burden score (OR=5.336, 95 % CI: 1.191-23.900, P<0.001) were the independent risk factors for CI in COPD patients (P<0.05)., Conclusion: When screening for cognitive impairment in COPD patients, the CSVD burden score can be used in conjunction with cognitive assessment scales to make judgments., Competing Interests: Declaration of Competing Interest 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., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: Parkinson's disease (PD) encompasses a range of non-motor symptoms attributed to deficits in various neurotransmitter systems. This study aimed to investigate the associations between cognitive and autonomic symptoms and the degeneration of brainstem monoaminergic nuclei, particularly the serotonergic and noradrenergic nuclei, in a prospective cohort of early PD patients., Methods: Twenty-eight early PD patients (with an average disease duration of approximately three years) underwent baseline [ 18 F]FP-CIT positron emission tomography (PET) scans, Montreal Cognitive Assessment (MoCA), and Composite Autonomic Symptom Scale-31 (COMPASS-31) evaluations, followed by repeat MoCA and COMPASS-31 assessments three years later. Regression models were utilized to analyze both cross-sectional and longitudinal changes in non-motor symptoms relative to baseline degeneration of the noradrenergic locus coeruleus (LC) and serotonergic raphe, normalized by striatal dopaminergic terminal loss., Results: Baseline LC and raphe degeneration in early PD was cross-sectionally associated with poorer MoCA performances. Over the three-year follow-up, gastrointestinal symptoms exhibited progression, while cognitive scores remained stable. Profound baseline degeneration of the LC and raphe, relative to nigrostriatal terminal loss, were predictive of subsequent accelerated deterioration in gastrointestinal symptoms., Conclusion: Brainstem non-dopaminergic dysfunction in early PD is linked to cognitive dysfunction and predicts progression in gastrointestinal symptoms, offering potential indicators for worsening non-motor trajectories., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jung Hwan Shin reports financial support provided by the Ministry of Science and ICT (MSIT), South Korea. Other authors declare 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.)

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care., (© 2024. The Author(s).)

The Alzheimer's Disease Neuroimaging Initiative (ADNI) Clinical Core is responsible for coordination of all clinical activities at the ADNI sites, including project management, regulatory oversight, and site management and monitoring, as well as the collection of all clinical data and management of all study data. The Clinical Core is also charged with determining the clinical classifications and criteria for enrollment in evolving AD trials and enabling the ongoing characterization of the cross-sectional features and longitudinal trajectories of the ADNI cohorts with application of these findings to optimal clinical trial designs. More than 2400 individuals have been enrolled in the cohorts since the inception of ADNI, facilitating refinement of our understanding of the AD trajectory and allowing academic and industry investigators to model therapeutic trials across the disease spectrum from the presymptomatic stage through dementia. HIGHLIGHTS: Since 2004, the Alzheimer's Disease Neuroimaging Initiative (ADNI) Clinical Core has overseen the enrollment of > 2400 participants with mild cognitive impairment, mild Alzheimer's disease (AD) dementia, and normal cognition. The longitudinal dataset has elucidated the full cognitive and clinical trajectory of AD from its presymptomatic stage through the onset of dementia. The ADNI data have supported the design of most major trials in the field., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Purpose: Brain aging is a complex and heterogeneous process characterized by both structural and functional decline. This study aimed to establish a novel deep learning (DL) method for predicting brain age by utilizing structural and metabolic imaging data., Methods: The dataset comprised participants from both the Universal Medical Imaging Diagnostic Center (UMIDC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The former recruited 395 normal control (NC) subjects, while the latter included 438 NC subjects, 51 mild cognitive impairment (MCI) subjects, and 56 Alzheimer's disease (AD) subjects. We developed a novel dual-pathway, 3D simple fully convolutional network (Dual-SFCNeXt) to estimate brain age using [ 18 F]fluorodeoxyglucose positron emission tomography ([ 18 F]FDG PET) and structural magnetic resonance imaging (sMRI) images of NC subjects as input. Several prevailing DL models were trained and tested using either MRI or PET data for comparison. Model accuracies were evaluated using mean absolute error (MAE) and Pearson's correlation coefficient (r). Brain age gap (BAG), deviations of brain age from chronologic age, was correlated with cognitive assessments in MCI and AD subjects., Results: Both PET- and MRI-based models achieved high prediction accuracy. The leading model was the SFCNeXt (the single-pathway version) for PET (MAE = 2.92, r = 0.96) and MRI (MAE = 3.23, r = 0.95) on all samples. By integrating both PET and MRI images, the Dual-SFCNeXt demonstrated significantly improved accuracy (MAE = 2.37, r = 0.97) compared to all single-modality models. Significantly higher BAG was observed in both the AD (P < 0.0001) and MCI (P < 0.0001) groups compared to the NC group. BAG correlated significantly with Mini-Mental State Examination (MMSE) scores (r=-0.390 for AD, r=-0.436 for MCI) and the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) scores (r = 0.333 for AD, r = 0.372 for MCI)., Conclusion: The integration of [ 18 F]FDG PET with structural MRI enhances the accuracy of brain age prediction, potentially introducing a new avenue for related multimodal brain age prediction studies., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: This study aimed to explore the associations between brain structures, cognition, and motor control in participants with mild cognitive impairment (MCI), with a focus on dual-task performance., Methods: Thirty MCI patients and thirty healthy controls were enrolled. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Structural magnetic resonance imaging data were analyzed using voxel-based morphometry (VBM) to calculate brain parenchyma volume and gray matter volume (GMV). Participants performed single- and dual-task Timed Up and Go (TUG) tests, and the correlations between significant GMV differences and task execution time was analyzed., Results: MCI patients showed significantly lower MoCA scores, particularly in visuospatial/executive, attention, and delayed recall domains (p < 0.05). Dual-task TUG execution time was significantly increased in MCI patients (p < 0.05). The GMV in the right anterior lobe of the cerebellum and both insulae was positively correlated with visuospatial/executive scores (FDR-corrected, p < 0.05). The GMV of the right cerebellar anterior lobe and insula were significantly reduced in MCI patients (p < 0.05). The GMV of the right cerebellar anterior lobe was negatively correlated with dual-task execution time (r = -0.32, p = 0.012)., Conclusion: Smaller GMV in the right anterior lobe of the cerebellum was associated with impaired dual-task performance, which may provide more evidence for the neural mechanisms of cognitive and motor function impairments in MCI., Competing Interests: Declaration of competing interest The authors report no conflict of interests related to this study., (Copyright © 2024. Published by Elsevier B.V.)

Background: The hypothalamus is a key brain structure involved in the pathogenesis of depression, and its abnormal activity is considered an important pathological mechanism for the formation of depression. The presence of abnormalities in the white matter integrity of hypothalamic subregions in mild cognitive impairment with depressive symptoms (D-MCI) remains unknown., Methods: In this study, we used diffusion tensor imaging (DTI) to explore the white matter integrity of hypothalamic subregions in D-MCI. On a 3 T magnetic resonance imaging scanner, we collected DTI data from 63 subjects. The subjects included 20 healthy controls (HC), 23 MCI patients without depression (nD-MCI), and 20 patients with D-MCI. The differences in DTI metrics of hypothalamic subregions of the three groups were compared using analysis of variance and post hoc t-tests. We looked at the relationship between clinical variables and DTI metrics in hypothalamus subregions using Pearson correlation analysis., Results: Compared with nD-MCI and HC groups, D-MCI group showed increased fractional anisotropy (FA) in anterior-inferior hypothalamus. There was a weak negative correlation between FA values in the anterior-inferior hypothalamus and depression scores in D-MCI patients., Conclusions: Our findings suggest that depressive symptoms in MCI patients are associated with abnormal white matter integrity in the anterior-inferior hypothalamus., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: Brain glucose hypometabolism, indexed by the fluorodeoxyglucose positron emission tomography ([ 18 F]FDG-PET) imaging, is a metabolic signature of Alzheimer's disease (AD). However, the underlying biological pathways involved in these metabolic changes remain elusive., Methods: Here, we integrated [ 18 F]FDG-PET images with blood and hippocampal transcriptomic data from cognitively unimpaired (CU, n = 445) and cognitively impaired (CI, n = 749) individuals using modular dimension reduction techniques and voxel-wise linear regression analysis., Results: Our results showed that multiple transcriptomic modules are associated with brain [ 18 F]FDG-PET metabolism, with the top hits being a protein serine/threonine kinase activity gene cluster (peak-t (223)  = 4.86, P value < 0.001) and zinc-finger-related regulatory units (peak-t (223)  = 3.90, P value < 0.001)., Discussion: By integrating transcriptomics with PET imaging data, we identified that serine/threonine kinase activity-associated genes and zinc-finger-related regulatory units are highly associated with brain metabolic changes in AD., Highlights: We conducted an integrated analysis of system-based transcriptomics and fluorodeoxyglucose positron emission tomography ([ 18 F]FDG-PET) at the voxel level in Alzheimer's disease (AD). The biological process of serine/threonine kinase activity was the most associated with [ 18 F]FDG-PET in the AD brain. Serine/threonine kinase activity alterations are associated with brain vulnerable regions in AD [ 18 F]FDG-PET. Zinc-finger transcription factor targets were associated with AD brain [ 18 F]FDG-PET metabolism., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Growing evidence indicates an important role of neurovascular unit (NVU) dysfunction in the pathophysiology of cerebral small vessel disease (cSVD). Individually measurable functions of the NVU have been correlated with cognitive function, but a combined analysis is lacking. We aimed to perform a unified analysis of NVU function and its relation with cognitive performance. The relationship between NVU function in the white matter and cognitive performance (both latent variables composed of multiple measurable variables) was investigated in 73 patients with cSVD (mean age 70 ± 10 years, 41% women) using canonical correlation analysis. MRI-based NVU function measures included (1) the intravoxel incoherent motion derived perfusion volume fraction (f) and microvascular diffusivity (D*), reflecting cerebral microvascular flow; (2) the IVIM derived intermediate volume fraction (f int ), indicative of the perivascular clearance system; and (3) the dynamic contrast-enhanced MRI derived blood-brain barrier (BBB) leakage rate (K i ) and leakage volume fraction (V L ), reflecting BBB integrity. Cognitive performance was composed of 13 cognitive test scores. Canonical correlation analysis revealed a strong correlation between the latent variables NVU function and cognitive performance (r 0.73; p = 0.02). For the NVU, the dominating variables were D*, f int , and K i . Cognitive performance was driven by multiple cognitive tests comprising different cognitive domains. The functionality of the NVU is correlated with cognitive performance in cSVD. Instead of focusing on individual pathophysiological mechanisms, future studies should target NVU dysfunction as a whole to acquire a coherent understanding of the complex disease mechanisms that occur in the NVU in cSVD.Trial registration: NTR3786 (Dutch Trial Register)., (© 2024. The Author(s).)