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© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/ by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com, Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions., This study was supported in the Netherlands by two Memorabel grants from Deltaplan Dementie (The Netherlands Organisation for Health Research and Development and Alzheimer Nederland; grant numbers 733050813,733050103 and 733050513), the Bluefield Project to Cure Frontotemporal Dementia, the Dioraphte foundation (grant number 1402 1300), the European Joint Programme—Neurodegenerative Disease Research and the Netherlands Organisation for Health Research and Development (PreFrontALS: 733051042, RiMod-FTD: 733051024); V.V. and S.K. have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 666992 (EuroPOND). E.B. was supported by the Hartstichting (PPP Allowance, 2018B011); in Belgium by the Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie; in the UK by the MRC UK GENFI grant (MR/M023664/1); J.D.R. is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH); I.J.S. is supported by the Alzheimer’s Association; J.B.R. is supported by the Wellcome Trust (103838); in Spain by the Fundació Marató de TV3 (20143810 to R.S.V.); in Germany by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198) and by grant 779357 ‘Solve-RD’ from the Horizon 2020 Research and Innovation Programme (to MS); in Sweden by grants from the Swedish FTD Initiative funded by the Schörling Foundation, grants from JPND PreFrontALS Swedish Research Council (VR) 529–2014-7504, Swedish Research Council (VR) 2015–02926, Swedish Research Council (VR) 2018–02754, Swedish Brain Foundation, Swedish Alzheimer Foundation, Stockholm County Council ALF, Swedish Demensfonden, Stohnes foundation, Gamla Tjänarinnor, Karolinska Institutet Doctoral Funding and StratNeuro. H.Z. is a Wallenberg Scholar.

The increasing availability of large high-dimensional data from experimental medicine, population-based and clinical cohorts, clinical trials, and electronic health records has the potential to transform dementia research. Our ability to make best use of this rich data will depend on utilisation of advanced machine learning and artificial intelligence (AI) techniques and collaboration across disciplinary and geographic boundaries.The Deep Dementia Phenotyping (DEMON) Network launched in 2019Membership on 4th February 2022 comprised 1,321 individuals from 61 countries across 6 continents (see Figure). Areas of expertise include dementia research (904; 68%), data science (692; 52%), clinical practice (244; 18%), industry (162; 12%), and regulation (26; 2%). Individual membership is free, and regular knowledge transfer events are provided including a monthly seminar series, talks and workshops, training, networking, and early career development. Each Working Group meets monthly, with multiple grants, reviews, and original research articles in progress. Eight state of the science position papers are in preparation, resulting from a Symposium held in April 2021. In January 2022, 110 early career researchers participated in the Network's flagship event 'NEUROHACK', a 4-day competitive global hackathon, with pilot grants awarded to those generating the most innovative solutions.The DEMON Network is a rapidly growing global platform for innovation that is supporting the global dementia research community to collaborate. Find out more at demondementia.com.

ImportanceSeveral ocular biomarkers have been proposed for the early detection of Alzheimer disease (AD) and mild cognitive impairment (MCI), particularly fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA).ObjectiveTo perform an umbrella review of systematic reviews to assess the diagnostic accuracy of ocular biomarkers for early diagnosis of Alzheimer disease.Data SourcesMEDLINE, Embase, and PsycINFO were searched from January 2000 to November 2021. The references of included reviews were also searched.Study SelectionSystematic reviews investigating the diagnostic accuracy of ocular biomarkers to detect AD and MCI, in secondary care or memory clinics, against established clinical criteria or clinical judgment.Data Extraction and SynthesisThe Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline checklist was followed and the Risk Of Bias in Systematic reviews tool was used to assess review quality.Main Outcomes and MeasuresThe prespecified outcome was the accuracy of ocular biomarkers for diagnosing AD and MCI. The area under the curve (AUC) was derived from standardized mean difference.ResultsFrom the 591 titles, 14 systematic reviews were included (median [range] number of studies in each review, 14 [5-126]). Only 4 reviews were at low risk of bias on all Risk of Bias in Systematic Reviews domains. The imaging-derived parameters with the most evidence for detecting AD compared with healthy controls were OCT peripapillary retinal nerve fiber layer thickness (38 studies including 1883 patients with AD and 2510 controls; AUC = 0.70; 95% CI, 0.53-0.79); OCTA foveal avascular zone (5 studies including 177 patients with AD and 371 controls; AUC = 0.73; 95% CI, 0.50-0.89); and saccadic eye movements prosaccade latency (30 studies including 651 patients with AD/MCI and 771 controls; AUC = 0.64; 95% CI, 0.58-0.69). Antisaccade error was investigated in fewer studies (12 studies including 424 patients with AD/MCI and 382 controls) and yielded the best accuracy (AUC = 0.79; 95% CI, 0.70-0.88).Conclusions and RelevanceThis umbrella review has highlighted limitations in design and reporting of the existing research on ocular biomarkers for diagnosing AD. Parameters with the best evidence showed poor to moderate diagnostic accuracy in cross-sectional studies. Future longitudinal studies should investigate whether changes in OCT and OCTA measurements over time can yield accurate predictions of AD onset.

Climate change threatens the future of humanity. It will also significantly impede our ability toconduct science, by destabilising societies globally. Aviation, including travel to scientificconferences, generates a huge carbon footprint. This must be addressed if we are to limit globalwarming to the 1.5C mandated by the UN Intergovernmental Panel on Climate Change (IPCC),and time is running very short: we are already at 1.2C of warming. This means we must urgentlytransform the way we attend conferences.In this report, authored by the Sustainability and Environment Action Special Interest Group (SEASIG),we analysed the carbon footprint of previous Organization for Human Brain Mapping(OHBM) meetings, and found that on average, attendees travelling to an in-person meetinggenerates over 10,000 tonnes of carbon. Virtually all these emissions are eliminated when wemeet online instead. The location of in-person meetings also matters: setting the meeting in aplace that requires more colleagues to take long-distance flights very significantly increases itsclimate costs, sometimes by up to three times as much as the lowest-carbon locations.We can do things differently, however. Hybrid meetings - accessible both in-person and online -are set to become the norm for academic societies around the world. Although driven by Covid,hybrid is here to stay, because of the many other benefits it brings to both accessibility andsustainability. There are also several other alternative meeting formats being explored byacademic societies, such as a biennial meeting (every other year), and multiple regional hubs, inwhich attendees travel to their nearest geographical meeting location.Using aviation carbon footprint modelling, we calculated the carbon savings that OHBM wouldmake under these future meeting formats. We also determined the most climate-friendly locationsfor in-person aspects of future meetings, and the least climate-friendly places to avoid. As a result,we recommend that all future OHBM meetings are fully hybrid. We furthermore recommend thatOHBM transitions to a multiple regional hub model (with hybrid attendance also supported), inlocations specifically chosen to minimise long-distance aviation. We do not advocate carbonoffsetting as a suitable alternative to tackling real-time reductions in aviation emissions.We conclude that updating the way OHBM meetings are run for a post-Covid, climate-crisis-erawill save thousands of tonnes of carbon at a time of climate emergency. Furthermore, setting themeeting in locations that minimise the need for long-distance flying is critical. Finally, supportingcolleagues to attend online and more locally will enhance accessibility, furthering the society’smission to provide educational forums for the exchange of ground-breaking neuroimagingresearch.

Healthy cognitive ageing is a societal and public health priority. Cerebrovascular risk factors increase the likelihood of dementia in older people but their impact on cognitive ageing in younger, healthy brains is less clear. The UK Biobank provides cognition and brain imaging measures in the largest population cohort studied to date. Here we show that cognitive abilities of healthy individuals (N = 22,059) in this sample are detrimentally affected by cerebrovascular risk factors. Structural equation modelling revealed that cerebrovascular risk is associated with reduced cerebral grey matter and white matter integrity within a fronto-parietal brain network underlying executive function. Notably, higher systolic blood pressure was associated with worse executive cognitive function in mid-life (44–69 years), but not in late-life (>70 years). During mid-life this association did not occur in the systolic range of 110–140 mmHg. These findings suggest cerebrovascular risk factors impact on brain structure and cognitive function in healthy people., Cerebrovascular risk factors reduce cognitive performance via changes in the integrity of a frontoparietal brain network in ageing. Modification of blood pressure, with antihypertensive treatment in mid-life, mitigates against cognitive decline over a specific blood pressure range.

Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Supplementary Information: Additional file 1 of A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study; Additional file 2 of A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study; both files are available online at https://doi.org/10.1186/s13024-021-00499-4 Copyright © The Author(s) 2021. Background: A detailed understanding of the pathological processes involved in genetic frontotemporal dementia is critical in order to provide the patients with an optimal future treatment. Protein levels in CSF have the potential to reflect different pathophysiological processes in the brain. We aimed to identify and evaluate panels of CSF proteins with potential to separate symptomatic individuals from individuals without clinical symptoms (unaffected), as well as presymptomatic individuals from mutation non-carriers. Methods: A multiplexed antibody-based suspension bead array was used to analyse levels of 111 proteins in CSF samples from 221 individuals from families with genetic frontotemporal dementia. The data was explored using LASSO and Random forest. Results: When comparing affected individuals with unaffected individuals, 14 proteins were identified as potentially important for the separation. Among these, four were identified as most important, namely neurofilament medium polypeptide (NEFM), neuronal pentraxin 2 (NPTX2), neurosecretory protein VGF (VGF) and aquaporin 4 (AQP4). The combined profile of these four proteins successfully separated the two groups, with higher levels of NEFM and AQP4 and lower levels of NPTX2 in affected compared to unaffected individuals. VGF contributed to the models, but the levels were not significantly lower in affected individuals. Next, when comparing presymptomatic GRN and C9orf72 mutation carriers in proximity to symptom onset with mutation non-carriers, six proteins were identified with a potential to contribute to a separation, including progranulin (GRN). Conclusion: In conclusion, we have identified several proteins with the combined potential to separate affected individuals from unaffected individuals, as well as proteins with potential to contribute to the separation between presymptomatic individuals and mutation non-carriers. Further studies are needed to continue the investigation of these proteins and their potential association to the pathophysiological mechanisms in genetic FTD. This study has received support from the Swedish FTD initiative funded by the Schörling Family Foundation. This work was also funded by KTH Center for Applied Precision Medicine (KCAP) funded by the Erling-Persson Family Foundation, grants from Vetenskapsrådet Dnr 529-2014-7504, VR 2015-02926 and 2018-02754, Swedish Alzheimer Foundation, Swedish Brain Foundation, Åhlén foundation, Demensfonden, Stohnes foundation, Gamla Tjänarinnor and Stockholm County Council ALF. Furthermore, support was received by the MRC UK GENFI grant (MR/M023664/1), the Bluefield Project, the JPND GENFI-PROX grant (2019-02248), the Dioraphte Foundation [grant numbers 09-02-00]; the Association for Frontotemporal Dementias Research Grant 2009; The Netherlands Organization for Scientific Research (NWO) (grant HCMI 056-13-018); ZonMw Memorabel (Deltaplan Dementie), (project numbers 733 050 103 and 733 050 813); JPND PreFrontAls consortium (project number 733051042). JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases - Project ID No 739510. M.S. was supported by the JPND grant “GENFI-prox” (by DLR/BMBF to M. S, joint with JDR., J.vS., M.O., B.B. and C.G.). Open Access funding provided by Royal Institute of Technology.

Motivated by a brain lesion application, we introduce penalized generalized estimating equations for relative risk regression for modelling correlated binary data. Brain lesions can have varying incidence across the brain and result in both rare and high incidence outcomes. As a result, odds ratios estimated from generalized estimating equations with logistic regression structures are not necessarily directly interpretable as relative risks. On the other hand, use of log-link regression structures with the binomial variance function may lead to estimation instabilities when event probabilities are close to 1. To circumvent such issues, we use generalized estimating equations with log-link regression structures with identity variance function and unknown dispersion parameter. Even in this setting, parameter estimates can be infinite, which we address by penalizing the generalized estimating functions with the gradient of the Jeffreys prior.Our findings from extensive simulation studies show significant improvement over the standard log-link generalized estimating equations by providing finite estimates and achieving convergence when boundary estimates occur. The real data application on UK Biobank brain lesion maps further reveals the instabilities of the standard log-link generalized estimating equations for a large-scale data set and demonstrates the clear interpretation of relative risk in clinical applications.

As the global health crisis unfolded throughout the world, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical and legal barriers and effectively enabled many individuals who have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g. caregiving responsibilities. Yet, the mere existence of online conferences is unfortunately no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the setup of the conference can provide more visibility to well-established researchers and reduce opportunities for early career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design.Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to: attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., A key symptom of frontotemporal dementia (FTD) is difficulty interacting socially with others. Social cognition problems in FTD include impaired emotion processing and theory of mind difficulties, and whilst these have been studied extensively in sporadic FTD, few studies have investigated them in familial FTD. Facial Emotion Recognition (FER) and Faux Pas (FP) recognition tests were used to study social cognition within the Genetic Frontotemporal Dementia Initiative (GENFI), a large familial FTD cohort of C9orf72, GRN, and MAPT mutation carriers. 627 participants undertook at least one of the tasks, and were separated into mutation-negative healthy controls, presymptomatic mutation carriers (split into early and late groups) and symptomatic mutation carriers. Groups were compared using a linear regression model with bootstrapping, adjusting for age, sex, education, and for the FP recognition test, language. Neural correlates of social cognition deficits were explored using a voxel-based morphometry (VBM) study. All three of the symptomatic genetic groups were impaired on both tasks with no significant difference between them. However, prior to onset, only the late presymptomatic C9orf72 mutation carriers on the FER test were impaired compared to the control group, with a subanalysis showing differences particularly in fear and sadness. The VBM analysis revealed that impaired social cognition was mainly associated with a left hemisphere predominant network of regions involving particularly the striatum, orbitofrontal cortex and insula, and to a lesser extent the inferomedial temporal lobe and other areas of the frontal lobe. In conclusion, theory of mind and emotion processing abilities are impaired in familial FTD, with early changes occurring prior to symptom onset in C9orf72 presymptomatic mutation carriers. Future work should investigate how performance changes over time, in order to gain a clearer insight into social cognitive impairment over the course of the disease.

BACKGROUND: The apolipoprotein E (APOE) gene ɛ4 allele is a risk factor for Alzheimer's disease and cardiovascular disease. However, its relationship with cognition and brain volume after stroke is not clear. OBJECTIVE: We compared cognition and medial temporal lobe volumes in APOEɛ4 carriers and non-carriers in the first year after ischemic stroke. METHODS: We sampled 20 APOEɛ4 carriers and 20 non-carriers from a larger cohort of 135 ischemic stroke participants in the longitudinal CANVAS study. Participants were matched on a range of demographic and stroke characteristics. We used linear mixed-effect models to compare cognitive domain z-scores (attention, processing speed, executive function, verbal and visual memory, language, visuospatial function) and regional medial temporal lobe volumes (hippocampal, entorhinal cortex) between groups at each time-point (3, 12-months post-stroke), and within groups across time-points. APOE gene single nucleotide polymorphisms (SNPs; rs7412, rs429358) were genotyped on venous blood. RESULTS: APOEɛ4 carriers and non-carriers did not differ on any demographic, clinical, or stroke variable. Carriers performed worse than non-carriers in verbal memory at 3 months post-stroke (p = 0.046), but were better in executive function at 12 months (p = 0.035). Carriers demonstrated a significant improvement in verbal memory (p = 0.012) and executive function (p = 0.015) between time-points. Non-carriers demonstrated a significant improvement in visual memory (p = 0.0005). Carriers had smaller bilateral entorhinal cortex volumes (p

IntroductionClinical apathy is a poorly understood neuropsychiatric syndrome characterised by a sig- nificant decrease in goal-directed, motivated behaviour. It occurs in ~30% of patients with cerebrovas- cular small vessel disease (SVD). With the aim of improving our mechanistic understanding of apathy, we conducted a multimodal investigation combining validated behavioural paradigms and magnetic resonance imaging (MRI) techniques.Methods83 patients with MRI evidence of SVD were recruited from the Oxford Vascular Study (OXVASC) and Oxford neurology clinics. They were investigated using a novel effort-based decision making task and the Apathy Evaluation Scale (AES). Structural and diffusion weighted MRI was conducted to measure white matter lesion load (WMLL) and tract integrity, indexed by Fractional anisotropy (FA).ResultsPatients with apathy demonstrated a significant reduction in motivated behaviour and were sig- nificantly less incentivised by low levels of reward. Diffusion weighted imaging demonstrated that apathy was characterised by focal changes to limbic association tracts, including the uncinate fasciculus and cingulum bundle, as well as fronto-striatal white matter tracts. Importantly, global measures of disease severity did not independently associate with apathy.DiscussionReduced incentivisation by low reward characterised apathy in SVD, as previously reported in Parkinson’s disease, suggesting a common mechanism underlying apathy across neurological diseases. The association of apathy with focal white matter tract changes is consistent with disruption to key frontal and fronto-striatal circuits which have been previously implicated in effort-based decision-making for rewards.youssuf.saleh@ndcn.ox.ac.uk

Executive dysfunction affects 40% of stroke patients, but is poorly predicted by characteristics of the stroke itself. Stroke typically occurs on a background of cerebrovascular burden, which impacts cognition and brain network structural integrity. We used structural equation modelling to investigate whether measures of white matter microstructural integrity (fractional anisotropy and mean diffusivity) and cerebrovascular risk factors better explain executive dysfunction than markers of stroke severity. 126 stroke patients (mean age 68.4 years) were scanned three months post-stroke and compared to 40 age- and sex-matched control participants on neuropsychological measures of executive function. Executive function was below what would be expected for age and education level in stroke patients as measured by the organizational components of the Rey Complex Figure Test, F(3,155) = 17, R2 = 0.25, p p 2 = 0.07, p p p p

Female sex, age and carriage of the apolipoprotein E e4 allele are the greatest risk factors for sporadic Alzheimer’s disease. The hippocampus has a selective vulnerability to atrophy in ageing that may be accelerated in Alzheimer’s disease, including in those with increased genetic risk of the disease, years before onset. Within the hippocampal complex, subfields represent cytoarchitectonic and connectivity based divisions. Variation in global hippocampal and subfield volume associated with sex, age and apolipoprotein E e4 status has the potential to provide a sensitive biomarker of future vulnerability to Alzheimer’s disease. Here, we examined non-linear age, sex and apolipoprotein E effects, and their interactions, on hippocampal and subfield volumes across several decades spanning mid-life to old age in 36 653 healthy ageing individuals. FMRIB Software Library derived estimates of total hippocampal volume and Freesurfer derived estimates hippocampal subfield volume were estimated. A model-free, sliding-window approach was implemented that does not assume a linear relationship between age and subfield volume. The annualized percentage of subfield volume change was calculated to investigate associations with age, sex and apolipoprotein E e4 homozygosity. Hippocampal volume showed a marked reduction in apolipoprotein E e4/e4 female carriers after age 65. Volume was lower in homozygous e4 individuals in specific subfields including the presubiculum, subiculum head, cornu ammonis 1 body, cornu ammonis 3 head and cornu ammonis 4. Nearby brain structures in medial temporal and subcortical regions did not show the same age, sex and apolipoprotein E interactions, suggesting selective vulnerability of the hippocampus and its subfields. The findings demonstrate that in healthy ageing, two factors—female sex and apolipoprotein E e4 status—confer selective vulnerability of specific hippocampal subfields to volume loss., Female sex, age and carriage of the APOE e4 allele are the greatest risk factors for sporadic Alzheimer's disease. Analysis of these three risk factors on hippocampal and subfield volumes in 36 653 healthy ageing individuals show two factors—female sex and APOE e4 status—confer selective vulnerability of specific hippocampal subfields to volume loss., Graphical Abstract Graphical Abstract

Patients with small vessel cerebrovascular disease frequently suffer from apathy, a debilitating neuropsychiatric syndrome, the underlying mechanisms of which remain to be established. Here we investigated the hypothesis that apathy is associated with disrupted decision making in effort-based decision making, and that these alterations are associated with abnormalities in the white matter network connecting brain regions that underpin such decisions. Eighty-two patients with MRI evidence of small vessel disease were assessed using a behavioural paradigm as well as diffusion weighted MRI. The decision-making task involved accepting or rejecting monetary rewards in return for performing different levels of physical effort (hand grip force). Choice data and reaction times were integrated into a drift diffusion model that framed decisions to accept or reject offers as stochastic processes approaching a decision boundary with a particular drift rate. Tract-based spatial statistics were used to assess the relationship between white matter tract integrity and apathy, while accounting for depression. Overall, patients with apathy accepted significantly fewer offers on this decision-making task. Notably, while apathetic patients were less responsive to low rewards, they were also significantly averse to investing in high effort. Significant reductions in white matter integrity were observed to be specifically related to apathy, but not to depression. These included pathways connecting brain regions previously implicated in effort-based decision making in healthy people. The drift rate to decision parameter was significantly associated with both apathy and altered white matter tracts, suggesting that both brain and behavioural changes in apathy are associated with this single parameter. On the other hand, depression was associated with an increase in the decision boundary, consistent with an increase in the amount of evidence required prior to making a decision. These findings demonstrate altered effort-based decision making for reward in apathy, and also highlight dissociable mechanisms underlying apathy and depression in small vessel disease. They provide clear potential brain and behavioural targets for future therapeutic interventions, as well as modelling parameters that can be used to measure the effects of treatment at the behavioural level., Apathy is common in patients with cerebrovascular small vessel disease. Saleh et al. show that apathy is associated with altered effort-based decision making for reward, and that these changes correlate with abnormalities in the white matter network connecting the medial frontal regions and basal ganglia

Highlights • We map the association of cerebrovascular risk with white matter hyperintensities. • Waist-to-hip ratio (WHR) and APOE ε4 status showed distinct spatial distributions. • WHR mediated the relationship white matter hyperintensities and speed of processing. • Managing visceral adiposity may be essential for mitigation of cognitive decline., Objectives White matter hyperintensities (WMHs) are considered macroscale markers of cerebrovascular burden and are associated with increased risk of vascular cognitive impairment and dementia. However, the spatial location of WMHs has typically been considered in broad categories of periventricular versus deep white matter. The spatial distribution of WHMs associated with individual cerebrovascular risk factors (CVR), controlling for frequently comorbid risk factors, has not been systematically investigated at the population level in a healthy ageing cohort. Furthermore, there is an inconsistent relationship between total white matter hyperintensity load and cognition, which may be due to the confounding of several simultaneous risk factors in models based on smaller cohorts. Methods We examined trends in individual CVR factors on total WMH burden in 13,680 individuals (aged 45–80) using data from the UK Biobank. We estimated the spatial distribution of white matter hyperintensities associated with each risk factor and their contribution to explaining total WMH load using voxel-wise probit regression and univariate linear regression. Finally, we explored the impact of CVR-related WMHs on speed of processing using regression and mediation analysis. Results Contrary to the assumed dominance of hypertension as the biggest predictor of WMH burden, we show associations with a number of risk factors including diabetes, heavy smoking, APOE ε4/ε4 status and high waist-to-hip ratio of similar, or greater magnitude to hypertension. The spatial distribution of WMHs varied considerably with individual cerebrovascular risk factors. There were independent effects of visceral adiposity, as measured by waist-to-hip ratio, and carriage of the APOE ε4 allele in terms of the unique spatial distribution of CVR-related WMHs. Importantly, the relationship between total WMH load and speed of processing was mediated by waist-to-hip ratio suggesting cognitive consequences to WMHs associated with excessive visceral fat deposition. Conclusion Waist-to-hip ratio, diabetes, heavy smoking, hypercholesterolemia and homozygous APOE ε4 status are important risk factors, beyond hypertension, associated with WMH total burden and warrant careful control across ageing. The spatial distribution associated with different risk factors may provide important clues as to the pathogenesis and cognitive consequences of WMHs. High waist-to-hip ratio is a key risk factor associated with slowing in speed of processing. With global obesity levels rising, focused management of visceral adiposity may present a useful strategy for the mitigation of cognitive decline in ageing.

Female sex, age and carriage of the APOE e4 allele are the greatest risk factors for sporadic Alzheimer's disease (AD). The hippocampus has a selective vulnerability to atrophy in ageing that may be accelerated in AD, including in those with increased genetic risk of AD. Within the hippocampal complex, subfields represent cytoarchitectonic and connectivity based divisions. The change in global hippocampal and subfield volume associated with sex, age and APOE e4 status in healthy ageing have not yet been established despite their potential to provide a sensitive biomarker of future vulnerability to AD. Here, we examined non-linear age, sex and APOE effects, and their interactions, on hippocampal and subfield volumes across several decades spanning mid-life to old age in 36 653 healthy ageing individuals. Hippocampal volume showed a marked reduction in APOE e4/e4 female carriers after age 65. Volume was lower in homozygous e4 individuals in specific subfields including the presubiculum, subiculum head, CA1 body, CA3 head and CA4. The findings demonstrate that in healthy ageing, two factors - female sex and APOE e4 status - confer selective vulnerability of specific hippocampal subfields to volume loss.

Over one-third of stroke patients has long-term cognitive impairment. The likelihood of cognitive dysfunction is poorly predicted by the location or size of the infarct. The macro-scale damage caused by ischaemic stroke is relatively localized, but the effects of stroke occur across the brain. Structural covariance networks represent voxelwise correlations in cortical morphometry. Atrophy and topographical changes within such distributed brain structural networks may contribute to cognitive decline after ischaemic stroke, but this has not been thoroughly investigated. We examined longitudinal changes in structural covariance networks in stroke patients and their relationship to domain-specific cognitive decline. Seventy-three patients (mean age, 67.41 years; SD = 12.13) were scanned with high-resolution magnetic resonance imaging at sub-acute (3 months) and chronic (1 year) timepoints after ischaemic stroke. Patients underwent a number of neuropsychological tests, assessing five cognitive domains including attention, executive function, language, memory and visuospatial function at each timepoint. Individual-level structural covariance network scores were derived from the sub-acute grey-matter probabilistic maps or changes in grey-matter probability maps from sub-acute to chronic using data-driven partial least squares method seeding at major nodes in six canonical high-order cognitive brain networks (i.e. dorsal attention, executive control, salience, default mode, language-related and memory networks). We then investigated co-varying patterns between structural covariance network scores within canonical distributed brain networks and domain-specific cognitive performance after ischaemic stroke, both cross-sectionally and longitudinally, using multivariate behavioural partial least squares correlation approach. We tested our models in an independent validation data set with matched imaging and behavioural testing and using split-half validation. We found that distributed degeneration in higher-order cognitive networks was associated with attention, executive function, language, memory and visuospatial function impairment in sub-acute stroke. From the sub-acute to the chronic timepoint, longitudinal structural co-varying patterns mirrored the baseline structural covariance networks, suggesting synchronized grey-matter volume decline occurred within established networks over time. The greatest changes, in terms of extent of distributed spatial co-varying patterns, were in the default mode and dorsal attention networks, whereas the rest were more focal. Importantly, faster degradation in these major cognitive structural covariance networks was associated with greater decline in attention, memory and language domains frequently impaired after stroke. Our findings suggest that sub-acute ischaemic stroke is associated with widespread degeneration of higher-order structural brain networks and degradation of these structural brain networks may contribute to longitudinal domain-specific cognitive dysfunction., Examining network-based degeneration, Veldsman and Cheng et al. show that higher-order structural covariance networks are associated with cognition in sub-acute stroke and that greater degeneration of these networks is associated with longitudinal cognitive decline after ischaemic stroke., Graphical Abstract Graphical Abstract

ObjectivesWhite matter hyperintensities (WMHs) are considered macroscale markers of cerebrovascular burden and are associated with increased risk of vascular cognitive impairment and dementia. However, the spatial location of WMHs has typically been considered in broad categories of periventricular versus deep white matter. The spatial distribution of WHMs associated with individual cerebrovascular risk factors (CVR), controlling for frequently comorbid risk factors, has not been systematically investigated at the population level in a healthy ageing cohort. Furthermore, there is an inconsistent relationship between total white matter hyperintensity load and cognition, which may be due to the confounding of several simultaneous risk factors in models based on smaller cohorts.MethodsWe examined trends in individual CVR factors on total WMH burden in 13,680 individuals (aged 45-80) using data from the UK Biobank. We estimated the spatial distribution of white matter hyperintensities associated with each risk factor and their contribution to explaining total WMH load using voxel-wise probit regression and univariate linear regression. Finally, we explored the impact of CVR-related WMHs on speed of processing using regression and mediation analysis.ResultsContrary to the assumed dominance of hypertension as the biggest predictor of WMH burden, we show associations with a number of risk factors including diabetes, heavy smoking, APOEε4/ε4 status and high waist-to-hip ratio of similar, or greater magnitude to hypertension. The spatial distribution of WMHs varied considerably with individual cerebrovascular risk factors. There were independent effects of visceral adiposity, as measured by waist-to-hip ratio, and carriage of the APOEε4 allele in terms of the unique spatial distribution of CVR-related WMHs. Importantly, the relationship between total WMH load and speed of processing was mediated by waist-to-hip ratio suggesting cognitive consequences to WMHs associated with excessive visceral fat deposition.ConclusionWaist-to-hip ratio, diabetes, heavy smoking, hypercholesterolemia and homozygous APOEε4 status are important risk factors, beyond hypertension, associated with WMH total burden and warrant careful control across ageing. The spatial distribution associated with different risk factors may provide important clues as to the pathogenesis and cognitive consequences of WMHs. High waist-to-hip ratio is a key risk factor associated with slowing in speed of processing. With global obesity levels rising, focused management of visceral adiposity may present a useful strategy for the mitigation of cognitive decline in ageing.

This is a working paper for a project launched and managed by the members of the OHBM Student and Postdoc Special Interest Group (SP-SIG, www.ohbmtrainees.com), in collaboration with two guest early career researchers, Dan Kessler from University of Michigan and Daniel Lurie from University of Berkeley. We would like to further develop the manuscript before submitting this work for peer review. Therefore, to provide advice that can be generalizable to a wide variety of situations, demographics, and countries, we are seeking contributions from the OHBM community. We would like to welcome everyone willing to participate to join us and discuss this subject on the associated Google group: https://groups.google.com/forum/#!forum/effective-self-management-for-ecrs The deadline for contributions is February 28th, 2019. All the questions with respect to this project can be directed to: ohbmtrainees@gmail.com

ObjectiveExecutive dysfunction affects 40% of stroke patients and is associated with poor quality of life. Stroke severity and lesion volume rarely predict whether a patient will have executive dysfunction. Stroke typically occurs on a background of cerebrovascular burden, which impacts cognition and brain network structural integrity. We investigated whether measures of white matter microstructural integrity and cerebrovascular risk factors better explain executive dysfunction than markers of stroke severity.MethodsWe used structural equation modelling to examine multivariate relationships between cerebrovascular risk, white matter microstructural integrity (fractional anisotropy and mean diffusivity), stroke characteristics and executive dysfunction in 126 stroke patients (mean age 68.4 years), three months post-stroke, and compared to 40 age- and sex-matched control participants. Executive function was measured using the Trail Making Tests, Clock Drawing task and Rey Complex Figure copy task. Microstructural integrity was estimated using a standard pipeline to process diffusion weighted images.ResultsExecutive function was below what would be expected for age and education level in stroke patients (t-test compared to controls t(79)=5.75, pInterpretationWhite matter microstructural degeneration of the superior longitudinal fasciculus in the executive control network better explains executive dysfunction than markers of stroke severity.

Disruptions to functional connectivity in subsystems of the default mode network are evident in Alzheimer's disease (AD). Functional connectivity estimates correlations in the time course of low-frequency activity. Much less is known about other potential perturbations to this activity, such as changes in the amplitude of oscillations and how this relates to cognition. We examined the amplitude of low-frequency fluctuations in 44 AD patients and 128 cognitively normal participants and related this to episodic memory, the core deficit in AD. We show higher amplitudes of low-frequency oscillations in AD patients. Rather than being compensatory, this appears to be maladaptive, with greater amplitude in the ventral default mode subnetwork associated with poorer episodic memory. Perturbations to default mode subnetworks in AD are evident in the amplitude of low-frequency oscillations in the resting brain. These disruptions are associated with episodic memory demonstrating their behavioral and clinical relevance in AD.

Modern clinical neuroscience was built on observations of how localized damage caused specific functional, cognitive and behavioral deficits. Stroke neurology was a cornerstone of understanding this functional specialization in the brain. But most lesion-symptom mapping provides little prognostic value above clinical observations. Stroke topography remains a poor indicator of long-term outcome, and with stroke a major risk factor for dementia, there is strong incentive to find markers of predictive value. There is now growing recognition that the damage caused by stroke does not occur in isolation but is embedded within a complex, highly interconnected, organized and dynamic system: the connectome. Early theories of the widespread effect of focal lesions are resurfacing, buoyed by sophisticated new methods and large-scale data sets. As with all emerging methods and technologies, there may be healthy skepticism as to the appropriateness of the method to the population under investigation or doubt that connectivity-derived metrics will ever be clinically translatable. While we acknowledge that there remain significant technical challenges to overcome, we argue that the methods provide real potential to illuminate our understanding of the widespread effects and clinical syndromes that can arise from diverse focal damage.

Introduction Poor sleep1 as well as white matter hyperintensities (WMH), which are macroscale markers of cerebrovascular health indicating white matter lesion,2 have been shown to increase the risk of dementia. However, the relationship between these two putative risk factors of dementia is unclear. Method Here we use data from the UK Biobank (N=5505, aged from 45 to 73) to elucidate the effect of poor sleep (insomnia, snoring, daytime sleepiness and short sleep duration) on WMH load. The sleep variables were obtained using a digital questionnaire, whereas the WMH load was derived from automated segmentation of T2 FLAIR magnetic resonance images using the BIANCA tool in FSL. Results We show that age, snoring and daytime sleepiness significantly predict a higher WMH load (linear model, adjusted R²=0.13, p Finally, a sleep burden score summing poor sleep markers significantly predicted the WMH load, when controlling for cardiovascular factors (table 1). Removing the sleep burden score leads to a significant decrease in the power of the model (ANOVA, p=0.027). Discussion This exploratory analysis confirms the impact of measures of poor sleep on cerebrovascular health, proposing a complex relationship between sleep and WMH loads involving cardiovascular features 3 4 in a large ageing population. Further work will examine the wider implications of measures of poor sleep on cognition and brain function. References Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 2010;341:c3666. Ju YS, Lucey BP, Holtzman DM. Sleepand Alzheimer disease pathology—a bidirectional relationship. Nature reviews Neurology 2014;10(2):115. Kocevska D, Cremers LG, Lysen TS, Luik AI, Ikram MA, Vernooij MW, et al. Sleep complaints and cerebral white matter: A prospective bidirectional study. J Psychiatr Res 2019;112:77–82. Lu S, Song L, Wang D, Zhang X, Lv X, Yin H, et al. White matter hyperintensity and cognitive impairments in chronic insomniacs. Neuroreport 2019;30(9):612–618.

Frontotemporal dementia (FTD) is a heterogeneous group of neurodegenerative disorders with both sporadic and genetic forms. Mutations in the progranulin gene (GRN) are a common cause of genetic FTD, causing either a behavioural presentation or, less commonly, language impairment. Presence on T2-weighted images of white matter hyperintensities (WMH) has been previously shown to be more commonly associated with GRN mutations rather than other forms of FTD. The aim of the current study was to investigate the longitudinal change in WMH and the associations of WMH burden with grey matter (GM) loss, markers of neurodegeneration and cognitive function in GRN mutation carriers. 336 participants in the Genetic FTD Initiative (GENFI) study were included in the analysis: 101 presymptomatic and 32 symptomatic GRN mutation carriers, as well as 203 mutation-negative controls. 39 presymptomatic and 12 symptomatic carriers, and 73 controls also had longitudinal data available. Participants underwent MR imaging acquisition including isotropic 1 mm T1-weighted and T2-weighted sequences. WMH were automatically segmented and locally subdivided to enable a more detailed representation of the pathology distribution. Log-transformed WMH volumes were investigated in terms of their global and regional associations with imaging measures (grey matter volumes), biomarker concentrations (plasma neurofilament light chain, NfL, and glial fibrillary acidic protein, GFAP), genetic status (TMEM106B risk genotype) and cognition (tests of executive function). Analyses revealed that WMH load was higher in both symptomatic and presymptomatic groups compared with controls and this load increased over time. In particular, lesions were seen periventricularly in frontal and occipital lobes, progressing to medial layers over time. However, there was variability in the WMH load across GRN mutation carriers - in the symptomatic group 25.0% had none/mild load, 37.5% had medium and 37.5% had a severe load - a difference not fully explained by disease duration. GM atrophy was strongly associated with WMH load both globally and in separate lobes, and increased WMH burden in the frontal, periventricular and medial regions was associated with worse executive function. Furthermore, plasma NfL and to a lesser extent GFAP concentrations were seen to be associated with increased lesion burden. Lastly, the presence of the homozygous TMEM106B rs1990622 TT risk genotypic status was associated with an increased accrual of WMH per year. In summary, WMH occur in GRN mutation carriers and accumulate over time, but are variable in their severity. They are associated with increased GM atrophy and executive dysfunction. Furthermore, their presence is associated with markers of WM damage (NfL) and astrocytosis (GFAP), whilst their accrual is modified by TMEM106B genetic status. WMH load may represent a target marker for trials of disease modifying therapies in individual patients but the variability across the GRN population would prevent use of such markers as a global outcome measure across all participants in a trial. ispartof: NEUROIMAGE-CLINICAL vol:24 ispartof: location:Netherlands status: published

This study evaluates residual fatigue and cognitive defects in patients after leucine-rich glioma-inactivated 1 antibody encephalitis.