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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.

Science and art have been intertwined for centuries, as both embody means for humans to represent, communicate, and interpret our external and internal worlds. The collective effort to gather and organize knowledge about the brain blends well with a wide array of human creative activities, from visual and performing arts to interactive media. It thus comes as no surprise that the Organization for Human Brain Mapping (OHBM) has a Special Interest Group (SIG) dedicated to providing a platform for (neuro)sci-art: the BrainArt SIG.Here, after properly introducing all the main characters, we follow the development of this captivating script: from its grassroots prelude within the Neuro Bureau to its recent online instantiations. In particular, we highlight our three exhibitions since becoming an OHBM SIG – Ars Cerebri, 2019; Neurodiversity, 2020; Big Data and Me, 2021 – the associated competitions, and the scientific visualization sessions that have contributed to making brain art a distinguishing feature of the OHBM annual meetings, for both in-person and virtual formats.Our digital object, written as a piece of theater, ends by highlighting the ways art can help (neuro)science reach a wider audience as well as break out of its comfort zone: a productive happily ever after!

Alzheimer’s disease and related dementias is a major public health burden – compounding over upcoming years due to longevity. Recently, clinical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals’ social capital and various indicators of Alzheimer’s disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them promising targets for preventive clinical action.

Alzheimer’s disease and related dementias (ADRD) are marked by intracellular tau aggregates in the medial-temporal lobe (MTL) and extracellular amyloid aggregates in the default network (DN). Here, we sought to clarify ADRD-related co-dependencies between the MTL’s most vulnerable structure, the hippocampus (HC), and the highly associative DN at a subregion resolution. We confronted the effects of APOE ɛ2 and ɛ4, rarely investigated together, with their impact on HC-DN co-variation regimes at the population level. In a two-pronged decomposition of structural brain scans from ∼40,000 UK Biobank participants, we located co-deviating structural patterns in HC and DN subregions as a function of ADRD family risk. Across the disclosed HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix’s fimbria, and their cortical partners related to ADRD risk. Phenome-wide profiling of HC-DN co- variation expressions from these population signatures revealed male-specific associations with air-pollution, and female-specific associations with cardiovascular traits. We highlighted three main factors associated with brain-APOE associations across the different gene variants: happiness, and satisfaction with friendships, and with family. We further showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our findings reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex, which we have linked to fine-grained structural divergences indicative of ADRD susceptibility.

Science and art have been intertwined for centuries, both embodying means for humans to represent, communicate and interpret our external and internal worlds. The collective effort to gather and organize knowledge about the brain blends well with a wide array of human creative activities, from visual and performing arts to interactive media. It thus comes as no surprise that the Organization for Human Brain Mapping has a Special Interest Group (SIG) dedicated to providing a platform for (neuro)sci-art: the BrainArt SIG.Here, after properly introducing all the main characters, we follow the development of this captivating script: from its grassroots prelude within the Neuro Bureau to its recent online instantiations. In particular, we highlight our three latest Exhibitions (Ars Cerebri, 2019; Neurodiversity, 2020; BigData & me, 2021) and the associated Competitions, not forgetting the scientific visualization sessions that have contributed to the making of brainart a distinguishing feature of the OHBM annual meeting.

We present MRI data from a single human volunteer consisting in over 599 multi-contrast MR images (T1-weighted, T2-weighted, proton density, fluid-attenuated inversion recovery, T2* gradient-echo, diffusion, susceptibility-weighted, arterial-spin labelled, and resting state BOLD functional connectivity imaging) acquired in over 73 sessions on 36 different scanners (13 models, three manufacturers) over the course of 15+ years (cf. Data records). Data included planned data collection acquired within the Consortium pour l’identification précoce de la maladie Alzheimer - Québec (CIMA-Q) and Canadian Consortium on Neurodegeneration in Aging (CCNA) studies, as well as opportunistic data collection from various protocols. These multiple within- and between-centre scans over a substantial time course of a single, cognitively healthy volunteer can be useful to answer a number of methodological questions of interest to the community., Measurement(s)brainTechnology Type(s)magnetic resonance imagingSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9925037

Scientific research aims to bring forward innovative ideas and constantly challenges existing knowledge structures and stereotypes. However, women, ethnic and cultural minorities, as well as individuals with disabilities, are systematically discriminated against or even excluded from promotions, publications, and general visibility. A more diverse workforce is more productive, and thus discrimination has a negative impact on science and the wider society, as well as on the education, careers, and well-being of individuals who are discriminated against. Moreover, the lack of diversity at scientific gatherings can lead to micro-aggressions or harassment, making such meetings unpleasant, or even unsafe environments for early career and underrepresented scientists. At the Organization for Human Brain Mapping (OHBM), we recognized the need for promoting underrepresented scientists and creating diverse role models in the field of neuroimaging. To foster this, the OHBM has created a Diversity and Inclusivity Committee (DIC). In this article, we review the composition and activities of the DIC that have promoted diversity within OHBM, in order to inspire other organizations to implement similar initiatives. Activities of the committee over the past four years have included (a) creating a code of conduct, (b) providing diversity and inclusivity education for OHBM members, (c) organizing interviews and symposia on diversity issues, and (d) organizing family-friendly activities and providing childcare grants during the OHBM annual meetings. We strongly believe that these activities have brought positive change within the wider OHBM community, improving inclusivity and fostering diversity while promoting rigorous, ground-breaking science. These positive changes could not have been so rapidly implemented without the enthusiastic support from the leadership, including OHBM Council and Program Committee, and the OHBM Special Interest Groups (SIGs), namely the Open Science, Student and Postdoc, and Brain-Art SIGs. Nevertheless, there remains ample room for improvement, in all areas, and even more so in the area of targeted attempts to increase inclusivity for women, individuals with disabilities, members of the LGBTQ+ community, racial/ethnic minorities, and individuals of lower socioeconomic status or from low and middle-income countries. Here, we present an overview of the DIC's composition, its activities, future directions and challenges. Our goal is to share our experiences with a wider audience to provide information to other organizations and institutions wishing to implement similar comprehensive diversity initiatives. We propose that scientific organizations can push the boundaries of scientific progress only by moving beyond existing power structures and by integrating principles of equity and inclusivity in their core values.

Alzheimer’s disease (AD) is a complex disease that attacks the brain that mostly affects people 65 years and older. AD affects more and more people each year. A major problem with AD is that it is diagnosed too late. A big goal is to find ways to help doctors identify the disease early, so they can better help AD patients. Biomarkers are something that can tell you if a part of the body is feeling healthy or is being attacked by a disease. This article will describe one exciting new category of biomarkers that carry information from the brain into the blood. These biomarkers can be used to see how healthy the brain is feeling or if it is getting hurt by a disease like AD.

Many imaging and genetics studies have aimed to clarify whether the brain acts as an intermediate phenotype mediating the influence of genes in human behaviour. Brain activations in response to task demands are heterogeneous at the individual level, but also follow common patterns at the group level. Some studies have addressed this tension between heterogeneity and homogeneity by identifying groups of individuals that share the same brain activations patterns, called brain activation subtypes. In this work, we aimed to assess the viability of brain subtypes as endophenotypes intermediate between genes and behavior. We extracted brain activation subtypes separately for seven fMRI tasks, in 842 participants from the Human Connectome Project (HCP). We estimated the heritability of these subtypes and their genetic correlation with behavioral measures obtained inside and outside the scanner. Across all tasks, subtypes ranged from a predominantly ‘deactivating’ pattern towards a more ‘activating’ pattern of brain activity, with a heritability estimate ranging from 0 to 0.62. We observed high genetic and phenotypic correlation between behavioral measures and brain activation subtypes only for language and working memory tasks. Our results showed a significant genetic grounding of brain activation subtypes and they appear as a simple yet effective technique to tackle heterogeneity into imaging genetics studies.

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

Introduction Brain cells secrete extracellular microvesicles (EVs) that cross the blood‐brain barrier. Involved in cell‐to‐cell communication, EVs contain surface markers and a biologically active cargo of molecules specific to their tissue (and cell) of origin, reflecting the tissue or cell's physiological state. Isolation of brain‐secreted EVs (BEVs) from blood provides a minimally invasive way to sample components of brain tissue in Alzheimer's disease (AD), and is considered a form of “liquid biopsy.” Methods We performed a comprehensive review of the PubMed literature to assess the biomarker and therapeutic potential of blood‐isolated BEVs in AD. Results We summarize methods used for BEV isolation, validation, and novel biomarker discovery, as well as provide insights from 26 studies in humans on the biomarker potential in AD of four cell‐specific BEVs isolated from blood: neuron‐, neural precursor‐, astrocyte‐, and brain vasculature–derived BEVs. Of these, neuron‐derived BEVs has been investigated on several fronts, and these include levels of amyloid‐β and tau proteins, as well as synaptic proteins. In addition, we provide a synopsis of the current landscape of BEV‐based evaluation/monitoring of AD therapeutics based on two published trials and a review of registered clinical trials. Discussion Blood‐isolated BEVs have emerged as a novel player in the study of AD, with enormous potential as a diagnostic, evaluation of therapeutics, and treatment tool. The literature has largely concentrated on neuron‐derived BEVs in the blood in AD. Given the multifactorial pathophysiology of AD, additional studies, in neuron‐derived and other brain cell–specific BEVs are warranted to establish BEVs as a robust blood‐based biomarker of AD.

Available online 30 April 2021. Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress. The present manuscript is part of a growing community effort to collate Brainhack-related insights and expertise into a Jupyter Book (http://brainhack.org/brainhack_jupyter_book/) that will serve as a centralized set of resources for the community; we acknowledge all the individuals who contributed and will make ongoing contributions to these resources. A pre-print version of the present manuscript is available as part of the Jupyter Book. Moreover, we would like to acknowledge all Brainhack organizers, supporters, presenters, and participants for their contribution to growing and maintaining this community. The benefits described in this manuscript would not be possible without them. We also thank all institutions, labs, and organizations who have helped this community grow, meet in stimulating environments, and add an excellent educational resource pool and agenda. With an expanding community, Brainhack’s support network keeps growing, and we thank all labs and individual researchers for their dedication and expertise offered to this community (see http://brainhack.org/brainhack_jupyter_book/acknowledgments.html for a full list of individual acknowledgments; an updated list will be maintained in the Jupyter Book). Grants and funding bodies: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 867458 awarded to Julia M. Huntenburg; from ANR-19-DATA-0025 NeuroWebLab for Katja Heuer, Roberto Toro, and Nicholas Traut; and from NIH K00MH122372 for Stephanie Noble. The Brainhack Community member list and contributions of the different authors are detailed at http://brainhack.org/brainhack_jupyter_book/contributors.html. Our crediting system is described here: http://brainhack.org/brainhack_jupyter_book/neuroview_authorship-agreement.html.

Calibrated fMRI based on arterial spin-labeling (ASL) and blood oxygen-dependent contrast (BOLD), combined with periods of hypercapnia and hyperoxia, can provide information on cerebrovascular reactivity (CVR), resting blood flow (CBF), oxygen extraction fraction (OEF), and resting oxidative metabolism (CMRO2). Vascular and metabolic integrity are believed to be affected in Alzheimer's disease (AD), thus, the use of calibrated fMRI in AD may help understand the disease and monitor therapeutic responses in future clinical trials. In the present work, we applied a calibrated fMRI approach referred to as Quantitative O2 (QUO2) in a cohort of probable AD dementia and age-matched control participants. The resulting CBF, OEF and CMRO2 values fell within the range from previous studies using positron emission tomography (PET) with 15O labeling. Moreover, the typical parietotemporal pattern of hypoperfusion and hypometabolism in AD was observed, especially in the precuneus, a particularly vulnerable region. We detected no deficit in frontal CBF, nor in whole grey matter CVR, which supports the hypothesis that the effects observed were associated specifically with AD rather than generalized vascular disease. Some key pitfalls affecting both ASL and BOLD methods were encountered, such as prolonged arterial transit times (particularly in the occipital lobe), the presence of susceptibility artifacts obscuring medial temporal regions, and the challenges associated with the hypercapnic manipulation in AD patients and elderly participants. The present results are encouraging and demonstrate the promise of calibrated fMRI measurements as potential biomarkers in AD. Although CMRO2 can be imaged with 15O PET, the QUO2 method uses more widely available imaging infrastructure, avoids exposure to ionizing radiation, and integrates with other MRI-based measures of brain structure and function., Highlights • An advanced calibrated fMRI method is employed to explore brain physiology in AD. • A pattern of hypoperfusion and hypometabolism was observed as in PET studies. • The method provides several potential biomarkers of interest in AD. • The technique may help by providing new insights into the pathophysiology of AD.

Introduction: We performed a systematic review and meta-analysis of the Alzheimer’s disease (AD)literature to examine consistency of functional connectivity alterations in AD dementia and mildcognitive impairment, using resting-state functional magnetic resonance imaging.Methods: Studies were screened using a standardized procedure. Multiresolution statistics wereperformed to assess the spatial consistency of findings across studies.Results: Thirty-four studies were included (1363 participants, average 40 per study). Consistentalterations in connectivity were found in the default mode, salience, and limbic networks in patientswith AD dementia, mild cognitive impairment, or in both groups.We also identified a strong tendencyin the literature toward specific examination of the default mode network.Discussion: Convergent evidence across the literature supports the use of resting-state connectivityas a biomarker of AD. The locations of consistent alterations suggest that highly connected hubregions in the brain might be an early target of AD. 2017 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer’s Association. This is anopen access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Keywords: Resting-state fMRI; Functional connectivity; Alzheimer’s disease; Mild cognitive impairment; Meta-analysis1. IntroductionAlzheimer’s disease (AD) exists on a continuumcomprising a

We present group eight resolutions of brain parcellations for clusters generated from resting-state functional magnetic resonance images for 99 cognitively normal elderly persons and 129 patients with mild cognitive impairment, pooled from four independent datasets. This dataset was generated as part of the following study: Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies (Tam et al., 2015) [1]. The brain parcellations have been registered to both symmetric and asymmetric MNI brain templates and generated using a method called bootstrap analysis of stable clusters (BASC) (Bellec et al., 2010) [2]. We present two variants of these parcellations. One variant contains bihemisphereic parcels (4, 6, 12, 22, 33, 65, 111, and 208 total parcels across eight resolutions). The second variant contains spatially connected regions of interest (ROIs) that span only one hemisphere (10, 17, 30, 51, 77, 199, and 322 total ROIs across eight resolutions). We also present maps illustrating functional connectivity differences between patients and controls for four regions of interest (striatum, dorsal prefrontal cortex, middle temporal lobe, and medial frontal cortex). The brain parcels and associated statistical maps have been publicly released as 3D volumes, available in .mnc and .nii file formats on figshare and on Neurovault. Finally, the code used to generate this dataset is available on Github.

Introduction: Although age is a major risk factor for Alzheimer’s disease (AD), it is not an inevitable consequence of aging nor is it exclusively an old-age disease. Several other major risk factors for AD are strongly associated with metabolism and include lack of exercise, obesity, diabetes, high blood pressure and cholesterol, over-consumption of alcohol and depression in addition to low educational level, social isolation, and cognitive inactivity. Approaches for Alzheimer prevention and treatment through manipulation of metabolism and utilization of active metabolites have great potential either as a primary or secondary treatment avenue or as a preventative strategy in high-risk individuals. Areas covered: This review outlines the current knowledge concerning the relationship between AD and metabolism and the novel treatments attempting to correct changes in AD patients determined through metabolomics or lipidomic analyses. Expert opinion: Metabolites are one of the main driving factors and indicators of AD and can offer many possible avenues for prevention and treatment. However, with the highly interconnected effects of metabolites and metabolism, as well as the many different routes for metabolism dysfunction, successful treatment would have to include the correction of metabolic errors as well as errors in transport and metabolite processing in order to affect and revert AD progression.

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer’s disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput ‘omics’ are unbiased data-driven techniques that probe the complex aetiology of Alzheimer’s disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer’s disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer’s disease.

Automatic alignment of brain anatomy in a standard space is a key step when processing magnetic resonance imaging for group analyses. Such brain registration is prone to failure, and the results are therefore typically reviewed visually to ensure quality. There is however no standard, validated protocol available to perform this visual quality control (QC). We propose here a standardized QC protocol for brain registration, with minimal training overhead and no required knowledge of brain anatomy. We validated the reliability of three-level QC ratings (OK, Maybe, Fail) across different raters. Nine experts each rated N = 100 validation images, and reached moderate to good agreement (kappa from 0.4 to 0.68, average of 0.54 ± 0.08), with the highest agreement for "Fail" images (Dice from 0.67 to 0.93, average of 0.8 ± 0.06). We then recruited volunteers through the Zooniverse crowdsourcing platform, and extracted a consensus panel rating for both the Zooniverse raters (N = 41) and the expert raters. The agreement between expert and Zooniverse panels was high (kappa = 0.76). Overall, our protocol achieved a good reliability when performing a two level assessment (Fail vs. OK/Maybe) by an individual rater, or aggregating multiple three-level ratings (OK, Maybe, Fail) from a panel of experts (3 minimum) or non-experts (15 minimum). Our brain registration QC protocol will help standardize QC practices across laboratories, improve the consistency of reporting of QC in publications, and will open the way for QC assessment of large datasets which could be used to train automated QC systems.

Cerebrovascular insufficiency appears years prior to clinical symptoms in Alzheimer’s disease. The soluble, highly toxic amyloid-β species, generated from the amyloidogenic processing of amyloid precursor protein, are known instigators of the chronic cerebrovascular insufficiency observed in both Alzheimer’s disease patients and transgenic mouse models. We have previously demonstrated that pioglitazone potently reverses cerebrovascular impairments in a mouse model of Alzheimer’s disease overexpressing amyloid-β. In this study, we sought to characterize the effects of amyloid-β overproduction on the cerebrovascular proteome; determine how pioglitazone treatment affected the altered proteome; and analyze the relationship between normalized protein levels and recovery of cerebrovascular function. Three-month-old wildtype and amyloid precursor protein mice were treated with pioglitazone- (20 mg/kg/day, 14 weeks) or control-diet. Cerebral arteries were surgically isolated, and extracted proteins analyzed by gel-free and gel-based mass spectrometry. 193 cerebrovascular proteins were abnormally expressed in amyloid precursor protein mice. Pioglitazone treatment rescued a third of these proteins, mainly those associated with oxidative stress, promotion of cerebrovascular vasocontractile tone, and vascular compliance. Our results demonstrate that amyloid-β overproduction perturbs the cerebrovascular proteome. Recovery of cerebrovascular function with pioglitazone is associated with normalized levels of key proteins in brain vessel function, suggesting that pioglitazone-responsive cerebrovascular proteins could be early biomarkers of Alzheimer’s disease., yes

Mentorship facilitates personal growth through pairing trainees with mentors who can share their expertise. In times of global integration, geographical proximity between mentors and mentees is relevant to a lesser degree. This has led to popularization of online mentoring programs. In this editorial, we introduce the history and architecture of the International Online Mentoring Programme organized by the Student and Postdoc Special Interest Group of the Organization for Human Brain Mapping.

Studies using resting-state functional magnetic resonance imaging (rsfMRI) are increasingly collecting data at multiple sites in order to speed up recruitment or increase sample size. Multisite studies potentially introduce systematic biases in connectivity measures across sites, which may negatively impact the detection of clinical effects. Long-term multisite biases (i.e. over several years) are still poorly understood. The main objective of this study was to assess the long-term consistency of rsfMRI multisite connectivity measures derived from the harmonized Canadian Dementia Imaging Protocol (CDIP, www.cdip-pcid.ca). Nine to ten minutes of functional BOLD images were acquired from an adult cognitively healthy volunteer scanned repeatedly at 13 Canadian sites on three scanner makes (General Electric, Philips and Siemens) over the course of 2.5 years. RsfMRI connectivity maps were extracted for each session in seven canonical functional networks. The reliability (spatial Pearson’s correlation) of maps was about 0.6, with moderate effects (up to 0.2) of scanner makes and sites. The time elapsed between scans had a negligible effect on the consistency of connectivity maps. To assess the utility of such measures in machine learning models, we pooled the long-term longitudinal data with a single-site, short-term (1 month) data sample acquired on 26 subjects (10 scans per subject), called HNU1. Using randomly selected pairs of scans from each subject, we quantified the ability of a data-driven unsupervised cluster analysis to match the two scans. In this “fingerprinting” experiment, we found that scans from the Canadian subject could be matched with high accuracy (>85% for some networks), and fell in the range of accuracies observed for the HNU1 subjects. Overall, these results support the feasibility of multivariate, machine learning analysis of rsfMRI measures in a multisite study that extends for several years, even with fairly short (approximately ten minutes) time series.

HighlightsReliable functional brain network subtypes accompany cognitive impairment in ADSymptom-related subtypes exist in the default-mode, limbic and salience networksA limbic subtype is associated with a familial risk of AD in healthy older adultsLimbic subtypes also associate with beta amyloid deposition and ApoE4In BriefWe found reliable subtypes of functional brain connectivity networks in older adults, associated with AD-related clinical symptoms in patients as well as several AD risk factors/biomarkers in asymptomatic individuals.SummaryThe heterogeneity of brain degeneration has not been investigated yet for functional brain network connectivity, a promising biomarker of Alzheimer’s disease. We coupled cluster analysis with resting-state functional magnetic resonance imaging to discover connectivity subtypes in healthy older adults and patients with cognitive disorders related to Alzheimer’s disease, noting associations between subtypes and cognitive symptoms in the default-mode, limbic and salience networks. In an independent asymptomatic cohort with a family history of Alzheimer’s dementia, the connectivity subtypes had good test-retest reliability across all tested networks. We found that a limbic subtype was overrepresented in these individuals, which was previously associated with symptoms. Other limbic subtypes showed associations with cerebrospinal fluid Aβ1-42levels and ApoE4 genotype. Our results demonstrate the existence of reliable subtypes of functional brain networks in older adults and support future investigations in limbic connectivity subtypes as early biomarkers of Alzheimer’s degeneration.

INTRODUCTIONWe performed a systematic review and meta-analysis of the Alzheimer’s disease (AD) literature to examine consistency of functional connectivity alterations in AD dementia and mild cognitive impairment (MCI), using resting-state functional magnetic resonance imaging (rsfMRI).METHODSStudies were screened using a standardized procedure. Multiresolution statistics were performed to assess the spatial consistency of findings across studies.RESULTSThirty-four studies were included (1,363 participants, average 40 per study). Consistent alterations in connectivity were found in the default-mode, salience and limbic networks in patients with AD dementia, MCI, or in both groups. We also identified a bias in the literature towards specific examination of the default-mode network.DISCUSSIONConvergent evidence across the literature supports the use of resting-state connectivity as a biomarker of AD. The locations of consistent alterations suggest that metabolically expensive hub regions in the brain might be an early target of AD.

We present group brain parcellations for clusters generated from resting-state functional magnetic resonance images for 99 cognitively normal elderly persons and 129 patients with mild cognitive impairment, pooled from four independent datasets. The brain parcellations have been registered to both symmetric and asymmetric MNI brain templates and generated using a method called bootstrap analysis of stable clusters (BASC, Bellec et al., 2010). Eight resolutions of clusters were selected using a data-driven method called MSTEPS (Bellec, 2013). We present two variants of these parcellations. One variant contains bihemisphereic parcels (4, 6, 12, 22, 33, 65, 111, and 208 total parcels across eight resolutions). The second variant contains spatially connected regions of interest (ROIs) that span only one hemisphere (10, 17, 30, 51, 77, 199, and 322 total ROIs across eight resolutions). We also present maps illustrating functional connectivity differences between patients and controls for four regions of interest (superior medial frontal cortex, dorsomedial prefrontal cortex, striatum, middle temporal lobe). The brain parcels and associated statistical maps have been publicly released as 3D volumes, available in .mnc and .nii file formats on figshare (http://dx.doi.org/10.6084/m9.figshare.1480461) and on Neurovault (http://neurovault.org/collections/1003/). This dataset was generated as part of the following study: Tam A, Dansereau C, Badhwar A, Orban P, Belleville S, Chertkow H, Dagher A, Hanganu A, Monchi O, Rosa-Neto P, Shmuel A, Wang S, Breitner J, Bellec P for the Alzheimer's Disease Neuroimaging Initiative (2015) Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies. Front. Aging Neurosci. 7:242. doi: 10.3389/fnagi.2015.00242 Finally, the code used to generate this dataset is available on Github (https://github.com/SIMEXP/mcinet).

International audience; The past several decades have seen an explosive growth in the number of published neuroimaging studies. In concert, the demand for freely available and openly accessible ‘study data’, that would facilitate future reanalysis, meta-analysis, hypothesis testing and repurpos-ing has also soared. Here we report on developments made to Brainspell[1] one of several web-based initiatives (e.g. BrainMap[2], NeuroVault[3], Neurosynth[4]) that allow individuals to search through and organize massive numbers of neuroimaging studies and results in meaningful ways.Distinct from other databases, Brainspell [http://brainspell.org] is the first web-based initiative to allow users to manually annotate and curate machine-parsed data, as well as manually extend the database via its crowdsourcing user interface. The goal of our Brainhack project was to improve Brainspell’s interface. We worked to (a) provide supplementary manual data edit options (b) facilitate efficient manual database extension, and (c) aid meaningful organization of data.

Resting-state functional connectivity is a promising biomarker for Alzheimer’s disease. However, previous resting-state functional magnetic resonance imaging studies in Alzheimer’s disease and mild cognitive impairment (MCI) have shown limited reproducibility as they have had small sample sizes and substantial variation in study protocol. We sought to identify functional brain networks and connections that could consistently discriminate normal aging from MCI despite variations in scanner manufacturer, imaging protocol, and diagnostic procedure. We therefore pooled four independent datasets, including 112 healthy controls and 143 patients with MCI, systematically testing multiple brain connections for consistent differences. The largest effects associated with MCI involved the ventromedial and dorsomedial prefrontal cortex, striatum, and middle temporal lobe. Compared with controls, patients with MCI exhibited significantly decreased connectivity within the frontal lobe, between frontal and temporal areas, and between regions of the cortico-striatal-thalamic loop. Despite the heterogeneity of methods among the four datasets, we identified robust MCI-related connectivity changes with small to medium effect sizes and sample size estimates recommending a minimum of 150 to 400 total subjects to achieve adequate statistical power. If our findings can be replicated and associated with other established biomarkers of Alzheimer’s disease (e.g. amyloid and tau quantification), then these functional connections may be promising candidate biomarkers for Alzheimer’s disease.