Multivariate consistency of resting-state fMRI connectivity maps acquired on a single individual over 2.5 years, 13 sites and 3 vendors

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. The main objective of this study was to assess the long-term consistency of rsfMRI connectivity maps derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol (CDIP, www.cdip-pcid.ca). Nine to 10 min 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. The consistency (spatial Pearson’s correlation) of rsfMRI connectivity maps for seven canonical networks ranged from 0.3 to 0.8, with a negligible effect of time, but significant site and vendor effects. We noted systematic differences in data quality (i.e. head motion, number of useable time frames, temporal signal-to-noise ratio) across vendors, which may also confound some of these results, and could not be disentangled in this sample. We also 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 two scans of the same subjects. In this “fingerprinting” experiment, we found that scans from the Canadian subject (Csub) could be matched with high accuracy intra-site (>95% for some networks), but that the accuracy decreased substantially for scans drawn from different sites and vendors, even falling outside of the range of accuracies observed in HNU1. Overall, our results demonstrate good multivariate stability of rsfMRI measures over several years, but substantial impact of scanning site and vendors. How detrimental these effects are will depend on the application, yet our results demonstrate that new methods for harmonizing multisite analysis represent an important area for future work

Effective Self-Management for Early Career Researchers in the Natural and Life Sciences

Early career researchers (ECRs) are faced with a range of competing pressures in academia, making self-management key to building a successful career. The Organization for Human Brain Mapping undertook a group effort to gather helpful advice for ECRs in self-management. Keywords: ECRs; career development; early career researchers; mentoring; networking; self-managemen

Structural and functional multiplatform MRI series of a single human volunteer over more than fifteen years

We present MRI data from a single human volunteer consisting in over 599 multi-contrast MR images (T1-weighted, T2-weighted, proton density, fuid-attenuated inversion recovery, T2* gradient-echo, difusion, susceptibility-weighted, arterial-spin labelled, and resting state BOLD functional connectivity imaging) acquired in over 73 sessions on 36 diferent 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’identifcation 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

Artificial intelligence for dementia research methods optimization

Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being used in dementia research. However, several methodological challenges exist that may limit the insights we can obtain from high-dimensional data and our ability to translate these findings into improved patient outcomes. To improve reproducibility and replicability, researchers should make their well-documented code and modeling pipelines openly available. Data should also be shared where appropriate. To enhance the acceptability of models and AI-enabled systems to users, researchers should prioritize interpretable methods that provide insights into how decisions are generated. Models should be developed using multiple, diverse datasets to improve robustness, generalizability, and reduce potentially harmful bias. To improve clarity and reproducibility, researchers should adhere to reporting guidelines that are co-produced with multiple stakeholders. If these methodological challenges are overcome, AI and ML hold enormous promise for changing the landscape of dementia research and care. HIGHLIGHTS: Machine learning (ML) can improve diagnosis, prevention, and management of dementia. Inadequate reporting of ML procedures affects reproduction/replication of results. ML models built on unrepresentative datasets do not generalize to new datasets. Obligatory metrics for certain model structures and use cases have not been defined. Interpretability and trust in ML predictions are barriers to clinical translation

Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: a systematic review

Introduction: Artificial intelligence (AI) and neuroimaging offer new opportunities for diagnosis and prognosis of dementia. Methods: We systematically reviewed studies reporting AI for neuroimaging in diagnosis and/or prognosis of cognitive neurodegenerative diseases. Results: A total of 255 studies were identified. Most studies relied on the Alzheimer's Disease Neuroimaging Initiative dataset. Algorithmic classifiers were the most commonly used AI method (48%) and discriminative models performed best for differentiating Alzheimer's disease from controls. The accuracy of algorithms varied with the patient cohort, imaging modalities, and stratifiers used. Few studies performed validation in an independent cohort. Discussion: The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions. We make recommendations to improve model validation including addressing key clinical questions, providing sufficient description of AI methods and validating findings in independent datasets. Collaborative approaches between experts in AI and medicine will help achieve the promising potential of AI tools in practice. Highlights: There has been a rapid expansion in the use of machine learning for diagnosis and prognosis in neurodegenerative disease Most studies (71%) relied on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with no other individual dataset used more than five times There has been a recent rise in the use of more complex discriminative models (e.g., neural networks) that performed better than other classifiers for classification of AD vs healthy controls We make recommendations to address methodological considerations, addressing key clinical questions, and validation We also make recommendations for the field more broadly to standardize outcome measures, address gaps in the literature, and monitor sources of bias

Identification and characterization of rearrangements in the vervet monkey genome

Several mechanisms can lead to the reorganization of genomes during speciation, including centromere repositioning, new centromere emergence or other chromosomal rearrangements. Using a comparative karyotype approach, I determined that the vervet genome contains at least 12 evolutionary young centromere locations.To study the evolutionary dynamics of centromere formation, I identified and validated the alpha-satellite repeat as a centromere-specific marker in the vervet using comparative genomics, sequence analysis and hybridization screening. I developed criteria to infer the position of vervet bacterial artificial chromosome (BAC) inserts based on alpha-satellite monomer content. In a complementary approach, I demarcated the pericentromeric boundaries in human and identified vervet BAC clones that mapped orthologously to these regions.In addition to centromeric analyses, I developed methodologies to detect other genome rearrangements, in particular vervet deletion/human insertion and vervet translocation events. The tools and approaches developed in this thesis will prove useful in cataloguing additional vervet genome rearrangements

Impact of therapeutics on neuroanatomical plasticity and cerebrovascular proteome in Alzheimer's disease mouse

Disease progression in Alzheimer's disease (AD) involves a complex interplay between numerous pathological processes that progressively impair both the neuronal and vascular components of the brain and culminate in cognitive decline. To date, increased amyloid-beta (Aβ) peptide, a cleavage product of the APP protein, has been advocated as the common mediator of both the neuronal and vascular damage incurred in AD. Recently, the thiazolidinedione (TZD) pioglitazone was demonstrated to counter several pathological processes in the brains of aged Aβ-overproducing APP transgenic mice. In particular, pioglitazone normalized cerebrovascular dysfunction, inflammation and oxidative stress, and improved deficits in neurometabolic coupling and cholinergic denervation (Nicolakakis et al., 2008). Presented in this thesis are the findings that pioglitazone treatment commencing in young APP mice fully reverses cerebrovascular dysfunction and partially reverses cognitive impairment. However, pioglitazone fails to improve the attenuated cognitive task-induced neuroanatomical plasticity in the hippocampus that we report for the first time in AD mice using magnetic resonance imaging methods. The vascular pathology appears to occur early in the disease process relative to Aβ peptide deposition and cognitive deficits. Thus it is important to understand the molecular mechanisms of Aβ-induced vascular pathology in AD and its reversal by candidate therapies, such as pioglitazone. To this end, we developed a new technique for the extraction of vascular protein from the mouse brain, compatible with two complementary mass spectrometry methods, to characterize the cerebrovascular proteome of normal (wild-type) mice. This approach allowed the identification of 6,630 proteins, mainly distributed in the endothelial and muscular compartments of the vascular wall. We found 192 proteins with significantly altered levels (upregulated or downregulated) in cerebral vessels of Aβ-overproducing APP mice, including proteins related to vessel structure, vasomotricity and free radical production. Pioglitazone treatment exerted significant benefits in the APP mice, with over a third of the altered protein levels returned to wild-type levels. These results suggest that pioglitazone may be of benefit to AD patients with concurrent cerebrovascular deficits. In addition, some of the identified proteins could represent potential biomarkers for assessing the efficacy of therapies targeting cerebrovascular deficits in AD.L'évolution de la maladie d'Alzheimer (MA) repose sur des interactions complexes entre plusieurs éléments pathologiques qui affectent les fonctions neuronales et vasculaires du cerveau, ce qui mène progressivement à la détérioration des fonctions cognitives et, ultimement, à la perte de mémoire. L'augmentation du peptide amyloïde-β (Aβ), un produit du métabolisme de la protéine précurseur de l'amyloïde (APP), est considérée comme le médiateur commun des altérations vasculaires et neuronales dans la MA. Des études récentes ont montré que la pioglitazone, un agoniste des récepteurs PPARγ, exerçait des effets bénéfiques chez des souris transgéniques âgées qui produisent des quantités accrues d'Aβ (souris APP). Notamment, la pioglitazone normalisait les fonctions cérébrovasculaires, réduisait le stress oxydatif et l'inflammation, améliorait les déficits du métabolisme cérébral et la dénervation cholinergique observée près des plaques séniles d'Aβ (Nicolakakis et al., 2008). Dans cette thèse, nous montrons que la pioglitazone administrée à de jeunes souris APP rétablit complètement les fonctions cérébrovasculaires et améliore légèrement les performances cognitives. Par contre, la pioglitazone n'a aucun effet bénéfique sur la réduction de la plasticité neuroanatomique de l'hippocampe induite par une tâche cognitive, telle que montrée pour la première fois chez des souris APP, en utilisant des méthodes d'imagerie par résonance magnétique. Il a été suggéré que la pathologie cérébrovasculaire dans la MA précède l'accumulation d'Aβ dans le cerveau et la manifestation des déficits cognitifs. Il apparaît donc important de comprendre les mécanismes moléculaires qui sous-tendent la pathologie vasculaire induite par l'Aβ et d'identifier comment ils sont altérés par des traitements efficaces comme la pioglitazone. A cette fin, nous avons développé une nouvelle technique pour l'extraction des protéines des vaisseaux sanguins cérébraux de souris compatible avec deux méthodes complémentaires de spectrométrie de masse pour identifier le protéome cérébrovasculaire chez la souris normale (souris de type sauvage). Notre analyse a permis d'identifier 6,630 protéines distribuées principalement dans les compartiments endothélial et musculaire de la paroi vasculaire. Nous avons trouvé des altérations aussi bien à la hausse qu'à la baisse dans 192 de ces protéines dans les vaisseaux cérébraux des souris APP, incluant les protéines liées à la vasomotricité, de la production de radicaux libres et de la structure des vaisseaux. De plus, la pioglitazone exerçait des effets bénéfiques importants chez les souris APP puisque plus du tiers des protéines altérées retrouvaient des taux comparables à ceux des souris de type sauvage. Ces résultats montrent le potentiel thérapeutique de la pioglitazone chez les patients atteints de la MA accompagnée d'une pathologie cérébrovasculaire. De plus, certaines des protéines identifiées représentent des bio-marqueurs probants pour l'évaluation de l'efficacité de nouveaux composés sur les déficits cérébrovasculaires de la MA

Distributed collaboration: the case for the enhancement of Brainspell’s interface

International audienceThe 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

Impaired structural correlates of memory in Alzheimer's disease mice

AbstractThe healthy adult brain demonstrates robust learning-induced neuroanatomical plasticity. While altered neuroanatomical plasticity is suspected to be a factor mitigating the progressive cognitive decline in Alzheimer's disease (AD), it is not known to what extent this plasticity is affected by AD. We evaluated whether spatial learning and memory-induced neuroanatomical plasticity are diminished in an adult mouse model of AD (APP mice) featuring amyloid beta-driven cognitive and cerebrovascular dysfunction. We also evaluated the effect of early, long-term pioglitazone-treatment on functional hyperemia, spatial learning and memory, and associated neuroanatomical plasticity. Using high-resolution post-mortem MRI and deformation-based morphometry, we demonstrate spatial learning and memory-induced focal volume increase in the hippocampus of wild-type mice, an effect that was severely attenuated in APP mice, consistent with their unsuccessful performance in the spatial Morris water maze. These findings implicate impaired neuroanatomical plasticity as an important contributing factor to cognitive deficits in the APP mouse model of AD. Pioglitazone-treatment in APP mice completely rescued functional hyperemia and exerted beneficial effects on spatial learning and memory-recall, but it did not improve hippocampal plasticity