Limbic Tract Integrity Contributes to Pattern Separation Performance Across the Lifespan.

Accurate memory for discrete events is thought to rely on pattern separation to orthogonalize the representations of similar events. Previously, we reported that a behavioral index of pattern separation was correlated with activity in the hippocampus (dentate gyrus, CA3) and with integrity of the perforant path, which provides input to the hippocampus. If the hippocampus operates as part of a broader neural network, however, pattern separation would likely also relate to integrity of limbic tracts (fornix, cingulum bundle, and uncinate fasciculus) that connect the hippocampus to distributed brain regions. In this study, healthy adults (20-89 years) underwent diffusion tensor imaging and completed the Behavioral Pattern Separation Task-Object Version (BPS-O) and Rey Auditory Verbal Learning Test (RAVLT). After controlling for global effects of brain aging, exploratory skeleton-wise and targeted tractography analyses revealed that fornix integrity (fractional anisotropy, mean diffusivity, and radial diffusivity; but not mode) was significantly related to pattern separation (measured using BPS-O and RAVLT tasks), but not to recognition memory. These data suggest that hippocampal disconnection, via individual- and age-related differences in limbic tract integrity, contributes to pattern separation performance. Extending our earlier work, these results also support the notion that pattern separation relies on broad neural networks interconnecting the hippocampus

Editorial: Embodied cognition over the lifespan. Theoretical issues and implications for applied settings

The editorial introduces The Special Topic on Embodied Cognition over the Lifespan and in Applied Settings. The Topic aimed at gathering evidence on the role of EC in development, adulthood, and aging, and to shed light on the applied fields benefiting from this approach

Investigating microstructural variation in the human hippocampus using non-negative matrix factorization

In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query hippocampus microstructure on a multivariate, voxelwise basis. Application of non-negative matrix factorization identifies spatial components (clusters of voxels sharing similar covariance patterns), as well as subject weightings (individual variance across hippocampus microstructure). By assessing the stability of spatial components as well as the accuracy of factorization, we identified 4 distinct microstructural components. Furthermore, we quantified the benefit of using multiple microstructural metrics by demonstrating that using three microstructural metrics (T1-weighted/T2-weighted signal, mean diffusivity and fractional anisotropy) produced more stable spatial components than when assessing metrics individually. Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. Through this approach we identified interpretable relationships between hippocampus microstructure and demographic and behavioural measures. Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component analyses

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Lifespan Changes of the Human Brain In Alzheimer's Disease

[EN] Brain imaging studies have shown that slow and progressive cerebral atrophy characterized the development of Alzheimer's Disease (AD). Despite a large number of studies dedicated to AD, key questions about the lifespan evolution of AD biomarkers remain open. When does the AD model diverge from the normal aging model? What is the lifespan trajectory of imaging biomarkers for AD? How do the trajectories of biomarkers in AD differ from normal aging? To answer these questions, we proposed an innovative way by inferring brain structure model across the entire lifespan using a massive number of MRI (N = 4329). We compared the normal model based on 2944 control subjects with the pathological model based on 3262 patients (AD + Mild cognitive Impaired subjects) older than 55 years and controls younger than 55 years. Our study provides evidences of early divergence of the AD models from the normal aging trajectory before 40 years for the hippocampus, followed by the lateral ventricles and the amygdala around 40 years. Moreover, our lifespan model reveals the evolution of these biomarkers and suggests close abnormality evolution for the hippocampus and the amygdala, whereas trajectory of ventricular enlargement appears to follow an inverted U-shape. Finally, our models indicate that medial temporal lobe atrophy and ventricular enlargement are two mid-life physiopathological events characterizing AD brain.This work benefited from the support of the project DeepVolBrain of the French National Research Agency (ANR-18-CE45-0013). This study was achieved within the context of the Laboratory of Excellence TRAIL ANR-10-LABX-57 for the BigDataBrain project. Moreover, we thank the Investments for the future Program IdEx Bordeaux (ANR-10-IDEX- 03-02, HL-MRI Project), Cluster of excellence CPU and the CNRS. This study has been also supported by the DPI2017-87743-R grant from the Spanish Ministerio de Economia, Industria y Competitividad. Moreover, this work is based on multiple samples. We wish to thank all investigators of these projects who collected these datasets and made them freely accessible. The C-MIND data used in the preparation of this article were obtained from the C-MIND Data Repository (accessed in Feb 2015) created by the C-MIND study of Normal Brain Development. This is a multisite, longitudinal study of typically developing children from ages newborn through young adulthood conducted by Cincinnati Children's Hospital Medical Center and UCLA and supported by the National Institute of Child Health and Human Development (Contract #s HHSN275200900018C). A listing of the participating sites and a complete listing of the study investigators can be found at https://research.cchmc.org/c-mind. The NDAR data used in the preparation of this manuscript were obtained from the NIH-supported National Database for Autism Research (NDAR). NDAR is a collaborative informatics system created by the National Institutes of Health to provide a national resource to support and accelerate research in autism. The NDAR dataset includes data from the NIH Pediatric MRI Data Repository created by the NIH MRI Study of Normal Brain Development. This is a multisite, longitudinal study of typically developing children from ages newborn through young adulthood conducted by the Brain Development Cooperative Group and supported by the National Institute of Child Health and Human Development, the National Institute on Drug Abuse, the National Institute of Mental Health, and the National Institute of Neurological Disorders and Stroke (Contract #s N01- HD02-3343, N01-MH9-0002, and N01-NS-9-2314, -2315, -2316, -2317, -2319 and -2320). A listing of the participating sites and a complete listing of the study investigators can be found at http://pediatricmri.nih.gov/nihpd/info/participating_centers.html. The ADNI data used in the preparation of this manuscript were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904). The ADNI is funded by the National Institute on Aging and the National Institute of Biomedical Imaging and Bioengineering and through generous contributions from the following: Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics NV, Johnson & Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc., F. 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A Hierarchical Approach to Assessing the Effects of Exercise on Cognition

Using a hierarchical approach across three studies, the aim of my thesis was to assess the relationship between exercise and cognition. In experiment one, based on a large, diverse sample, I found that regular exercise was positively associated with reasoning and verbal performance. In experiment two, I examined whether measures of strength and cardiovascular health were related to cognition. I found that the plank (a measure capturing aspects of both strength and aerobic capacity) was associated with performance on tasks relying on verbal and memory function in young adults. However, when aerobic or resistance exercise was introduced to a group of sedentary participants (experiment three), I found neither intervention had an effect on cognitive performance. Taken together, these results suggest that exercise benefits cognition when it is a regular part of an individual’s lifestyle, however, introducing exercise for a transient period, even to those who are sedentary, provides no benefit

The impact of diet-based glycaemic response and glucose regulation on cognition: evidence across the lifespan

The brain has a high metabolic rate and its metabolism is almost entirely restricted to oxidative utilisation of glucose. These factors emphasise the extreme dependence of neural tissue on a stable and adequate supply of glucose. Whereas initially it was thought that only glucose deprivation (i.e. under hypoglycaemic conditions) can affect brain function, it has become apparent that low-level fluctuations in central availability can affect neural and consequently, cognitive performance. In the present paper the impact of diet-based glycaemic response and glucose regulation on cognitive processes across the lifespan will be reviewed. The data suggest that although an acute rise in blood glucose levels has some short-term improvements of cognitive function, a more stable blood glucose profile, which avoids greater peaks and troughs in circulating glucose is associated with better cognitive function and a lower risk of cognitive impairments in the longer term. Therefore, a habitual diet that secures optimal glucose delivery to the brain in the fed and fasting states should be most advantageous for the maintenance of cognitive function. Although the evidence to date is promising, it is insufficient to allow firm and evidence-based nutritional recommendations. The rise in obesity, diabetes and metabolic syndrome in recent years highlights the need for targeted dietary and lifestyle strategies to promote healthy lifestyle and brain function across the lifespan and for future generations. Consequently, there is an urgent need for hypothesis-driven, randomised controlled trials that evaluate the role of different glycaemic manipulations on cognition

Neural correlates of prenatal stress in young women.

open5noBACKGROUND: Prenatal stress is hypothesized to have a disruptive impact on neurodevelopmental trajectories, but few human studies have been conducted on the long-term neural correlates of prenatal exposure to stress. The aim of this study was to explore the relationship between prenatal stress exposure and gray-matter volume and resting-state functional connectivity in a sample of 35 healthy women aged 14-40 years. METHOD: Voxel-based morphometry and functional connectivity analyses were performed on the whole brain and in specific regions of interest (hippocampus and amygdala). Data about prenatal/postnatal stress and obstetric complications were obtained by interviewing participants and their mothers, and reviewing obstetric records. RESULTS: Higher prenatal stress was associated with decreased gray-matter volume in the left medial temporal lobe (MTL) and both amygdalae, but not the hippocampus. Variance in gray-matter volume of these brain areas significantly correlated with depressive symptoms, after statistically adjusting for the effects of age, postnatal stress and obstetric complications. Prenatal stress showed a positive linear relationship with functional connectivity between the left MTL and the pregenual cortex. Moreover, connectivity between the left MTL and the left medial-orbitofrontal cortex partially explained variance in the depressive symptoms of offspring. CONCLUSIONS: In young women, exposure to prenatal stress showed a relationship with the morphometry and functional connectivity of brain areas involved in the pathophysiology of depressive disorders. These data provide evidence in favor of the hypothesis that early exposure to stress affects brain development and identified the MTL and amygdalae as possible targets of such exposure.openFavaro, Angela; Tenconi, Elena; Degortes, Daniela; Manara, R; Santonastaso, PaoloFavaro, Angela; Tenconi, Elena; Degortes, Daniela; Manara, R; Santonastaso, Paol

More than a feeling: A unified view of stress measurement for population science.

Stress can influence health throughout the lifespan, yet there is little agreement about what types and aspects of stress matter most for human health and disease. This is in part because "stress" is not a monolithic concept but rather, an emergent process that involves interactions between individual and environmental factors, historical and current events, allostatic states, and psychological and physiological reactivity. Many of these processes alone have been labeled as "stress." Stress science would be further advanced if researchers adopted a common conceptual model that incorporates epidemiological, affective, and psychophysiological perspectives, with more precise language for describing stress measures. We articulate an integrative working model, highlighting how stressor exposures across the life course influence habitual responding and stress reactivity, and how health behaviors interact with stress. We offer a Stress Typology articulating timescales for stress measurement - acute, event-based, daily, and chronic - and more precise language for dimensions of stress measurement