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Background: As the population ages, maintaining mental health and well-being of older adults is a public health priority. Beyond objective measures of health, self-perceived quality of life (QoL) is a good indicator of successful aging. In older adults, it has been shown that QoL is related to structural brain changes. However, QoL is a multi-faceted concept and little is known about the specific relationship of each QoL domain to brain structure, nor about the links with other aspects of brain integrity, including white matter microstructure, brain perfusion and amyloid deposition, which are particularly relevant in aging. Therefore, we aimed to better characterize the brain biomarkers associated with each QoL domain using a comprehensive multimodal neuroimaging approach in older adults., Methods: One hundred and thirty-five cognitively unimpaired older adults (mean age ± SD: 69.4 ± 3.8 y) underwent structural and diffusion magnetic resonance imaging, together with early and late florbetapir positron emission tomography scans. QoL was assessed using the brief version of the World Health Organization's QoL instrument, which allows measuring four distinct domains of QoL: self-perceived physical health, psychological health, social relationships and environment. Multiple regression analyses were carried out to identify the independent global neuroimaging predictor(s) of each QoL domain, and voxel-wise analyses were then conducted with the significant predictor(s) to highlight the brain regions involved. Age, sex, education and the other QoL domains were entered as covariates in these analyses. Finally, forward stepwise multiple regressions were conducted to determine the specific items of the relevant QoL domain(s) that contributed the most to these brain associations., Results: Only physical health QoL was associated with global neuroimaging values, specifically gray matter volume and white matter mean kurtosis, with higher physical health QoL being associated with greater brain integrity. These relationships were still significant after correction for objective physical health and physical activity measures. No association was found with global brain perfusion or global amyloid deposition. Voxel-wise analyses revealed that the relationships with physical health QoL concerned the anterior insula and ventrolateral prefrontal cortex, and the corpus callosum, corona radiata, inferior frontal white matter and cingulum. Self-perceived daily living activities and self-perceived pain and discomfort were the items that contributed the most to these associations with gray matter volume and white matter mean kurtosis, respectively., Conclusions: Better self-perceived physical health, encompassing daily living activities and pain and discomfort, was the only QoL domain related to brain structural integrity including higher global gray matter volume and global white matter microstructural integrity in cognitively unimpaired older adults. The relationships involved brain structures belonging to the salience network, the pain pathway and the empathy network. While previous studies showed a link between objective measures of physical health, our findings specifically highlight the relevance of monitoring and promoting self-perceived physical health in the older population. Longitudinal studies are needed to assess the direction and causality of the relationships between QoL and brain integrity., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Measures of resting-state functional connectivity allow the description of neuronal networks in humans and provide a window on brain function in normal and pathological conditions. Characterizing neuronal networks in animals is complementary to studies in humans to understand how evolution has modelled network architecture. The mouse lemur (Microcebus murinus) is one of the smallest and more phylogenetically distant primates as compared to humans. Characterizing the functional organization of its brain is critical for scientists studying this primate as well as to add a link for comparative animal studies. Here, we created the first functional atlas of mouse lemur brain and describe for the first time its cerebral networks. They were classified as two primary cortical networks (somato-motor and visual), two high-level cortical networks (fronto-parietal and fronto-temporal) and two limbic networks (sensory-limbic and evaluative-limbic). Comparison of mouse lemur and human networks revealed similarities between mouse lemur high-level cortical networks and human networks as the dorsal attentional (DAN), executive control (ECN), and default-mode networks (DMN). These networks were however not homologous, possibly reflecting differential organization of high-level networks. Finally, cerebral hubs were evaluated. They were grouped along an antero-posterior axis in lemurs while they were split into parietal and frontal clusters in humans., (Copyright © 2020. Published by Elsevier Inc.)

Objective: An increasing number of human in vivo magnetic resonance imaging (MRI) studies have focused on examining the structure and function of the subfields of the hippocampal formation (the dentate gyrus, CA fields 1-3, and the subiculum) and subregions of the parahippocampal gyrus (entorhinal, perirhinal, and parahippocampal cortices). The ability to interpret the results of such studies and to relate them to each other would be improved if a common standard existed for labeling hippocampal subfields and parahippocampal subregions. Currently, research groups label different subsets of structures and use different rules, landmarks, and cues to define their anatomical extents. This paper characterizes, both qualitatively and quantitatively, the variability in the existing manual segmentation protocols for labeling hippocampal and parahippocampal substructures in MRI, with the goal of guiding subsequent work on developing a harmonized substructure segmentation protocol., Method: MRI scans of a single healthy adult human subject were acquired both at 3 T and 7 T. Representatives from 21 research groups applied their respective manual segmentation protocols to the MRI modalities of their choice. The resulting set of 21 segmentations was analyzed in a common anatomical space to quantify similarity and identify areas of agreement., Results: The differences between the 21 protocols include the region within which segmentation is performed, the set of anatomical labels used, and the extents of specific anatomical labels. The greatest overall disagreement among the protocols is at the CA1/subiculum boundary, and disagreement across all structures is greatest in the anterior portion of the hippocampal formation relative to the body and tail., Conclusions: The combined examination of the 21 protocols in the same dataset suggests possible strategies towards developing a harmonized subfield segmentation protocol and facilitates comparison between published studies., (Copyright © 2015 Elsevier Inc. All rights reserved.)

The aim of this study was to explore whether musical practice-related gray matter increases in brain regions are accompanied by modifications in their resting-state functional connectivity. 16 young musically experienced adults and 17 matched nonmusicians underwent an anatomical magnetic resonance imaging (MRI) and a resting-state functional MRI (rsfMRI). A whole-brain two-sample t test run on the T1-weighted structural images revealed four clusters exhibiting significant increases in gray matter (GM) volume in the musician group, located within the right posterior and middle cingulate gyrus, left superior temporal gyrus and right inferior orbitofrontal gyrus. Each cluster was used as a seed region to generate and compare whole-brain resting-state functional connectivity maps. The two clusters within the cingulate gyrus exhibited greater connectivity for musicians with the right prefrontal cortex and left temporal pole, which play a role in autobiographical and semantic memory, respectively. The cluster in the left superior temporal gyrus displayed enhanced connectivity with several language-related areas (e.g., left premotor cortex, bilateral supramarginal gyri). Finally, the cluster in the right inferior frontal gyrus displayed more synchronous activity at rest with claustrum, areas thought to play a role in binding sensory and motor information. We interpreted these findings as the consequence of repeated collaborative use in general networks supporting some of the memory, perceptual-motor and emotional features of musical practice., (Copyright © 2014 Elsevier Inc. All rights reserved.)

More educated elders are less susceptible to age-related or pathological cognitive changes. We aimed at providing a comprehensive contribution to the neural mechanism underlying this effect thanks to a multimodal approach. Thirty-six healthy elders were selected based on neuropsychological assessments and cerebral amyloid imaging, i.e. as presenting normal cognition and a negative florbetapir-PET scan. All subjects underwent structural MRI, FDG-PET and resting-state functional MRI scans. We assessed the relationships between years of education and i) gray matter volume, ii) gray matter metabolism and iii) functional connectivity in the brain areas showing associations with both volume and metabolism. Higher years of education were related to greater volume in the superior temporal gyrus, insula and anterior cingulate cortex and to greater metabolism in the anterior cingulate cortex. The latter thus showed both volume and metabolism increases with education. Seed connectivity analyses based on this region showed that education was positively related to the functional connectivity between the anterior cingulate cortex and the hippocampus as well as the inferior frontal lobe, posterior cingulate cortex and angular gyrus. Increased connectivity was in turn related with improved cognitive performances. Reinforcement of the connectivity of the anterior cingulate cortex with distant cortical areas of the frontal, temporal and parietal lobes appears as one of the mechanisms underlying education-related reserve in healthy elders., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Studies of functional connectivity suggest that the default mode network (DMN) might be relevant for cognitive functions. Here, we examined metabolic and structural connectivity between major DMN nodes, the posterior cingulate (PCC) and medial prefrontal cortex (MPFC), in relation to normal working memory (WM). DMN was captured using independent component analysis of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) data from 35 young healthy adults (27.1 ± 5.1 years). Metabolic connectivity, a correlation between FDG uptake in PCC and MPFC, was examined in groups of subjects with (relative to median) low (n=18) and high (n=17) performance on digit span backward test as an index of verbal WM. In addition, fiber tractography based on PCC and MPFC nodes as way points was performed in a subset of subjects. FDG uptake in the DMN nodes did not differ between high and low performers. However, significantly (p=0.01) lower metabolic connectivity was found in the group of low performers. Furthermore, as compared to high performers, low performers showed lower density of the left superior cingulate bundle. Verbal WM performance is related to metabolic and structural connectivity within the DMN in young healthy adults. Metabolic connectivity as quantified with FDG-PET might be a sensitive marker of the normal variability in some cognitive functions., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Normal aging is characterized by brain glucose metabolism decline predominantly in the prefrontal cortex. The goal of the present study was to assess whether this change was associated with age-related alteration of white matter (WM) structural integrity and/or functional connectivity. FDG-PET data from 40 young and 57 elderly healthy participants from two research centers (n=49/48 in Center 1/2) were analyzed. WM volume from T1-weighted MRI (Center 1), fractional anisotropy from diffusion-tensor imaging (Center 2), and resting-state fMRI data (Center 1) were also obtained. Group comparisons were performed within each imaging modality. Then, positive correlations were assessed, within the elderly, between metabolism in the most affected region and the other neuroimaging modalities. Metabolism decline in the elderly predominated in the left inferior frontal junction (LIFJ). LIFJ hypometabolism was significantly associated with macrostructural and microstructural WM disturbances in long association fronto-temporo-occipital fibers, while no relationship was found with functional connectivity. The findings offer new perspectives to understand normal aging processes and open avenues for future studies to explore causality between age-related metabolism and connectivity changes., (Copyright © 2013 Elsevier Inc. All rights reserved.)

There is a great deal of heterogeneity in the impact of aging on cognition and cerebral functioning. One potential factor contributing to individual differences among the elderly is the cognitive reserve, which designates the partial protection from the deleterious effects of aging that lifetime experience provides. Neuroimaging studies examining task-related activation in elderly people suggested that cognitive reserve takes the form of more efficient use of brain networks and/or greater ability to recruit alternative networks to compensate for age-related cerebral changes. In this exploratory multi-center study, we examined the relationships between cognitive reserve, as measured by education and verbal intelligence, and cerebral metabolism at rest (FDG-PET) in a sample of 74 healthy older participants. Higher degree of education and verbal intelligence was associated with less metabolic activity in the right posterior temporoparietal cortex and the left anterior intraparietal sulcus. Functional connectivity analyses of resting-state fMRI images in a subset of 41 participants indicated that these regions belong to the default mode network and the dorsal attention network respectively. Lower metabolism in the temporoparietal cortex was also associated with better memory abilities. The findings provide evidence for an inverse relationship between cognitive reserve and resting-state activity in key regions of two functional networks respectively involved in internal mentation and goal-directed attention., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Identifying the specific substrates of memory deficits in early Alzheimer's disease would help to develop clinically-relevant therapies. The present study assesses the relationships between encoding versus retrieval deficits in patients with amnestic Mild Cognitive Impairment (aMCI) and atrophy specifically within the hippocampus and throughout the white matter. Twenty-two aMCI patients underwent T1-weighted MRI scans and neuropsychological testing. Grey matter and white matter segments obtained from the MRI images were each entered in correlation analyses, assessed only in the hippocampus for grey matter segments, with encoding and retrieval memory performances. For the grey matter segments, the resulting spmT correlation maps were then superimposed onto a 3D surface view of the hippocampus to identify the relative involvement of the different subfields, a method already used and validated elsewhere. Memory encoding deficits specifically correlated with CA1 subfield atrophy, while no relationship was found with white matter atrophy. In contrast, retrieval deficits were weakly related to hippocampal atrophy and did not involve a particular subfield, while they strongly correlated with loss of white matter, specifically in medial parietal and frontal areas. In aMCI patients, encoding impairment appears specifically related to atrophy of the CA1 hippocampal subfield, consistent with the predominance of encoding deficits and CA1 atrophy in aMCI. In contrast, episodic retrieval deficits seem to be underlain by more distributed tissue losses, consistent with a disruption of a hippocampo-parieto-frontal network., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippocampus. The hippocampal shape variations among a population can be usually described using statistical shape models (SSMs). Conventional SSMs model the modes of variations among the population via principal component analysis (PCA). Although these modes are representative of variations within the training data, they are not necessarily discriminative on labeled data or relevant to the differences between the subpopulations. We use the shape descriptors from SSM as features to classify AD from normal control (NC) cases. In this study, a Hotelling's T2 test is performed to select a subset of landmarks which are used in PCA. The resulting variation modes are used as predictors of AD from NC. The discrimination ability of these predictors is evaluated in terms of their classification performances with bagged support vector machines (SVMs). Restricting the model to landmarks with better separation between AD and NC increases the discrimination power of SSM. The predictors extracted on the subregions also showed stronger correlation with the memory-related measurements such as Logical Memory, Auditory Verbal Learning Test (AVLT) and the memory subscores of Alzheimer Disease Assessment Scale (ADAS)., (Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.)

Recent advances in neuroimaging have highlighted the interest to differentiate hippocampal subfields for cognitive neurosciences and more notably in assessing the effects of normal and pathological aging. The main goal of the present study is to investigate the effects of normal aging onto the volume of the different hippocampal subfields. For this purpose, we developed a new magnetic resonance sequence together with reliable tracing guidelines to assess the volume of different subfields of the hippocampus using a 3 Tesla scanner, and estimated the validity of a simpler and less time-consuming method based on the widely-used automatic Voxel-Based Morphometry (VBM) technique. Three hippocampal regions of interest were delineated on the right and left hippocampi of 50 healthy subjects between 18 and 68 years old corresponding to the CA1, subiculum and other (including CA2-3-4 and Dentate Gyrus) subfields. A strong effect of age was found on the volume of the subiculum only, with a decrease paralleling that of the global gray matter volume, while CA1 and other subfields seemed relatively spared. Although less precise than the ROI-tracing technique, the VBM-based method appeared as a reliable alternative especially to distinguish CA1 and subiculum subfields. Our findings of a specific effect of age on the subiculum are consistent with the developmental hypothesis ("last-in first-out" theory). This contrasts with the predominant vulnerability of the CA1 subfield to Alzheimer's disease reported in several previous studies, suggesting that the assessment of hippocampal subfields may improve the discrimination between normal and pathological aging., (Copyright 2010 Elsevier Inc. All rights reserved.)

We describe a new method to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls, based on multidimensional classification of hippocampal shape features. This approach uses spherical harmonics (SPHARM) coefficients to model the shape of the hippocampi, which are segmented from magnetic resonance images (MRI) using a fully automatic method that we previously developed. SPHARM coefficients are used as features in a classification procedure based on support vector machines (SVM). The most relevant features for classification are selected using a bagging strategy. We evaluate the accuracy of our method in a group of 23 patients with AD (10 males, 13 females, age+/-standard-deviation (SD)=73+/-6 years, mini-mental score (MMS)=24.4+/-2.8), 23 patients with amnestic MCI (10 males, 13 females, age+/-SD=74+/-8 years, MMS=27.3+/-1.4) and 25 elderly healthy controls (13 males, 12 females, age+/-SD=64+/-8 years), using leave-one-out cross-validation. For AD vs controls, we obtain a correct classification rate of 94%, a sensitivity of 96%, and a specificity of 92%. For MCI vs controls, we obtain a classification rate of 83%, a sensitivity of 83%, and a specificity of 84%. This accuracy is superior to that of hippocampal volumetry and is comparable to recently published SVM-based whole-brain classification methods, which relied on a different strategy. This new method may become a useful tool to assist in the diagnosis of Alzheimer's disease.

While the hippocampus is constantly reported as the site of earliest and highest structural alteration in Alzheimer's disease (AD), findings regarding the metabolic status of this region are rather heterogeneous. It has been proposed that only a time-consuming individual region-of-interest (ROI) approach would allow the detection of hypometabolism in this complex and small area. Our main goal with this study is to assess whether more automatic and clinically useful methods would be sensitive enough when considering other methodological confounds. From a single PET data set collected in 28 patients with amnestic Mild Cognitive Impairment (aMCI) and 19 controls, we assessed the effects of partial volume effect (PVE) correction, scaling (using vermis or global means), and analysis method (individual ROI versus more automatic template-based ROI or voxel-based approaches) on hippocampal hypometabolism detection in aMCI. PVE correction and scaling both showed a significant effect on group comparison, while the analysis method (individual versus template-based ROI) surprisingly did not. Hippocampal metabolic decrease was significant in all vermis-scaled conditions, and more so after PVE correction. Our findings highlight the crucial relevance of using reference-region-based (instead of global) scaling, and the higher sensitivity of PVE-corrected PET measures, to detect hippocampal hypometabolism in aMCI. They also show that hippocampal metabolic decline can be detected using template-based ROI as well as voxel-based methods. These findings have clinical relevance since they support the validity of more automatic and time-saving approaches to assess hippocampal metabolism changes in aMCI and early AD.

The time-scale of medial temporal lobe (MTL) involvement in storage and retrieval of episodic memory is keenly debated. To test competitive theories of long-term memory consolidation, the present work aimed at characterizing which cerebral regions are involved during retrieval of recent and remote strictly episodic autobiographical memory. Using positron emission tomography (PET), we examined mental retrieval of recent (0-1 year) and remote (5-10 years) autobiographical memories, controlling for the nature of the autobiographical memories (i.e., specificity, state of consciousness, vividness of mental visual imagery, emotion) retrieved during scanning by behavioral measures assessed at debriefing for each event recalled. Cognitive results showed that specificity and emotion did not change with time interval although both autonoetic consciousness and mental image quality were significantly higher for recent memories, suggesting an underlying shift in the phenomenal experience of remembering with the passage of time. The SPM analysis revealed common activations during the recollection of recent and remote memories that involved a widespread but mainly left-sided cerebral network, consistent with previous studies. Subtraction analysis demonstrated that the retrieval of recent (relative to remote) autobiographical memories principally activated the left dorsolateral prefrontal cortex whereas the retrieval of remote (relative to recent) autobiographical memories activated the inferior parietal cortex bilaterally. ROIs analysis revealed more hippocampal activity for remote memories than for recent ones and a preferentially right-sided involvement of the hippocampal responses whatever the remoteness of autobiographical memories. New insights based on higher hippocampal response to the remoteness of episodic autobiographical memories challenge the standard model and are less discrepant with the multiple trace theory., (Copyright 2004 Elsevier Inc.)

This study was designed to map in Alzheimer's disease patients the correlations between resting-state brain glucose utilization measured by PET and the number of intrusions obtained by means of a specially designed episodic memory test separately in free recall and in cued recall. SPM revealed significant negative correlations between the number of intrusions in free recall and the metabolism of the right superior frontal gyrus. For the intrusions in cued recall, the negative correlations concerned the left rhinal cortex. Our findings suggest that intrusions in free recall reflect perturbations in strategic processes and that intrusions in cued recall are triggered by the cue in a relatively automatic manner. Frontal dysfunction would be responsible for the former and rhinal dysfunction for the latter.