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

Structural correlates of impaired working memory in hippocampal sclerosis

PURPOSE: Temporal lobe epilepsy (TLE) has been considered to impair long-term memory, whilst not affecting working memory, but recent evidence suggests that working memory is compromised. Functional MRI (fMRI) studies demonstrate that working memory involves a bilateral frontoparietal network the activation of which is disrupted in hippocampal sclerosis (HS). A specific role of the hippocampus to deactivate during working memory has been proposed with this mechanism faulty in patients with HS. Structural correlates of disrupted working memory in HS have not been explored. METHODS: We studied 54 individuals with medically refractory TLE and unilateral HS (29 left) and 28 healthy controls. Subjects underwent 3T structural MRI, a visuospatial n-back fMRI paradigm and diffusion tensor imaging (DTI). Working memory capacity assessed by three span tasks (digit span backwards, gesture span, motor sequences) was combined with performance in the visuospatial paradigm to give a global working memory measure. Gray and white matter changes were investigated using voxel-based morphometry and voxel-based analysis of DTI, respectively. KEY FINDINGS: Individuals with left or right HS performed less well than healthy controls on all measures of working memory. fMRI demonstrated a bilateral frontoparietal network during the working memory task with reduced activation of the right parietal lobe in both patient groups. In left HS, gray matter loss was seen in the ipsilateral hippocampus and parietal lobe, with maintenance of the gray matter volume of the contralateral parietal lobe associated with better performance. White matter integrity within the frontoparietal network, in particular the superior longitudinal fasciculus and cingulum, and the contralateral temporal lobe, was associated with working memory performance. In right HS, gray matter loss was also seen in the ipsilateral hippocampus and parietal lobe. Working memory performance correlated with the gray matter volume of both frontal lobes and white matter integrity within the frontoparietal network and contralateral temporal lobe. SIGNIFICANCE: Our data provide further evidence that working memory is disrupted in HS and impaired integrity of both gray and white matter is seen in functionally relevant areas. We suggest this forms the structural basis of the impairment of working memory, indicating widespread and functionally significant structural changes in patients with apparently isolated HS

Microstructural Alterations in Hippocampal Subfields Mediate Age-Related Memory Decline in Humans.

Aging, even in the absence of clear pathology of dementia, is associated with cognitive decline. Neuroimaging, especially diffusion-weighted imaging, has been highly valuable in understanding some of these changes in live humans, non-invasively. Traditional tensor techniques have revealed that the integrity of the fornix and other white matter tracts significantly deteriorates with age, and that this deterioration is highly correlated with worsening cognitive performance. However, traditional tensor techniques are still not specific enough to indict explicit microstructural features that may be responsible for age-related cognitive decline and cannot be used to effectively study gray matter properties. Here, we sought to determine whether recent advances in diffusion-weighted imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI) and Constrained Spherical Deconvolution, would provide more sensitive measures of age-related changes in the microstructure of the medial temporal lobe. We evaluated these measures in a group of young (ages 20-38 years old) and older (ages 59-84 years old) adults and assessed their relationships with performance on tests of cognition. We found that the fiber density (FD) of the fornix and the neurite density index (NDI) of the fornix, hippocampal subfields (DG/CA3, CA1, and subiculum), and parahippocampal cortex, varied as a function of age in a cross-sectional cohort. Moreover, in the fornix, DG/CA3, and CA1, these changes correlated with memory performance on the Rey Auditory Verbal Learning Test (RAVLT), even after regressing out the effect of age, suggesting that they were capturing neurobiological properties directly related to performance in this task. These measures provide more details regarding age-related neurobiological properties. For example, a change in fiber density could mean a reduction in axonal packing density or myelination, and the increase in NDI observed might be explained by changes in dendritic complexity or even sprouting. These results provide a far more comprehensive view than previously determined on the possible system-wide processes that may be occurring because of healthy aging and demonstrate that advanced diffusion-weighted imaging is evolving into a powerful tool to study more than just white matter properties

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

Hippocampal subfields and limbic white matter jointly predict learning rate in older adults

First published online: 04 December 2019Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants aged 61-82 years (Mage = 69.66, SDage = 3.92 years), we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task of recall over five repeated trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, and their latent interaction. Results showed limbic WM and the interaction of HC and WM-but not HC volume alone-predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher WM anisotropy. We conclude that the structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults

Measuring cortical connectivity in Alzheimer's disease as a brain neural network pathology: Toward clinical applications

Objectives: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer’s disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. Methods: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). Results: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior–posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. Conclusions: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD. (JINS, 2016, 22, 138–163

Recognition Memory Dysfunction Relates to Hippocampal Subfield Volume: A Study of Cognitively Normal and Mildly Impaired Older Adults.

ObjectivesThe current study examined recognition memory dysfunction and its neuroanatomical substrates in cognitively normal older adults and those diagnosed with mild cognitive impairment (MCI).MethodsParticipants completed the Mnemonic Similarity Task, which provides simultaneous measures of recognition memory and mnemonic discrimination. They also underwent structural neuroimaging to assess volume of medial temporal cortex and hippocampal subfields.ResultsAs expected, individuals diagnosed with MCI had significantly worse recognition memory performance and reduced volume across medial temporal cortex and hippocampal subfields relative to cognitively normal older adults. After controlling for diagnostic group differences, however, recognition memory was significantly related to whole hippocampus volume, and to volume of the dentate gyrus/CA3 subfield in particular. Recognition memory was also related to mnemonic discrimination, a fundamental component of episodic memory that has previously been linked to dentate gyrus/CA3 structure and function.DiscussionResults reveal that hippocampal subfield volume is sensitive to individual differences in recognition memory in older adults independent of clinical diagnosis. This supports the notion that episodic memory declines along a continuum within this age group, not just between diagnostic groups

Systems modeling of white matter microstructural abnormalities in Alzheimer's disease

INTRODUCTION: Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression. METHODS: We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD. RESULTS: We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions. DISCUSSION: Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD

Neuroinflammation and white matter alterations in obesity assessed by Diffusion Basis Spectrum Imaging

Human obesity is associated with low-grade chronic systemic inflammation, alterations in brain structure and function, and cognitive impairment. Rodent models of obesity show that high-calorie diets cause brain inflammation (neuroinflammation) in multiple regions, including the hippocampus, and impairments in hippocampal-dependent memory tasks. To determine if similar effects exist in humans with obesity, we applied Diffusion Basis Spectrum Imaging (DBSI) to evaluate neuroinflammation and axonal integrity. We examined diffusion-weighted magnetic resonance imaging (MRI) data in two independent cohorts of obese and non-obese individuals (Cohort 1: 25 obese/21 non-obese; Cohort 2: 18 obese/41 non-obese). We applied Tract-based Spatial Statistics (TBSS) to allow whole-brain white matter (WM) analyses and compare DBSI-derived isotropic and anisotropic diffusion measures between the obese and non-obese groups. In both cohorts, the obese group had significantly greater DBSI-derived restricted fraction (DBSI-RF; an indicator of neuroinflammation-related cellularity), and significantly lower DBSI-derived fiber fraction (DBSI-FF; an indicator of apparent axonal density) in several WM tracts (all correcte