Graph Spectral Characterization of Brain Cortical Morphology

The human brain cortical layer has a convoluted morphology that is unique to each individual. Characterization of the cortical morphology is necessary in longitudinal studies of structural brain change, as well as in discriminating individuals in health and disease. A method for encoding the cortical morphology in the form of a graph is presented. The design of graphs that encode the global cerebral hemisphere cortices as well as localized cortical regions is proposed. Spectral metrics derived from these graphs are then studied and proposed as descriptors of cortical morphology. As proof-of-concept of their applicability in characterizing cortical morphology, the metrics are studied in the context of hemispheric asymmetry as well as gender dependent discrimination of cortical morphology.Comment: arXiv admin note: substantial text overlap with arXiv:1810.1033

Shared latent structures between imaging features and biomarkers in early stages of Alzheimer's disease: a predictive study

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Magnetic resonance imaging (MRI) provides high resolution brain morphological information and is used as a biomarker in neurodegenerative diseases. Population studies of brain morphology often seek to identify pathological structural changes related to different diagnostic categories (e.g: controls, mild cognitive impairment or dementia) which normally describe highly heterogeneous groups with a single categorical variable. Instead, multiple biomarkers are used as a proxy for pathology and are more powerful in capturing structural variability. Hence, using the joint modeling of brain morphology and biomarkers, we aim at describing structural changes related to any brain condition by means of few underlying processes. In this regard, we use a multivariate approach based on Projection to Latent Structures in its regression variant (PLSR) to study structural changes related to aging and AD pathology. MRI volumetric and cortical thickness measurements are used for brain morphology and cerebrospinal fluid (CSF) biomarkers (t-tau, p-tau and amyloid-beta) are used as a proxy for AD pathology. By relating both sets of measurements, PLSR finds a low-dimensional latent space describing AD pathological effects on brain structure. The proposed framework allows to separately model aging effects on brain morphology as a confounder variable orthogonal to the pathological effect. The predictive power of the associated latent spaces (i.e. the capacity of predicting biomarker values) is assessed in a cross-validation framework.Peer ReviewedPostprint (author's final draft

Blood-based bioenergetic profiling is related to differences in brain morphology in African Americans with Type 2 diabetes.

Blood-based bioenergetic profiling has promising applications as a minimally invasive biomarker of systemic bioenergetic capacity. In the present study, we examined peripheral blood mononuclear cell (PBMC) mitochondrial function and brain morphology in a cohort of African Americans with long-standing Type 2 diabetes. Key parameters of PBMC respiration were correlated with white matter, gray matter, and total intracranial volumes. Our analyses indicate that these relationships are primarily driven by the relationship of systemic bioenergetic capacity with total intracranial volume, suggesting that systemic differences in mitochondrial function may play a role in overall brain morphology

Differential detection of impact site versus rotational site injury by magnetic resonance imaging and microglial morphology in an unrestrained mild closed head injury model.

Seventy-five percent of all traumatic brain injuries are mild and do not cause readily visible abnormalities on routine medical imaging making it difficult to predict which individuals will develop unwanted clinical sequelae. Microglia are brain-resident macrophages and early responders to brain insults. Their activation is associated with changes in morphology or expression of phenotypic markers including P2Y12 and major histocompatibility complex class II. Using a murine model of unrestrained mild closed head injury (mCHI), we used microglia as reporters of acute brain injury at sites of impact versus sites experiencing rotational stress 24 h post-mCHI. Consistent with mild injury, a modest 20% reduction in P2Y12 expression was detected by quantitative real-time PCR (qPCR) analysis but only in the impacted region of the cortex. Furthermore, neither an influx of blood-derived immune cells nor changes in microglial expression of CD45, TREM1, TREM2, major histocompatibility complex class II or CD40 were detected. Using magnetic resonance imaging (MRI), small reductions in T2 weighted values were observed but only near the area of impact and without overt tissue damage (blood deposition, edema). Microglial morphology was quantified without cryosectioning artifacts using ScaleA(2) clarified brains from CX3CR1-green fluorescence protein (GFP) mice. The cortex rostral to the mCHI impact site receives greater rotational stress but neither MRI nor molecular markers of microglial activation showed significant changes from shams in this region. However, microglia in this rostral region did display signs of morphologic activation equivalent to that observed in severe CHI. Thus, mCHI-triggered rotational stress is sufficient to cause injuries undetectable by routine MRI that could result in altered microglial surveillance of brain homeostasis. Acute changes in microglial morphology reveal brain responses to unrestrained mild traumatic brain injury In areas subjected to rotational stress distant from impact site In the absence of detectable changes in standard molecular indicators of brain damage, inflammation or microglial activation. That might result in decreased surveillance of brain function and increased susceptibility to subsequent brain insults

Endocranial Morphology of the Extinct North American Lion (Panthera atrox)

The extinct North American lion (Panthera atrox) is one of the largest felids (Mammalia, Carnivora) to have ever lived, and it is known from a plethora of incredibly well-preserved remains. Despite this abundance of material, there has been little research into its endocranial anatomy. CT scans of a skull of P. atrox from the Pleistocene La Brea Tar pits were used to generate the first virtual endocranium for this species and to elucidate previously unknown details of its brain size and gross structure, cranial nerves, and inner-ear morphology. Results show that its gross brain anatomy is broadly similar to that of other pantherines, although P. atrox displays less cephalic flexure than either extant lions or tigers, instead showing a brain shape that is reminiscent of earlier felids. Despite this unusual reduction in flexure, the estimated absolute brain size for this specimen is one of the largest reported for any felid, living or extinct. Its encephalization quotient (brain size as a fraction of the expected brain mass for a given body mass) is also larger than that of extant lions but similar to that of the other pantherines. The advent of CT scans has allowed nondestructive sampling of anatomy that cannot otherwise be studied in these extinct lions, leading to a more accurate reconstruction of endocranial morphology and its evolution

The influence of skull shape modularity on internal skull structures: a 3D-Pilot study using bears

In order to capture the phenotypic variation of the internal skull structures, such as the sinuses or the brain, it is necessary to perform CT scans in a large number of specimens, which is difficult and expensive. Therefore, while the external morphology of the mammalian cranium has been the subject of many morphometric studies, the internal structures of the cranium have been comparatively less studied. Here, we explore how the variation of external shape reflects the morphology of internal structures. We use the family Ursidae (Carnivora, Mammalia) as a case study because bears have a wide variability of cranial morphologies in part associated with different trophic ecologies. To do this, we digitized a set of landmarks in 3D with a Microscribe G2X from the external surface of the cranium in a wide sample of bears. Additionally, the crania of seven bear species were CT-scanned and prepared digitally to visualize the 3D models of the external cranium morphology and of internal structures. Subsequently, we divided the landmarks into two modules, splanchnocranium and neurocranium, and we perform a two-block partial least squares analysis (2B PLS) to explore the intraspecific (static) morphological changes associated with the covariation between them. These morphological changes were visualized using the morphing technique with the 3D models, looking at both the external shape and the internal structures. In addition, we inferred the volume of the sinuses and of the brain in each hypothetical model. Our results show that the first two PLS axes are associated externally with changes in the basicranial angle, face length and cranium height and width. Concerning the internal structures, there are parallel changes in dorso-ventral and medio-lateral expansion of sinuses and brain, accompanied by their corresponding changes in volume. In contrast, the third PLS axis is related to opposite changes in the volume of sinuses and brain. These preliminary results suggest that the opposite relationship between sinuses and brain volumes in the bear cranium is not as evident as expected, at least at intraspecific level.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

What contributes to individual differences in brain structure?

Individual differences in adult human brain structure have been found to reveal a great deal of information about variability in behaviors, cognitive abilities and mental and physical health. Driven by such evidence, what contributes to individual variation in brain structure has gained accelerated attention as a research question. Findings thus far appear to support the notion that an individual’s brain architecture is determined largely by genetic and environmental influences. This review aims to evaluate the empirical literature on whether and how genes and the environment contribute to individual differences in brain structure. It first considers how genetic and environmental effects may separately contribute to brain morphology, by examining evidence from twin, genome-wide association, cross-sectional and longitudinal studies. Next, evidence for the influence of the complex interplay between genetic and environmental factors, characterized as gene-environment interactions and correlations, is reviewed. In evaluating the extant literature, this review will conclude that both genetic and environmental factors play critical roles in contributing to individual variability in brain structure