Deformation-based shape analysis of the hippocampus in the semantic variant of primary progressive aphasia and Alzheimer’s disease

Background Increasing evidence shows that the semantic variant of primary progressive aphasia (svPPA) is characterized by hippocampal atrophy. However, less is known about disease-related morphological hippocampal changes. The goal of the present study is to conduct a detailed characterization of the impact of svPPA on global hippocampus volume and morphology compared with control subjects and patients with Alzheimer’s disease (AD). Methods We measured hippocampal volume and deformation-based shape differences in 22 patients with svPPA compared with 99 patients with AD and 92 controls. Multiple Automatically Generated Templates Brain Segmentation Algorithm (MAGeT-Brain) was used on MRI images obtained at the diagnostic visit. Results Comparable left and right hippocampal atrophy were observed in svPPA and AD. Deformation-based shape analysis showed a common pattern of morphological deformation in svPPA and AD compared with controls. More specifically, both svPPA and AD showed inward deformations in the dorsal surface of the hippocampus, from head to tail on the left side, and more limited to the anterior portion of the body in the right hemisphere. These results also pointed out that both diseases are characterized by a lateral displacement of the central part (body) of the hippocampus. Discussion Our study provides critical new evidence of hippocampal morphological changes in svPPA, similar to those found in AD. These findings highlight the importance of considering morphological hippocampal changes as part of the anatomical profile of patients with svPPA

Involvement of the habenula in the pathophysiology of autism spectrum disorder.

Funder: Fondation Brain Canada; doi: http://dx.doi.org/10.13039/100009408The habenula is a small epithalamic structure with widespread connections to multiple cortical, subcortical and brainstem regions. It has been identified as the central structure modulating the reward value of social interactions, behavioral adaptation, sensory integration and circadian rhythm. Autism spectrum disorder (ASD) is characterized by social communication deficits, restricted interests, repetitive behaviors, and is frequently associated with altered sensory perception and mood and sleep disorders. The habenula is implicated in all these behaviors and results of preclinical studies suggest a possible involvement of the habenula in the pathophysiology of this disorder. Using anatomical magnetic resonance imaging and automated segmentation we show that the habenula is significantly enlarged in ASD subjects compared to controls across the entire age range studied (6-30 years). No differences were observed between sexes. Furthermore, support-vector machine modeling classified ASD with 85% accuracy (model using habenula volume, age and sex) and 64% accuracy in cross validation. The Social Responsiveness Scale (SRS) significantly differed between groups, however, it was not related to individual habenula volume. The present study is the first to provide evidence in human subjects of an involvement of the habenula in the pathophysiology of ASD

Heritability of hippocampal subfield volumes using a twin and non-twin siblings design

The hippocampus is composed of distinct subfields linked to diverse functions and disorders. The subfields can be mapped using high-resolution magnetic resonance images, and their volumes can potentially be used as quantitative phenotypes for genetic investigation of hippocampal function. We estimated the heritability of hippocampus subfield volumes of 465 subjects from the Human Connectome Project (twins and non-twin siblings) using two methods. The first used a univariate model to estimate heritability with and without adjustment for total brain volume (TBV) and ipsilateral hippocampal volume to determine if heritability was uniquely attributable to subfield volume rather than confounds that attributed to global volumes. We observed the right: subiculum, cornu ammonis 2/3, and cornu ammonis 4/dentate gyrus subfields had the highest significant heritability estimates after adjusting for ipsilateral hippocampal volume. In the second analysis, we used a bivariate model to investigate the shared heritability and genetic correlation of the subfield volumes with TBV and ipsilateral hippocampal volume. Genetic correlation demonstrates shared genetic architecture between phenotypes and shared heritability is what proportion of the genetic architecture of one trait is shared by the other. Highest genetic correlations were between subfield volumes and ipsilateral hippocampal volume than with TBV. The pattern was opposite for shared heritability suggesting that subfields share greater proportion of the genetic architecture with TBV than with ipsilateral hippocampal volume. The relationship between the genetic architecture of TBV, hippocampal volume, and of individual subfields should be accounted for when using hippocampal subfield volumes as quantitative phenotypes for imaging genetics studies. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc

MRI atlas of a lizard brain

Magnetic resonance imaging (MRI) is an established technique for neuroanatomical analysis, being particularly useful in the medical sciences. However, the application of MRI to evolutionary neuroscience is still in its infancy. Few magnetic resonance brain atlases exist outside the standard model organisms in neuroscience and no magnetic resonance atlas has been produced for any reptile brain. A detailed understanding of reptilian brain anatomy is necessary to elucidate the evolutionary origin of enigmatic brain structures such as the cerebral cortex. Here, we present a magnetic resonance atlas for the brain of a representative squamate reptile, the Australian tawny dragon (Agamidae: Ctenophorus decresii), which has been the subject of numerous ecological and behavioral studies. We used a high-field 11.74T magnet, a paramagnetic contrasting-enhancing agent and minimum-deformation modeling of the brains of thirteen adult male individuals. From this, we created a high-resolution three-dimensional model of a lizard brain. The 3D-MRI model can be freely downloaded and allows a better comprehension of brain areas, nuclei, and fiber tracts, facilitating comparison with other species and setting the basis for future comparative evolution imaging studies. The MRI model and atlas of a tawny dragon brain (Ctenophorus decresii) can be viewed online and downloaded using the Wiley Biolucida Server at wiley.biolucida.net.Government of Australia, Grant/Award Numbers: APA#31/2011, IPRS#1182/2010; National Science and Engineering Research Council of Canada, Grant/Award Number: PGSD3-415253-2012; Quebec Nature and Technology Research Fund, Grant/AwardNumber: 208332; National Imaging Facility of Australia; Spanish Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional, Grant/Award Number:BFU2015-68537-

Inter- and intra-individual variation in brain structural-cognition relationships in aging

The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure

Bilateral Amygdala Radio-Frequency Ablation for Refractory Aggressive Behavior Alters Local Cortical Thickness to a Pattern Found in Non-refractory Patients

Aggressive behaviors comprise verbal and/or physical aggression directed toward oneself, others, or objects and are highly prevalent among psychiatric patients, especially patients diagnosed with autism spectrum disorder and severe intellectual disabilities. Some of these patients are considered refractory to treatment, and functional neurosurgery targeting the amygdala can result in widespread plastic brain changes that might reflect ceasing of some abnormal brain function, offering symptom alleviation. This study investigated cortical thickness changes in refractory aggressive behavior patients that were treated with bilateral amygdala ablation and compared to control patients presenting non-refractory aggressive behavior [three refractory and seven non-refractory patients, all males diagnosed with autism spectrum disorder (ASD) and intellectual disabilities]. The Overt Aggression Scale (OAS) was used to quantify behavior and magnetic resonance imaging was performed to investigate cortical thickness. Before surgery, both groups presented similar total OAS score, however refractory patients presented higher physical aggression against others. After surgery the refractory group showed 88% average reduction of aggressive behavior. Imaging analysis showed that while refractory patients present an overall reduction in cortical thickness compared to non-refractory patients across both timepoints, the local pattern of thickness difference found in areas of the neurocircuitry of aggressive behavior present before surgery is diminished and no longer detected after surgery. These results corroborate the hypotheses on induction of widespread neuronal plasticity following functional neurosurgical procedures resulting in modifications in brain morphology and improvement in behavior. Further studies are necessary to determine the underlying cause of these morphological changes and to better understand and improve treatment options

Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning?:A multi-method and multi-dataset study

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images. Each study, however, uses different datasets, classification algorithms, and validation techniques. Here, we perform a critical appraisal of the accuracy of machine learning methodologies used in SZ/HC classifications studies by comparing three machine learning algorithms (logistic regression [LR], support vector machines [SVMs], and linear discriminant analysis [LDA]) on three independent datasets (435 subjects total) using two tissue density estimates and cortical thickness (CT). Performance is assessed using 10-fold cross-validation, as well as a held-out validation set. Classification using CT outperformed tissue densities, but there was no clear effect of dataset. LR, SVMs, and LDA each yielded the highest accuracies for a different feature set and validation paradigm, but most accuracies were between 55 and 70%, well below previously reported values. The highest accuracy achieved was 73.5% using CT data and an SVM. Taken together, these results illustrate some of the obstacles to constructing effective disease classifiers, and suggest that tissue densities and CT may not be sufficiently sensitive for SZ/HC classification given current available methodologies and sample sizes

A Multi-Modal MRI Analysis of Cortical Structure in Relation to Gender Dysphoria, Sexual Orientation, and Age in Adolescents.

Gender dysphoria (GD) is characterized by distress due to an incongruence between experienced gender and sex assigned at birth. Sex-differentiated brain regions are hypothesized to reflect the experienced gender in GD and may play a role in sexual orientation development. Magnetic resonance brain images were acquired from 16 GD adolescents assigned female at birth (AFAB) not receiving hormone therapy, 17 cisgender girls, and 14 cisgender boys (ages 12-17 years) to examine three morphological and microstructural gray matter features in 76 brain regions: surface area (SA), cortical thickness (CT), and T1 relaxation time. Sexual orientation was represented by degree of androphilia-gynephilia and sexual attraction strength. Multivariate analyses found that cisgender boys had larger SA than cisgender girls and GD AFAB. Shorter T1, reflecting denser, macromolecule-rich tissue, correlated with older age and stronger gynephilia in cisgender boys and GD AFAB, and with stronger attractions in cisgender boys. Thus, cortical morphometry (mainly SA) was related to sex assigned at birth, but not experienced gender. Effects of experienced gender were found as similarities in correlation patterns in GD AFAB and cisgender boys in age and sexual orientation (mainly T1), indicating the need to consider developmental trajectories and sexual orientation in brain studies of GD

Deformation-based Morphometry MRI Reveals Brain Structural Modifications in Living Mu Opioid Receptor Knockout Mice

Mu opioid receptor (MOR) activation facilitates reward processing and reduces pain, and brain networks underlying these effects are under intense investigation. Mice lacking the MOR gene (MOR KO mice) show lower drug and social reward, enhanced pain sensitivity and altered emotional responses. Our previous neuroimaging analysis using Resting-state (Rs) functional Magnetic Resonance Imaging (fMRI) showed significant alterations of functional connectivity (FC) within reward/aversion networks in these mice, in agreement with their behavioral deficits. Here we further used a structural MRI approach to determine whether volumetric alterations also occur in MOR KO mice. We acquired anatomical images using a 7-Tesla MRI scanner and measured deformation-based morphometry (DBM) for each voxel in subjects from MOR KO and control groups. Our analysis shows marked anatomical differences in mutant animals. We observed both local volumetric contraction (striatum, nucleus accumbens, bed nucleus of the stria terminalis, hippocampus, hypothalamus and periacqueducal gray) and expansion (prefrontal cortex, amygdala, habenula, and periacqueducal gray) at voxel level. Volumetric modifications occurred mainly in MOR-enriched regions and across reward/aversion centers, consistent with our prior FC findings. Specifically, several regions with volume differences corresponded to components showing highest FC changes in our previous Rs-fMRI study, suggesting a possible function-structure relationship in MOR KO-related brain differences. In conclusion, both Rs-fMRI and volumetric MRI in live MOR KO mice concur to disclose functional and structural whole-brain level mechanisms that likely drive MOR-controlled behaviors in animals, and may translate to MOR-associated endophenotypes or disease in humans

High spatial overlap but diverging age-related trajectories of cortical magnetic resonance imaging markers aiming to represent intracortical myelin and microstructure

ABSTRACT: Statistical effects of cortical metrics derived from standard T1- and T2-weighted magnetic resonance imaging (MRI) images, such as gray–white matter contrast (GWC), boundary sharpness coefficient (BSC), T1-weighted/T2-weighted ratio (T1w/T2w), and cortical thickness (CT), are often interpreted as representing or being influenced by intracortical myelin content with little empirical evidence to justify these interpretations. We first examined spatial correspondence with more biologically specific microstructural measures, and second compared between-marker age-related trends with the underlying hypothesis that different measures primarily driven by similar changes in myelo- and microstructural underpinnings should be highly related. Cortical MRI markers were derived from MRI images of 127 healthy subjects, aged 18–81, using cortical surfaces that were generated with the CIVET 2.1.0 pipeline. Their gross spatial distributions were compared with gene expression-derived cell-type densities, histology-derived cytoarchitecture, and quantitative R1 maps acquired on a subset of participants. We then compared between-marker age-related trends in their shape, direction, and spatial distribution of the linear age effect. The gross anatomical distributions of cortical MRI markers were, in general, more related to myelin and glial cells than neuronal indicators. Comparing MRI markers, our results revealed generally high overlap in spatial distribution (i.e., group means), but mostly divergent age trajectories in the shape, direction, and spatial distribution of the linear age effect. We conclude that the microstructural properties at the source of spatial distributions of MRI cortical markers can be different from microstructural changes that affect these markers in aging