Identification of voxel-based texture abnormalities as new biomarkers for schizophrenia and major depressive patients using layer-wise relevance propagation on deep learning decisions.

Non-segmented MRI brain images are used for the identification of new Magnetic Resonance Imaging (MRI) biomarkers able to differentiate between schizophrenic patients (SCZ), major depressive patients (MD) and healthy controls (HC). Brain texture measures such as entropy and contrast, capturing the neighboring variation of MRI voxel intensities, were computed and fed into deep learning technique for group classification. Layer-wise relevance was applied for the localization of the classification results. Texture feature map of non-segmented brain MRI scans were extracted from 141 SCZ, 103 MD and 238 HC. The gray level co-occurrence matrix (GLCM) was calculated on a voxel-by-voxel basis in a cube of voxels. Deep learning tested if texture feature map could predict diagnostic group membership of three classes under a binary classification (SCZ vs. HC, MD vs. HC, SCZ vs. MD). The method was applied in a repeated nested cross-validation scheme and cross-validated feature selection. The regions with the highest relevance (positive/negative) are presented. The method was applied on non-segmented images reducing the computation complexity and the error associated with segmentation process.

Effect of childhood physical abuse on social anxiety is mediated via reduced frontal lobe and amygdala-hippocampus complex volume in adult clinical high-risk subjects.

BACKGROUND: Childhood adverse experiences (CAE) are associated with clinical psychiatric disorders and symptoms, and with volumetric abnormalities in the amygdala-hippocampus complex (AmHiC) and frontal lobe (FroL) in adulthood. AIM: To study whether CAE are associated with reduced AmHiC and FroL and whether these structures mediate the effect of CAE on social anxiety and depression. METHOD: In seven European centres, 374 patients with recent onset of psychosis (n = 127), clinical high-risk to psychosis (n = 119) or recent onset of depression (n = 128) were scanned with MRI and their FroL and AmHiC volumes were measured. They all completed self-report scales for assessment of CAE, social anxiety and depression. RESULTS: Of the CAE domains, physical abuse was associated specifically with reduced grey and white matter volumes of FroL and AmHiC in psychotic and high-risk patients. After controlling intracranial volume, PhyAb associated significantly with FroL and its grey matter volume in high-risk patients only. In mediation analyses, the effect of physical abuse on social anxiety was mediated via reduced FroL grey mater volume in high-risk patients. In them, when the effects of AmHiC and depression were controlled, the effect of physical abuse on social anxiety was mediated via FroL grey matter volume reduction. CONCLUSIONS: Childhood physical abuse is associated with reduced frontal lobe and amygdala-hippocampus complex volume in adult subjects with psychotic symptoms. Reduced frontal lobe and amygdala-hippocampus complex volume mediate the effect of physical abuse on social anxiety in high-risk patients. The effect of physical abuse on depression-independent social anxiety is mediated via reduced frontal lobe.

The 16p11.2 locus modulates brain structures common to autism, schizophrenia and obesity.

Anatomical structures and mechanisms linking genes to neuropsychiatric disorders are not deciphered. Reciprocal copy number variants at the 16p11.2 BP4-BP5 locus offer a unique opportunity to study the intermediate phenotypes in carriers at high risk for autism spectrum disorder (ASD) or schizophrenia (SZ). We investigated the variation in brain anatomy in 16p11.2 deletion and duplication carriers. Beyond gene dosage effects on global brain metrics, we show that the number of genomic copies negatively correlated to the gray matter volume and white matter tissue properties in cortico-subcortical regions implicated in reward, language and social cognition. Despite the near absence of ASD or SZ diagnoses in our 16p11.2 cohort, the pattern of brain anatomy changes in carriers spatially overlaps with the well-established structural abnormalities in ASD and SZ. Using measures of peripheral mRNA levels, we confirm our genomic copy number findings. This combined molecular, neuroimaging and clinical approach, applied to larger datasets, will help interpret the relative contributions of genes to neuropsychiatric conditions by measuring their effect on local brain anatomy.

Disentangling in vivo the effects of iron content and atrophy on the ageing human brain.

Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21-88 years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.

Hispanic ethnicity and risk for combat-related posttraumatic stress disorder.

Hispanic veterans are said to exhibit higher risk of developing posttraumatic stress disorder (PTSD) than veterans of other racial/ethnic backgrounds. This prediction is based largely on findings from the National Vietnam Veterans Readjustment Study (NVVRS; R. A. Kulka et al., 1990a, 1990b). This article first summarizes the findings of the NVVRS with regard to race/ethnicity and PTSD, and then it makes a careful assessment of both the external and the internal validity of these findings. Conceptual issues are addressed and, where possible, further analyses of the NVVRS data set are conducted to identify factors that account for ethnic differences in rates of the disorder. Possible mediators of the effects of Hispanic ethnicity on vulnerability to PTSD are identified, including psychosocial factors (racial/ethnic discrimination and alienation) and sociocultural influences (stoicism and normalization of stress, alexithymia, and fatalism). Areas in which future research is needed are indicated.

Empathy: a physiological substrate.

The relation between empathy (defined as the ability to perceive accurately how another person is feeling) and physiology was studied in 31 Ss. Ss viewed 15-min martial interactions and used a rating dial to indicate continuously how they thought a designated spouse was feeling. Rating accuracy was determined by comparing Ss' ratings with identical self-ratings obtained previously from the target spouse. Physiological linkage between S and target was determined using bivariate time-series analyses applied to 5 autonomic and somatic measures obtained from the S during the rating task and from the target spouse during the original conversation. Accuracy of rating negative emotion was greatest when S and target evidenced high levels of physiological linkage across time. Accuracy of detecting positive emotion was related to a state of low cardiovascular around in the S, but not to physiological linkage between S and target.