Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia

We present a feature extraction method to emphasize the interrelationship between gray and white matter and identify tissue distribution abnormalities in schizophrenia. This approach utilizes novel features called structural phase and magnitude images. The phase image indicates the relative contribution of gray and white matter, and the magnitude image reflects the overall tissue concentration. Three different analyses are applied to the phase and magnitude images obtained from 120 healthy controls and 120 schizophrenia patients. First, a single-subject subtraction analysis is computed for an initial evaluation. Second, we analyze the extracted features using voxel based morphometry (VBM) to detect voxelwise group differences. Third, source based morphometry (SBM) analysis was used to determine abnormalities in structural networks that co-vary in a similar way. Six networks were identified showing significantly lower white-to-gray matter in schizophrenia, including thalamus, right precentral-postcentral, left pre/post-central, parietal, right cuneus-frontal, and left cuneus-frontal sources. Interestingly, some networks look similar to functional patterns, such as sensory-motor and vision. Our findings demonstrate that structural phase and magnitude images can naturally and efficiently summarize the associated relationship between gray and white matter. Our approach has wide applicability for studying tissue distribution differences in the healthy and diseased brain

Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification.

Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level. Among the different approaches aiming to study white matter abnormalities at the subject level, normative modeling analysis takes a step towards subject-level predictions by identifying affected brain locations in individual subjects based on extreme deviations from a normative range. Here, we leveraged a large harmonized diffusion MRI dataset from 512 healthy controls and 601 individuals diagnosed with schizophrenia, to study whether normative modeling can improve subject-level predictions from a binary classifier. To this aim, individual deviations from a normative model of standard (fractional anisotropy) and advanced (free-water) dMRI measures, were calculated by means of age and sex-adjusted z-scores relative to control data, in 18 white matter regions. Even though larger effect sizes are found when testing for group differences in z-scores than are found with raw values (p < .001), predictions based on summary z-score measures achieved low predictive power (AUC < 0.63). Instead, we find that combining information from the different white matter tracts, while using multiple imaging measures simultaneously, improves prediction performance (the best predictor achieved AUC = 0.726). Our findings suggest that extreme deviations from a normative model are not optimal features for prediction. However, including the complete distribution of deviations across multiple imaging measures improves prediction, and could aid in subject-level classification

Large-Scale Fusion of Gray Matter and Resting-State Functional MRI Reveals Common and Distinct Biological Markers across the Psychosis Spectrum in the B-SNIP Cohort

To investigate whether aberrant interactions between brain structure and function present similarly or differently across probands with psychotic illnesses [schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar I disorder with psychosis (BP)] and whether these deficits are shared with their first-degree non-psychotic relatives. A total of 1199 subjects were assessed, including 220 SZ, 147 SAD, 180 psychotic BP, 150 first-degree relatives of SZ, 126 SAD relatives, 134 BP relatives, and 242 healthy controls (1). All subjects underwent structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) scanning. Joint-independent component analysis (jICA) was used to fuse sMRI gray matter and rs-fMRI amplitude of low-frequency fluctuations data to identify the relationship between the two modalities. jICA revealed two significantly fused components. The association between functional brain alteration in a prefrontal–striatal–thalamic–cerebellar network and structural abnormalities in the default mode network was found to be common across psychotic diagnoses and correlated with cognitive function, social function, and schizo-bipolar scale scores. The fused alteration in the temporal lobe was unique to SZ and SAD. The above effects were not seen in any relative group (including those with cluster-A personality). Using a multivariate-fused approach involving two widely used imaging markers, we demonstrate both shared and distinct biological traits across the psychosis spectrum. Furthermore, our results suggest that the above traits are psychosis biomarkers rather than endophenotypes

Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and related humans in the Netherlands

In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and related humans on farms. High number of farm infections (68/126) in minks and farm related personnel (>50% of farms) were detected, with limited spread to the general human population. Three of five initial introductions of SARS-CoV-2 lead to subsequent spread between mink farms until November 2020. The largest cluster acquired a mutation in the receptor binding domain of the Spike protein (position 486), evolved faster and spread more widely and longer. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combing genetic information with epidemiological information at the animal-human interface

MALINGERING: THE USE OF A PSYCHOLOGICAL TEST BATTERY TO DETECT TWO KINDS OF SIMULATION (FAKING, BENDER-GESTALT, DISSIMULATION, MMPI).

Malingering refers to the voluntary production of false or greatly exaggerated symptoms in pursuit of an obviously recognizable goal. Numerous studies have shown the psychological tests can detect persons faking various mental disorders; however, the majority of these are plagued by methodological flaws that seriously limit their validity and generalizability. The present study employed a contrasted-groups design that allowed for a rigorous test of the hypothesis that a battery of psychological tests can detect persons given a financial incentive to fake insanity or mental retardation. In addition to using two tests previously employed in simulation research (MMPI and Bender Gestalt), an instrument whose sole purpose is to differentiate malingerers from genuinely impaired adults was developed for validation in this study. This pen-and-paper test (the Malingering Scale) consists of 90 arithmetic, vocabulary, information and abstraction items, and requires 20 minutes to complete. One hundred male adults were divided into five groups of 20 subjects. Two groups consisted of genuinely impaired subjects (either mentally retarded or psychotic inpatients). The other three groups were drawn from a population of prison inmates. Two of the latter groups were offered a financial incentive for successful simulation of a mental disorder (either mental retardation or "insanity") while the fifth group consisted of inmates controls (answering honestly). The test battery was administered to all subjects and scored by examiners who were naive to the purpose of the study. A series of item analyses established the internal consistency of the Malingering Scale and identified those items which best differentiate malingerers from the genuinely impaired. These items were assembled into scoring keys for subjects faking each condition. All test scores were then entered into a series of discriminant function analyses which confirmed the hypothesis that the battery provided more powerful discrimination of subject groups than any single test. Overall, 84% of the subjects were accurately classified into their respective group, and 96% of subjects were correctly identified as either malingering or not malingering. The most powerful single instrument proved to be the Malingering Scale. Direction for future research, including the necessity for cross validation of the Malingering Scale, were discussed

Target Optimization in tDCS

Transcranial direct current stimulation (tDCS) is an emerging neuromodulation therapy that has been experimentally determined to affect a wide range of behaviors and diseases ranging from motor, cognitive, and memory processes to depression and pain syndromes. The effects of tDCS may be inhibitory or excitatory, depending on the relative polarities of electrodes and their proximity to different brain structures. This distinction is believed to relate to the interaction of current flow with activation thresholds of different neural complexes. tDCS currents are typically applied via a single pair of large electrodes, with one (the active electrode) sited close to brain structures associated with targeted processes. To efficiently direct current toward the areas presumed related to these effects, we devised a method of steering current toward a selected area by reference to a 19-electrode montage applied to a high-resolution finite element model of the head. We used a nonlinear optimization procedure to maximize mean current densities inside the left inferior frontal gyrus, while simultaneously restricting overall current and median current densities within the accumbens. We found that a distributed current pattern could be found that would indeed direct current toward the inferior frontal gyrus in this way, and compared it to other candidate 2-electrode configurations. Further, we found a combination of 4 anterior-posterior electrodes could direct current densities to the accumbens. We conclude that a similar method using multiple electrodes may be a useful means of directing current toward or away from specific brain regions and also of reducing tDCS side effects