Neural Correlates of Positive and Negative Formal Thought Disorder in Individuals with Schizophrenia: An ENIGMA Schizophrenia Working Group Study.

Formal thought disorder (FTD) is a key clinical factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, relationship between FTD symptom dimensions and patterns of regional brain volume deficiencies in schizophrenia remain to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles based on a large multi-site cohort through the ENIGMA Schizophrenia Working Group (752 individuals with schizophrenia and 1256 controls), to unravel the neuroanatomy of positive, negative and total FTD in schizophrenia and their cellular bases. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks for positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD was also linked to microglial cell types. These findings relate different dimensions of FTD to distinct brain structural changes and their cellular underpinnings, improve our mechanistic understanding of these key psychotic symptoms.

The neurobiology of autism spectrum disorder as it relates to twice exceptionality.

There is a long-standing association between exceptional cognitive abilities of various sorts and neuropsychiatric illness, but it has historically largely been investigated in an exploratory and non-systematic way. One group in which this association has been investigated with more rigor is in subjects who have been identified as twice exceptional; an educational term describing subjects who are both gifted and diagnosed with a neuropsychiatric disorder. This term covers multiple conditions, but is of specific interest in particular in the study of autism spectrum disorder. Recent findings have led to the development of a hypothesis that a certain degree of the neurobiology associated with autism might even be advantageous for individuals and could lead to high giftedness, while becoming disadvantageous, once a certain threshold is surpassed. In this model, the same neurobiological mechanisms confer an increasing advantage up to a certain threshold, but become pathological past that point. Twice-exceptional individuals would be exactly at the inflection point, being highly gifted, but also symptomatic at the same time. Here, we review how existing neuroimaging literature on autism spectrum disorder can inform research on twice exceptionality specifically. We propose to study key neural networks with a robust implication in ASD to identify the neurobiology underlying twice-exceptionality. A better understanding of the neural mechanisms of twice exceptionality should help to better understand resilience and vulnerability to neurodevelopmental disorders and to. further support affected individuals.

The functional neural architecture of dysfunctional reward processing in autism.

Functional imaging studies have found differential neural activation patterns during reward-paradigms in patients with autism spectrum disorder (ASD) compared to neurotypical controls. However, publications report conflicting results on the directionality and location of these aberrant activations. We here quantitatively summarized relevant fMRI papers in the field using the anatomical likelihood estimation (ALE) algorithm. Patients with ASD consistently showed hypoactivations in the striatum across studies, mainly in the right putamen and accumbens. These regions are functionally involved in the processing of rewards and are enrolled in extensive neural networks involving limbic, cortical, thalamic and mesencephalic regions. The striatal hypo-activations found in our ALE meta-analysis, which pooled over contrasts derived from the included studies on reward-processing in ASD, highlight the role of the striatum as a key neural correlate of impaired reward processing in autism. These changes were present for studies using social and non-social stimuli alike. The involvement of these regions in extensive networks associated with the processing of both positive and negative emotion alike might hint at broader impairments of emotion processing in the disorder.

Adolescent Resting-State Brain Networks and Unique Variability of Conduct Problems Within the Externalizing Dimension.

The externalizing psychopathological dimension is associated with alterations in adolescents' functional brain connectivity. The current study aims to identify the functional correlates of the unique variability in conduct problems within the context of the broad externalizing dimension. The broad externalizing dimension and unique variability in conduct problems were estimated using a bifactor model. Resting-state data were available for a sample of 125 adolescents. Based on multiresolution parcellation of functional brain networks atlas, major resting-state functional brain networks and the connectivity correlates of unique conduct problems and the broad externalizing dimension were established. The broad externalizing dimension was related to connectivity alterations in the ventral attention/salience network, while unique variability in conduct problems dimension was related to connectivity alterations in the cerebellum crusi as well as the mesolimbic network. The current study is a first step toward the identification of functional resting-state network correlates of broad and specific variability in the externalizing dimension.

Mesolimbic connectivity signatures of impulsivity and BMI in early adolescence.

Across age groups, differences in connectivity of the mesolimbic and the prefrontal cortex co-vary with trait impulsivity and sensation-seeking. Impulsivity and sensation-seeking are also known to increase during early adolescence as maturation of subcortical structures outpaces that of the prefrontal cortex. While an imbalance between the striatum and prefrontal cortex is considered a normal developmental process, higher levels of adolescent impulsivity and sensation-seeking are associated with an increased risk for diverse problems, including obesity. To determine how the relationship between sensation-seeking, impulsivity and body mass index (BMI) is related to shared neural correlates we measured their relationships with the connectivity of nuclei in the striatum and dopaminergic midbrain in young adolescents. Data were collected from 116 children between the ages of 12 and 14, and included resting state functional magnetic resonance imaging, personality measures from the Substance Use Risk Profile Scale, and BMI Z-score for age. The shared variance for the connectivity of regions of interest in the substantia nigra, ventral tegmental area, ventral striatum and sub-thalamic nucleus, personality measures and BMI Z-score for age, were analyzed using partial least squares correlation. This analysis identified a single significant striato-limbic network that was connected with the substantia nigra, ventral tegmental area and sub-thalamic nuclei (p = 0.002). Connectivity within this network which included the hippocampi, amygdalae, parahippocampal gyri and the regions of interest, correlated positively with impulsivity and BMI Z-score for age and negatively with sensation-seeking. Together, these findings emphasize that, in addition to the well-established role that frontostriatal circuits play in the development of adolescent personality traits, connectivity of limbic regions with the striatum and midbrain also impact impulsivity, sensation-seeking and BMI Z-score in adolescents.

Overweight is not associated with cortical thickness alterations in children.

INTRODUCTION: Several studies report an association between body mass index (BMI) and cortical thickness in adults. Some studies demonstrate diffuse cortical thinning in obesity, while others report effects in areas that are associated with self-regulation, such as lateral prefrontal cortex. METHODS: This study used multilevel modeling of data from the NIH Pediatric MRI Data Repository, a mixed longitudinal and cross-sectional database, to examine the relationship between cortical thickness and body weight in children. Cortical thickness was computed at 81,942 vertices of 716 MRI scans from 378 children aged between 4 and 18 years. Body mass index Z score for age was computed for each participant. We performed vertex-wise statistical analysis of the relationship between cortical thickness and BMI, accounting for age and gender. In addition, cortical thickness was extracted from regions of interest in prefrontal cortex and insula. RESULTS: No significant association between cortical thickness and BMI was found, either by statistical parametric mapping or by region of interest analysis. RESULTS remained negative when the analysis was restricted to children aged 12-18. CONCLUSIONS: The correlation between BMI and cortical thickness was not found in this large pediatric sample. The association between BMI and cortical thinning develops after adolescence. This has implications for the nature of the relationship between brain anatomy and weight gain.

Age effects on voxel-based relaxometry used for epileptic patients.

PURPOSE: T2 voxel-based relaxometry (VBR) is a technique that allows for a quantitative, unbiased analysis of T2 relaxation time across the whole brain. Previous studies have shown that this technique is effective for clinical analysis of single patients; however, the effects of age normal age-related changes on these data were unknown. Our study was therefore designed to assess the effect of normal aging on VBR data. METHODS: A linear regression with age as a predictor of T2 was run in both a (1) whole-brain voxel-based manner to determine regions which showed significant age-related change and subsequently (2) on a selection of regions-of-interest to allow for a more detailed analysis of the trends. RESULTS: T2 estimates showed a significant increase with age in the frontal lobe white matter and a significant decrease with age in the putamen with region-of-interest and voxel-based regressions (p<0.05). There was also a general trend for T2 to decrease in inferior temporal lobe grey matter in the voxel-based regression. CONCLUSIONS: Age causes changes in T2 relaxation time in healthy control subjects, with increases being observed in frontal lobe white matter and decreases in the putamen. These changes should be accounted for when interpreting single subject VBR data.