Increased persuadability and credulity in people with corpus callosum dysgenesis

Corpus callosum dysgenesis is one of the most common congenital neurological malformations. Despite being a clear and identifiable structural alteration of the brains white matter connectivity, the impact of corpus callosum dysgenesis on cognition and behavior has remained unclear. Here we build upon past clinical observations in the literature to define the clinical phenotype of corpus callosum dysgenesis better using unadjusted and adjusted group differences compared with a neurotypical sample on a range of social and cognitive measures that have been previously reported to be impacted by a corpus callosum dysgenesis diagnosis. Those with a diagnosis of corpus callosum dysgenesis (n = 22) demonstrated significantly higher persuadability, credulity, and insensitivity to social trickery than neurotypical (n = 86) participants, after controlling for age, sex, education, autistic-like traits, social intelligence, and general cognition. To explore this further, machine learning, utilizing a set neurotypical sample for training the normative covariance structure of our psychometric variables, was used to test whether these dimensions possessed the capability to discriminate between a test-set of neurotypical and corpus callosum dysgenesis participants. We found that participants with a diagnosis of corpus callosum dysgenesis were best classed within dimension space along the same axis as persuadability, credulity, and insensitivity to social trickery after controlling for age and sex, with Leave-One-Out-Cross-Validation across 250 training-set permutations providing a mean accuracy of 71.7 percent. These results have wide-reaching implications for a) the characterization of corpus callosum dysgenesis, and b) the role of the corpus callosum in social inference.

Differential Developmental Associations of Material Hardship Exposure and Adolescent Amygdala–Prefrontal Cortex White Matter Connectivity

Accumulating literature has linked poverty to brain structure and function, particularly in affective neural regions; however, few studies have examined associations with structural connections or the importance of developmental timing of exposure. Moreover, prior neuroimaging studies have not used a proximal measure of poverty (i.e., material hardship, which assesses food, housing, and medical insecurity) to capture the lived experience of growing up in harsh economic conditions. The present investigation addressed these gaps collectively by examining the associations between material hardship (ages 1, 3, 5, 9, and 15 years) and white matter connectivity of frontolimbic structures (age of 15 years) in a low-income sample. We applied probabilistic tractography to diffusion imaging data collected from 194 adolescents. Results showed that material hardship related to amygdala–prefrontal, but not hippocampus–prefrontal or hippocampus–amygdala, white matter connectivity. Specifically, hardship during middle childhood (ages 5 and 9 years) was associated with greater connectivity between the amygdala and dorsomedial pFC, whereas hardship during adolescence (age of 15 years) was related to reduced amygdala–orbitofrontal (OFC) and greater amygdala–subgenual ACC connectivity. Growth curve analyses showed that greater increases of hardship across time were associated with both greater (amygdala–subgenual ACC) and reduced (amygdala–OFC) white matter connectivity. Furthermore, these effects remained above and beyond other types of adversity, and greater hardship and decreased amygdala–OFC connectivity were related to increased anxiety and depressive symptoms. Results demonstrate that the associations between material hardship and white matter connections differ across key prefrontal regions and developmental periods, providing support for potential windows of plasticity for structural circuits that support emotion processing.

Investigating the Relationship between White Matter Connectivity and Motivational Circuits in Subjects with Deficit Schizophrenia: A Diffusion Tensor Imaging (DTI) Study

Deficit schizophrenia is a subtype of schizophrenia presenting primary and enduring negative symptoms (NS). Although one of the most updated hypotheses indicates a relationship between NS and impaired motivation, only a few studies have investigated abnormalities of motivational circuits in subjects with deficit schizophrenia (DS). Our aim was to investigate structural connectivity within motivational circuits in DS. We analyzed diffusion tensor imaging (DTI) data from 46 subjects with schizophrenia (SCZ) and 35 healthy controls (HCs). SCZ were classified as DS (n = 9) and non-deficit (NDS) (n = 37) using the Schedule for Deficit Syndrome. The connectivity index (CI) and the Fractional Anisotropy (FA) of the connections between selected brain areas involved in motivational circuits were examined. DS, as compared with NDS and HCs, showed increased CI between the right amygdala and dorsal anterior insular cortex and increased FA of the pathway connecting the left nucleus accumbens with the posterior insular cortex. Our results support previous evidence of distinct neurobiological alterations underlying different clinical subtypes of schizophrenia. DS, as compared with NDS and HCs, may present an altered pruning process (consistent with the hyperconnectivity) in cerebral regions involved in updating the stimulus value to guide goal-directed behavior.

Left angular gyrus disconnection impairs multiplication fact retrieval

Arithmetic fact retrieval has been suggested to recruit a left-lateralized network comprising perisylvian language areas, parietal areas such as the angular gyrus (AG), and subcortical structures such as the hippocampus. However, the underlying white matter connectivity of these areas has not been evaluated systematically so far. Using simple multiplication problems, we evaluated how disconnections in parietal brain areas affected arithmetic fact retrieval following stroke. We derived disconnectivity measures by jointly considering data from n=73 patients with acute unilateral lesions in either hemisphere and a white-matter tractography atlas (HCP-842) using the Lesion Quantification Toolbox (LQT). Whole-brain voxel-based analysis indicated a left-hemispheric cluster of white matter fibers connecting the AG and superior temporal areas to be associated with a fact retrieval deficit. Subsequent analyses of direct grey-to-grey matter disconnections revealed that disconnections of additional left-hemispheric areas (e.g., between the superior temporal gyrus and parietal areas) were significantly associated with the observed fact retrieval deficit. Results imply that disconnections of parietal areas (i.e., the AG) with language-related areas (i.e., superior and middle temporal gyri) seem specifically detrimental to arithmetic fact retrieval. This suggests that arithmetic fact retrieval recruits a widespread left-hemispheric network and emphasizes the relevance of white matter connectivity for number processing.

Identifying Prepubertal Children with Risk for Suicide Using Deep Neural Network Trained on Multimodal Brain Imaging-Derived Phenotypes

Suicide is among the leading causes of death in youth worldwide. Early identification of children with high risk for suicide is key to effective screening and prevention strategies. Brain imaging can show functional or structural abnormalities related to youth suicidality, but literature is scarce. Here we tested the extent to which brain imaging is useful in predicting suicidal risk in children. In the largest to date, multi-site, multi-ethnic, epidemiological developmental samples in the US (N = 6,172; the ABCD study), we trained and validated machine learning models and deep neural networks on the multimodal brain imaging derived phenotypes (morphometry, white matter connectivity, functional activation, and connectivity) along with behavioral and self-reported psychological questionnaire data. The model trained on diffusion white matter connectomes showed the best performance (test AUC-ROC = 74.82) with a one percentage increase compared with the baseline model trained on behavioral and psychological data (test AUC-ROC = 74.16). Models trained on other MRI modalities showed similar but slightly lower performances. Model interpretation showed the important brain features involved in attention, emotion regulation, and motor coordination, such as the anterior cingulate cortex, temporal gyrus, and precentral gyrus. It further showed that the interaction of brain features with depression and impulsivity measures contributed to the optimal prediction of youth suicidality. This study demonstrates the potential utility of a multimodal brain imaging approach to youth suicidality prediction and uncovers the relationships of the psychological and multi-dimensional and multi-modal neural features to youth suicidality.

Tau deposition and structural connectivity demonstrate differential association patterns with neurocognitive tests

Tau neurofibrillary tangles have a central role in the pathogenesis of Alzheimer’s Disease (AD). Mounting evidence indicates that the propagation of tau is assisted by brain connectivity with weakened white-matter integrity along the propagation pathways. Recent advances in tau positron emission tomography tracers and diffusion magnetic resonance imaging allow the visualization of tau pathology and white-matter connectivity of the brain in vivo. The current study aims to investigate how tau deposition and structural connectivity are associated with memory function in prodromal AD. In this study, tau accumulation and structural connectivity data from 83 individuals (57 cognitively normal participants and 26 participants with mild cognitive impairment) were associated with neurocognitive test scores. Statistical analyses were performed in 70 cortical/subcortical brain regions to determine: 1. the level of association between tau and network metrics extracted from structural connectivity and 2. the association patterns of brain memory function with tau accumulation and network metrics. The results showed that tau accumulation and network metrics were correlated in early tau deposition regions. Furthermore, tau accumulation was associated with worse performance in almost all neurocognitive tests performance evaluated in the study. In comparison, decreased network connectivity was associated with declines in the delayed memory recall in Craft Stories and Benson Figure Copy. Interaction analysis indicates that tau deposition and dysconnectivity have a synergistic effect on the delayed Benson Figure Recall. Overall, our findings indicate that both tau deposition and structural dysconnectivity are associated with neurocognitive dysfunction. They also suggest that tau-PET may have better sensitivity to neurocognitive performance than diffusion MRI-derived measures of white-matter connectivity.