Characterizing cognitive subtypes in schizophrenia using cortical curvature.

Cognitive deficits are a core symptom of schizophrenia, but research on their neural underpinnings has been challenged by the heterogeneity in deficits' severity among patients. Here, we address this issue by combining logistic regression and random forest to classify two neuropsychological profiles of patients with high (HighCog) and low (LowCog) cognitive performance in two independent samples. We based our analysis on the cortical features grey matter volume (VOL), cortical thickness (CT), and mean curvature (MC) of N = 57 patients (discovery sample) and validated the classification in an independent sample (N = 52). We investigated which cortical feature would yield the best classification results and expected that the 10 most important features would include frontal and temporal brain regions. The model based on MC had the best performance with area under the curve (AUC) values of 76% and 73%, and identified fronto-temporal and occipital brain regions as the most important features for the classification. Moreover, subsequent comparison analyses could reveal significant differences in MC of single brain regions between the two cognitive profiles. The present study suggests MC as a promising neuroanatomical parameter for characterizing schizophrenia cognitive subtypes.

Functional connectivity MRI provides an imaging correlate for chimeric antigen receptor T-cell-associated neurotoxicity.

Background: Treatment of hematological malignancies with chimeric antigen receptor modified T cells (CART) is highly efficient, but often limited by an immune effector cell-associated neurotoxicity syndrome (ICANS). As conventional MRI is often unremarkable during ICANS, we aimed to examine whether resting-state functional MRI (rsfMRI) is suitable to depict and quantify brain network alterations underlying ICANS in the individual patient. Methods: The dysconnectivity index (DCI) based on rsfMRI was longitudinally assessed in systemic lymphoma patients and 1 melanoma patient during ICANS and before or after clinical resolution of ICANS. Results: Seven lymphoma patients and 1 melanoma patient (19-77 years; 2 female) were included. DCI was significantly increased during ICANS with normalization after recovery (P = .0039). Higher ICANS grades were significantly correlated with increased DCI scores (r = 0.7807; P = .0222). DCI increase was most prominent in the inferior frontal gyrus and the frontal operculum (ie, Broca's area) and in the posterior parts of the superior temporal gyrus and the temporoparietal junction (ie, Wernicke's area) of the language-dominant hemisphere, thus reflecting the major clinical symptoms of nonfluent dysphasia and dyspraxia. Conclusions: RsfMRI-based DCI might be suitable to directly quantify the severity of ICANS in individual patients undergoing CAR T-transfusion. Besides ICANS, DCI seems a promising diagnostic tool to quantify functional brain network alterations during encephalopathies of different etiologies, in general.

Variable functional connectivity architecture of the preterm human brain: Impact of developmental cortical expansion and maturation.

Functional connectivity (FC) is known to be individually unique and to reflect cognitive variability. Although FC can serve as a valuable correlate and potential predictor of (patho-) physiological nervous function in high-risk constellations, such as preterm birth, templates for individualized FC analysis are lacking, and knowledge about the capacity of the premature brain to develop FC variability is limited. In a cohort of prospectively recruited, preterm-born infants undergoing magnetic resonance imaging close to term-equivalent age, we show that the overall pattern could be reliably detected with a broad range of interindividual FC variability in regions of higher-order cognitive functions (e.g., association cortices) and less interindividual variability in unimodal regions (e.g., visual and motor cortices). However, when comparing the preterm and adult brains, some brain regions showed a marked shift in variability toward adulthood. This shift toward greater variability was strongest in cognitive networks like the attention and frontoparietal networks and could be partially predicted by developmental cortical expansion. Furthermore, FC variability was reflected by brain tissue characteristics indicating cortical maturation. Brain regions with high functional variability (e.g., the inferior frontal gyrus and temporoparietal junction) displayed lower cortical maturation at birth compared with somatosensory cortices. In conclusion, the overall pattern of interindividual variability in FC is already present preterm; however, some brain regions show increased variability toward adulthood, identifying characteristic patterns, such as in cognitive networks. These changes are related to postnatal cortical expansion and maturation, allowing for environmental and developmental factors to translate into marked individual differences in FC.