Errormonitoringbytheposteriormedialfrontalcortex(pMFC)hasbeenlinkedtopost-errorbehavioraladaptationeffectsandcognitivecontrol dynamics in lateral prefrontal cortex (LPFC). It remains unknown, however, whether control adjustments following errors produce post-error behavioral adjustments (PEBAs) by inhibiting inappropriate responses or facilitating goal-directed ones. Here we used functional magnetic resonance imaging to investigate the hemodynamic correlates of PEBAs in a stimulus-response compatibility task. Our task was designed to test whetherPEBAsareimplementedbysuppressingmotorresponsesprimedbyirrelevantstimulusfeatures(facelocation),redirectingattentionto relevant features (face gender), or both or neither of these possibilities. Independent of PEBAs, error-related pMFC activation was followed by post-error recruitment of prefrontal and parietal control regions and, crucially, both (1) suppressed response-related activity in sensorimotor cortex and (2) enhanced target processing in face-sensitive sensory cortex ("fusiform face area"). More importantly, by investigating the covariation between post-error hemodynamic activity and individual differences in PEBAs, we showed that modulation of task-related motor and sensory processing was dependent on whether participants produced generally slower responses ("post-error slowing"; PES) or selectively reduced interference effects ("post-error reduction of interference"; PERI), respectively. Each of these behaviorally dependent effects was mediated by distinct LPFC control mechanisms (PES: inferior frontal junction; PERI: superior frontal sulcus). While establishing relationships between PEBAs and cognitive control, our findings suggest that the neural architecture underlying sequential behavioral adaptation may be determined primarily by how control is executed by the individual when adjustments are needed.

Altered structural brain asymmetry in autism spectrum disorder (ASD) has been reported. However, findings have been inconsistent, likely due to limited sample sizes. Here we investigated 1,774 individuals with ASD and 1,809 controls, from 54 independent data sets of the ENIGMA consortium. ASD was significantly associated with alterations of cortical thickness asymmetry in mostly medial frontal, orbitofrontal, cingulate and inferior temporal areas, and also with asymmetry of orbitofrontal surface area. These differences generally involved reduced asymmetry in individuals with ASD compared to controls. Furthermore, putamen volume asymmetry was significantly increased in ASD. The largest case-control effect size was Cohen’s d = −0.13, for asymmetry of superior frontal cortical thickness. Most effects did not depend on age, sex, IQ, severity or medication use. Altered lateralized neurodevelopment may therefore be a feature of ASD, affecting widespread brain regions with diverse functions. Large-scale analysis was necessary to quantify subtle alterations of brain structural asymmetry in ASD.

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Structural brain anomalies in AN as expressed in CT and subcortical volume are primarily the consequence of malnutrition and unlikely to reflect premorbid trait markers or permanent scars, but longitudinal data are needed.

Anorexia nervosa (AN) is a serious eating disorder characterized by self-starvation and extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual brain scans, and AN may be a valuable model disorder to study structural neuroplasticity. Structural magnetic resonance imaging studies have found reduced gray matter volume and cortical thinning in acutely underweight patients to normalize following successful treatment. However, some well-controlled studies have found regionally greater gray matter and persistence of structural alterations following long-term recovery. Findings from diffusion tensor imaging studies of white matter integrity and connectivity are also inconsistent. Furthermore, despite the severity of AN, the number of existing structural neuroimaging studies is still relatively low, and our knowledge of the underlying cellular and molecular mechanisms for macrostructural brain changes is rudimentary. We critically review the current state of structural neuroimaging in AN and discuss the potential neurobiological basis of structural brain alterations in the disorder, highlighting impediments to progress, recent developments, and promising future directions. In particular, we argue for the utility of more standardized data collection, adopting a connectomics approach to understanding brain network architecture, employing advanced magnetic resonance imaging methods that quantify biomarkers of brain tissue microstructure, integrating data from multiple imaging modalities, strategic longitudinal observation during weight restoration, and large-scale data pooling. Our overarching objective is to motivate carefully controlled research of brain structure in eating disorders, which will ultimately help predict therapeutic response and improve treatment.