Intra-individual cortical networks in Anorexia Nervosa: Evidence from a longitudinal dataset.

OBJECTIVE: This work investigates cortical thickness (CT) and gyrification patterns in Anorexia Nervosa (AN) before and after short-term weight restoration using graph theory tools. METHODS: 38 female adolescents with AN underwent structural magnetic resonance imaging scans at baseline and after - on average - 3.5 months following short-term weight restoration while 53 age-matched healthy controls (HCs) were scanned once. Graph measures were compared between groups and longitudinally within the AN group. Associations with clinical measures such as age of onset, duration of illness, BMI standard deviation score (BMI-SDS), and longitudinal weight changes were tested via stepwise regression. RESULTS: Cortical thickness graphs of patients with acute AN displayed lower modularity and small-world index (SWI) than HCs. Modularity recovered after weight gain. Reduced global efficiency and SWI were observed in patients at baseline compared to HCs based on gyrification networks. Significant associations between local clustering of CT at admission and BMI-SDS, and clustering/global efficiency of gyrification and duration of illness emerged. CONCLUSIONS: Our results indicate a shift towards less organised CT networks in patients with acute AN. After weight recovery, the disarrangement seems to be partially reduced. However, longer-term follow-ups are needed to determine whether cortical organizational patterns fully return to normal.

Neural mechanisms underlying social recognition and theory of mind in adolescent patients with bulimia nervosa and transdiagnostic comparison with anorexia nervosa.

INTRODUCTION: Theory of mind (ToM) is important for social interactions and typical development and has been found to be impaired in patients with anorexia nervosa (AN) and bulimia nervosa (BN). Hypoactivation in frontotemporal brain regions seems to be the underlying neural mechanism in AN while whole-brain analyses in BN are lacking. METHODS: We used the well-validated social recognition task fMRI paradigm to assess ToM in a total of 72 female adolescents (16 BN, 18 AN and 38 matched healthy controls [HC]). RESULTS: Compared to HCBN , patients with BN showed hyperactivity during ToM-activity in the right frontal pole, middle temporal gyrus and left temporal pole and differed fundamentally from hypoactivation in these regions observed in patients with AN before and after short-term weight rehabilitation. Interaction and overlap analyses confirmed that similar regions were affected in opposite directions in both diseases. Hyperactivations in BN in the right middle temporal gyrus and right frontal pole were associated with clinical BN-severity markers binging and purging frequency. DISCUSSION: The hyperactivation in BN suggest different underlying neural mechanisms for ToM compared to AN. Hyperactivity might correspond to a different but also ineffective cognitive style in patients with BN when approaching social interactions. These important transdiagnostic differences are relevant for future brain-targeted therapeutic approaches.

Effects of Early-Life Adversity on Hippocampal Structures and Associated HPA Axis Functions.

Early-life adversity (ELA) is one of the major risk factors for serious mental and physical health risks later in life. ELA has been associated with dysfunctional neurodevelopment, especially in brain structures such as the hippocampus, and with dysfunction of the stress system, including the hypothalamic-pituitary-adrenal (HPA) axis. Children who have experienced ELA are also more likely to suffer from mental health disorders such as depression later in life. The exact interplay of aberrant neurodevelopment and HPA axis dysfunction as risks for psychopathology is not yet clear. We investigated volume differences in the bilateral hippocampus and in stress-sensitive hippocampal subfields, behavior problems, and diurnal cortisol activity in 24 children who had experienced documented ELA (including out-of-home placement) in a circumscribed duration of adversity only in their first 3 years of life in comparison to data on 25 control children raised by their biological parents. Hippocampal volumes and stress-sensitive hippocampal subfields (Cornu ammonis [CA]1, CA3, and the granule-cell layer of the dentate gyrus [GCL-DG]) were significantly smaller in children who had experienced ELA, taking psychiatric diagnoses and dimensional psychopathological symptoms into account. ELA moderated the relationship between left hippocampal volume and cortisol: in the control group, hippocampal volumes were not related to diurnal cortisol, while in ELA children, a positive linear relationship between left hippocampal volume and diurnal cortisol was present. Our findings show that ELA is associated with altered development of the hippocampus, and an altered relationship between hippocampal volume and HPA axis activity in youth in care, even after they have lived in stable and caring foster family environments for years. Altered hippocampal development after ELA could thus be associated with a risk phenotype for the development of psychiatric disorders later in life.

A multicohort, longitudinal study of cerebellar development in attention deficit hyperactivity disorder.

BACKGROUND: The cerebellum supports many cognitive functions disrupted in attention deficit hyperactivity disorder (ADHD). Prior neuroanatomic studies have been often limited by small sample sizes, inconsistent findings, and a reliance on cross-sectional data, limiting inferences about cerebellar development. Here, we conduct a multicohort study using longitudinal data, to characterize cerebellar development. METHODS: Growth trajectories of the cerebellar vermis, hemispheres and white matter were estimated using piecewise linear regression from 1,656 youth; of whom 63% had longitudinal data, totaling 2,914 scans. Four cohorts participated, all contained childhood data (age 4-12 years); two had adolescent data (12-25 years). Growth parameters were combined using random-effects meta-analysis. RESULTS: Diagnostic differences in growth were confined to the corpus medullare (cerebellar white matter). Here, the ADHD group showed slower growth in early childhood compared to the typically developing group (left corpus medullare z = 2.49, p = .01; right z = 2.03, p = .04). This reversed in late childhood, with faster growth in ADHD in the left corpus medullare (z = 2.06, p = .04). Findings held when gender, intelligence, comorbidity, and psychostimulant medication were considered. DISCUSSION: Across four independent cohorts, containing predominately longitudinal data, we found diagnostic differences in the growth of cerebellar white matter. In ADHD, slower white matter growth in early childhood was followed by faster growth in late childhood. The findings are consistent with the concept of ADHD as a disorder of the brain's structural connections, formed partly by developing cortico-cerebellar white matter tracts.

Patterns and correlates of expressed emotion, perceived criticism, and rearing style in first admitted early-onset schizophrenia spectrum disorders.

The aim of this study was to assess patterns and correlates of family variables in 31 adolescents treated for their first episode of a schizophrenia spectrum disorder (early-onset schizophrenia [EOS]). Expressed emotion, perceived criticism, and rearing style were assessed. Potential correlates were patient psychopathology, premorbid adjustment, illness duration, quality of life (QoL), sociodemographic variables, patient and caregiver "illness concept," and caregiver personality traits and support. Families were rated as critical more frequently by patients than raters (55% vs. 13%). Perceived criticism was associated with worse QoL in relationship with parents and peers. An adverse rearing style was associated with a negative illness concept in patients, particularly with less trust in their physician. Future research should examine perceived criticism as a predictor of relapse and indicator of adolescents with EOS who need extended support and treatment. Rearing style should be carefully observed because of its link with patients' illness concept and, potentially, to service engagement and medication adherence.

Morphological changes in the brain of acutely ill and weight-recovered patients with anorexia nervosa. A meta-analysis and qualitative review.

OBJECTIVE: Acute anorexia nervosa (AN) leads to reduced gray (GM) and white matter (WM) volume in the brain, which however improves again upon restoration of weight. Yet little is known about the extent and clinical correlates of these brain changes, nor do we know much about the time-course and completeness of their recovery. METHODS: We conducted a meta-analysis and a qualitative review of all magnetic resonance imaging studies involving volume analyses of the brain in both acute and recovered AN. RESULTS: We identified structural neuroimaging studies with a total of 214 acute AN patients and 177 weight-recovered AN patients. In acute AN, GM was reduced by 5.6% and WM by 3.8% compared to healthy controls (HC). Short-term weight recovery 2-5 months after admission resulted in restitution of about half of the GM aberrations and almost full WM recovery. After 2-8 years of remission GM and WM were nearly normalized, and differences to HC (GM: -1.0%, WM: -0.7%) were no longer significant, although small residual changes could not be ruled out. In the qualitative review some studies found GM volume loss to be associated with cognitive deficits and clinical prognosis. CONCLUSIONS: GM and WM were strongly reduced in acute AN. The completeness of brain volume rehabilitation remained equivocal.

Confound-leakage: confound removal in machine learning leads to leakage.

BACKGROUND: Machine learning (ML) approaches are a crucial component of modern data analysis in many fields, including epidemiology and medicine. Nonlinear ML methods often achieve accurate predictions, for instance, in personalized medicine, as they are capable of modeling complex relationships between features and the target. Problematically, ML models and their predictions can be biased by confounding information present in the features. To remove this spurious signal, researchers often employ featurewise linear confound regression (CR). While this is considered a standard approach for dealing with confounding, possible pitfalls of using CR in ML pipelines are not fully understood. RESULTS: We provide new evidence that, contrary to general expectations, linear confound regression can increase the risk of confounding when combined with nonlinear ML approaches. Using a simple framework that uses the target as a confound, we show that information leaked via CR can increase null or moderate effects to near-perfect prediction. By shuffling the features, we provide evidence that this increase is indeed due to confound-leakage and not due to revealing of information. We then demonstrate the danger of confound-leakage in a real-world clinical application where the accuracy of predicting attention-deficit/hyperactivity disorder is overestimated using speech-derived features when using depression as a confound. CONCLUSIONS: Mishandling or even amplifying confounding effects when building ML models due to confound-leakage, as shown, can lead to untrustworthy, biased, and unfair predictions. Our expose of the confound-leakage pitfall and provided guidelines for dealing with it can help create more robust and trustworthy ML models.

Recovery-Associated Resting-State Activity and Connectivity Alterations in Anorexia Nervosa.

BACKGROUND: Previous studies provided controversial insight on the impact of starvation, disease status, and underlying gray matter volume (GMV) changes on resting-state functional magnetic resonance imaging alterations in anorexia nervosa (AN). Here, we adapt a combined longitudinal and cross-sectional approach to disentangle the effects of these factors on resting-state alterations in AN. METHODS: Overall, 87 female subjects were included in the study: adolescent patients with acute AN scanned at inpatient admission (n = 22, mean age 15.3 years) and at discharge (n = 21), patients who recovered from AN (n = 21, mean age 22.3 years), and two groups of healthy age-matched control subjects (both n = 22, mean age 16.0 and 22.5 years, respectively). Whole-brain measures of resting-state activity and functional connectivity were computed (network-based statistics, global correlation, integrated local correlation, and fractional amplitude of low-frequency fluctuations) to assess resting-state functional magnetic resonance imaging alterations over the course of AN treatment before and after controlling for underlying GMV. RESULTS: Patients with acute AN displayed strong and widespread prefrontal, sensorimotor, parietal, temporal, precuneal, and insular reductions of resting-state connectivity and activity. All alterations were independent of GMV and were largely normalized in short-term recovered AN and absent in long-term recovered patients. CONCLUSIONS: Resting-state functional magnetic resonance imaging alterations in AN constitute acute and GMV-independent, presumably starvation-related, phenomena. The majority of alterations found here normalized over the course of recovery without evidence for possible preexisting trait- or remaining "scar" effects.

Comprehensive verbal fluency features predict executive function performance.

Semantic verbal fluency (sVF) tasks are commonly used in clinical diagnostic batteries as well as in a research context. When performing sVF tasks to assess executive functions (EFs) the sum of correctly produced words is the main measure. Although previous research indicates potentially better insights into EF performance by the use of finer grained sVF information, this has not yet been objectively evaluated. To investigate the potential of employing a finer grained sVF feature set to predict EF performance, healthy monolingual German speaking participants (n = 230) were tested with a comprehensive EF test battery and sVF tasks, from which features including sum scores, error types, speech breaks and semantic relatedness were extracted. A machine learning method was applied to predict EF scores from sVF features in previously unseen subjects. To investigate the predictive power of the advanced sVF feature set, we compared it to the commonly used sum score analysis. Results revealed that 8 / 14 EF tests were predicted significantly using the comprehensive sVF feature set, which outperformed sum scores particularly in predicting cognitive flexibility and inhibitory processes. These findings highlight the predictive potential of a comprehensive evaluation of sVF tasks which might be used as diagnostic screening of EFs.