NIHR Maudsley Dementia Biomedical Research Unit

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

CONTEXT: Although differences in clinical characteristics exist between major depressive disorder (MDD) and bipolar disorder (BD), consistent structural brain abnormalities that distinguish the disorders have not been identified. OBJECTIVES: To investigate structural brain changes in MDD using meta-analysis of primary studies; assess the effects of medication, demographic, and clinical variables; and compare the findings with those of a meta-analysis of studies on BD. DATA SOURCES: The MEDLINE, EMBASE, and PsycINFO databases were searched for studies from January 1, 1980, to February 2, 2010. STUDY SELECTION: Two hundred twenty-five studies that used magnetic resonance imaging or x-ray computed tomography to compare brain structure in patients with MDD with that of controls were included in an online database, and 143 that measured common brain structures were selected for meta-analysis. DATA EXTRACTION: Twenty-five variables, including demographic and clinical data, were extracted from each study, when available. For the meta-analysis, mean structure size and standard deviation were extracted for continuous variables, and the proportion of patients and controls with an abnormality in brain structure was extracted for categorical variables. DATA SYNTHESIS: Compared with the structure of a healthy brain, MDD was associated with lateral ventricle enlargement; larger cerebrospinal fluid volume; and smaller volumes of the basal ganglia, thalamus, hippocampus, frontal lobe, orbitofrontal cortex, and gyrus rectus. Patients during depressive episodes had significantly smaller hippocampal volume than patients during remission. Compared with BD patients, those with MDD had reduced rates of deep white matter hyperintensities, increased corpus callosum cross-sectional area, and smaller hippocampus and basal ganglia. Both disorders were associated with increased lateral ventricle volume and increased rates of subcortical gray matter hyperintensities compared with healthy controls. CONCLUSIONS: The meta-analyses revealed structural brain abnormalities in MDD that are distinct from those observed in BD. These findings may aid investigators attempting to discriminate mood disorders using structural magnetic resonance imaging data.

Psychosis is a heterogeneous psychiatric condition for which a multitude of risk and protective factors have been suggested. This umbrella review aimed to classify the strength of evidence for the associations between each factor and psychotic disorders whilst controlling for several biases. The Web of Knowledge database was searched to identify systematic reviews and meta-analyses of observational studies which examined associations between socio-demographic, parental, perinatal, later factors or antecedents and psychotic disorders, and which included a comparison group of healthy controls, published from 1965 to January 31, 2017. The literature search and data extraction followed PRISMA and MOOSE guidelines. The association between each factor and ICD or DSM diagnoses of non-organic psychotic disorders was graded into convincing, highly suggestive, suggestive, weak, or non-significant according to a standardized classification based on: number of psychotic cases, random-effects p value, largest study 95% confidence interval, heterogeneity between studies, 95% prediction interval, small study effect, and excess significance bias. In order to assess evidence for temporality of association, we also conducted sensitivity analyses restricted to data from prospective studies. Fifty-five meta-analyses or systematic reviews were included in the umbrella review, corresponding to 683 individual studies and 170 putative risk or protective factors for psychotic disorders. Only the ultra-high-risk state for psychosis (odds ratio, OR=9.32, 95% CI: 4.91-17.72) and Black-Caribbean ethnicity in England (OR=4.87, 95% CI: 3.96-6.00) showed convincing evidence of association. Six factors were highly suggestive (ethnic minority in low ethnic density area, second generation immigrants, trait anhedonia, premorbid IQ, minor physical anomalies, and olfactory identification ability), and nine were suggestive (urbanicity, ethnic minority in high ethnic density area, first generation immigrants, North-African immigrants in Europe, winter/spring season of birth in Northern hemisphere, childhood social withdrawal, childhood trauma, Toxoplasma gondii IgG, and non-right handedness). When only prospective studies were considered, the evidence was convincing for ultra-high-risk state and suggestive for urbanicity only. In summary, this umbrella review found several factors to be associated with psychotic disorders with different levels of evidence. These risk or protective factors represent a starting point for further etiopathological research and for the improvement of the prediction of psychosis.

CONTEXT: Despite 25 years of structural imaging in bipolar disorder, brain regions affected in the disorder are ill defined. OBJECTIVES: To use meta-analytical techniques to investigate structural brain changes in bipolar disorder and to assess the effect of medication use and demographic and clinical variables. DATA SOURCES: The MEDLINE, EMBASE, and PsycINFO databases were searched from 1980-2007 for studies using magnetic resonance imaging or x-ray computed tomography to compare brain structure in patients with bipolar disorder and controls. STUDY SELECTION: We identified 1471 unique publications from which 141 studies were included in a database and 98 were selected for meta-analysis. DATA EXTRACTION: Twenty-six demographic and clinical variables were extracted from each study where available. For the meta-analysis, mean structure size and standard deviation were extracted for continuous variables, and numbers of patients and controls with an abnormality were extracted for binary variables. DATA SYNTHESIS: Bipolar disorder was associated with lateral ventricle enlargement (effect size = 0.39; 95% confidence interval, 0.24-0.55; P = 8 x 10(-7)) and increased rates of deep white matter hyperintensities (odds ratio = 2.49; 95% confidence interval, 1.64-3.79; P = 2 x 10(-5)) but not periventricular hyperintensities. Gray matter volume increased among patients when the proportion of patients using lithium increased (P = .004). Calculations from this meta-analysis show current imaging studies (which typically examine 8 regions) have a 34% chance of making a type I error. Type II errors are also appreciable (for example, 70% when measuring the lateral ventricular volume in a typical study involving 25 patients and 33 controls). CONCLUSIONS: The meta-analyses revealed robust but regionally nonspecific changes of brain structure in bipolar disorder. Individual studies will remain underpowered unless sample size is increased or improvements in phenotypic selection and imaging methods are made to reduce within-study heterogeneity. The provision of online databases, as illustrated herein, may facilitate a more refined design and analysis of structural imaging data sets in bipolar disorder.

Myelination, the elaboration of myelin surrounding neuronal axons, is essential for normal brain function. The development of the myelin sheath enables rapid synchronized communication across the neural systems responsible for higher order cognitive functioning. Despite this critical role, quantitative visualization of myelination in vivo is not possible with current neuroimaging techniques including diffusion tensor and structural magnetic resonance imaging (MRI). Although these techniques offer insight into structural maturation, they reflect several different facets of development, e.g., changes in axonal size, density, coherence, and membrane structure; lipid, protein, and macromolecule content; and water compartmentalization. Consequently, observed signal changes are ambiguous, hindering meaningful inferences between imaging findings and metrics of learning, behavior or cognition. Here we present the first quantitative study of myelination in healthy human infants, from 3 to 11 months of age. Using a new myelin-specific MRI technique, we report a spatiotemporal pattern beginning in the cerebellum, pons, and internal capsule; proceeding caudocranially from the splenium of the corpus callosum and optic radiations (at 3-4 months); to the occipital and parietal lobes (at 4-6 months); and then to the genu of the corpus callosum and frontal and temporal lobes (at 6-8 months). Our results also offer preliminary evidence of hemispheric myelination rate differences. This work represents a significant step forward in our ability to appreciate the fundamental process of myelination, and provides the first ever in vivo visualization of myelin maturation in healthy human infancy.

Anxiety disorders are common, complex psychiatric disorders with twin heritabilities of 30–60%. We conducted a genome-wide association study of Lifetime Anxiety Disorder (ncase = 25 453, ncontrol = 58 113) and an additional analysis of Current Anxiety Symptoms (ncase = 19 012, ncontrol = 58 113). The liability scale common variant heritability estimate for Lifetime Anxiety Disorder was 26%, and for Current Anxiety Symptoms was 31%. Five novel genome-wide significant loci were identified including an intergenic region on chromosome 9 that has previously been associated with neuroticism, and a locus overlapping the BDNF receptor gene, NTRK2. Anxiety showed significant positive genetic correlations with depression and insomnia as well as coronary artery disease, mirroring findings from epidemiological studies. We conclude that common genetic variation accounts for a substantive proportion of the genetic architecture underlying anxiety.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. This makes the neuroanatomy of autism inherently difficult to describe. Here, we demonstrate how a multiparameter classification approach can be used to characterize the complex and subtle structural pattern of gray matter anatomy implicated in adults with ASD, and to reveal spatially distributed patterns of discriminating regions for a variety of parameters describing brain anatomy. A set of five morphological parameters including volumetric and geometric features at each spatial location on the cortical surface was used to discriminate between people with ASD and controls using a support vector machine (SVM) analytic approach, and to find a spatially distributed pattern of regions with maximal classification weights. On the basis of these patterns, SVM was able to identify individuals with ASD at a sensitivity and specificity of up to 90% and 80%, respectively. However, the ability of individual cortical features to discriminate between groups was highly variable, and the discriminating patterns of regions varied across parameters. The classification was specific to ASD rather than neurodevelopmental conditions in general (e.g., attention deficit hyperactivity disorder). Our results confirm the hypothesis that the neuroanatomy of autism is truly multidimensional, and affects multiple and most likely independent cortical features. The spatial patterns detected using SVM may help further exploration of the specific genetic and neuropathological underpinnings of ASD, and provide new insights into the most likely multifactorial etiology of the condition.

CONTEXT: Blood-based analytes may be indicators of pathological processes in Alzheimer disease (AD). OBJECTIVE: To identify plasma proteins associated with AD pathology using a combined proteomic and neuroimaging approach. DESIGN: Discovery-phase proteomics to identify plasma proteins associated with correlates of AD pathology. Confirmation and validation using immunodetection in a replication set and an animal model. SETTING: A multicenter European study (AddNeuroMed) and the Baltimore Longitudinal Study of Aging. PARTICIPANTS: Patients with AD, subjects with mild cognitive impairment, and healthy controls with standardized clinical assessments and structural neuroimaging. MAIN OUTCOME MEASURES: Association of plasma proteins with brain atrophy, disease severity, and rate of clinical progression. Extension studies in humans and transgenic mice tested the association between plasma proteins and brain amyloid. RESULTS: Clusterin/apolipoprotein J was associated with atrophy of the entorhinal cortex, baseline disease severity, and rapid clinical progression in AD. Increased plasma concentration of clusterin was predictive of greater fibrillar amyloid-beta burden in the medial temporal lobe. Subjects with AD had increased clusterin messenger RNA in blood, but there was no effect of single-nucleotide polymorphisms in the gene encoding clusterin with gene or protein expression. APP/PS1 transgenic mice showed increased plasma clusterin, age-dependent increase in brain clusterin, as well as amyloid and clusterin colocalization in plaques. CONCLUSIONS: These results demonstrate an important role of clusterin in the pathogenesis of AD and suggest that alterations in amyloid chaperone proteins may be a biologically relevant peripheral signature of AD.

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD. Genetic analyses of depression based on minimal phenotyping identify nonspecific genetic risk factors shared between major depressive disorder (MDD) and other psychiatric conditions, suggesting that this approach may have limited ability to identify pathways specific to MDD.

We interrogate the joint genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic and molecular genetic levels of analysis. We identify four broad factors (neurodevelopmental, compulsive, psychotic and internalizing) that underlie genetic correlations among the disorders and test whether these factors adequately explain their genetic correlations with biobehavioral traits. We introduce stratified genomic structural equation modeling, which we use to identify gene sets that disproportionately contribute to genetic risk sharing. This includes protein-truncating variant-intolerant genes expressed in excitatory and GABAergic brain cells that are enriched for genetic overlap across disorders with psychotic features. Multivariate association analyses detect 152 (20 new) independent loci that act on the individual factors and identify nine loci that act heterogeneously across disorders within a factor. Despite moderate-to-high genetic correlations across all 11 disorders, we find little utility of a single dimension of genetic risk across psychiatric disorders either at the level of biobehavioral correlates or at the level of individual variants. Joint analysis of 11 major psychiatric disorders identifies four broad factor underlying genetic correlations among the disorders. Association analyses detect 152 loci acting on these factors and identify 9 loci that act heterogeneously across disorders.

Summary Patients who recover from an acute episode of psychosis are frequently prescribed prophylactic antipsychotics for many years, especially if they are diagnosed as having schizophrenia. However, there is a dearth of evidence concerning the long-term effectiveness of this practice, and growing concern over the cumulative effects of antipsychotics on physical health and brain structure. Although controversy remains concerning some of the data, the wise psychiatrist should regularly review the benefit to each patient of continuing prophylactic antipsychotics against the risk of side-effects and loss of effectiveness through the development of supersensitivity of the dopamine D 2 receptor. Psychiatrists should work with their patients to slowly reduce the antipsychotic to the lowest dose that prevents the return of distressing symptoms. Up to 40% of those whose psychosis remits after a first episode should be able to achieve a good outcome in the long term either with no antipsychotic medication or with a very low dose.

CONTEXT: Neuroimaging studies of brain anatomy in autism spectrum disorder (ASD) have mostly been based on measures of cortical volume (CV). However, CV is a product of 2 distinct parameters, cortical thickness (CT) and surface area (SA), that in turn have distinct genetic and developmental origins. OBJECTIVE: To investigate regional differences in CV, SA, and CT as well as their relationship in a large and well-characterized sample of men with ASD and matched controls. DESIGN: Multicenter case-control design using quantitative magnetic resonance imaging. SETTING: Medical Research Council UK Autism Imaging Multicentre Study. PARTICIPANTS: A total of 168 men, 84 diagnosed as having ASD and 84 controls who did not differ significantly in mean (SD) age (26 [7] years vs 28 [6] years, respectively) or full-scale IQ (110 [14] vs 114 [12], respectively). MAIN OUTCOME MEASURES: Between-group differences in CV, SA, and CT investigated using a spatially unbiased vertex-based approach; the degree of spatial overlap between the differences in CT and SA; and their relative contribution to differences in regional CV. RESULTS: Individuals with ASD differed from controls in all 3 parameters. These mainly consisted of significantly increased CT within frontal lobe regions and reduced SA in the orbitofrontal cortex and posterior cingulum. These differences in CT and SA were paralleled by commensurate differences in CV. The spatially distributed patterns for CT and SA were largely nonoverlapping and shared only about 3% of all significantly different locations on the cerebral surface. CONCLUSIONS: Individuals with ASD have significant differences in CV, but these may be underpinned by (separable) variations in its 2 components, CT and SA. This is of importance because both measures result from distinct developmental pathways that are likely modulated by different neurobiological mechanisms. This finding may provide novel targets for future studies into the etiology of the condition and a new way to fractionate the disorder.

Preventing psychosis in patients at clinical high risk may be a promising avenue for pre-emptively ameliorating outcomes of the most severe psychiatric disorder. However, information on how each preventive intervention fares against other currently available treatment options remains unavailable. The aim of the current study was to quantify the consistency and magnitude of effects of specific preventive interventions for psychosis, comparing different treatments in a network meta-analysis. PsycINFO, Web of Science, Cochrane Central Register of Controlled Trials, and unpublished/grey literature were searched up to July 18, 2017, to identify randomized controlled trials conducted in individuals at clinical high risk for psychosis, comparing different types of intervention and reporting transition to psychosis. Two reviewers independently extracted data. Data were synthesized using network meta-analyses. The primary outcome was transition to psychosis at different time points and the secondary outcome was treatment acceptability (dropout due to any cause). Effect sizes were reported as odds ratios and 95% confidence intervals (CIs). Sixteen studies (2,035 patients, 57% male, mean age 20.1 years) reported on risk of transition. The treatments tested were needs-based interventions (NBI); omega-3 + NBI; ziprasidone + NBI; olanzapine + NBI; aripiprazole + NBI; integrated psychological interventions; family therapy + NBI; D-serine + NBI; cognitive behavioural therapy, French & Morrison protocol (CBT-F) + NBI; CBT-F + risperidone + NBI; and cognitive behavioural therapy, van der Gaag protocol (CBT-V) + CBT-F + NBI. The network meta-analysis showed no evidence of significantly superior efficacy of any one intervention over the others at 6 and 12 months (insufficient data were available after 12 months). Similarly, there was no evidence for intervention differences in acceptability at either time point. Tests for inconsistency were non-significant and sensitivity analyses controlling for different clustering of interventions and biases did not materially affect the interpretation of the results. In summary, this study indicates that, to date, there is no evidence that any specific intervention is particularly effective over the others in preventing transition to psychosis. Further experimental research is needed.

Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (r g = 0.24, p = 1.8 10 -7 versus r g = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 10 -4 ). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.

OBJECTIVE: To determine dosing and side effects of dihydroergotamine as they affect outcomes in primary headache disorders. METHODS: We audited our use of dihydroergotamine for inpatient management of disabling primary headache, focusing on the commonly treated problems. RESULTS: Of patients interviewed, 114 had chronic migraine, 38 had cluster headache, and 11 had new daily persistent headache (NDPH). The mean time to follow-up for the entire cohort was 11 months. The data suggest that IV dihydroergotamine given over 5 days produces improvement in headache and disability in patients with migraine more than shorter courses. It does so with a cumulative effect after discharge up to a month. Giving more dihydroergotamine predicts a greater pain-free rate. Patients with cluster headache benefit from IV dihydroergotamine. In patients with NDPH, only those with migrainous symptoms responded and in that group the response was less robust compared with that seen in the chronic migraine cohort. CONCLUSIONS: Intravenous dihydroergotamine is well-tolerated, and longer treatments produce a better outcome. Nausea is the most common adverse effect, and its control is associated with a better outcome.

Abstract Depression is a leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Here, using non-overlapping Psychiatric Genomics Consortium (PGC) datasets as a reference, we estimate polygenic risk scores for depression (depression-PRS) in a discovery ( N = 10,674) and replication ( N = 11,214) imaging sample from UK Biobank. We report 77 traits that are significantly associated with depression-PRS, in both discovery and replication analyses. Mendelian Randomisation analysis supports a potential causal effect of liability to depression on brain white matter microstructure ( β : 0.125 to 0.868, p FDR < 0.043). Several behavioural traits are also associated with depression-PRS ( β : 0.014 to 0.180, p FDR : 0.049 to 1.28 × 10 −14 ) and we find a significant and positive interaction between depression-PRS and adverse environmental exposures on mental health outcomes. This study reveals replicable associations between depression-PRS and white matter microstructure. Our results indicate that white matter microstructure differences may be a causal consequence of liability to depression.

BACKGROUND: Conversion disorder is largely managed by neurologists, for whom it presents great challenges to understanding and management. This study aimed to quantify these challenges, examining how neurologists understand conversion disorder, and what they tell their patients. METHODS: A postal survey of all consultant neurologists in the UK registered with the Association of British Neurologists. RESULTS: 349 of 591 practising consultant neurologists completed the survey. They saw conversion disorder commonly. While they endorsed psychological models for conversion, they diagnosed it according to features of the clinical presentation, most importantly inconsistency and abnormal illness behaviour. Most of the respondents saw feigning as entangled with conversion disorder, with a minority seeing one as a variant of the other. They were quite willing to discuss psychological factors as long as the patient was receptive but were generally unwilling to discuss feigning even though they saw it as their responsibility. Those who favoured models in terms of feigning were older, while younger, female neurologists preferred psychological models, believed conversion would one day be understood neurologically and found communicating with their conversion patients easier than it had been in the past. DISCUSSION: Neurologists accept psychological models for conversion disorder but do not employ them in their diagnosis; they do not see conversion as clearly different from feigning. This may be changing as younger, female neurologists endorse psychological views more clearly and find it easier to discuss with their patients.

State-of-the-art research on brain asymmetry, explained from molecular to clinical levels. Hemispheric asymmetry is one of the basic aspects of perception and cognitive processing. The different functions of the left and right hemispheres of the brain have been studied with renewed interest in recent years, as scholars explore applications to new areas, new measuring techniques, and new theoretical approaches. This volume provides a comprehensive view of the latest research in brain asymmetry, offering not only recent empirical and clinical findings but also a coherent theoretical approach to the subject. In chapters that report on the field at levels from the molecular to the clinical, leading researchers address such topics as the evolution and genetics of brain asymmetry; animal models; findings from structural and functional neuroimaging techniques and research; sex differences and hormonal effects; sleep asymmetry; cognitive asymmetry in visual and auditory perception; and auditory laterality and speech perception, memory, and asymmetry in the context of developmental, neurological, and psychiatric disorders. Contributors Katrin Amunts, Ulrike Bayer, Alfredo Brancucci, Vince D. Calhoun, Maria Casagrande, Marco Catani, Michael C. Corballis, Patricia E. Cowell, Timothy J. Crow, Tom Eichele, Stephanie Forkel, Patrick J. Gannon, Isabelle George, Onur Güntürkün, Heikki Hämäläinen, Markus Hausmann, Joseph B. Hellige, Kenneth Hugdahl, Masud Husain, Grégoria Kalpouzos, Bruno Laeng, Martina Manns, Chikashi Michimata, Deborah W. Moncrieff, Lars Nyberg, Godfrey Pearlson, Stefan Pollmann, Victoria Singh-Curry, Iris E.C. Sommer, Tao Sun, Nathan Swanson, Fiia Takio, Michel Thiebaut de Schotten, René Westerhausen

OBJECTIVE: Childhood maltreatment is associated with various cognitive deficits, including inhibitory deficits and hypersensitivity to negative feedback. The authors used a stop-signal task to investigate the association between severe childhood abuse and inhibitory and error processing brain activation in medication-naive, drug-free young people with and without severe childhood abuse, controlling for psychiatric comorbidities by including a psychiatric control group. METHOD: Using functional MRI, the authors compared brain activation in 22 age- and gender-matched young people exposed to severe childhood abuse, 17 psychiatric comparison subjects matched for psychiatric diagnoses with the abused group, and 27 healthy comparison subjects during an individually adjusted tracking stop-signal task designed to elicit 50% inhibition failures. RESULTS: During failed inhibition, the childhood abuse group showed increased brain activation relative to the healthy comparison group in typical error processing regions of the dorsomedial frontal cortex, including the left and right presupplementary and supplementary motor area and anterior cingulate cortex. The increased activation in a smaller cluster in the supplementary motor area survived comparison with the psychiatric comparison group. No group differences in activation were observed for successful inhibition. CONCLUSIONS: The findings suggest that severe childhood abuse is associated with abnormally increased activation in classical dorsomedial frontal error-processing regions; furthermore, the increased activation in the supplementary motor area was abuse specific. However, childhood abuse was not associated with inhibitory dysfunction. Increased sensitivity of error-detection networks in participants in the childhood abuse group may be due to the constant need to monitor their own actions in order to avoid painful mistakes, which are often associated with harsh punishment in abusive settings.