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Phenotyping of major depressive disorder (MDD) in research can vary from study to study, which, together with heterogeneity of the disorder, may contribute to the inconsistent associations with various risk factors including neuroimaging features. These aspects also potentially underlie previous problems with machine learning methods using imaging data to inform predictive biomarkers. In this study we therefore aimed to examine the classification accuracy of structural and functional connectomes across different depressive phenotypes, including separating MDD subgroups into those with and without early childhood adversity (one of the largest risk factors for MDD associated with brain development). We applied logistic ridge regression to classify control and MDD participants defined according to six different MDD definitions in a large community-based sample (N= 14, 507). We used brain connectomic data based on six structural and two functional network weightings and conducted a comprehensive analysis to (i) explore how well different connectome modalities predict different MDD phenotypes commonly used in research, (ii) investigate whether stratification of MDD based on the presence or absence of early childhood adversity (measured with the childhood trauma questionnaire) can improve prediction accuracies, and (iii) identify important predictive features that are consistent across MDD phenotypes. We find that functional connectomes consistently outperform structural connectomes as features for MDD classification across phenotypes. Highest accuracy of 61.06% (chance level 50.0%) was achieved when predicting the Currently Depressed phenotype (i.e. the phenotype defined by the presence of more than five symptoms of depression in the past two weeks) with features based on partial correlation functional connectomes. Accuracy of classifying Currently Depressed participants with added CTQ threshold criterion rose to 65.74%. Application of the Jaccard index to assess predictive feature overlap indicated that there were neurobiological differences between MDD patients with and without childhood adversity. Further to that, analysis of predictive features for different MDD phenotypes with binomial tests revealed sensorimotor and visual functional subnetworks as consistently important for prediction. Our results provide the basis for future research, and indicate that differences in sensorimotor and visual subnetworks may serve as important biomarkers of MDD.

Individuals with schizophrenia show impairments in associative learning. One well-studied, quantifiable form of associative learning is Pavlovian fear conditioning. However, to date, studies of fear conditioning in schizophrenia have been inconclusive, possibly because they lacked sufficient power. To address this issue, we pooled data from four independent fear conditioning studies that included a total of 77 individuals with schizophrenia and 74 control subjects. Skin conductance responses (SCRs) to stimuli that were paired (the CS + ) or not paired (CS−) with an aversive, unconditioned stimulus were measured, and the success of acquisition of differential conditioning (the magnitude of CS + vs. CS− SCRs) and responses to CS + and CS− separately were assessed. We found that acquisition of differential conditioned fear responses was significantly lower in individuals with schizophrenia than in healthy controls (Cohen’s d = 0.53). This effect was primarily related to a significantly higher response to the CS− stimulus in the schizophrenia compared to the control group. Moreover, the magnitude of this response to the CS− in the schizophrenia group was correlated with the severity of delusional ideation (p = 0.006). Other symptoms or antipsychotic dose were not associated with fear conditioning measures. In conclusion, individuals with schizophrenia who endorse delusional beliefs may be over-responsive to neutral stimuli during fear conditioning. This finding is consistent with prior models of abnormal associative learning in psychosis.

There is increasing interest in using data-driven unsupervised methods to identify structural underpinnings of common mental illnesses, including Major Depressive Disorder (MDD) and associated traits such as cognition. However, studies are often limited to severe clinical cases with small sample sizes and most do not include replication. Here, we examine two relatively large samples with structural magnetic resonance imaging (MRI), measures of lifetime MDD and cognitive variables: Generation Scotland (GS subsample, N = 980), and UK Biobank (UKB, N = 8900); for discovery and replication, using an exploratory approach. Regional measures of FreeSurfer derived cortical thickness (CT), cortical surface area (CSA), cortical volume (CV) and subcortical volume (subCV) were input into a clustering process, controlling for common covariates. The main analysis steps involved constructing participant K-nearest neighbour graphs, and graph partitioning with Markov Stability to determine optimal clustering of participants. Resultant clusters were i) checked whether they were replicated in an independent cohort, and ii) tested for associations with depression status, and cognitive measures. Participants separated into two clusters based on structural brain measurements in GS subsample, with large Cohen's d effect sizes between clusters in higher order cortical regions, commonly associated with executive function and decision making. Clustering was replicated in the UKB sample, with high correlations of cluster effect sizes for CT, CSA, CV and subCV between cohorts across regions. The identified clusters were not significantly different with respect to MDD case-control status in either cohort (GS subsample: pFDR = 0.2239 - 0.6585; UKB: pFDR = 0.2003 - 0.7690). Significant differences in general cognitive ability were, however, found between the clusters for both datasets; for CSA, CV, subCV (GS subsample: d = 0.2529 - 0.3490, pFDR < 0.005; UKB: d = 0.0868 - 0.1070, pFDR < 0.005). Our results suggest that there are replicable natural groupings of participants based on cortical and subcortical brain measures, which may be related to differences in cognitive performance, but not to the MDD case-control status.

Background Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. Methods Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. Conclusions This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals.

IntroductionChildhood trauma and adversity are common across societies and have strong associations with physical and psychiatric morbidity throughout the life-course. One mechanism through which childhood trauma may predispose individuals to poor psychiatric outcomes, such as raised risk of lifetime depression, could be via associations with brain structure. This study aimed to elucidate the associations between childhood trauma scores and brain structure across two large, independent community cohorts.MethodsThe two samples comprised (i) a subsample of individuals from Generation Scotland with imaging and in-depth phenotyping, including the CTQ-28 (n=1,024); and (ii) individuals from UK Biobank with imaging and a modified summary CTQ measure (n=27,202). This comprised n=28,226 for mega-analysis. Scans were processed using FreeSurfer image processing software, providing cortical and subcortical as well as global brain metrics. Regression models were used to determine associations between these metrics and childhood trauma measures. Associations between childhood trauma measures and psychiatric phenotypes were also explored.ResultsChildhood trauma measures associated with lifetime risk of depression diagnosis with similar ORs across cohorts (OR 1.06, 1.23 GS and UKB respectively), which also related to earlier onset and more recurrent course within both samples. There was also evidence for associations between childhood trauma measures and a range of brain structures. Replicated findings included reduced global brain volumes, reduced cortical surface area but not thickness, with highest effects at mega-analysis seen in the frontal (β=-0.0385, SE=0.0048, p(FDR)=5.43×10−15) and parietal lobes (β=-0.0387, SE=0.005, p(FDR)=1.56×10−14). At a regional level, one subcortical regional volume in particular – the ventral diencephalon (VDc) – displayed significant associations with childhood trauma measures across the two cohorts and at mega-analysis (β=-0.0232, SE=0.0039, p(FDR)=2.91×10−8). There was also evidence for associations with reduced hippocampus, thalamus, and nucleus accumbens volumes, however these were not as consistent across cohorts.DiscussionThere was strong evidence for associations between childhood trauma and reduced global and regional brain volumes across cohorts. In particular, the presence of an association between childhood trauma and the volume of the VDc (which includes the hypothalamic area), with replication, provides further evidence of the importance of neuroendocrine stress response pathways in links between early life stress and clinical outcomes.

Background: Major Depressive Disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls.Methods: Participants from Generation Scotland (N=1,109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n=43), MDD-remitted (n=282), or controls (n=784). Analysis included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition (e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)). Results for remitted-MDD were less consistent.Conclusions: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by g, with no evidence for affective biases in remitted individuals.

BackgroundIndividuals with schizophrenia show impairments in associative learning. One well-studied, quantifiable form of associative learning is Pavlovian fear conditioning. However, to date, studies of fear conditioning in schizophrenia have been inconclusive, possibly because they lacked sufficient power.MethodsTo address this issue, data were pooled from 4 independent fear conditioning studies that included a total of 77 individuals with schizophrenia and 74 control subjects. Skin conductance responses (SCRs) during fear conditioning to stimuli that were paired (the CS+) and not paired (CS-) with an aversive, unconditioned stimulus were measured, and the success of acquisition of differential conditioning (the magnitude of CS+ vs. CS-SCRs) and responses to CS+ and CS-separately were assessed.ResultsAcquisition of differential conditioned fear responses was significantly lower in individuals with schizophrenia than in healthy controls (Cohen’s d = 0.53). This effect was primarily related to a significantly higher response to the CS-stimulus in the schizophrenia compared to the control group. The magnitude of this response to the CS- in the schizophrenia group was correlated with the severity of delusional ideation. Other symptoms or antipsychotic dose were not associated with fear conditioning measures.ConclusionsIndividuals with schizophrenia who endorse delusional beliefs are over-responsive to neutral stimuli during fear conditioning. This finding is consistent with prior models of aberrant learning in psychosis.

Background: Suicide is the second leading cause on death in young people and self-harm is one of the strongest predictors of death by suicide. Little is known about the impact of covid-19 lockdown on hospital presentations with self-harm. Method: We used electronic patient records from 23 hospital emergency departments in 10 countries to examine differences in hospital emergency psychiatric presentations for self-harm of youths through age 18 in March and April 2020 compared with the same period in 2019. To compare the number of hospital presentations a negative binomial model was used. For other variables, individual participant data (IPD) meta-analyses were carried out. Findings: The total number of emergency psychiatric hospital presentations decreased from 1,239 in 2019 to 834 in 2020, IRR 0·67, 95% CI 0·62-0·73. The proportion of youths presenting with self-harm increased from 50% in 2019 to 57% in 2020, OR 1·33, 95% CI 1·07-1·64, but there was no difference in the proportion presenting with severe self-harm. Within self-harm presentations, the proportion of youths with emotional disorders increased from 58% to 66%, OR 1·58, 95% CI 1·06-2·36. The proportion of youths admitted to an observation ward also decreased from 13% to 9% in 2020, OR 0·52, 95% CI 0·28 to 0·96. There were no differences in other outcomes and no evidence that youths from deprived areas or from ethnic minorities were disproportionally affected. Interpretation: During lockdowns, there are likely to be fewer hospital emergency psychiatric presentations. Many children and adolescents with psychiatric emergencies might not receive any service. Developing intensive community care services with outreach capabilities should be prioritised. Funding Statement: None. Declaration of Interests: In the last three years Dr. Carucci had collaborations within projects from the European Union (7th Framework Program) and as sub-investigator in sponsored clinical trials by Shire Pharmaceutical Company, Lundbeck, Otsuka, Janssen Cilag and Angelini. Travel support from Fidia Farmaceutici. PLP has received research funding from the German Federal Ministry of Education and Research (BMBF), the German Federal Institute for Drugs and Medical devices (BfARM), the Baden Wuerttemberg state foundation, eh Volkswagen foundation, Lundbeck and Servier. He received a speaker´s honorarium from Shire. All remaining authors have no competing interests to declare. Ethics Approval Statement: This study is based on the data from the NCDR obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. The study was approved by the King’s College London/South London and Maudsley NHS Foundation Trust service evaluation and clinical audit committee Ref no: AP1312/05/2020.

It has been proposed that the Glutamate (Glu) system is implicated in autism spectrum disorders (ASD) via an imbalance between excitatory and inhibitory brain circuits, which impacts on brain function. Here, we investigated the excitatory-inhibitory imbalance theory by measuring Glu-concentrations and the relationship with resting-state function. Nineteen adult males with ASD and 19 age and sex-matched healthy controls (HC) (23 - 58 years) underwent Proton Magnetic Resonance Spectroscopy of the dorsal anterior cingulate cortex (dACC) and resting-state functional Magnetic Resonance Imaging (fMRI). Glu and Glx concentrations were compared between groups. Seed-based functional connectivity was analyzed with a priori seeds of the right and left dACC. Finally, metabolite concentrations were related to functional connectivity coefficients and compared between both groups. Individuals with ASD showed significantly negative associations between increased Glx concentrations and reduced functional connectivity between the dACC and insular, limbic and parietal regions. In contrast, HC displayed a positive relationship between the same metabolite and connectivity measures. We provided new evidence to support the excitatory-inhibitory imbalance theory, where excitatory Glx concentrations were related to functional dysconnectivity in ASD. Future research is needed to investigate large-scale functional networks in association with both excitatory and inhibitory metabolites in subpopulations of ASD.

Background: Depression is the leading cause of disability worldwide with >50% of cases emerging before the age of 25yrs. Large-scale neuroimaging studies in depression implicate robust structural brain differences in the disorder. However most studies have been conducted in adults and therefore, the temporal origins of depression-related imaging features remain unknown. This has important implications for understanding aetiology and informing timings of potential intervention. Methods: Here, we examine associations between brain structure (cortical metrics and white matter microstructural integrity) and depression ratings (from caregiver and child), in a large sample of early adolescents from the Adolescent Brain and Cognitive Development (ABCD) Study (N=9981, 9-11-year olds). Findings: We report significantly decreased global cortical and white matter metrics, and regionally in frontal, limbic and temporal areas in adolescent depression (Cohen’s d = -0.018 to -0.041, β = -0.019 to -0.057). Further, we report consistently stronger imaging associations for caregiver-reported compared to child-reported depression ratings. Divergences between reports (caregiver vs child) were found to significantly relate to negative socio-environmental factors (e.g., family conflict, absolute β=0.048 to 0.169). Interpretation: Depression ratings in early adolescence were associated with similar imaging findings to those seen in adult depression samples, suggesting neuroanatomical abnormalities may be present early in the disease course, arguing for the importance of early intervention. Associations between socio-environmental factors and reporter discrepancy warrant further consideration, both in the wider context of the assessment of adolescent psychopathology, and in relation to their role in aetiology. Funding: The study is funded by Wellcome Trust Strategic Award “Stratifying Resilience and Depression Longitudinally” (STRADL) (Reference 104036/Z/14/Z) and MRC Mental Health Data Pathfinder Award (Reference MC_PC_17209). HCW is supported by a JMAS SIM fellowship from the Royal College of Physicians of Edinburgh and by an ESAT College Fellowship from the University of Edinburgh. AMM receives the Wellcome Trust Strategic Award (Reference 104036/Z/14/Z). Declaration of Interests: AMM has received research funding from The Sackler Trust, Eli Lilly and Janssen. No other conflicts of interest declared by other authors. Ethics Approval Statement: The study was approved by the National Institute of Mental Health Data Archive, United States (NIMH). Data was accessed through the NDA data base (http://nda.nih.gov/abcd, Federal-Wide Assurance: FWA00018101).

A prominent risk factor for psychosis is its high heritability. This offers us a means to identify potential biomarkers of risk and resilience by focusing on people who are at familial high risk, but are currently free of both illness and medication. The genetic underpinnings of this risk allow us to gain a more mechanistic understanding, which may better guide therapeutic development and prevention strategies. Here, we summarize two prospective longitudinal familial high-risk studies: the Edinburgh High Risk Study of schizophrenia and the Bipolar Family Study. This work highlights the complex interactions between molecular mechanisms and environmental circumstances in the generation and perpetuation of psychosis.

Clinical studies have reported altered reward processing in major depressive disorder. Using dynamic causal modelling, Rupprecher et al. show that blunted reward-related effective connectivity from the medial prefrontal cortex to the striatum is associated with increased severity of depressive symptoms., Major depressive disorder is a leading cause of disability and significant mortality, yet mechanistic understanding remains limited. Over the past decade evidence has accumulated from case-control studies that depressive illness is associated with blunted reward activation in the basal ganglia and other regions such as the medial prefrontal cortex. However it is unclear whether this finding can be replicated in a large number of subjects. The functional anatomy of the medial prefrontal cortex and basal ganglia has been extensively studied and the former has excitatory glutamatergic projections to the latter. Reduced effect of glutamatergic projections from the prefrontal cortex to the nucleus accumbens has been argued to underlie motivational disorders such as depression, and many prominent theories of major depressive disorder propose a role for abnormal cortico-limbic connectivity. However, it is unclear whether there is abnormal reward-linked effective connectivity between the medial prefrontal cortex and basal ganglia related to depression. While resting state connectivity abnormalities have been frequently reported in depression, it has not been possible to directly link these findings to reward-learning studies. Here, we tested two main hypotheses. First, mood symptoms are associated with blunted striatal reward prediction error signals in a large community-based sample of recovered and currently ill patients, similar to reports from a number of studies. Second, event-related directed medial prefrontal cortex to basal ganglia effective connectivity is abnormally increased or decreased related to the severity of mood symptoms. Using a Research Domain Criteria approach, data were acquired from a large community-based sample of subjects who participated in a probabilistic reward learning task during event-related functional MRI. Computational modelling of behaviour, model-free and model-based functional MRI, and effective connectivity dynamic causal modelling analyses were used to test hypotheses. Increased depressive symptom severity was related to decreased reward signals in areas which included the nucleus accumbens in 475 participants. Decreased reward-related effective connectivity from the medial prefrontal cortex to striatum was associated with increased depressive symptom severity in 165 participants. Decreased striatal activity may have been due to decreased cortical to striatal connectivity consistent with glutamatergic and cortical-limbic related theories of depression and resulted in reduced direct pathway basal ganglia output. Further study of basal ganglia pathophysiology is required to better understand these abnormalities in patients with depressive symptoms and syndromes.

The aim of this study was to test whether bilinear and nonlinear effective connectivity (EC) measures of working memory fMRI data can differentiate between patients with schizophrenia (SZ) and healthy controls (HC). We applied bilinear and nonlinear Dynamic Causal Modeling (DCM) for the analysis of verbal working memory in 16 SZ and 21 HC. The connection strengths with nonlinear modulation between the dorsolateral prefrontal cortex (DLPFC) and the ventral tegmental area/substantia nigra (VTA/SN) were evaluated. We used Bayesian Model Selection at the group and family levels to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging was used to assess the connection strengths with nonlinear modulation. The DCM analyses revealed that SZ and HC used different bilinear networks despite comparable behavioral performance. In addition, the connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area showed differences between SZ and HC. The adoption of different functional networks in SZ and HC indicated neurobiological alterations underlying working memory performance, including different connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area. These novel findings may increase our understanding of connectivity in working memory in schizophrenia.

Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behaviour (e.g. Bayesian models– top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist & neural networks – bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i.e. understanding behavioural vs. neurobiological anomalies) about the nature of the disorder. As such, these computational studies have mostly supported diverging hypotheses of schizophrenia's pathophysiology, resulting in a literature that is not always expanding coherently. Some of these hypotheses are however ripe for revision using novel empirical evidence. Here we present a review that first synthesises the literature of computational modelling for schizophrenia and psychotic symptoms into categories supporting the Dopamine, Glutamate, GABA, Dysconnection and Bayesian inference hypotheses respectively. Secondly, we compare model predictions against the accumulated empirical evidence and finally we identify specific hypotheses that have been left relatively under-investigated.

Background.Abnormalities of emotion-related brain circuitry, including cortico-thalamic-limbic regions underpin core symptoms of bipolar disorder (BD) and major depressive disorder (MDD). It is unclear whether these abnormalities relate to symptoms of the disorder, are present in unaffected relatives, or whether they can predict future illness.Method.The Bipolar Family Study (BFS) is a prospective longitudinal study that has examined individuals at familial risk of mood disorder and healthy controls on three occasions, 2 years apart. The current study concerns imaging data from the second assessment; 51 controls and 81 high-risk (HR) individuals performing an emotional memory task. The latter group was divided into 61 HR individuals who were well, and 20 who met diagnostic criteria for MDD. At the time of the third assessment a further 11 HR individuals (from the Well group) had developed MDD. The current analyses focused on (i) differences between groups based on diagnostic status at the time of the scan, and (ii) predictors of future illness, comparing the 11 HR individuals who became unwell after the second scanning assessment to those who remained well.Results.All groups demonstrated typical emotional modulation of memory and associated brain activations. For analysis (i) the HR MDD group demonstrated increased thalamic activation v. HR Well. (ii) HR Well individuals who subsequently became ill showed increased activation of thalamus, insula and anterior cingulate compared to those who remained well.Conclusions.These findings suggest evidence for specific changes related to the presence of illness and evidence that changes in brain function in cortico-thalamic-limbic regions precede clinical illness.

Grant information: STRADL is supported by the Wellcome Trust through a Strategic Award (104036/Z/14/Z). GS:SFHS received core support from the CSO of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). ADM is supported by Innovate UK, the European Commission, the Scottish Funding Council via the Scottish Imaging Network SINAPSE, and the CSO. HCW is supported by a JMAS SIM Fellowship from the Royal College of Physicians of Edinburgh, by an ESAT College Fellowship from the University of Edinburgh, and has received previous funding from the Sackler Trust. LR has previously received financial support from Pfizer (formerly Wyeth) in relation to imaging studies of people with schizophrenia and bipolar disorder. JDH is supported by the MRC. DJM is an NRS Clinician, funded by the CSO. RMR is supported by the British Heart Foundation. ISP-V and MRM are supported by the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health; and MRM is also supported by the MRC (MC_UU_12013/6). JMW is supported by MRC UK Dementia Research Institute and MRC Centre and project grants, EPSRC, Fondation Leducq, Stroke Association, British Heart Foundation, Alzheimer Society, and the European Union H2020 PHC-03-15 SVDs@Target grant agreement (666881). DJP is supported by Wellcome Trust Longitudinal Population Study funding (216767/Z/19/Z) the Eva Lester bequest to the University of Edinburgh. AMM is additionally supported by the MRC (MC_PC_17209, MC_PC_MR/R01910X/1, MR/S035818/1), The Wellcome Trust (216767/Z/19/Z ), The Sackler Trust, and has previously received research funding from Pfizer, Eli Lilly, and Janssen. Both AMM and IJD are members of The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1); funding from the BBSRC and MRC is gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Background\ud \ud Studies have identified perturbations in facial processing in bipolar disorder and major depressive disorder (MDD), but their relationship to genetic risk and early development of illness is unclear.\ud \ud \ud Methods\ud \ud The Scottish Bipolar Family Study is a prospective longitudinal investigation examining young individuals (age 16–25) at familial risk of mood disorder. Participants underwent functional MRI using an implicit facial processing task employing angry and neutral faces. An explicit facial expression recognition task was completed outside the scanner. Clinical outcomes obtained 2 years after the scan were used to categorise participants into controls (n = 54), high-risk individuals who had developed MDD (HR MDD; n = 30) and high-risk individuals who remained well (HR Well, n = 43).\ud \ud \ud Results\ud \ud All groups demonstrated activation patterns typically observed during facial processing, including activation of the amygdala, hippocampus, fusiform gyrus and middle frontal regions. Notably, the HR MDD group showed reduced activation of the anterior cingulate gyrus versus both the control and HR Well group for angry faces, and versus the HR Well group for neutral faces. Outside the scanner, the HR MDD group was less accurate in recognising fearful expressions than the HR Well group.\ud \ud \ud Conclusions\ud \ud Here, we demonstrate functional abnormalities of the anterior cingulate cortex alongside facial emotional recognition deficits in high-risk individuals in the early stages of depression compared with both controls and at-risk individuals who remained well. These neural changes were associated with a current or future diagnosis of MDD and were not simply associated with increased familial risk.

BackgroundPrevious neuroimaging studies indicate abnormalities in cortico-limbic circuitry in mood disorder. Here we employ prospective longitudinal voxel-based morphometry to examine the trajectory of these abnormalities during early stages of illness development.MethodUnaffected individuals (16–25 years) at high and low familial risk of mood disorder underwent structural brain imaging on two occasions 2 years apart. Further clinical assessment was conducted 2 years after the second scan (time 3). Clinical outcome data at time 3 was used to categorize individuals: (i) healthy controls (‘low risk’, n = 48); (ii) high-risk individuals who remained well (HR well, n = 53); and (iii) high-risk individuals who developed a major depressive disorder (HR MDD, n = 30). Groups were compared using longitudinal voxel-based morphometry. We also examined whether progress to illness was associated with changes in other potential risk markers (personality traits, symptoms scores and baseline measures of childhood trauma), and whether any changes in brain structure could be indexed using these measures.ResultsSignificant decreases in right amygdala grey matter were found in HR MDD v. controls (p = 0.001) and v. HR well (p = 0.005). This structural change was not related to measures of childhood trauma, symptom severity or measures of sub-diagnostic anxiety, neuroticism or extraversion, although cross-sectionally these measures significantly differentiated the groups at baseline.ConclusionsThese longitudinal findings implicate structural amygdala changes in the neurobiology of mood disorder. They also provide a potential biomarker for risk stratification capturing additional information beyond clinically ascertained measures.

Background The amygdala plays a central role in detecting and responding to fear-related stimuli. A number of recent studies have reported decreased amygdala activation in schizophrenia to emotional stimuli (such as fearful faces) compared with matched neutral stimuli (such as neutral faces). We investigated whether the apparent decrease in amygdala activation in schizophrenia could actually derive from increased amygdala activation to the neutral comparator stimuli. Methods Nineteen patients with schizophrenia and 24 matched control participants viewed pictures of faces with either fearful or neutral facial expressions, and a baseline condition, during functional magnetic resonance imaging scanning. Results Patients with schizophrenia showed a relative decrease in amygdala activation to fearful faces compared with neutral faces. However, this difference resulted from an increase in amygdala activation to the neutral faces in patients with schizophrenia, not from a decreased response to the fearful faces. Conclusions Patients with schizophrenia show an increased response of the amygdala to neutral faces. This is sufficient to explain their apparent deficit in amygdala activation to fearful faces compared with neutral faces. The inappropriate activation of neural systems involved in fear to otherwise neutral stimuli may contribute to the development of psychotic symptoms in schizophrenia.

BACKGROUND. The disrupted in schizophrenia 1 (DISC1) gene locus was originally identified in a Scottish pedigree with a high incidence of psychiatric disorders that is associated with a balanced t(1;11)(q42.1;q14.3) chromosomal translocation. Here, we investigated whether members of this family carrying the t(1;11)(q42.1;q14.3) translocation have a common brain-related phenotype and whether this phenotype is similar to that observed in schizophrenia (SCZ), using multivariate pattern recognition techniques. METHODS. We measured cortical thickness, cortical surface area, subcortical volumes, and regional cerebral blood flow (rCBF) in healthy controls (HC) (n = 24), patients diagnosed with SCZ (n = 24), patients diagnosed with bipolar disorder (BP) (n = 19), and members of the original Scottish family (n = 30) who were either carriers (T+) or noncarriers (T–) of the DISC1 translocation. Binary classification models were developed to assess the differences and similarities across groups. RESULTS. Based on cortical thickness, 72% of the T– group were assigned to the HC group, 83% of the T+ group were assigned to the SCZ group, and 45% of the BP group were classified as belonging to the SCZ group, suggesting high specificity of this measurement in predicting brain-related phenotypes. Shared brain-related phenotypes between SCZ and T+ individuals were found for cortical thickness only. Finally, a classification accuracy of 73% was achieved when directly comparing the pattern of cortical thickness of T+ and T– individuals. CONCLUSION. Together, the results of this study suggest that the DISC1 translocation may increase the risk of psychiatric disorders in this pedigree by affecting neurostructural phenotypes such as cortical thickness. FUNDING. This work was supported by the National Health Service Research Scotland, the Scottish Translational Medicine Research Collaboration, the Innovative Medicines Initiative (IMI), the Engineering and Physical Sciences Research Council (EPSRC), The Wellcome Trust, the National Institute of Health Research (NIHR), and Pfizer.

BackgroundImpulsivity is a core feature of borderline personality disorder (BPD) and is most frequently measured using self-rating scales. There is a need to find objective, valid and reliable measures of impulsivity. This study aimed to examine performance of participants with BPD compared with healthy controls on delay and probabilistic discounting tasks and the stop-signal task (SST), which are objective measures of choice and motor impulsivity, respectively.MethodA total of 20 participants with BPD and 21 healthy control participants completed delay and probabilistic discounting tasks and the SST. They also completed the Barratt Impulsiveness Scale (BIS), a self-rating measure of impulsivity.ResultsParticipants with BPD showed significantly greater delay discounting than controls, manifest as a greater tendency to accept the immediately available lesser reward rather than waiting longer for a greater reward. Similarly they showed significantly greater discounting of rewards by the probability of payout, which correlated with past childhood trauma. Participants with BPD were found to choose the more certain and/or immediate rewards, irrespective of the value. On the SST the BPD and control groups did not differ significantly, demonstrating no difference in motor impulsivity. There was no significant difference between groups on self-reported impulsivity as measured by the BIS.ConclusionsMeasures of impulsivity show that while motor impulsivity was not significantly different in participants with BPD compared with controls, choice or reward-related impulsivity was significantly affected in those with BPD. This suggests that choice impulsivity but not motor impulsivity is a core feature of BPD.

Background: Borderline personality disorder (BPD) is a prevalent and disabling psychiatric condition commonly associated with early life adversity. Social difficulties are a prominent symptom of BPD, particularly a fear of abandonment and rejection. There has recently been a growing interest in the neural basis of these social symptoms and their relationship to early experience. Methods: In the current study, we examined social brain function and learning in BPD using functional MRI. Participants with BPD (n=20) and healthy controls (n=16) completed a computerized parametric social exclusion task (the “Cyberball” task). Brain activation was compared between groups and related to social symptom status and experiences of childhood trauma. Additional analyses were conducted using a reinforcement learning model treating social inclusion as a rewarding event. Results: Participants with BPD demonstrated a group effect of decreased right temporoparietal junction (TPJ) activation (p < 0.013, FWE-corrected). Increased fear of abandonment in BPD was associated with reduced inclusion-related activation of the inferior frontal gyrus (p = 0.003, FWE-corrected). Across all participants, TPJ inclusion-related activation was modified by prior experience of childhood physical neglect (p < 0.001, FWE-corrected). Reinforcement learning modelling revealed decreased midbrain responses to social inclusion in BPD participants (p = 0.028, FWE-corrected within midbrain mask), with decreased anticipatory midbrain activation in anticipation of social inclusion specifically associated with fears of abandonment (p = 0.019, FWE-corrected within a midbrain mask). Conclusions: The findings demonstrate alterations in social brain function and social reinforcement learning in BPD, which are influenced by both early life experience and symptom status.

Background Chemotherapy-induced peripheral neuropathy affects 30% of cancer survivors. Findings from animal studies suggest that brainstem descending inhibitory pathways are important in chronic neuropathic pain. An aberrant descending pain modulation system has been implicated in human neuropathic pain. Whether aberrant descending pain modulation before chemotherapy is associated with development of chemotherapy-induced peripheral neuropathy is unclear. We aimed to assess descending pain modulation systems using functional MRI (fMRI) in chemotherapy-naive patients with cancer to determine whether differences are associated with subsequent development of the neuropathy. Methods In this multicentre prospective cohort study, adult patients with cancer and no chronic pain, neuropathy, or risk factors for neuropathy were recruited from the oncology clinic before onset of chemotherapy. After patients had given written informed consent, descending inhibitory pathways were challenged (jittered punctate stimuli 256 mN Somedic von Frey filament) during a 3T fMRI scan, and images analysed with FSL software. Sample size was based on published fMRI estimates. Chemotherapy-induced peripheral neuropathy was diagnosed with the CIPN20 questionnaire. Findings 30 patients were recruited (mean age 60·4 years [SD 7·9]). We report a preliminary analysis of the first 12 patients (60·6 [8·3], six women); six had colorectal cancer, four gynaecological cancer, and two lung cancer. Seven patients (three men, four women) developed chemotherapy-induced peripheral neuropathy. After data brain extraction, registration, B0 unwarping, and motion correction, FEAT was used for first and second level analysis. Mean group level comparisons between patients with and without the neuropathy were conducted with mixed-effects analysis (z threshold 2·3, regions considered significant at p Interpretation These preliminary results suggest that baseline differences exist, before peripheral nerve injury, in the descending pain modulation system of patients who go on to develop chemotherapy-induced peripheral neuropathy. These differences might aid development of biomarkers to guide chemotherapy choices. Limitations of the study include the small sample size for the present analysis, the observational nature of the study, and the possibility of unknown confounders. Strengths include the prospective design in a unique patient cohort and the high sensitivity of fMRI. Funding Wellcome Trust via Scottish Translational Medicine and Therapeutics Initiative (STMTI).

Theories of schizophrenia propose that abnormal functioning of the neural reward system is linked to negative and psychotic symptoms, by disruption of reward processing and promotion of context-independent false associations. Recently, it has been argued that an insula-anterior cingulate cortex (ACC) salience network system enables switching of brain states from the default mode to a task-related activity mode. Abnormal interaction between the insula-ACC system and reward processing regions may help explain abnormal reinforcer processing and symptoms. Here we use functional magnetic resonance imaging to assess the neural correlates of reward processing in schizophrenia. Furthermore, we investigated functional connectivity between the dopaminergic midbrain, a key region for the processing of reinforcers, and other brain regions. In response to rewards, controls activated task related regions (striatum, amygdala/hippocampus and midbrain) and the insula-ACC salience network. Patients similarly activated the insula-ACC salience network system but failed to activate task related regions. Reduced functional connectivity between the midbrain and the insula was found in schizophrenia, with the extent of this abnormality correlating with increased psychotic symptoms. The findings support the notion that reward processing is abnormal in schizophrenia and highlight the potential role of abnormal interactions between the insula-ACC salience network and reward regions.

A recent 'mega-analysis' combining genome-wide association study data from over 40,000 individuals identified novel genetic loci associated with schizophrenia (SCZ) at genome-wide significance level. The strongest finding was a locus within an intron of a putative primary transcript for microRNA MIR137. In the current study, we examine the impact of variation at this locus (rs1625579, G/T; where T is the common and presumed risk allele) on brain activation during a sentence completion task that differentiates individuals with SCZ, bipolar disorder (BD), and their relatives from controls. We examined three groups of individuals performing a sentence completion paradigm: (i) individuals at high genetic risk of SCZ (n=44), (ii) individuals at high genetic risk of BD (n=90), and (iii) healthy controls (n=81) in order to test the hypothesis that genotype at rs1625579 would influence brain activation. Genotype groups were assigned as 'RISK-' for GT and GG individuals, and 'RISK+' for TT homozygotes. The main effect of genotype was significantly greater activation in the RISK- individuals in the posterior right medial frontal gyrus, BA 6. There was also a significant genotype(*)group interaction in the left amygdala and left pre/postcentral gyrus. This was due to differences between the controls (where individuals with the RISK- genotype showed greater activation than RISK+ subjects) and the SCZ high-risk group, where the opposite genotype effect was seen. These results suggest that the newly identified SCZ locus may influence brain activation in a manner that is partly dependent on the presence of existing genetic susceptibility for SCZ.

Bipolar disorder and schizophrenia share a number of clinical features and genetic risk variants of small effect, suggesting overlapping pathogenic mechanisms. The effect of single genetic risk variants on brain function is likely to differ in people at high familial risk versus controls as these individuals have a higher overall genetic loading and are therefore closer to crossing a threshold of disease liability. Therefore, whilst the effects of genetic risk variants on brain function may be similar across individuals at risk of both disorders, they are hypothesized to differ compared to that seen in control subjects. We sought to examine the effects of the DISC1 Leu(607) Phe polymorphism on brain activation in young healthy individuals at familial risk of bipolar disorder (n = 84), in a group of controls (n = 78), and in a group at familial risk of schizophrenia (n = 47), performing a language task. We assessed whether genotype effects on brain activation differed according to risk status. There was a significant genotype × group interaction in a cluster centered on the left pre/postcentral gyrus, extending to the inferior frontal gyrus. The origin of this genotype × group effect originated from a significant effect of the presumed risk variant (Phe) on brain activation in the control group, which was absent in both high-risk groups. Differential effects of this polymorphism in controls compared to the two familial groups suggests a commonality of effect across individuals at high-risk of the disorders, which is likely to be dependant upon existing genetic background.

Context: Recent theories have suggested that the inappropriate activation of limbic motivational systems in response to neutral stimuli may underlie the development of delusions in schizophrenia. Objective: To investigate the activation of the amygdala, midbrain, and ventral striatum during an aversive pavlovian conditioning task in patients with schizophrenia and healthy control participants using functional magnetic resonance imaging. Design: Cross-sectional case-control functional neuroimaging study. Setting: Academic medical center. Participants: Twenty patients with DSM-IV–diagnosed schizophrenia or schizoaffective disorder and 20 healthy control participants. Main Outcome Measures: Regional brain activation as assessed by functional magnetic resonance imaging blood oxygen level–dependent responses, and delusional symptom severity on the Positive and Negative Syndrome Scale. Results: Patients with schizophrenia showed abnormal activation of the amygdala, midbrain, and ventral striatum during conditioning. Activation of the midbrain in response to neutral rather than aversive cues during conditioning was correlated with the severity of delusional symptoms in the patient group (corrected P = .04). Conclusion: Inappropriate activation of the midbrain in response to neutral stimuli during conditioning is associated with the severity of delusional symptoms in patients with schizophrenia.