Identification of endophenotypes can improve prevention, detection and development of new treatments. We therefore investigated whether aberrant affective cognition constitutes an endophenotype for affective disorders by being present in monozygotic (MZ) twins with unipolar or bipolar disorder in partial remission (i.e. affected) and their unaffected co-twins (i.e. high-risk) relative to twins with no family history of affective disorder (i.e. low-risk).

We conducted an assessor blind cross-sectional study from 2014 to 2017 of MZ twins using Danish population-based registers in recruitment. Twins attended one test session involving neurocognitive testing, clinical ratings and questionnaires. Main outcomes were attention to and recognition of emotional facial expressions, the memory of emotional self-referential words, emotion regulation and coping strategies.

Participants were 103 affected, 44 high-risk and 36 low-risk MZ twins. Groups were demographically well-balanced and showed comparable non-affective cognitive performance. We observed no aberrant affective cognition in affected and high-risk relative to low-risk twins. However, high-risk twins displayed attentional avoidance of emotional faces (ps ⩽ 0.009) and more use of task-oriented coping strategies (p = 0.01) compared with affected twins. In contrast did affected twins show more emotion-oriented coping than high- and low-risk twins (ps ⩽ 0.004).

Our findings provide no support of aberrant affective cognition as an endophenotype for affective disorders. High-risk twins’ attentional avoidance of emotional faces and greater use of task-oriented coping strategies may reflect compensatory mechanisms.

Depression is increasingly recognized as a chronic and relapsing disorder. However, an important minority of patients who start treatment for their major depressive episode recover to euthymia. It is clinically important to be able to predict such individuals.

The study is a secondary analysis of a recently completed pragmatic megatrial examining first- and second-line treatments for hitherto untreated episodes of non-psychotic unipolar major depression (n = 2011). Using the first half of the cohort as the derivation set, we applied multiply-imputed stepwise logistic regression with backward selection to build a prediction model to predict remission, defined as scoring 4 or less on the Patient Health Quetionnaire-9 at week 9. We used three successively richer sets of predictors at baseline only, up to week 1, and up to week 3. We examined the external validity of the derived prediction models with the second half of the cohort.

In total, 37.0% (95% confidence interval 34.8–39.1%) were in remission at week 9. Only the models using data up to week 1 or 3 showed reasonable performance. Age, education, length of episode and depression severity remained in the multivariable prediction models. In the validation set, the discrimination of the prediction model was satisfactory with the area under the curve of 0.73 (0.70–0.77) and 0.82 (0.79–0.85), while the calibration was excellent with non-significant goodness-of-fit χ2 values (p = 0.41 and p = 0.29), respectively.

Patients and clinicians can use these prediction models to estimate their predicted probability of achieving remission after acute antidepressant therapy.

A wealth of clinical studies have identified objective biomarkers, which separate schizophrenia patients from healthy controls on a group level, but current diagnostic systems solely include clinical symptoms. In this study, we investigate if machine learning algorithms on multimodal data can serve as a framework for clinical translation.

Forty-six antipsychotic-naïve, first-episode schizophrenia patients and 58 controls underwent neurocognitive tests, electrophysiology, and magnetic resonance imaging (MRI). Patients underwent clinical assessments before and after 6 weeks of antipsychotic monotherapy with amisulpride. Nine configurations of different supervised machine learning algorithms were applied to first estimate the unimodal diagnostic accuracy, and next to estimate the multimodal diagnostic accuracy. Finally, we explored the predictability of symptom remission.

Cognitive data significantly classified patients from controls (accuracies = 60–69%; p values = 0.0001–0.009). Accuracies of electrophysiology, structural MRI, and diffusion tensor imaging did not exceed chance level. Multimodal analyses with cognition plus any combination of one or more of the remaining three modalities did not outperform cognition alone. None of the modalities predicted symptom remission.

In this multivariate and multimodal study in antipsychotic-naïve patients, only cognition significantly discriminated patients from controls, and no modality appeared to predict short-term symptom remission. Overall, these findings add to the increasing call for cognition to be included in the definition of schizophrenia. To bring about the full potential of machine learning algorithms in first-episode, antipsychotic-naïve schizophrenia patients, careful a priori variable selection based on independent data as well as inclusion of other modalities may be required.

Chronic opioid exposure is common world-wide, but behavioural performance remains under-investigated. This study aimed to investigate visuospatial memory performance in opioid-exposed and dependent clinical populations and its associations with measures of intelligence and cognitive impulsivity.

We recruited 109 participants: (i) patients with a history of opioid dependence due to chronic heroin use (n = 24), (ii) heroin users stabilised on methadone maintenance treatment (n = 29), (iii) participants with a history of chronic pain and prescribed tramadol and codeine (n = 28) and (iv) healthy controls (n = 28). The neuropsychological tasks from the Cambridge Neuropsychological Test Automated Battery included the Delayed Matching to Sample (DMS), Pattern Recognition Memory, Spatial Recognition Memory, Paired Associate Learning, Spatial Span Task, Spatial Working Memory and Cambridge Gambling Task. Pre-morbid general intelligence was assessed using the National Adult Reading Test.

As hypothesised, this study identified the differential effects of chronic heroin and methadone exposures on neuropsychological measures of visuospatial memory (p < 0.01) that were independent of injecting behaviour and dependence status. The study also identified an improvement in DMS performance (specifically at longer delays) when the methadone group was compared with the heroin group and also when the heroin group was stabilised onto methadone. Results identified differential effects of chronic heroin and methadone exposures on various neuropsychological measures of visuospatial memory independently from addiction severity measures, such as injecting behaviour and dependence status.

Psychotic experiences (PEs) may predict a range of common, non-psychotic disorders as well as psychotic disorders. In this representative, general population-based cohort study, both psychotic and non-psychotic disorder outcomes of PE were analysed, as were potential moderators.

Addresses were contacted in a multistage clustered probability sampling frame covering 11 districts and 302 neighbourhoods at baseline (n = 4011). Participants were interviewed with the Composite International Diagnostic Interview (CIDI) both at baseline and at 6-year follow-up. Participants with PE at baseline were clinically re-interviewed with the SCID-I at follow-up. The role of socio-demographics, characteristics of PE, co-occurrence of mood disorders and family history of mental disorders were tested in the association between baseline PE and follow-up diagnosis.

In the participants with baseline PE, the psychotic disorder diagnosis rate at follow up was 7.0% – much lower than the rates of DSM-IV mood disorders without psychotic features (42.8%) and other non-psychotic disorders (24.1%). Within the group with baseline PE, female sex, lower socio-economic status, co-occurrence of mood disorders, family history of a mental disorder and persistence of PE predicted any follow-up DSM diagnosis. Furthermore, onset of psychotic v. non-psychotic disorder was predicted by younger age (15–30 years), co-presence of delusional and hallucinatory PE and family history of severe mental illness.

The outcome of PE appears to be a consequence of baseline severity of multidimensional psychopathology and familial risk. It may be useful to consider PE as a risk indicator that has trans-diagnostic value.

Evidence suggests that cannabis use, childhood adversity, and urbanicity, in interaction with proxy measures of genetic risk, may facilitate onset of psychosis in the sense of early affective dysregulation becoming ‘complicated’ by, first, attenuated psychosis and, eventually, full-blown psychotic symptoms.

Data were derived from three waves of the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2). The impact of environmental risk factors (cannabis use, childhood adversity, and urbanicity) was analyzed across severity levels of psychopathology defined by the degree to which affective dysregulation was ‘complicated’ by low-grade psychotic experiences (‘attenuated psychosis’ – moderately severe) and, overt psychotic symptoms leading to help-seeking (‘clinical psychosis’ – most severe). Familial and non-familial strata were defined based on family history of (mostly) affective disorder and used as a proxy for genetic risk in models of family history × environmental risk interaction.

In proxy gene–environment interaction analysis, childhood adversity and cannabis use, and to a lesser extent urbanicity, displayed greater-than-additive risk if there was also evidence of familial affective liability. In addition, the interaction contrast ratio grew progressively greater across severity levels of psychosis admixture (none, attenuated psychosis, clinical psychosis) complicating affective dysregulation.

Known environmental risks interact with familial evidence of affective liability in driving the level of psychosis admixture in states of early affective dysregulation in the general population, constituting an affective pathway to psychosis. There is interest in decomposing family history of affective liability into the environmental and genetic components that underlie the interactions as shown here.

Studies have demonstrated that decreases in slow-wave activity (SWA) predict decreases in depressive symptoms in those with major depressive disorder (MDD), suggesting that there may be a link between SWA and mood. The aim of the present study was to determine if the consequent change in SWA regulation following a mild homeostatic sleep challenge would predict mood disturbance.

Thirty-seven depressed and fifty-nine healthy adults spent three consecutive nights in the sleep laboratory. On the third night, bedtime was delayed by 3 h, as this procedure has been shown to provoke SWA. The Profile of Mood States questionnaire was administered on the morning following the baseline and sleep delay nights to measure mood disturbance.

Results revealed that following sleep delay, a lower delta sleep ratio, indicative of inadequate dissipation of SWA from the first to the second non-rapid eye movement period, predicted increased mood disturbance in only those with MDD.

These data demonstrate that in the first half of the night, individuals with MDD who have less SWA dissipation as a consequence of impaired SWA regulation have greater mood disturbance, and may suggest that appropriate homeostatic regulation of sleep is an important factor in the disorder.

Hearing voices can be a distressing and disabling experience for some, whilst it is a valued experience for others, so-called ‘healthy voice-hearers’. Cognitive models of psychosis highlight the role of memory, appraisal and cognitive biases in determining emotional and behavioural responses to voices. A memory bias potentially associated with distressing voices is the overgeneral memory bias (OGM), namely the tendency to recall a summary of events rather than specific occasions. It may limit access to autobiographical information that could be helpful in re-appraising distressing experiences, including voices.

We investigated the possible links between OGM and distressing voices in psychosis by comparing three groups: (1) clinical voice-hearers (N = 39), (2) non-clinical voice-hearers (N = 35) and (3) controls without voices (N = 77) on a standard version of the autobiographical memory test (AMT). Clinical and non-clinical voice-hearers also completed a newly adapted version of the task, designed to assess voices-related memories (vAMT).

As hypothesised, the clinical group displayed an OGM bias by retrieving fewer specific autobiographical memories on the AMT compared with both the non-clinical and control groups, who did not differ from each other. The clinical group also showed an OGM bias in recall of voice-related memories on the vAMT, compared with the non-clinical group.

Clinical voice-hearers display an OGM bias when compared with non-clinical voice-hearers on both general and voices-specific recall tasks. These findings have implications for the refinement and targeting of psychological interventions for psychosis.

Transition across eating disorder diagnoses is common, reflecting instability of specific eating disorder presentations. Previous studies have examined temporal stability of diagnoses in adult treatment-seeking samples but have not uniformly captured initial presentation for treatment. The current study examines transitions across eating disorder diagnostic categories in a large, treatment-seeking sample of individuals born in Sweden and compares these transitions across two birth cohorts and from initial diagnosis.

Data from Swedish eating disorders quality registers were extracted in 2013, including 9622 individuals who were seen at least twice from 1999 to 2013. Patterns of remission were examined in the entire sample and subsequently compared across initial diagnoses. An older (born prior to 1990) and younger birth cohort were also identified, and analyses compared these cohorts on patterns of diagnostic transition.

Although diagnostic instability was common, transition between threshold eating disorder diagnoses was infrequent. For all diagnoses, transition to remission was likely to occur following a diagnosis state that matched initial diagnosis, or through a subthreshold diagnostic state. Individuals in the younger cohort were more likely to transition to a state of remission than those in the older cohort.

Results indicate more temporal continuity in eating disorder presentations than suggested by previous research and highlight the importance of early detection and intervention in achieving remission.

The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition methods have been applied recently to predict many psychiatric disorders, these techniques have not been utilized to predict subtypes of posttraumatic stress disorder (PTSD), including the dissociative subtype of PTSD (PTSD + DS).

Using Multiclass Gaussian Process Classification within PRoNTo, we examined the classification accuracy of: (i) the mean amplitude of low-frequency fluctuations (mALFF; reflecting spontaneous neural activity during rest); and (ii) seed-based amygdala complex functional connectivity within 181 participants [PTSD (n = 81); PTSD + DS (n = 49); and age-matched healthy trauma-unexposed controls (n = 51)]. We also computed mass-univariate analyses in order to observe regional group differences [false-discovery-rate (FDR)-cluster corrected p < 0.05, k = 20].

We found that extracted features could predict accurately the classification of PTSD, PTSD + DS, and healthy controls, using both resting-state mALFF (91.63% balanced accuracy, p < 0.001) and amygdala complex connectivity maps (85.00% balanced accuracy, p < 0.001). These results were replicated using independent machine learning algorithms/cross-validation procedures. Moreover, areas weighted as being most important for group classification also displayed significant group differences at the univariate level. Here, whereas the PTSD + DS group displayed increased activation within emotion regulation regions, the PTSD group showed increased activation within the amygdala, globus pallidus, and motor/somatosensory regions.

The current study has significant implications for advancing machine learning applications within the field of psychiatry, as well as for developing objective biomarkers indicative of diagnostic heterogeneity.

Lower intelligence quotient (IQ) has frequently been reported in patients with schizophrenia. However, it is unclear whether IQ declines (further) after illness onset and what the familial contribution is to this change. Therefore, we investigate IQ changes during the course of illness in patients with non-affective psychosis, their siblings and controls.

Data are part of the longitudinal Genetic Risk and Outcome of Psychosis (GROUP) study in the Netherlands and Belgium. Participants underwent three measurements, each approximately 3 years apart. A total of 1022 patients with non-affective psychosis [illness duration: 4.34 (s.d. = 4.50) years], 977 of their siblings, and 565 controls had at least one measure of IQ (estimated from four subtests of the WAIS-III).

At baseline, IQ was significantly lower in patients (IQ = 97.8) and siblings (IQ = 108.2; p < 0.0001) than in controls (IQ = 113.0; p < 0.0001), and in patients as compared with siblings (p < 0.0001). Over time, IQ increased in all groups. In siblings, improvement in IQ was significantly more pronounced (+0.7 points/year) than in patients (+0.5 points/year; p < 0.0001) and controls (+0.3 points/year; p < 0.0001). IQ increase was not significantly correlated with improvement in (sub)clinical outcome in any of the groups.

During the first 10 years of the illness, IQ increases to a similar (and subtle) extent in a relatively high-functioning group of schizophrenia patients and controls, despite the lower IQ in patients at baseline. In addition, the siblings’ IQ was intermediate at baseline, but over time the increase in IQ was more pronounced.

The prevalence of mental disorders among Black, Latino, and Asian adults is lower than among Whites. Factors that explain these differences are largely unknown. We examined whether racial/ethnic differences in exposure to traumatic events (TEs) or vulnerability to trauma-related psychopathology explained the lower rates of psychopathology among racial/ethnic minorities.

We estimated the prevalence of TE exposure and associations with onset of DSM-IV depression, anxiety and substance disorders and with lifetime post-traumatic stress disorder (PTSD) in the Collaborative Psychiatric Epidemiology Surveys, a national sample (N = 13 775) with substantial proportions of Black (35.9%), Latino (18.9%), and Asian Americans (14.9%).

TE exposure varied across racial/ethnic groups. Asians were most likely to experience organized violence – particularly being a refugee – but had the lowest exposure to all other TEs. Blacks had the greatest exposure to participation in organized violence, sexual violence, and other TEs, Latinos had the highest exposure to physical violence, and Whites were most likely to experience accidents/injuries. Racial/ethnic minorities had lower odds ratios of depression, anxiety, and substance disorder onset relative to Whites. Neither variation in TE exposure nor vulnerability to psychopathology following TEs across racial/ethnic groups explained these differences. Vulnerability to PTSD did vary across groups, however, such that Asians were less likely and Blacks more likely to develop PTSD following TEs than Whites.

Lower prevalence of mental disorders among racial/ethnic minorities does not appear to reflect reduced vulnerability to TEs, with the exception of PTSD among Asians. This highlights the importance of investigating other potential mechanisms underlying racial/ethnic differences in psychopathology.

The structural integrity of the anterior cingulum has been repeatedly observed to be abnormal in patients with schizophrenia. More recently, aberrant myelination of frontal fasciculi, especially, cingulum has been proposed to underlie delayed corollary discharges that can affect sense of agency and contribute to delusions of control (Schneiderian delusions). Using the magnetization transfer phenomenon at an ultra-high field 7T MRI, we investigated the putative myelin content of cingulum bundle in patients with schizophrenia.

Seventeen clinically stable patients with schizophrenia and 20 controls were recruited for this 7T MRI study. We used a region-of-interest method and extracted magnetization transfer ratio (MTR) from left and right dorsal cingulum bundles and estimated patients v. controls differences. We also related the cingulum MTR values to the severity of Schneiderian delusions.

Patients had a significant reduction in the MTR, indicating reduced myelin content, in the cingulum bundle (right cingulum Hedges’ g = 0.91; left cingulum g = 0.03). The reduced MTR of left cingulum was associated with higher severity of Schneiderian delusions (τ = −0.45, p = 0.026) but no such relationship was seen for the right cingulum MTR (τ = −0.136, p = 0.50) among patients. The association between the left cingulum MTR and Schneiderian delusions was not explained by the presence of other delusions, hallucinations, disorganization or negative symptoms.

Dysmyelination of the cingulum bundle is seen in a subgroup of patients with schizophrenia and may be involved in the mechanism of Schneiderian delusions.

Despite the high prevalence of mental disorders, mental health literacy has been comparatively neglected. People's symptom-management strategies will be influenced by their mental health literacy. This study sought to determine the feasibility of using the World Health Organization mhGAP-Intervention Guide (IG) as an educational tool for one-on-one contact in a clinical setting to increase literacy on the specified mental disorders.

This study was conducted in 20 health facilities in Makueni County, southeast Kenya which has one of the poorest economies in Kenya. It has no psychiatrist or clinical psychologist. We recruited 3267 participants from a community that had already been exposed to community mental health services. We used Mental Health Knowledge Schedule to measure the changing patterns of mental health knowledge after a period of 3 months, following a training intervention using the WHO mhGAP-IG.

Overall, there was a significant increase in mental health related knowledge [mean range 22.4–23.5 for both post-test and pre-test scores (p < 0.001)]. This increase varied with various socio-demographic characteristics such as sex, marital status, level of education, employment status and wealth index.

mhGAP-IG is a feasible tool to increase mental health literacy in low-resource settings where there are no mental health specialists. Our study lends evidence that the WHO Mental Health Action Plan 2013–2020 and reduction of the treatment gap may be accelerated by the use of mhGAP-IG through improving knowledge about mental illness and potentially subsequent help seeking for early diagnosis and treatment.

Patient expectancy is an important source of placebo effects in antidepressant clinical trials, but all prior studies measured expectancy prior to the initiation of medication treatment. Little is known about how expectancy changes during the course of treatment and how such changes influence clinical outcome. Consequently, we undertook the first analysis to date of in-treatment expectancy during antidepressant treatment to identify its clinical and demographic correlates, typical trajectories, and associations with treatment outcome.

Data were combined from two randomized controlled trials of antidepressant medication for major depressive disorder in which baseline and in-treatment expectancy assessments were available. Machine learning methods were used to identify pre-treatment clinical and demographic predictors of expectancy. Multilevel models were implemented to test the effects of expectancy on subsequent treatment outcome, disentangling within- and between-patient effects.

Random forest analyses demonstrated that whereas more severe depressive symptoms predicted lower pre-treatment expectancy, in-treatment expectancy was unrelated to symptom severity. At each measurement point, increased in-treatment patient expectancy significantly predicted decreased depressive symptoms at the following measurement (B = −0.45, t = −3.04, p = 0.003). The greater the gap between expected treatment outcomes and actual depressive severity, the greater the subsequent symptom reductions were (B = 0.49, t = 2.33, p = 0.02).

Greater in-treatment patient expectancy is associated with greater subsequent depressive symptom reduction. These findings suggest that clinicians may benefit from monitoring and optimizing patient expectancy during antidepressant treatment. Expectancy may represent another treatment parameter, similar to medication compliance and side effects, to be regularly monitored during antidepressant clinical management.

We examined the prevalence of self-perceived respiratory symptoms (SRS) in the absence of any objective findings of respiratory pathology, and the association of such prevalence with psychological factors and healthcare use in the general population.

The study was conducted among a nationally representative sample of Finnish adults (BRIF8901). Respiratory functioning was measured by a spirometry test. Structured questionnaires were used to measure SRS, physician visits and psychological factors of alexithymia, sense of coherence, illness worry and common mental disorders. Individuals with a diagnosed respiratory disease or a severe psychiatric disorder, determined in a diagnostic interview, were excluded, giving a sample comprising 4544 participants.

Twenty-six per cent of the general population and 36% of those with no diagnosed severe psychiatric disorder or respiratory disease experienced SRS despite a normal spirometry result. Psychological factors were associated with SRS (0.0001 < p < 0.032), and on the number of physician visit explaining 42.7% of the difference in visits between individuals with and without SRS, respectively. Illness worry was associated most strongly with SRS [odds ratio (OR) 1.29, 95% confidence interval (CI) 1.19–1.41, p < 0.0001] and higher numbers of physician visits (OR 1.35, CI 1.32–1.38, p < 0.00001), even after several adjustments.

Respiratory symptoms without objective findings are common in the general population. The study results underline the role of psychological factors in the reporting of respiratory symptoms and the associated medical burden, thereby indicating the functional nature of the symptomatology.

Social disadvantage consistently predicts both self-reported distress and clinically diagnosed disorders such as depression. Yet, many individuals who are exposed to disadvantage do not report high levels of distress. This study extends our recent work showing that high cognitive ability may protect against the negative health consequences of exposure to disadvantaged backgrounds. We test whether this ‘buffer effect’ exists across clinically relevant indices of mental health in a population-representative sample.

In total, 27 985 participants were drawn from the UK Household Longitudinal Study (Understanding Society). Clinical diagnoses of depression and clinically relevant measures of psychological distress [i.e. Short Form-12 (SF-12) Mental Component, General Health Questionnaire (GHQ)] and trait neuroticism were assessed. Cognitive ability was derived from performance on word recall, verbal fluency and numerical ability tasks. Early-life disadvantage was gauged using family background measures assessing parental education and occupation at age 14.

Background disadvantage predicted increased levels of reported psychological distress and neuroticism. These associations were moderated by cognitive ability. Across all available mental health measures, the negative association between early-life disadvantage and poor adult mental health was strongest at low (−1 s.d.) cognitive ability and was no longer evident at high (+1 s.d.) levels of cognitive ability.

The results provide support for a cognitive buffering hypothesis linking high cognitive ability to a decrease in the magnitude of the social gradient in mental health. Those disadvantaged by both low socioeconomic status and low cognitive ability may benefit from targeted prevention and treatment programmes aiming to reduce socioeconomic disparities in mental health.

Studies on the stability of genetic risk for depression have relied on self-reported symptoms rather than diagnoses and/or short follow-up time. Our aim is to determine to what degree genetic and environmental influences on clinically assessed major depressive disorder (MDD) are stable between age 18 and 45.

A population-based sample of 11 727 twins (6875 women) born between 1967 and 1991 was followed from 2006 to 2015 in health registry data from primary care that included diagnoses provided by treating physicians. Individuals with schizophrenia or bipolar disorder (n = 163) were excluded. We modelled genetic and environmental risk factors for MDD in an accelerated longitudinal design.

The best-fitting model indicated that genetic influences on MDD were completely stable from ages 18 to 45 and explained 38% of the variance. At each age, the environmental risk of MDD was determined by the risk at the preceding observation, plus new environmental risk, with an environmental correlation of +0.60 over 2 years. The model indicated no effects of shared environment and no environmental effects stable throughout the observational period. All long-term stability was therefore explained by genetic factors.

Different processes unfolded in the genetic and environmental risk for MDD. The genetic component is stable from later adolescence to middle adulthood and accounted for nearly all long-term stability. Therefore, molecular genetic studies can use age-heterogenous samples when investigating genetic risk variants of MDD. Environmental risk factors were stable over a short span of years with associations rapidly decreasing and no evidence of permanent environmental scarring.

Maternal smoking during pregnancy (MSDP) has been linked to offspring's externalizing problems. It has been argued that socio-demographic factors (e.g. maternal age and education), co-occurring environmental risk factors, or pleiotropic genetic effects may account for the association between MSDP and later outcomes. This study provides a comprehensive investigation of the association between MSDP and a single harmonized component of externalizing: aggressive behaviour, measured throughout childhood and adolescence.

Data came from four prospective twin cohorts – Twins Early Development Study, Netherlands Twin Register, Childhood and Adolescent Twin Study of Sweden, and FinnTwin12 study – who collaborate in the EU-ACTION consortium. Data from 30 708 unrelated individuals were analysed. Based on item level data, a harmonized measure of aggression was created at ages 9–10; 12; 14–15 and 16–18.

MSDP predicted aggression in childhood and adolescence. A meta-analysis across the four samples found the independent effect of MSDP to be 0.4% (r = 0.066), this remained consistent when analyses were performed separately by sex. All other perinatal factors combined explained 1.1% of the variance in aggression across all ages and samples (r = 0.112). Paternal smoking and aggressive parenting strategies did not account for the MSDP-aggression association, consistent with the hypothesis of a small direct link between MSDP and aggression.

Perinatal factors, including MSDP, account for a small portion of the variance in aggression in childhood and adolescence. Later experiences may play a greater role in shaping adolescents’ aggressive behaviour.

Attention-deficit/hyperactivity disorder (ADHD) is a developmental condition that profoundly affects quality of life. Although mounting evidence now suggests uncontrolled mind-wandering as a core aspect of the attentional problems associated with ADHD, the neural mechanisms underpinning this deficit remains unclear. To that extent, competing views argue for (i) excessive generation of task-unrelated mental content, or (ii) deficiency in the control of task-relevant cognition.

In a cross-sectional investigation of a large neurotypical cohort (n = 184), we examined alterations in the intrinsic brain functional connectivity architecture of the default mode (DMN) and frontoparietal (FPN) networks during resting state functional magnetic resonance imaging in relation to ADHD symptomatology, which could potentially underlie changes in ongoing thought within variable environmental contexts.

The results illustrated that ADHD symptoms were linked to lower levels of detail in ongoing thought while the participants made more difficult, memory based decisions. Moreover, greater ADHD scores were associated with lower levels of connectivity between the DMN and right sensorimotor cortex, and between the FPN and right ventral visual cortex. Finally, a combination of high levels of ADHD symptomology with reduced FPN connectivity to the visual cortex was associated with reduced levels of detail in thought.

The results of our study suggest that the frequent mind-wandering observed in ADHD may be an indirect consequence of the deficient control of ongoing cognition in response to increasing environmental demands, and that this may partly arise from dysfunctions in the intrinsic organisation of the FPN at rest.