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Investing in strangers in a socio-economic exchange is risky, as we may be uncertain whether they will reciprocate. Nevertheless, the potential rewards for cooperating can be great. Here, we used a cross sectional sample (n = 784) to study how the challenges of cooperation versus defection are negotiated across an important period of the lifespan: from adolescence to young adulthood (ages 14 to 25). We quantified social behaviour using a multi round investor-trustee task, phenotyping individuals using a validated model whose parameters characterise patterns of real exchange and constitute latent social characteristics. We found highly significant differences in investment behaviour according to age, sex, socio-economic status and IQ. Consistent with the literature, we showed an overall trend towards higher trust from adolescence to young adulthood but, in a novel finding, we characterized key cognitive mechanisms explaining this, especially regarding socio-economic risk aversion. Males showed lower risk-aversion, associated with greater investments. We also found that inequality aversion was higher in females and, in a novel relation, that socio-economic deprivation was associated with more risk averse play. Published version

Multiple psychiatric disorders have been associated with abnormalities in both the innate and adaptive immune systems. The role of these abnormalities in pathogenesis, and whether they are driven by psychiatric risk variants, remains unclear. We test for enrichment of GWAS variants associated with multiple psychiatric disorders (cross-disorder or trans-diagnostic risk), or 5 specific disorders (cis-diagnostic risk), in regulatory elements in immune cells. We use three independent epigenetic datasets representing multiple organ systems and immune cell subsets. Trans-diagnostic and cis-diagnostic risk variants (for schizophrenia and depression) are enriched at epigenetically active sites in brain tissues and in lymphoid cells, especially stimulated CD4+ T cells. There is no evidence for enrichment of either trans-risk or cis-risk variants for schizophrenia or depression in myeloid cells. This suggests a possible model where environmental stimuli activate T cells to unmask the effects of psychiatric risk variants, contributing to the pathogenesis of mental health disorders., This work was funded by an Medical Research Council award MR/S006257/1 (M.E.L.); NIHR Senior Investigator award (E.T.B); Open Targets grant OTAR040 (B.S., G.T.). Wellcome Trust grant WT206194 (G.T.); US Veterans Affairs Career Development Award (D.F.L.); NIHR Research Professorship RP-2017-08-ST2-002 (M.R.C.). This work was additionally supported by the NIHR Cambridge Biomedical Research Centre.

Funder: U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH), The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from cells of origin, through axon trajectories, to synaptic terminals. Advances in neuroimaging combined with network science have taken the lead in developing complex wiring diagrams or connectomes of the human brain. A key question is how well these magnetic resonance imaging (MRI)-derived networks and hubs reflect the anatomic "hard wiring" first proposed to underlie the distribution of information for large-scale network interactions. In this review, we address this challenge by focusing on what is known about monosynaptic prefrontal cortical connections in non-human primates and how this compares to MRI-derived measurements of network organization in humans. First, we outline the anatomic cortical connections and pathways for each prefrontal cortex (PFC) region. We then review the available MRI-based techniques for indirectly measuring structural and functional connectivity, and introduce graph theoretical methods for analysis of hubs, modules, and topologically integrative features of the connectome. Finally, we bring these two approaches together, using specific examples, to demonstrate how monosynaptic connections, demonstrated by tract-tracing studies, can directly inform understanding of the composition of PFC nodes and hubs, and the edges or pathways that connect PFC to cortical and subcortical areas.

Psychological androgyny has long been associated with greater cognitive flexibility, adaptive behavior, and better mental health, but whether a similar concept can be defined using neural features remains unknown. Using the neuroimaging data from 9620 participants, we found that global functional connectivity was stronger in the male brain before middle age but became weaker after that, when compared with the female brain, after systematic testing of potentially confounding effects. We defined a brain gender continuum by estimating the likelihood of an observed functional connectivity matrix to represent a male brain. We found that participants mapped at the center of this continuum had fewer internalizing symptoms compared with those at the 2 extreme ends. These findings suggest a novel hypothesis proposing that there exists a neuroimaging concept of androgyny using the brain gender continuum, which may be associated with better mental health in a similar way to psychological androgyny.

The effects of the COVID-19 pandemic on population mental health are unknown. We need to understand the scale of any such impact in different sections of the population, who is most affected and how best to mitigate, prevent and treat any excess morbidity. We propose a coordinated and interdisciplinary mental health science response.

Figure S1. Analysis of residual head movement based on DVARS, which is a time series of the root mean squares (RMS) of the derivatives of the timecourses of all within-brain voxels for each volume. The analysis was conducted using code publishes by the Brain and Mind Lab at Aalto University, Finland. (PDF 345 kb)

Background Autism is a highly varied and heritable neurodevelopmental condition, and common variants explain approximately 50% of the genetic variance of autism. One of the genes implicated in autism is the oxytocin receptor (OXTR). The current study combined genetic and brain imaging (fMRI) data to examine the moderating effect of genotype on the association between diagnosis and brain activity in response to a test of cognitive empathy. Methods Participants were adolescents (mean age = 14.7 ± 1.7) who were genotyped for single nucleotide polymorphisms (SNPs) within the OXTR and underwent functional brain imaging while completing the adolescent version of the ‘Reading the Mind in the Eyes’ Test (Eyes Test). Results Two (rs2254298, rs53576) of the five OXTR SNPs examined were significantly associated with brain activity during the Eyes Test, and three of the SNPs (rs2254298, rs53576, rs2268491) interacted with diagnostic status to predict brain activity. All of the effects localized to the right supramarginal gyrus (rSMG) and an overlap analysis revealed a large overlap of the effects. An exploratory analysis showed that activity within an anatomically defined rSMG and genotype can predict diagnostic status with reasonable accuracy. Conclusions This is one of the first studies to investigate OXTR and brain function in autism. The findings suggest a neurogenetic mechanism by which OXTR-dependent activity within the rSMG is related to the aetiology of autism. Electronic supplementary material The online version of this article (10.1186/s13229-019-0258-4) contains supplementary material, which is available to authorized users.

Assessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions. We illustrate the use of LCS models with two empirical examples. In a lifespan cognitive training study (COGITO, N=204 (N=32 imaging) on two waves) we observe correlated change in brain and behaviour in the context of a high-intensity training intervention. In an adolescent development cohort (NSPN, N=176, two waves) we find greater variability in cortical thinning in males than in females. To facilitate the adoption of LCS by the developmental community, we provide analysis code that can be adapted by other researchers and basic primers in two freely available SEM software packages (lavaan and Ωnyx).HighlightsWe describe Latent change score modelling as a flexible statistical toolKey developmental questions can be readily formalized using LCS modelsWe provide accessible open source code and software examples to fit LCS modelsWhite matter structural change is negatively correlated with processing speed gainsFrontal lobe thinning in adolescence is more variable in males than females

Network analysis can help uncover meaningful regularities in the organization of complex systems. Among these, rich clubs are a functionally important property of a variety of social, technological and biological networks. Rich clubs emerge when nodes that are somehow prominent or 'rich' (e.g., highly connected) interact preferentially with one another. The identification of rich clubs is non-trivial, especially in weighted networks, and to this end multiple distinct metrics have been proposed. Here we describe a unifying framework for detecting rich clubs which intuitively generalizes various metrics into a single integrated method. This generalization rests upon the explicit incorporation of randomized control networks into the measurement process. We apply this framework to real-life examples, and show that, depending on the selection of randomized controls, different kinds of rich-club structures can be detected, such as topological and weighted rich clubs., 6 pages, 3 figures

Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimal in the critical state. Recent experimental observations of neuronal activity patterns following power-law distributions, a hallmark of systems at a critical state, have led to the hypothesis that human brain dynamics could be poised at a phase transition between ordered and disordered activity. A so far unresolved question concerns the medical significance of critical brain activity and how it relates to pathological conditions. Using data from invasive electroencephalogram recordings from humans we show that during epileptic seizure attacks neuronal activity patterns deviate from the normally observed power-law distribution characterizing critical dynamics. The comparison of these observations to results from a computational model exhibiting self-organized criticality (SOC) based on adaptive networks allows further insights into the underlying dynamics. Together these results suggest that brain dynamics deviates from criticality during seizures caused by the failure of adaptive SOC., Author Summary Over the recent years it has become apparent that the concept of phase transitions is not only applicable to the systems classically considered in physics. It applies to a much wider class of complex systems exhibiting phases, characterized by qualitatively different types of long-term behavior. In the critical states, which are located directly at the transition, small changes can have a large effect on the system. This and other properties of critical states prove to be advantageous for computation and memory. It is therefore suspected that also cerebral neural networks operate close to criticality. This is supported by the in vitro and in vivo measurements of power-laws of certain scaling relationships that are the hallmarks of phase transitions. While critical dynamics is arguably an attractive mode of normal brain functioning, its relation to pathological brain conditions is still unresolved. Here we show that brain dynamics deviates from a critical state during epileptic seizure attacks in vivo. Furthermore, insights from a computational model suggest seizures to be caused by the failure of adaptive self-organized criticality, a mechanism of self-organization to criticality based on the interplay between network dynamics and topology.

National audience; Les processus à longue mémoire peuvent sérieusement compromettre l'estimation des paramètres des modèles linéaires ainsi que les variances associées. Les modèles classiques ARMA peuvent fournir une approche adéquate au problème de courte dépendance pour les systèmes linéaires invariants dans le temps. Cependant, ils s'avèrent inefficaces pour des bruits invariants d'échelle. Ici, nous présentons une nouvelle approche de moindres-carrés pondérés dans le domaine des ondelettes (MCPO). Celle-ci fournit un estimateur du maximum de vraissemblance (MV) approché des paramètres du signal et du bruit. Les propriétés statistiques de cet estimateur, y compris une approximation des limites de Cramèr-Rao, sont établies d'un point de vue théorique puis comparées à ses performances empiriques pour diverses situations de données simulées. En comparaison aux moindres carrés ordinaires (MCO) ou encore aux estimateurs type ARMA, on montre que le MCPO est plus efficace et permet un excellent contrôle des risques de 1ère et 2nde espèce. La méthode est ensuite illustrée sur des séquences neurophysiologiques d'IRMf.

Much is known about how age affects the brain during tightly controlled, though largely contrived, experiments, but do these effects extrapolate to everyday life? Naturalistic stimuli, such as movies, closely mimic the real world and provide a window onto the brain's ability to respond in a timely and measured fashion to complex, everyday events. Young adults respond to these stimuli in a highly synchronized fashion, but it remains to be seen how age affects neural responsiveness during naturalistic viewing. To this end, we scanned a large (N = 218), population-based sample from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) during movie-watching. Intersubject synchronization declined with age, such that older adults' response to the movie was more idiosyncratic. This decreased synchrony related to cognitive measures sensitive to attentional control. Our findings suggest that neural responsivity changes with age, which likely has important implications for real-world event comprehension and memory.

Supplemental material, supplementary_file for Fractionation of impulsive and compulsive trans-diagnostic phenotypes and their longitudinal associations by Samuel R Chamberlain, Jeggan Tiego, Leonardo F Fontenelle, Roxanne Hook, Linden Parkes, Rebecca Segrave, Tobias U Hauser, Ray J Dolan, Ian M Goodyer, Ed Bullmore, Jon E Grant and Murat Yücel in Australian & New Zealand Journal of Psychiatry

Supplemental material, supplementary_file for Fractionation of impulsive and compulsive trans-diagnostic phenotypes and their longitudinal associations by Samuel R Chamberlain, Jeggan Tiego, Leonardo F Fontenelle, Roxanne Hook, Linden Parkes, Rebecca Segrave, Tobias U Hauser, Ray J Dolan, Ian M Goodyer, Ed Bullmore, Jon E Grant and Murat Yücel in Australian & New Zealand Journal of Psychiatry

Supplemental material, sj-pdf-1-ctj-10.1177_17407745211024764 for Challenges and opportunities for conducting a vaccine trial during the COVID-19 pandemic in the United Kingdom by M Estée Török, Benjamin R Underwood, Mark Toshner, Claire Waddington, Emad Sidhom, Katherine Sharrocks, Rachel Bousfield, Charlotte Summers, Caroline Saunders, Zoe McIntyre, Helen Morris, Jo Piper, Gloria Calderon, Sarah Dennis, Tracy Assari, Anita Marguerie de Rotrou, Ashley Shaw, John Bradley, John O’Brien, Robert C Rintoul, Ian Smith, Ed Bullmore and Krishna Chatterjee in Clinical Trials

The COVID-19 pandemic has resulted in unprecedented challenges for healthcare systems worldwide. It has also stimulated research in a wide range of areas including rapid diagnostics, novel therapeutics, use of technology to track patients and vaccine development. Here, we describe our experience of rapidly setting up and delivering a novel COVID-19 vaccine trial, using clinical and research staff and facilities in three National Health Service Trusts in Cambridgeshire, United Kingdom. We encountered and overcame a number of challenges including differences in organisational structures, research facilities available, staff experience and skills, information technology and communications infrastructure, and research training and assessment procedures. We overcame these by setting up a project team that included key members from all three organisations that met at least daily by teleconference. This group together worked to identify the best practices and procedures and to harmonise and cascade these to the wider trial team. This enabled us to set up the trial within 25 days and to recruit and vaccinate the participants within a further 23 days. The lessons learned from our experiences could be used to inform the conduct of clinical trials during a future infectious disease pandemic or public health emergency.

Supplemental material, sj-pdf-1-ctj-10.1177_17407745211024764 for Challenges and opportunities for conducting a vaccine trial during the COVID-19 pandemic in the United Kingdom by M Estée Török, Benjamin R Underwood, Mark Toshner, Claire Waddington, Emad Sidhom, Katherine Sharrocks, Rachel Bousfield, Charlotte Summers, Caroline Saunders, Zoe McIntyre, Helen Morris, Jo Piper, Gloria Calderon, Sarah Dennis, Tracy Assari, Anita Marguerie de Rotrou, Ashley Shaw, John Bradley, John O’Brien, Robert C Rintoul, Ian Smith, Ed Bullmore and Krishna Chatterjee in Clinical Trials

OBJECTIVE: Young adulthood is a crucial neurodevelopmental period during which impulsive and compulsive problem behaviours commonly emerge. While traditionally considered diametrically opposed, impulsive and compulsive symptoms tend to co-occur. The objectives of this study were as follows: (a) to identify the optimal trans-diagnostic structural framework for measuring impulsive and compulsive problem behaviours, and (b) to use this optimal framework to identify common/distinct antecedents of these latent phenotypes. METHOD: In total, 654 young adults were recruited as part of the Neuroscience in Psychiatry Network, a population-based cohort in the United Kingdom. The optimal trans-diagnostic structural model capturing 33 types of impulsive and compulsive problem behaviours was identified. Baseline predictors of subsequent impulsive and compulsive trans-diagnostic phenotypes were characterised, along with cross-sectional associations, using partial least squares. RESULTS: Current problem behaviours were optimally explained by a bi-factor model, which yielded dissociable measures of impulsivity and compulsivity, as well as a general disinhibition factor. Impulsive problem behaviours were significantly explained by prior antisocial and impulsive personality traits, male gender, general distress, perceived dysfunctional parenting and teasing/arguments within friendships. Compulsive problem behaviours were significantly explained by prior compulsive traits and female gender. CONCLUSION: This study demonstrates that trans-diagnostic phenotypes of 33 impulsive and compulsive problem behaviours are identifiable in young adults, utilising a bi-factor model based on responses to a single questionnaire. Furthermore, these phenotypes have different antecedents. The findings yield a new framework for fractionating impulsivity and compulsivity, and suggest different early intervention targets to avert emergence of problem behaviours. This framework may be useful for future biological and clinical dissection of impulsivity and compulsivity.

¬¬¬Abstract Objective: To explore the possibilities of radioligands against the mitochondrial outer membrane protein TSPO as biomarkers for mitochondrial disease, we performed positron emission tomography (PET)-MR brain imaging with [11C]PK11195 in 14 patients with genetically confirmed mitochondrial disease and 33 matched controls. Methods: A case-control study of PET-MR imaging with the TSPO radioligand [11C]PK11195. Results: 46% of symptomatic patients had volumes of abnormal radiotracer binding greater than the 95th percentile in controls. [11C]PK11195 binding was generally greater in grey matter and significantly decreased in white matter. This was most striking in patients with nuclear TYMP or mitochondrial m.3243A>G MT-TL1 mutations, in keeping with differences in mitochondrial density seen post mortem. Some regional binding patterns corresponded to clinical presentation and underlying mutation, even in the absence of structural changes on MRI. This was most obvious for the cerebellum, where patients with ataxia had decreased binding in the cerebellar cortex, but not necessarily volume loss. Overall, there was a positive correlation between aberrant [11C]PK11195 binding and clinical severity. Conclusion: These findings endorse the use of PET imaging with TSPO radioligands as a non-invasive in vivo biomarker of mitochondrial pathology. Classification of Evidence: This study provides Class III evidence that PET-MR brain imaging with TSPO radioligands identifies mitochondrial pathology.

Humans can process facial characteristics both rapidly and accurately, especially emotional expressions. Evoked-related potentials were used to examine brain activity during presentation of happy and neutral faces in an oddball paradigm. Mismatch negativity (MMN)- like activity was evident in most of the channels starting in lateral posterior channels and then spreading medially and anteriorly with a maximum value arround 280 ms.

Psychophysical studies show that human listeners are highly sensitive to temporal asymmetry. When an amplitude modulator that is asymmetric in time is applied to a sinusoidal tone, the direction of the asymmetry affects the timbre of the sound. Magnetoencephalography study was carried out to investigate the temporal processing at the level of the auditory cortex by analyzing middle latency auditory evoked fields (MAEF). Spatio-temporal analysis revealed the effects of temporal asymmetry at the level of the primary auditory cortex. The resulting morphology of the source waveforms depended strongly on the temporal features of the envelope of the sounds and less on the specific spectral content of the carrier.

International audience; no abstract

International audience; no abstract