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The Hierarchical Taxonomy of Psychopathology (HiTOP) organizes phenotypes of mental disorder based on empirical covariation, offering a comprehensive organizational framework from narrow symptoms to broader patterns of psychopathology. We argue that established self-report measures of psychopathology from the pre-HiTOP era should be systematically integrated into HiTOP to foster cumulative research and further the understanding of psychopathology structure. Hence, in this study, we mapped 92 established psychopathology (sub)scales onto the current HiTOP working model using data from an extensive battery of self-report assessments that was completed by community participants and outpatients (N = 909). Content validity ratings of the item pool were used to select indicators for a bifactor-(S-1) model of the p factor and five HiTOP spectra (i.e., internalizing, thought disorder, detachment, disinhibited externalizing, and antagonistic externalizing). The content-based HiTOP scales were validated against personality disorder diagnoses as assessed by standardized interviews. We then located established scales within the taxonomy by estimating the extent to which scales reflected higher-level HiTOP dimensions. The analyses shed light on the location of established psychopathology scales in HiTOP, identifying pure markers and blends of HiTOP spectra, as well as pure markers of the p factor (i.e., scales assessing mentalizing impairment and suspiciousness/epistemic mistrust). National Institute for Health Research (NIHR) Senior Investigator Award [NF-SI0514-10157]; NIH-NIDS [5R01NS092701-03]; Wellcome Trust Published version This work was supported by a National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI0514-10157) awarded to Peter Fonagy. The work was also supported by NIH-NIDS Grant 5R01NS092701-03 and a Wellcome Trust Principal Research Fellowship awarded to P. Read Montague.

The evolution of human cognitive function is reliant on complex social interactions which form the behavioural foundation of who we are. These social capacities are subject to dramatic change in disease and injury; yet their supporting neural substrates remain poorly understood. Hyperscanning employs functional neuroimaging to simultaneously assess brain activity in two individuals and offers the best means to understand the neural basis of social interaction. However, present technologies are limited, either by poor performance (low spatial/temporal precision) or an unnatural scanning environment (claustrophobic scanners, with interactions via video). Here, we describe hyperscanning using wearable magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs). We demonstrate our approach by simultaneously measuring brain activity in two subjects undertaking two separate tasks—an interactive touching task and a ball game. Despite large and unpredictable subject motion, sensorimotor brain activity was delineated clearly, and the correlation of the envelope of neuronal oscillations between the two subjects was demonstrated. Our results show that unlike existing modalities, OPM-MEG combines high-fidelity data acquisition and a naturalistic setting and thus presents significant potential to investigate neural correlates of social interaction. Published version

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