Connecting quantitatively derived personality-psychopathology models and neuroscience

Midfrontal conflict theta and parietal P300 are linked to a latent factor of DSM externalising disorders

Psychiatric illnesses form spectra rather than categories, with symptoms varying continuously across individuals, i.e., there is no clear break between health and disorder. Dimensional measures of behaviour and brain activity are promising targets for studying biological mechanisms that are common across disorders. Here, we assessed the extent to which neural measures of the sensitivity of the three biological systems in the reinforcement sensitivity theory (RST) could account for individual differences in a latent general factor estimated from symptom counts across externalising disorders (EXTs). RST explanatory power was pitted against reduced P300, a reliable indicator of externalising per previous research. We assessed 206 participants for DSM-5 EXTs (antisocial personality disorder, conduct disorder, attention-deficit/hyperactivity disorder, intermittent explosive disorder symptoms, alcohol use disorder, and cannabis use disorder). Of the final sample, 49% met diagnostic criteria for at least one of the EXTs. Electroencephalographic measures of the sensitivities of the behavioural activation system (BAS), the fight/flight/freeze system, and the behavioural inhibition system (BIS), as well as P300 were extracted from the gold bar-lemon and stop-signal tasks. As predicted, we found that low neural BIS sensitivity and low P300 were uniquely and negatively associated with our latent factor of externalising. Contrary to prediction, neural BAS/"dopamine" sensitivity was not associated with externalising. Our results provide empirical support for low BIS sensitivity and P300 as neural mechanisms common to disorders within the externalising spectrum; but, given the low N involved, future studies should seek to assess the replicability of our findings and, in particular, the differential involvement of the three RST systems.

New approaches to deep phenotyping in addictions

OBJECTIVE

The causes of substance use disorders (SUDs) are largely unknown and the effectiveness of their treatments is limited. One crucial impediment to research and treatment progress surrounds how SUDs are classified and diagnosed. Given the substantial heterogeneity among individuals diagnosed with a given SUD (e.g., alcohol use disorder [AUD]), identifying novel research and treatment targets and developing new study designs is daunting.

METHOD

In this article, we review and integrate two recently developed frameworks, the National Institute on Drug Abuse's Phenotyping Assessment Battery (NIDA PhAB) and the Hierarchical Taxonomy of Psychopathology (HiTOP), that hope to accelerate progress in understanding the causes and consequences of psychopathology by means of deep phenotyping, or finer-grained analysis of phenotypes.

RESULTS AND CONCLUSIONS

NIDA PhAB focuses on addiction-related processes across multiple units of analysis, whereas HiTOP focuses on clinical phenotypes and covers a broader range of psychopathology. We highlight that NIDA PhAB and HiTOP together provide deep and broad characterizations of people diagnosed with SUDs and complement each other in their efforts to address widely known limitations of traditional classification systems and their diagnostic categories. Next, we show how NIDA PhAB and HiTOP can be integrated to facilitate optimal rich phenotyping of addiction-related phenomena. Finally, we argue that such deep phenotyping promises to advance our understanding of the neurobiology of SUD and addiction, which will guide the development of personalized medicine and interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Specialised minds: extending adaptive explanations of personality to the evolution of psychopathology

Traditional evolutionary theory invoked natural and sexual selection to explain species- and sex-typical traits. However, some heritable inter-individual variability in behaviour and psychology - personality - is probably adaptive. Here we extend this insight to common psychopathological traits. Reviewing key findings from three background areas of importance - theoretical models, non-human personality and evolved human social dynamics - we propose that a combination of social niche specialisation, negative frequency-dependency, balancing selection and adaptive developmental plasticity should explain adaptation for individual differences in psychology - 'specialised minds' - explaining some variance in personality and psychopathology trait dimensions, which share various characteristics. We suggest that anthropological research of behavioural differences should be extended past broad demographic factors (age and sex) to include individual specialisations. As a first step towards grounding psychopathology in ancestral social structure, we propose a minimum plausible prevalence, given likely ancestral group sizes, for negatively frequency-dependent phenotypes to be maintained as specialised tails of adaptive distributions - below the calculated prevalence, specialisation is highly unlikely. For instance, chronic highly debilitating forms of autism or schizophrenia are too rare for such explanations, whereas attention-deficit-hyperactivity disorder and broad autism phenotypes are common enough to have existed in most hunter-gatherer bands, making adaptive explanations more plausible.

Non-human contributions to personality neuroscience – from fish through primates. An introduction to the special issue

The most fundamental emotional systems that show trait control are evolutionarily old and extensively conserved. Psychology in general has benefited from non-human neuroscience and from the analytical simplicity of behaviour in those with simpler nervous systems. It has been argued that integration between personality, psychopathology, and neuroscience is particularly promising if we are to understand the neurobiology of human experience. Here, we provide some general arguments for a non-human approach being at least as productive in relation to personality, psychopathology, and their interface. Some early personality theories were directly linked to psychopathology (e.g., Eysenck, Panksepp, and Cloninger). They shared a common interest in brain systems that naturally led to the use of non-human data; behavioural, neural, and pharmacological. In Eysenck’s case, this also led to the selective breeding, at the Maudsley Institute, of emotionally reactive and non-reactive strains of rat as models of trait neuroticism or trait emotionality. Dimensional personality research and categorical approaches to clinical disorder then drifted apart from each other, from neuropsychology, and from non-human data. Recently, the conceptualizations of both healthy personality and psychopathology have moved towards a common hierarchical trait perspective. Indeed, the proposed two sets of trait dimensions appear similar and may even be eventually the same. We provide, here, an introduction to this special issue of Personality Neuroscience, where the authors provide overviews of detailed areas where non-human data inform human personality and its psychopathology or provide explicit models for translation to human neuroscience. Once all the papers in the issue have appeared, we will also provide a concluding summary of them.