By some accounts, as many as 93% of individuals diagnosed with antisocial personality disorder (ASPD) or psychopathy also meet criteria for some form of substance use disorder (SUD). This high level of comorbidity, combined with an overlapping biopsychosocial profile, and potentially interacting features, has made it difficult to delineate the shared/unique characteristics of each disorder. Moreover, while rarely acknowledged, both SUD and antisociality exist as highly heterogeneous disorders in need of more targeted parcellation. While emerging data-driven nosology for psychiatric disorders (e.g., Research Domain Criteria (RDoC), Hierarchical Taxonomy of Psychopathology (HiTOP)) offers the opportunity for a more systematic delineation of the externalizing spectrum, the interrogation of large, complex neuroimaging-based datasets may require data-driven approaches that are not yet widely employed in psychiatric neuroscience. With this in mind, the proposed article sets out to provide an introduction into machine learning methods for neuroimaging that can help parse comorbid, heterogeneous externalizing samples. The modest machine learning work conducted to date within the externalizing domain demonstrates the potential utility of the approach but remains highly nascent. Within the paper, we make suggestions for how future work can make use of machine learning methods, in combination with emerging psychiatric nosology systems, to further diagnostic and etiological understandings of the externalizing spectrum. Finally, we briefly consider some challenges that will need to be overcome to encourage further progress in the field.

Traditionally, personality has been conceptualized in terms of dimensions of human experience – habitual ways of thinking, feeling, and behaving. By contrast, psychopathology has traditionally been conceptualized in terms of categories of disorder – disordered thinking, feeling, and behaving. The empirical literature, however, routinely shows that psychopathology does not coalesce into readily distinguishable categories. Indeed, psychopathology tends to delineate dimensions that are relatively similar to dimensions of personality. In this special issue of Personality Neuroscience, authors took up the challenge of reconceptualizing personality and psychopathology in terms of connected and interrelated dimensions, and they considered the utility of pursuing neuroscientific inquiry from this more integrative perspective. In this editorial article, we provide the relevant background to the interface between personality, psychopathology, and neuroscience; summarize contributions to the special issue; and point toward directions for continued research and refinement. All told, it is evident that quantitatively derived, integrative models of personality–psychopathology represent a particularly promising conduit for advancing our understanding of the neurobiological foundation of human experience, both functional and dysfunctional.

Recently developed quantitative models of psychopathology (i.e., Hierarchical Taxonomy of Psychopathology) identify an Antagonistic Externalizing spectrum that captures the psychological disposition toward criminal and antisocial behavior. The purpose of the present study was to examine relations between Antagonistic psychopathology (and associated Five-Factor model Antagonism/Agreeableness) and neural functioning related to social-cognitive Theory of Mind using a large sample (N = 973) collected as part of the Human Connectome Project (Van Essen et al., 2013a). No meaningful relations between Antagonism/Antagonistic Externalizing and Theory of Mind-related neural activity or synchrony were observed (p < .005). We conclude by outlining methodological considerations (e.g., validity of social cognition task and low test–retest reliability of functional biomarkers) that may account for these null results, and present recommendations for future research.

Psychophysiological measures have become increasingly accessible to researchers and many have properties that indicate their use as individual difference indicators. For example, the error-related negativity (ERN), an event-related potential (ERP) thought to reflect error-monitoring processes, has been related to individual differences, such as Neuroticism and Conscientiousness traits. Although various tasks have been used to elicit the ERN, only a few studies have investigated its variability across tasks when examining the relations between the ERN and personality traits. In this project, we examined the relations of the ERN elicited from four variants of the Flanker task (Arrow, Social, Unpleasant, and Pleasant) that were created to maximize the differences in their relevance to personality traits. A sample of 93 participants with a history of treatment for psychopathology completed the four tasks as well as self-report measures of the general and maladaptive five-factor model (FFM) traits. Confirmatory factor analyses (CFAs) of ERN amplitudes indicated that three of the four tasks (Arrow, Social, and Unpleasant) were unidimensional. Another set of CFAs indicated that a general factor underlies the ERN elicited from all tasks as well as unique task-specific variances. The correlations of estimated latent ERN scores and personality traits did not reflect the hypothesized correlation patterns. Variability across tasks and the hierarchical model of the ERN may aid in understanding psychopathology dimensions and in informing future endeavors integrating the psychophysiological methods into the study of personality. Recommendations for future research on psychophysiological indicators as individual differences are discussed.

Quantitative models of psychopathology (i.e., HiTOP) propose that personality and psychopathology are intertwined, such that the various processes that characterize personality traits may be useful in describing and predicting manifestations of psychopathology. In the current study, we used data from the Human Connectome Project (N = 1050) to investigate neural activation following receipt of a reward during an fMRI task as one shared mechanism that may be related to the personality trait Extraversion (specifically its sub-component Agentic Extraversion) and internalizing psychopathology. We also conducted exploratory analyses on the links between neural activation following reward receipt and the other Five-Factor Model personality traits, as well as separate analyses by gender. No significant relations (p < .005) were observed between any personality trait or index of psychopathology and neural activation following reward receipt, and most effect sizes were null to very small in nature (i.e., r < |.05|). We conclude by discussing the appropriate interpretation of these null findings, and provide suggestions for future research that spans psychological and neurobiological levels of analysis.

Personality has been correlated with differences in cytokine expression, an indicator of peripheral inflammation; however, the associations between personality and central markers of inflammation have never been investigated in vivo in humans. Microglia are the resident macrophages of the central nervous system, and the first responders to tissue damage and brain insult. Microglial activation is associated with elevated expression of translocator protein 18kDa (TSPO), which can be imaged with positron emission tomography (PET) to quantify immune activation in the human brain. This study aimed to investigate the association between personality and TSPO expression across the psychosis spectrum. A total of 61 high-resolution [18F]FEPPA PET scans were conducted in 28 individuals at clinical high risk (CHR) for psychosis, 19 First-Episode Psychosis (FEP), and 14 healthy volunteers (HVs), and analyzed using a two-tissue compartment model and plasma input function to obtain a total volume of distribution (VT) as an index of brain TSPO expression (controlling for the rs6971 TSPO polymorphism). Personality was assessed using the Revised NEO Personality Inventory (NEO-PI-R). We found TSPO expression to be specifically associated with neuroticism. A positive association between TSPO expression and neuroticism was found in HVs, in contrast to a nonsignificant, negative association in CHR and significant negative association in FEP. The TSPO-associated neuroticism trait indicates an unexplored connection between neuroimmune activation and personality that varies across the psychosis spectrum.

A growing body of research supports the value of a multimodal assessment approach, drawing on measures from different response modalities, for clarifying how core biobehavioral processes relate to various clinical problems and dimensions of psychopathology. Using data for 507 healthy adults, the current study was undertaken to integrate self-report and neurophysiological (brain potential) measures as a step toward a multimodal measurement model for the trait of affiliative capacity (AFF) – a biobehavioral construct relevant to adaptive and maladaptive social-interpersonal functioning. Individuals low in AFF exhibit a lack of interpersonal connectedness, deficient empathy, and an exploitative-aggressive social style that may be expressed transdiagnostically in antagonistic externalizing or distress psychopathology. Specific aims were to (1) integrate trait scale and brain potential indicators into a multimodal measure of AFF and (2) evaluate associations of this multimodal measure with criterion variables of different types. Results demonstrated (1) success in creating a multimodal measure of AFF from self-report and neural indicators, (2) effectiveness of this measure in predicting both clinical-diagnostic and neurophysiological criterion variables, and (3) transdiagnostic utility of the multimodal measure at both specific-disorder and broad symptom-dimension levels. Our findings further illustrate the value of psychoneurometric operationalizations of biobehavioral trait dimensions as referents for clarifying transdiagnostic relationships between biological systems variables and empirically defined dimensions of psychopathology.

Posttraumatic stress disorder (PTSD) is often complicated by the after-effects of mild traumatic brain injury (mTBI). The mixture of brain conditions results in abnormal affective and cognitive functioning, as well as maladaptive behavior. To better understand how brain activity explains cognitive and emotional processes in these conditions, we used an emotional N-back task and functional magnetic resonance imaging (fMRI) to study neural responses in US military veterans after deployments to Iraq and Afghanistan. Additionally, we sought to examine whether hierarchical dimensional models of maladaptive personality could account for the relationship between combat-related brain conditions and fMRI responses under cognitive and affective challenge. FMRI data, measures of PTSD symptomatology (PTSS), blast-induced mTBI (bmTBI) severity, and maladaptive personality (MMPI-2-RF) were gathered from 93 veterans. Brain regions central to emotion regulation were selected for analysis, and consisted of bilateral amygdala, bilateral dorsolateral prefrontal (dlPFC), and ventromedial prefrontal/subgenual anterior cingulate (vmPFC-sgACC). Cognitive load increased activity in dlPFC and reduced activity in emotional responding brain regions. However, individuals with greater PTSS showed blunted deactivations in bilateral amygdala and vmPFC-sgACC, and weaker responses in right dlPFC. Additionally, we found that elevated emotional/internalizing dysfunction (EID), specifically low positive emotionality (RC2), accounted for PTSS-related changes in bilateral amygdala under increased cognitive load. Findings suggest that PTSS might result in amygdala and vmPFC-sgACC activity resistant to moderation by cognitive demands, reflecting emotion dysregulation despite a need to marshal cognitive resources. Anhedonia may be an important target for interventions that improve the affective and cognitive functioning of individuals with PTSD.

There is an expanding literature on the theoretical and empirical connections between personality and psychopathology, and their shared neurobiological correlates. Recent cybernetic theories of personality and psychopathology, as well as affective neuroscience theory, provide grounding for understanding neurobiological–personality–psychopathology (NPP) associations. With the emergence of large sample datasets (e.g., Human Connectome Project) advanced quantitative modeling can be used to rigorously test dynamic statistical representations of NPP connections. Also, research suggests that these connections are influenced by sex, and large samples provide the opportunity to examine how NPP associations might be moderated by sex. The current study used a large sample from the Duke Neurogenetics Study (DNS) to examine how amygdala activation to facial expressions was linked with self-report of personality traits and clinical interviews of internalizing and externalizing symptoms of psychopathology. Structural equation modeling results revealed direct associations of amygdala activation with personality trait expression, as well as indirect associations (though personality) with symptoms of psychopathology. Moreover, the NPP links were moderated by sex. The current results are in line with research that identifies a broader role played by the amygdala in personality and provide potential insights for continued research in personality neuroscience and recent theories on the neurobiology of personality.

Predictive associations were estimated between socioemotional dispositions measured at 10–17 years using the Child and Adolescent Dispositions Scale (CADS) and future individual differences in white matter microstructure measured at 22–31 years of age. Participants were 410 twins (48.3% monozygotic) selected for later neuroimaging by oversampling on risk for psychopathology from a representative sample of child and adolescent twins. Controlling for demographic covariates and total intracranial volume (TICV), each CADS disposition (negative emotionality, prosociality, and daring) rated by one of the informants (parent or youth) significantly predicted global fractional anisotropy (FA) averaged across the major white matter tracts in brain in adulthood, but did so through significant interactions with sex after false discovery rate (FDR) correction. In females, each 1 SD difference in greater parent-rated prosociality was associated with 0.43 SD greater FA (p < 0.0008). In males, each 1 SD difference in greater parent-rated daring was associated with 0.24 SD lower FA (p < 0.0008), and each 1 SD difference in greater youth-rated negative emotionality was associated with 0.18 SD greater average FA (p < 0.0040). These findings suggest that CADS dispositions are associated with FA, but associations differ by sex. Exploratory analyses suggest that FA may mediate the associations between dispositions and psychopathology in some cases. These associations over 12 years could reflect enduring brain–behavior associations in spite of transactions with the environment, but could equally reflect processes in which dispositional differences in behavior influence the development of white matter. Future longitudinal studies are needed to resolve the causal nature of these sex-moderated associations.

“Personality is an abstraction used to explain consistency and coherency in an individual’s pattern of affects, cognitions, desires and behaviors [ABCDs]” (Revelle, 2007, p. 37). But personality research currently provides more a taxonomy of patterns than theories of fundamental causes. Psychiatric disorders can be viewed as involving extremes of personality but are diagnosed via symptom patterns not biological causes. Such surface-level taxonomic description is necessary for science, but consistent predictive explanation requires causal theory. Personality constructs, and especially their clinical extremes, should predict variation in ABCD patterns, with parsimony requiring the lowest effective causal level of explanation. But, even biologically inspired personality theories currently use an intuitive language-based approach for scale development that lacks biological anchors. I argue that teleonomic “purpose” explains the organisation and outputs of conserved brain emotion systems, where high activation is adaptive in specific situations but is otherwise maladaptive. Simple modulators of whole-system sensitivity evolved because the requisite adaptive level can vary across people and time. Sensitivity to a modulator is an abstract predictive personality factor that operates at the neural level but provides a causal explanation of both coherence and occasional apparent incoherence in ABCD variation. Neuromodulators impact all levels of the “personality hierarchy” from metatraits to aspects: stability appears altered by serotonergic drugs, neuroticism by ketamine and trait anxiety by simple anxiolytic drugs. Here, the tools of psychiatry transfer to personality research and imply both interaction between levels and oblique factor mappings to ABCD. On this view, much psychopathology reflects extremes of neural-level personality factors, and we can view much pharmacotherapy as temporarily altering personality. So, particularly for personality factors linked to basic emotions and their disorders, I think we should start with evolutionary biology and look directly at conserved neural-level modulators for our explanatory personality constructs and only invoke higher order, emergent, explanations when neural-level explanation fails.