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.

The hollow-mask illusion is an optical illusion where a concave face is perceived as convex. It has been demonstrated that individuals with schizophrenia and anxiety are less susceptible to the illusion than controls. Previous research has shown that the P300 and P600 event-related potentials (ERPs) are affected in individuals with schizophrenia. Here, we examined whether individual differences in neuroticism and anxiety scores, traits that have been suggested to be risk factors for schizophrenia and anxiety disorders, affect ERPs of healthy participants while they view concave faces. Our results confirm that the participants were susceptible to the illusion, misperceiving concave faces as convex. We additionally demonstrate significant interactions of the concave condition with state anxiety in central and parietal electrodes for P300 and parietal areas for P600, but not with neuroticism and trait anxiety. The state anxiety interactions were driven by low-state anxiety participants showing lower amplitudes for concave faces compared to convex. The P300 and P600 amplitudes were smaller when a concave face activated a convex face memory representation, since the stimulus did not match the active representation. The opposite pattern was evident in high-state anxiety participants in regard to state anxiety interaction and the hollow-mask illusion, demonstrating larger P300 and P600 amplitudes to concave faces suggesting impaired late information processing in this group. This could be explained by impaired allocation of attentional resources in high-state anxiety leading to hyperarousal to concave faces that are unexpected mismatches to standard memory representations, as opposed to expected convex faces.

Narcissism is a Janusian personality construct, associated with both grandiose self-assuredness and dominance, as well as vulnerable insecurity and reactivity. Central questions of intra- and interpersonal functioning in narcissism are still a matter of debate. Neuroscience could help to understand the paradoxical patterns of experience and behavior beyond the limitations of self-reports. We provide a systematic review of 34 neuroscience studies on grandiose, vulnerable, pathological narcissism, and Narcissistic Personality Disorder (NPD), spanning experimental investigations of intra- and interpersonal mechanisms, research on neurophysiological and neuroendocrine aspects of baseline function, and brain structural correlates. While neuroscience has scarcely directly studied vulnerable narcissism, grandiose narcissism is associated with heightened vigilance to ego threat and stress responses following ego threat, as well as heightened stress indicators in baseline measures. Such responses are not commonly observed in self-reports, highlighting the potential of neuroscience to augment our understanding of self-regulatory dynamics in narcissism. Interpersonal functioning is characterized by deficits in social–affective processes. Both involve altered activity within the salience network, pointing to a double dissociation regarding the expression of narcissism and self/other oriented situational focus. Findings are summarized in an integrative model providing testable hypotheses for future research along with methodological recommendations.

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.

Like socio-economic status and cognitive abilities, personality traits predict important life outcomes. Traits that reflect unusually low or high approach motivations, such as low extraversion and high disinhibition, are linked to various forms of mental disorder. Similarly, the dopamine system is theoretically linked to approach motivation traits and to various forms of mental disorder. Identifying neural contributions to extremes of such traits should map to neural sources of psychopathology, with dopamine a prime candidate. Notably, dopamine cells fire in response to unexpected reward, which suggests that the size of non-invasive, scalp-recorded potentials evoked by unexpected reward could reflect sensitivity in approach motivation traits. Here, we evaluated the validity of evoked electroencephalography (EEG) responses to unexpected reward in a monetary gain/loss task to assess approach motivation traits in 137 participants, oversampled for externalizing psychopathology symptoms. We demonstrated that over the 0–400 ms period in which feedback on the outcome was presented, responses evoked by unexpected reward contributed to all theoretically relevant approach motivation trait domains (disinhibition, extraversion and the behavioural activation system); and did so only at times when dopamine responses normally peak and reportedly code salience (70–100 ms) and valuation (200–300 ms). In particular, we linked “dopaminergic” salience and valuation to the psychopathology-related constructs of low extraversion (social anxiety) and high disinhibition (impulsivity) respectively, making the evoked potential components biomarker candidates for indexing aberrant processing of unexpected reward.

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.

Jaak Panksepp’s Affective Neuroscience Theory is of high relevance not only for a better understanding of affective brain disorders but also in personality research. To make Panksepp’s theory more accessible for psychologists and psychiatrists, Davis, Panksepp, and Normansell (2003) developed the Affective Neuroscience Personality Scales (ANPS). These scales assess the manifestation of the primary emotional traits in humans based on a personality trait approach. Given their putative foundation in old subcortical areas in the brain, these primary emotional traits (assessed via the ANPS) could represent the evolutionarily oldest manifestations of personality (but this notion is still a matter of a debate). However, the ANPS inventories were based on using contextual items (e.g., about specific attitudes, behaviors, and feelings in specific situations). Recently, an adjective-based ANPS (ANPS-Adjective Ratings or ANPS-AR) was developed for a less context-dependent and more efficient assessment of Panksepp’s primary emotional systems in humans for use by both individuals and independent observer raters. The present work introduces the first German version of the ANPS-AR. Moreover, the current work investigates the original and ANPS-AR versions of the ANPS and their associations with the Big Five personality traits in two independent English- and German-speaking samples. The results show that the ANPS measures are very similarly correlated with the Big Five personality traits across different samples and scales. This work replicates the previous findings in an English version, and demonstrates the reliability and validity of the adjective-based German ANPS-AR.