Can neuroscience help to understand narcissism? A systematic review of an emerging field

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.

State anxiety influences P300 and P600 event-related potentials over parietal regions in the hollow-mask illusion experiment

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.

Early and late signals of unexpected reward contribute to low extraversion and high disinhibition, respectively

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.

The hierarchical structure of error-related negativities elicited from affective and social stimuli and their relations to personality traits

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.

Machine learning approaches for parsing comorbidity/heterogeneity in antisociality and substance use disorders: A primer

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.

Connecting quantitatively derived personality–psychopathology models and neuroscience

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.

Investigating the neural substrates of Antagonistic Externalizing and social-cognitive Theory of Mind: an fMRI examination of functional activity and synchrony

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.

An fMRI investigation of the relations between Extraversion, internalizing psychopathology, and neural activation following reward receipt in the Human Connectome Project sample

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 neuroscience and psychopathology: should we start with biology and look for neural-level factors?

“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.

Neural signatures of promotion versus prevention goal priming: fMRI evidence for distinct cognitive-motivational systems

Regulatory focus theory (RFT) postulates two cognitive-motivational systems for personal goal pursuit: the promotion system, which is associated with ideal goals (an individual’s hopes, dreams, and aspirations), and the prevention system, which is associated with ought goals (an individual’s duties, responsibilities, and obligations). The two systems have been studied extensively in behavioral research with reference to differences between promotion and prevention goal pursuit as well as the consequences of perceived attainment versus nonattainment within each system. However, no study has examined the neural correlates of each combination of goal domain and goal attainment status. We used a rapid masked idiographic goal priming paradigm and functional magnetic resonance imaging to present individually selected promotion and prevention goals, which participants had reported previously that they were close to attaining (“match”) or far from attaining (“mismatch”). Across the four priming conditions, significant activations were observed in bilateral insula (Brodmann area (BA) 13) and visual association cortex (BA 18/19). Promotion priming discriminantly engaged left prefrontal cortex (BA 9), whereas prevention priming discriminantly engaged right prefrontal cortex (BA 8/9). Activation in response to promotion goal priming was also correlated with an individual difference measure of perceived success in promotion goal attainment. Our findings extend the construct validity of RFT by showing that the two systems postulated by RFT, under conditions of both attainment and nonattainment, have shared and distinct neural correlates that interface logically with established network models of self-regulatory cognition.