Automating the analysis of facial emotion expression dynamics: A computational framework and application in psychotic disorders.

Facial emotion expressions play a central role in interpersonal interactions; these displays are used to predict and influence the behavior of others. Despite their importance, quantifying and analyzing the dynamics of brief facial emotion expressions remains an understudied methodological challenge. Here, we present a method that leverages machine learning and network modeling to assess the dynamics of facial expressions. Using video recordings of clinical interviews, we demonstrate the utility of this approach in a sample of 96 people diagnosed with psychotic disorders and 116 never-psychotic adults. Participants diagnosed with schizophrenia tended to move from neutral expressions to uncommon expressions (e.g., fear, surprise), whereas participants diagnosed with other psychoses (e.g., mood disorders with psychosis) moved toward expressions of sadness. This method has broad applications to the study of normal and altered expressions of emotion and can be integrated with telemedicine to improve psychiatric assessment and treatment.

Dissociation of basolateral and central amygdala effective connectivity predicts the stability of emotion-related impulsivity in adolescents and emerging adults with borderline personality symptoms: a resting-state fMRI study.

BACKGROUND: Borderline personality disorder (BPD) is associated with altered activity in the prefrontal cortex (PFC) and amygdala, yet no studies have examined fronto-limbic circuitry in borderline adolescents and emerging adults. Here, we examined the contribution of fronto-limbic effective connectivity (EC) to the longitudinal stability of emotion-related impulsivity, a key feature of BPD, in symptomatic adolescents and young adults. METHODS: We compared resting-state EC in 82 adolescents and emerging adults with and without clinically significant borderline symptoms (n BPD = 40, ages 13-30). Group-specific directed networks were estimated amongst fronto-limbic nodes including PFC, ventral striatum (VS), central amygdala (CeN), and basolateral amygdala (BLA). We examined the association of directed centrality metrics with initial levels and rates of change in emotion-related impulsivity symptoms over a one-year follow-up using latent growth curve models (LGCMs). RESULTS: In controls, ventromedial prefrontal cortex (vmPFC) and dorsal ACC had a directed influence on CeN and VS, respectively. In the BPD group, bilateral BLA had a directed influence on CeN, whereas in the healthy group CeN influenced BLA. LGCMs indicated that emotion-related impulsivity was stable across a one-year follow-up in the BPD group. Further, higher EC of R CeN to other regions in controls was associated with stronger within-person decreases in emotion-related impulsivity. CONCLUSIONS: Functional inputs from BLA and vmPFC appear to play competing roles in influencing CeN activity. In borderline adolescents and young adults, BLA may predominate over CeN activity, while in controls the ability of CeN to influence BLA activity predicted more rapid reductions in emotion-related impulsivity.

Explanatory personality science in the neuroimaging era: The map is not the territory.

The recent rise of magnetic resonance imaging (MRI) has led to a proliferation of studies that seek to link individual differences in personality directly to their neural correlates. These studies function to describe personality at a lower level of analysis, but they do little to advance the field's understanding of the causal mechanisms that give rise to personality traits. To transition to a more explanatory personality neuroscience, researchers should strive to conduct theory-driven empirical studies that bridge multiple levels of analysis. Effectively doing so will require a continued reliance on rich description, strong theories, large samples, and careful behavioral experimentation. Integrating these components will lead to more robust and informative studies of personality neuroscience that help to move the field closer to explaining the causal sources of individual differences.

Disentangling cognitive processes in externalizing psychopathology using drift diffusion modeling: Antagonism, but not disinhibition, is associated with poor cognitive control.

Although externalizing psychopathology has been linked to deficits in cognitive control, the cognitive processes underlying this association are unclear. Here, we provide a theoretical account of how research on cognitive processes can help to integrate and distinguish personality and psychopathology. We then apply this account to connect the two major subcomponents of externalizing, Antagonism and Disinhibition, with specific control processes using a battery of inhibitory control tasks and corresponding computational modeling. Participants (final N = 104) completed the flanker, go/no-go, and recent probes tasks, as well as normal and maladaptive personality inventories and measures of psychological distress. We fit participants' task behavior using a hierarchical drift diffusion model (DDM) to decompose their responses into specific cognitive processes. Using multilevel structural equation models, we found that Antagonism was associated with faster RTs on the flanker task and lower accuracy on flanker and go/no-go tasks. These results were complemented by DDM parameter associations: Antagonism was linked to decreased threshold and drift rate parameter estimates in the flanker task and a decreased drift rate on no-go trials. Altogether, our findings indicate that Antagonism is associated with specific impairments in fast (sub-second) inhibitory control processes involved in withholding prepared/prepotent responses and filtering distracting information. Disinhibition and momentary distress, however, were not associated with task performance.

From Description to Explanation: Integrating Across Multiple Levels of Analysis to Inform Neuroscientific Accounts of Dimensional Personality Pathology.

Dimensional approaches to psychiatric nosology are rapidly transforming the way researchers and clinicians conceptualize personality pathology, leading to a growing interest in describing how individuals differ from one another. Yet, in order to successfully prevent and treat personality pathology, it is also necessary to explain the sources of these individual differences. The emerging field of personality neuroscience is well-positioned to guide the transition from description to explanation within personality pathology research. However, establishing comprehensive, mechanistic accounts of personality pathology will require personality neuroscientists to move beyond atheoretical studies that link trait differences to neural correlates without considering the algorithmic processes that are carried out by those correlates. We highlight some of the dangers we see in overpopulating personality neuroscience with brain-trait associational studies and offer a series of recommendations for personality neuroscientists seeking to build explanatory theories of personality pathology.

Parental Expressed Emotion-Criticism and Neural Markers of Sustained Attention to Emotional Faces in Children.

There is growing evidence for the role of environmental influences on children's information-processing biases for affectively salient stimuli. The goal of this study was to extend this research by examining the relation between parental criticism (expressed emotion-criticism, or EE-Crit) and children's processing of facial displays of emotion. Specifically, we examined the relation between EE-Crit and children's sensitivity in detecting facial displays of emotion. We also examined a neural marker of sustained attention, the late positive potential (LPP) event-related potential component (ERP). Participants were 87 children (ages 7-11 years; 53.3% female, 77.8% Caucasian) and their parents (ages 24-71; 90% female, 88.9% Caucasian). Parents completed the Five-Minute Speech Sample to determine levels of EE-Crit toward their child. Children completed a morphed faces task during which behavioral and ERP responses were assessed. Although there were no group differences in sensitivity in detecting facial displays of emotion, we found that children of parents exhibiting high, compared to low, EE-Crit displayed less attention (smaller LPP magnitudes) to all facial displays of emotion (fearful, happy, sad). These results suggest that children of critical parents may exhibit an avoidant pattern of attention to affectively-salient interpersonal stimuli.

Interpersonal dysfunction in borderline personality: a decision neuroscience perspective.

Borderline personality disorder (BPD) is characterized by disadvantageous decisions that are often expressed in close relationships and associated with intense negative emotions. Although functional neuroimaging studies of BPD have described regions associated with altered social cognition and emotion processing, these correlates do not inform an understanding of how brain activity leads to maladaptive choices. Drawing on recent research, we argue that formal models of decision-making are crucial to elaborating theories of BPD that bridge psychological constructs, behavior, and neural systems. We propose that maladaptive interactions between Pavlovian and instrumental influences play a crucial role in the expression of interpersonal problems. Finally, we articulate specific hypotheses about how clinical features of BPD may map onto neural systems that implement separable decision processes.