BDNF polymorphism-dependent OFC and DLPFC plasticity differentially moderates implicit and explicit bias.

This study examined the role of orbitofrontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC) plasticity in controlling implicit and explicit social biases. Normal controls and patients with varied OFC and DLPFC lesion size and single nucleotide polymorphisms (SNPs) in the brain-derived neurotrophic factor (BDNF) gene, which promotes (methionine-valine [Met/Val] SNP) or stifles (valine-valine [Val/Val] SNP) plasticity in damaged PFC regions, completed measures of implicit and explicit social bias. Patients and controls demonstrated comparable levels of implicit bias, but patients with Met/Val SNPs exhibited less implicit bias when they had smaller OFC lesions compared with Val/Val patients with similar size lesions and those with large OFC lesions. Both patients and controls demonstrated patterns of explicit bias consistent with hypotheses. Patients with Met/Val SNPs exhibited less explicit bias when they had smaller DLPFC lesions sizes compared with Val/Val patients with similar size lesions and those with large DLPFC lesions. OFC lesion size and BDNF SNP type did not moderate explicit bias; DLPFC lesion size and BDNF SNP type did not moderate implicit bias (nor did other medial or lateral regions). Findings suggest that plasticity within specific PFC regions modulates the type and degree of social bias that individuals' exhibit.

Modeling strategic use of human computer interfaces with novel hidden Markov models.

Immersive software tools are virtual environments designed to give their users an augmented view of real-world data and ways of manipulating that data. As virtual environments, every action users make while interacting with these tools can be carefully logged, as can the state of the software and the information it presents to the user, giving these actions context. This data provides a high-resolution lens through which dynamic cognitive and behavioral processes can be viewed. In this report, we describe new methods for the analysis and interpretation of such data, utilizing a novel implementation of the Beta Process Hidden Markov Model (BP-HMM) for analysis of software activity logs. We further report the results of a preliminary study designed to establish the validity of our modeling approach. A group of 20 participants were asked to play a simple computer game, instrumented to log every interaction with the interface. Participants had no previous experience with the game's functionality or rules, so the activity logs collected during their naïve interactions capture patterns of exploratory behavior and skill acquisition as they attempted to learn the rules of the game. Pre- and post-task questionnaires probed for self-reported styles of problem solving, as well as task engagement, difficulty, and workload. We jointly modeled the activity log sequences collected from all participants using the BP-HMM approach, identifying a global library of activity patterns representative of the collective behavior of all the participants. Analyses show systematic relationships between both pre- and post-task questionnaires, self-reported approaches to analytic problem solving, and metrics extracted from the BP-HMM decomposition. Overall, we find that this novel approach to decomposing unstructured behavioral data within software environments provides a sensible means for understanding how users learn to integrate software functionality for strategic task pursuit.

Anhedonia in combat veterans with penetrating head injury.

Anhedonia is a common symptom following traumatic brain injury. The neural basis of anhedonia is poorly understood, but believed to involve disturbed reward processing, rather than the loss of sense of pleasure. This analysis was undertaken to determine if injury to specific regions of prefrontal cortex (PFC) result in anhedonia. A CT-based lesion analysis was undertaken in 192 participants of the Vietnam Head Injury Study, most with penetrating head injury. Participants were divided into left and right ventrolateral prefrontal, bilateral ventromedial prefrontal, and other injury locations. Anhedonia was measured by self-report in each group using the four-item anhedonia subscale score of the Beck Depression Inventory-II. Individuals with right ventrolateral injury reported greater severity of anhedonia compared to those with injury in the left ventrolateral region. These findings support an association between injury in the right ventrolateral PFC and anhedonia.

Personality, Cognitive Style, Motivation, and Aptitude Predict Systematic Trends in Analytic Forecasting Behavior.

The decision sciences are increasingly challenged to advance methods for modeling analysts, accounting for both analytic strengths and weaknesses, to improve inferences taken from increasingly large and complex sources of data. We examine whether psychometric measures-personality, cognitive style, motivated cognition-predict analytic performance and whether psychometric measures are competitive with aptitude measures (i.e., SAT scores) as analyst sample selection criteria. A heterogeneous, national sample of 927 participants completed an extensive battery of psychometric measures and aptitude tests and was asked 129 geopolitical forecasting questions over the course of 1 year. Factor analysis reveals four dimensions among psychometric measures; dimensions characterized by differently motivated "top-down" cognitive styles predicted distinctive patterns in aptitude and forecasting behavior. These dimensions were not better predictors of forecasting accuracy than aptitude measures. However, multiple regression and mediation analysis reveals that these dimensions influenced forecasting accuracy primarily through bias in forecasting confidence. We also found that these facets were competitive with aptitude tests as forecast sampling criteria designed to mitigate biases in forecasting confidence while maximizing accuracy. These findings inform the understanding of individual difference dimensions at the intersection of analytic aptitude and demonstrate that they wield predictive power in applied, analytic domains.

The role of executive function and the dorsolateral prefrontal cortex in the expression of neuroticism and conscientiousness.

The current study examined how specific neurological systems contribute to the expression of multiple personality dimensions. We used individuals with traumatic brain injuries to examine the contribution of the dorsolateral prefrontal cortex (DLPFC)--a region important for executive function and attention-to the expression of neuroticism and conscientiousness factors and facets. Results from Voxel-Based Lesion-Symptom Mapping analyses revealed that focal damage to the left DLPFC (Brodmann's area 9) was associated with high neuroticism and low conscientious factor and facet scores (anxiety and self-discipline, respectively). Compared with lesioned and normal controls, veterans with damage in left DLPFC also reported higher neuroticism and lower conscientiousness facet scores, slower reaction times on the California Computerized Assessment Package assessment, and lower scores on the Delis-Kaplan executive function battery. Findings suggest that while neuroticism and conscientiousness remain psychometrically independent personality dimensions, their component facets may rely on a common neurocognitive infrastructure and executive function resources in general.

Prediction-error in the context of real social relationships modulates reward system activity.

The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward-social validation-and this activity's relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants' expectations for their romantic partners' positive regard of them were confirmed (validated) or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.