Faculty Bibliography

OBJECTIVE: We sought to establish prevalence rates and detail patterns of comorbidity for generalized anxiety disorder, separation anxiety disorder, and social phobia in preschool-aged children. METHOD: The Duke Preschool Anxiety Study, a screen-stratified, cross-sectional study, drew from pediatric primary care and oversampled for children at risk for anxiety. A total of 917 parents of preschool children (aged 2-5 years) completed the Preschool Age Psychiatric Assessment. RESULTS: Generalized anxiety disorder, separation anxiety disorder, and social phobia are common in preschool-aged children attending pediatric primary care. Three-fourths of preschoolers with an anxiety disorder only had a single anxiety disorder. Generalized anxiety disorder displayed the greatest degree of comorbidity: with separation anxiety disorder (odds ratio [OR] = 4.1, 95% CI = 2.0-8.5), social phobia (OR = 6.4, 95% CI = 3.1-13.4), disruptive behavior disorders (OR = 5.1, 95% CI = 1.6-15.8), and depression (OR = 3.7, 95% CI = 1.1-12.4). CONCLUSIONS: The weakness of association between generalized anxiety disorder and depression stands in contrast to substantial associations between these 2 disorders reported in older individuals. Attenuated associations in preschool-aged children could translate into clinical opportunities for targeted early interventions, aimed at modifying the developmental trajectory of anxiety disorders.

Progress disseminating and implementing evidence-based psychological treatments (EBPTs) for the anxiety disorders has been gradual. To date, the dominant approach for promoting the uptake of EBPTs in clinical settings has been to target the education and training of mental health providers, with many consumers remaining unaware of the potential benefits of EBPTs for anxiety disorders. Direct-to-consumer (DTC) marketing may be a promising vehicle for increasing EBPT utilization rates in the treatment of anxiety disorders. This paper provides an overview of the rationale and important considerations for applying DTC efforts to promote evidence-based care in the treatment of anxiety disorders, and reviews current DTC efforts in this area, including resources on the Internet and other media and in-person events. We conclude with recommendations for future efforts in the DTC marketing of EBPTs for the anxiety disorders, including the need for increased funding and grassroots efforts to inform consumers about anxiety disorders and their most effective treatments.

Relations between parental socialization and infants' prosocial behavior were investigated in sixty three 18- and 30-month old children. Parents' socialization techniques (e.g., directives, negotiation, reasoning) differed for the two age groups, as did relations between socialization and different forms of emerging prosocial behavior (helping; sharing).

We examined whether error monitoring, operationalized as the degree to which individuals slow down after committing an error (i.e., posterror slowing), is differentially important in the learning of rule-based versus information-integration category structures. Rule-based categories are most efficiently solved through the application of an explicit verbal strategy (e.g., "sort by color"). In contrast, information-integration categories are believed to be learned in a trial-by-trial, associative manner. Our results indicated that posterror slowing predicts enhanced rule-based but not information-integration category learning. Implications for multiple category-learning systems are discussed.

In reconsolidation studies, memories are typically retrieved by an exposure to a single conditioned stimulus (CS). We have previously demonstrated that reconsolidation processes are CS-selective, suggesting that memories retrieved by the CS exposure are discrete and reconsolidate separately. Here, using a compound stimulus in which two distinct CSs are concomitantly paired with the same aversive unconditioned stimulus (US), we show in rats that reexposure to one of the components of the compound CS triggers extinction or reconsolidation of the other component. This suggests that the original training conditions play a critical role in memory retrieval and reconsolidation.

Over a decade ago, the fMRI Data Center (fMRIDC) pioneered open-access data sharing in the task-based functional neuroimaging community. Well ahead of its time, the fMRIDC effort encountered logistical, sociocultural and funding barriers that impeded the field-wise instantiation of open-access data sharing. In 2009, ambitions for open-access data sharing were revived in the resting state functional MRI community in the form of two grassroots initiatives: the 1000 Functional Connectomes Project (FCP) and its successor, the International Neuroimaging Datasharing Initiative (INDI). Beyond providing open access to thousands of clinical and non-clinical imaging datasets, the FCP and INDI have demonstrated the feasibility of large-scale data aggregation for hypothesis generation and testing. Yet, the success of the FCP and INDI should not be confused with widespread embracement of open-access data sharing. Reminiscent of the challenges faced by fMRIDC, key controversies persist and include participant privacy, the role of informatics, and the logistical and cultural challenges of establishing an open science ethos. We discuss the FCP and INDI in the context of these challenges, highlighting the promise of current initiatives and suggesting solutions for possible pitfalls.

Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, "venetian blind" artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies.