Faculty Bibliography

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.

Multivariate supervised learning methods exhibit a remarkable ability to decode externally driven sensory, behavioral, and cognitive states from functional neuroimaging data. Although they are typically applied to task-based analyses, supervised learning methods are equally applicable to intrinsic effective and functional connectivity analyses. The obtained models of connectivity incorporate the multivariate interactions between all brain regions simultaneously, which will result in a more accurate representation of the connectome than the ones available with standard bivariate methods. Additionally the models can be applied to decode or predict the time series of intrinsic brain activity of a region from an independent dataset. The obtained prediction accuracy provides a measure of the integration between a brain region and other regions in its network, as well as a method for evaluating acquisition and preprocessing pipelines for resting state fMRI data. This article describes a method for learning multivariate models of connectivity. The method is applied in the non-parametric prediction accuracy, influence, and reproducibility-resampling (NPAIRS) framework, to study the regional variation of prediction accuracy and reproducibility (Strother et al., 2002). The resulting spatial distribution of these metrics is consistent with the functional hierarchy proposed by Mesulam (1998). Additionally we illustrate the utility of the multivariate regression connectivity modeling method for optimizing experimental parameters and assessing the quality of functional neuroimaging data.

BACKGROUND: An increasing body of research points to a significant association of obesity to Attention-Deficit/Hyperactivity Disorder (ADHD) and deficits in executive functions. There is also preliminary evidence suggesting that children with ADHD may be at risk of obesity in adulthood. DISCUSSION: In this article, we discuss the evidence showing that ADHD and/or deficits in executive functions are a barrier to a successful weight control in individuals enrolled in weight loss programs. Impairing symptoms of ADHD or deficits in executive functions may foster dysregulated eating behaviors, such as binge eating, emotionally-induced eating or eating in the absence of hunger, which, in turn, may contribute to unsuccessful weight loss. ADHD-related behaviors or neurocognitive impairment may also hamper a regular and structured physical activity. There is initial research showing that treatment of comorbid ADHD and executive functions training significantly improve the outcome of obesity in individuals with comorbid ADHD or impairment in executive functions. SUMMARY: Preliminary evidence suggests that comorbid ADHD and deficits in executive functions are a barrier to a successful weight loss in individuals involved in obesity treatment programs. If further methodologically sound evidence confirms this relationship, screening and effectively managing comorbid ADHD and/or executive functions deficits in individuals with obesity might have the potential to reduce not only the burden of ADHD but also the obesity epidemics.

Self-monitoring is an important clinical technique used in cognitive-behavioral therapy. It is frequently used for homework assignments in the context of comprehensive treatments. A description of self-monitoring and practical considerations is presented, followed by an examination of self-monitoring as a means to facilitate collaborative empiricism in therapy. It may foster collaboration between therapist and client in collecting and reviewing essential data, inform treatment planning, and enhance the client's sense of agency. A clinical case example is included to provide an emphasis on clinical application. We conclude by noting potential mechanisms for facilitating change through the use of self-monitoring. Continued examination of applied clinical practice, including strategies such as self-monitoring, is needed to further our understanding of the mechanisms of therapeutic change.

To examine relations between infant social withdrawal behavior and maternal major depression (MDD), 155 mother-infant dyads were evaluated at the 6-month primary care visit. Maternal depression was determined based on a psychiatric interview. Infant social withdrawal behavior was assessed with the Alarm Distress Baby Scale (ADBB; A. Guedeney & J. Fermanian, 2001) based on videotaped mother-infant interactions. Of the sample, 18.7% of mothers were diagnosed with MDD, and 39.4% of infants scored above the clinical ADBB cutoff. Infants of depressed mothers were more likely to score positive on the ADBB (75.8 vs. 31.0%, p < .001) and showed distinct patterns of withdrawal behavior. Within the group of withdrawn infants, however, no differential patterns of behavior could be identified for infants of depressed mothers as compared to infants of mothers with no depression. These findings confirm the validity of the ADBB for detection of infant social withdrawal in the context of MDD. At the same time, they support evidence that the ADBB identifies nonspecific infant distress behaviors. Future studies will need to determine if and how positive ADBB screening results in the absence of maternal MDD might be associated with other maternal psychiatric disorders such as anxiety or borderline personality disorder. These results have important implications for screening guidelines in primary care.

Within the last three decades, the study of conditions that co-occur with intellectual disabilities has flourished. The present paper provides an analysis of the content of 405 papers that were reviewed on the topic. From these papers, trends emerged. The papers fell into one of three broad categories; comorbid psychopathology, comorbid medical problems, and comorbid challenging behaviors. Also, the volume of studies has been increasing rapidly. Implications of these and related issues are discussed. (C) 2013 Elsevier Ltd. All rights reserved.

Researchers have indicated that persons with autism spectrum disorder (ASD) population evince higher rates of comorbid symptoms. While the relationship between comorbid symptoms and factors such as autism symptom severity, IQ level, age, communication abilities, and degree of social impairment were previously examined, there has been limited research on the effect of race in this area. The current study examined the potential role of race in comorbid symptoms in toddlers with ASD and atypically developing toddlers without a diagnosis of ASD using The Baby and Infant Screen for Children with aUtIsm Traits Part 2 (BISCUIT-Part 2). Based on the current findings, African-American toddlers evinced higher rates of comorbid symptoms than Caucasian toddlers and toddlers of other races. In addition, toddlers with ASD evinced higher rates of comorbid symptoms than atypically developing toddlers without a diagnosis of ASD. Implications regarding these findings are discussed. (C) 2013 Elsevier Ltd. All rights reserved.

OBJECTIVE This study examined the extent to which therapists who participated in a randomized controlled trial (RCT) of evidence-based treatments continued to use them with nonstudy clients after the trial as well as the types of treatment used and the reasons for their continued use. METHODS Semistructured interviews and focus groups were conducted with 38 therapists, three clinical supervisors, and eight clinic directors three months after an RCT of evidence-based treatments for depression, anxiety, and conduct disorders among children and adolescents. The therapists had been assigned randomly to one of three conditions: modular (N=15), allowing flexible use and informed adaptations of treatment components; standard (N=13), using full treatment manuals; and usual care (N=10). Grounded-theory analytic methods were used to analyze interview transcripts. RESULTS Twenty-six therapists (93%) assigned to the modular or standard condition used the treatments with nonstudy cases. Of those, 24 (92%) therapists, including all but two assigned to the standard condition, reported making some adaptation or modification, including using only some modules with all clients or all modules with some clients; changing the order or presentation of the modules to improve the flow or to work around more immediate issues; and using the modules with others, including youths with co-occurring disorders, youths who did not meet the age criteria, and adults. CONCLUSIONS The results provide insight into the likely sustainability of evidence-based treatments, help to explain why the outcomes of the RCT favored a modular approach, and highlight the strengths and limitations of use of evidence-based treatments.

Distress-linked activation of the maternal hypothalamic-pituitary-adrenal (HPA)-axis is considered a pathway by which affect regulation impacts the fetal milieu and neurodevelopment. There is little direct evidence for this conceptual model. In 103 women [mean age 27.45 (+/-5.65) years] at 36-38 weeks gestation, salivary cortisol was measured before/after stress tasks; distress questionnaires were completed. At 18.49 (+/-1.83) weeks, infants underwent the Harvard Infant Behavioral Reactivity Protocol assessing cry/motor responses to novelty; women reported on infant behavior and postnatal distress. Prenatal cortisol and distress were not significantly correlated (all ps > .10). Proportional odds logistic regressions showed that neither prenatal nor postnatal distress was associated with infant responses to the Harvard Protocol yet pre-stress cortisol and maternal age were: The odds of being classified as High Reactive were 1.60 times higher [95% CI: 1.04, 2.46] for each unit of added cortisol and .90 times lower [95% CI: .82, .99] for every additional year in maternal age. No associations were found between cortisol or prenatal distress and mother-rated infant behavior; postnatal distress was positively associated with mother-rated infant negative behavior (p = .03). Observer and mother-rated infant behavior were not associated (all ps > .05). Based on independent observations of infants in contrast to maternal perceptions, these results lend support to the hypothesis that pregnant women's HPA-axis activity influences infant behavior. The impact of maternal distress was not supported, except in so far as postnatal distress may increase the likelihood of making negative judgments about infant behavior. (c) 2012 Wiley Periodicals, Inc. Dev Psychobiol.