Faculty Bibliography

OBJECTIVES: Noise often has detrimental effects on performance. However, because of the phenomenon of stochastic resonance (SR), auditory white noise (WN) can alter the "signal to noise" ratio and improve performance. The Moderate Brain Arousal (MBA) model postulates different levels of internal "neural noise" in individuals with different attentional capacities. This in turn determines the particular WN level most beneficial in each individual case-with one level of WN facilitating poor attenders but hindering super-attentive children. The objective of the present study is to find out if added WN affects cognitive performance differently in children that differ in attention ability. METHODS: Participants were teacher-rated super- (N = 25); normal- (N = 29) and sub-attentive (N = 36) children (aged 8 to 10 years). Two non-executive function (EF) tasks (a verbal episodic recall task and a delayed verbal recognition task) and two EF tasks (a visuo-spatial working memory test and a Go-NoGo task) were performed under three WN levels. The non-WN condition was only used to control for potential differences in background noise in the group testing situations. RESULTS: There were different effects of WN on performance in the three groups-adding moderate WN worsened the performance of super-attentive children for both task types and improved EF performance in sub-attentive children. The normal-attentive children's performance was unaffected by WN exposure. The shift from moderate to high levels of WN had little further effect on performance in any group. SIGNIFICANCE: The predicted differential effect of WN on performance was confirmed. However, the failure to find evidence for an inverted U function challenges current theories. Alternative explanations are discussed. We propose that WN therapy should be further investigated as a possible non-pharmacological treatment for inattention.

Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual "atlases" that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures.

In the last decade, diffusion MRI (dMRI) studies of the human and animal brain have been used to investigate a multitude of pathologies and drug-related effects in neuroscience research. Study after study identifies white matter (WM) degeneration as a crucial biomarker for all these diseases. The tool of choice for studying WM is dMRI. However, dMRI has inherently low signal-to-noise ratio and its acquisition requires a relatively long scan time; in fact, the high loads required occasionally stress scanner hardware past the point of physical failure. As a result, many types of artifacts implicate the quality of diffusion imagery. Using these complex scans containing artifacts without quality control (QC) can result in considerable error and bias in the subsequent analysis, negatively affecting the results of research studies using them. However, dMRI QC remains an under-recognized issue in the dMRI community as there are no user-friendly tools commonly available to comprehensively address the issue of dMRI QC. As a result, current dMRI studies often perform a poor job at dMRI QC. Thorough QC of dMRI will reduce measurement noise and improve reproducibility, and sensitivity in neuroimaging studies; this will allow researchers to more fully exploit the power of the dMRI technique and will ultimately advance neuroscience. Therefore, in this manuscript, we present our open-source software, DTIPrep, as a unified, user friendly platform for thorough QC of dMRI data. These include artifacts caused by eddy-currents, head motion, bed vibration and pulsation, venetian blind artifacts, as well as slice-wise and gradient-wise intensity inconsistencies. This paper summarizes a basic set of features of DTIPrep described earlier and focuses on newly added capabilities related to directional artifacts and bias analysis.

Sharing drafts of scientific manuscripts on preprint hosting services for early exposure and pre-publication feedback is a well-accepted practice in fields such as physics, astronomy, or mathematics. The field of neuroscience, however, has yet to adopt the preprint model. A reason for this reluctance might partly be the lack of central preprint services for the field of neuroscience. To address this issue, we announce the launch of Preprints of the R-fMRI Network (PRN), a community funded preprint hosting service. PRN provides free-submission and free hosting of manuscripts for resting state functional magnetic resonance imaging (R-fMRI) and neuroscience related studies. Submissions will be peer viewed and receive feedback from readers and a panel of invited consultants of the R-fMRI Network. All manuscripts and feedback will be freely available online with citable permanent URL for open-access. The goal of PRN is to supplement the "peer reviewed" journal publication system - by more rapidly communicating the latest research achievements throughout the world. We hope PRN will help the field to embrace the preprint model and thus further accelerate R-fMRI and neuroscience related studies, eventually enhancing human mental health.

Pavlovian threat conditioning is a behavioral paradigm that has been successfully utilized to define the mechanisms underlying threat (fear) memory formation. The amygdala is a temporal lobe structure required for the acquisition, consolidation, and expression of threat (fear) memories. In particular, the lateral nucleus of the amygdala (LA) is the major input structure of the amygdala and is required for all aspects of threat learning and memory. The LA expresses many neurotransmitter and neuromodulator receptors. This chapter covers the molecular mechanisms that occur downstream of these receptors and how they influence LA-dependent Pavlovian threat learning.

Reviews the book, Reading Anna Freud by Nick Midgley (see record 2012-32286-000). Reading Anna Freud is less a work of criticism than a work of orientation, and doubly valuable as such. First, because of the Freud family fame, one sometimes presumes one knows more about them than one really does (indeed, a misplaced presumption of familiarity is at the core of so much of the popular contempt hurled Sigmund's way). Second, orienting yourself to Anna Freud is a way of orienting yourself to child mental health: from how we speak to children and the role of schools in a child's psychological health to developmental psychopathology and the consultation-liaison service. What comes through in Reading Anna Freud is that the core of Freud's success was not just patient, compassionate intellectualism, genes, or an ability to get published, but advocacy. Moreover, you do not need a degree or an internal review board to be an advocate. In fact, it is in this regard that she is most inspiring. Although the book provides a historical and personal orientation, it is intended as an orientation to Freud's intellectual contributions, and Midgely does an excellent job translating her work, some of it nearly a century old, into a language that is still alive, relevant, and enriching.

The future of the textbook as we know it is in doubt. Knowledge is being shuttled into the virtual world, where it is collaborative, linked, multimedia, and transnational. The iterative nature of knowledge never fit comfortably with textbooks. They have always been notoriously out of date by the time they roll off the press. Nevertheless, there remains something comforting in the textbook's authoritative heft, which is lost not only in the vapor-thin flicker of Web pages but also in the suspicion with which we approach anything online, knowing full well that the provenance is dubious. Sock puppetry is not just a children's craft anymore; it's a modern form of authorship. Of course, textbooks have value as a corpus of knowledge that is not constantly changing; as a way of studying a topic without being distracted by the rabbit holes of the Internet; and as a backup: all knowledge will not be lost in a blackout. What the future of the textbook means for expert knowledge is unclear. How can hardcover and paperback textbooks carve out a place in tomorrow's society? One answer may be to look back.

This article proposes that wisdom is an integral ingredient in effective therapy, and offers a way of thinking about how wisdom grounded in systems thinking can be enacted and embodied. Rigor, imagination, humility, and love are four components that make up systemic wisdom in psychotherapy. Rigor refers to the establishment and maintenance of a viable frame for therapy; imagination to the pragmatics of meaning-making; humility, to the experience of complexity and chaos in the therapy system; and love, to the fundamental, biologically based emotional structure of the therapy relationship. These ideas pertain to work with individuals, couples, and families and are meant as principles rather than as a specific model. Therapy organized by these principles is effective by virtue of its aesthetic quality-its connecting of parts to whole and whole to parts-in addition to its instrumentality.

This article reviews the progression of a research program designed to develop, implement, and study the implementation of "achievable" evidence-based practices (EBPs) in schools. We review challenges encountered and ideas to overcome them to enhance this avenue of research. The article presents two federally funded randomized controlled trials involving comparison of a four-component targeted intervention (Quality Assessment and Improvement, Family Engagement and Empowerment, Modular Evidence-Based Practice, Implementation Support) versus a comparison intervention focused on personal wellness. In both studies, primary aims focused on changes in clinician attitudes and behavior, including the delivery of high-quality EBPs and secondary aims focused on student-level impacts. A number of challenges, many not reported in the literature, are reviewed, and ideas for overcoming them are presented. Given the reality that the majority of youth mental health services are delivered in schools and the potential of school mental health services to provide a continuum of mental health care from promotion to intervention, it is critical that the field consider and address the logistical and methodological challenges associated with implementing and studying EBP implementation by clinicians.