Faculty Bibliography

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.

The Patient Protection and Affordable Care Act of 2010 (ACA) is revamping the access, quality, and financing of the health and mental health systems. However, its impact on training and education in clinical psychology is unclear. This article aims to identify specific components of the ACA, in particular the Mental and Behavioral Health Education and Training Grants, that are expected to affect training and education in the field. The article further connects the ACA with four paradigm shifts in clinical psychology that have broad implications for training and educationevidence-based practices, research methodology, interprofessionalism, and the quality indicator movement. The overarching goal of this article is to begin timely discussions on the future directions of the field under the current healthcare reform.

In many systems, sleep plays a vital role in memory consolidation and synaptic homeostasis. These processes together help store information of biological significance and reset synaptic circuits to facilitate acquisition of information in the future. In this review, we describe recent evidence of sleep-dependent changes in olfactory system structure and function which contribute to odor memory and perception. During slow-wave sleep, the piriform cortex becomes hypo-responsive to odor stimulation and instead displays sharp-wave activity similar to that observed within the hippocampal formation. Furthermore, the functional connectivity between the piriform cortex and other cortical and limbic regions is enhanced during slow-wave sleep compared to waking. This combination of conditions may allow odor memory consolidation to occur during a state of reduced external interference and facilitate association of odor memories with stored hedonic and contextual cues. Evidence consistent with sleep-dependent odor replay within olfactory cortical circuits is presented. These data suggest that both the strength and precision of odor memories is sleep-dependent. The work further emphasizes the critical role of synaptic plasticity and memory in not only odor memory but also basic odor perception. The work also suggests a possible link between sleep disturbances that are frequently co-morbid with a wide range of pathologies including Alzheimer's disease, schizophrenia and depression and the known olfactory impairments associated with those disorders.

Longitudinal MR imaging during early brain development provides important information about growth patterns and the development of neurological disorders. We propose a new framework for studying brain growth patterns within and across populations based on MRI contrast changes, measured at each time point of interest and at each voxel. Our method uses regression in the LogOdds space and an information-theoretic measure of distance between distributions to capture contrast in a manner that is robust to imaging parameters and without requiring intensity normalization. We apply our method to a clinical neuroimaging study on early brain development in autism, where we obtain a 4D spatiotemporal model of contrast changes in multimodal structural MRI.

Quantitative imaging biomarkers are important for assessment of impact, recovery and treatment efficacy in patients with traumatic brain injury (TBI). To our knowledge, the identification of such biomarkers characterizing disease progress and recovery has been insufficiently explored in TBI due to difficulties in registration of baseline and follow-up data and automatic segmentation of tissue and lesions from multimodal, longitudinal MR image data. We propose a new methodology for computing imaging biomarkers in TBI by extending a recently proposed spatiotemporal 4D modeling approach in order to compute quantitative features of tissue change. The proposed method computes surface-based and voxel-based measurements such as cortical thickness, volume changes, and geometric deformation. We analyze the potential for clinical use of these biomarkers by correlating them with TBI-specific patient scores at the level of the whole brain and of individual regions. Our preliminary results indicate that the proposed voxel-based biomarkers are correlated with clinical outcomes.

This paper proposes a novel method that extends spatiotemporal growth modeling to distribution-valued data. The method relaxes assumptions on the underlying noise models by considering the data to be represented by the complete probability distributions rather than a representative, single-valued summary statistics like the mean. When summarizing by the latter method, information on the underlying variability of data is lost early in the process and is not available at later stages of statistical analysis. The concept of 'distance' between distributions and an 'average' of distributions is employed. The framework quantifies growth trajectories for individuals and populations in terms of the complete data variability estimated along time and space. Concept is demonstrated in the context of our driving application which is modeling of age-related changes along white matter tracts in early neurodevelopment. Results are shown for a single subject with Krabbe's disease in comparison with a normative trend estimated from 15 healthy controls.

We present a new framework for spatiotemporal analysis of parameterized functions attributed by properties of 4D longitudinal image data. Our driving application is the measurement of temporal change in white matter diffusivity of fiber tracts. A smooth temporal modeling of change from a discrete-time set of functions is obtained with an extension of the logistic growth model to time-dependent spline functions, capturing growth with only a few descriptive parameters. An unbiased template baseline function is also jointly estimated. Solution is demonstrated via energy minimization with an extension to simultaneous modeling of trajectories for multiple subjects. The new framework is validated with synthetic data and applied to longitudinal DTI from 15 infants. Interpretation of estimated model growth parameters is facilitated by visualization in the original coordinate space of fiber tracts.

Following intranasal administration of oxytocin (OT), we measured, via functional MRI, changes in brain activity during judgments of socially (Eyes) and nonsocially (Vehicles) meaningful pictures in 17 children with high-functioning autism spectrum disorder (ASD). OT increased activity in the striatum, the middle frontal gyrus, the medial prefrontal cortex, the right orbitofrontal cortex, and the left superior temporal sulcus. In the striatum, nucleus accumbens, left posterior superior temporal sulcus, and left premotor cortex, OT increased activity during social judgments and decreased activity during nonsocial judgments. Changes in salivary OT concentrations from baseline to 30 min postadministration were positively associated with increased activity in the right amygdala and orbitofrontal cortex during social vs. nonsocial judgments. OT may thus selectively have an impact on salience and hedonic evaluations of socially meaningful stimuli in children with ASD, and thereby facilitate social attunement. These findings further the development of a neurophysiological systems-level understanding of mechanisms by which OT may enhance social functioning in children with ASD.