Faculty Bibliography

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.

Diffusion tensor imaging has become an important modality in the field of neuroimaging to capture changes in micro-organization and to assess white matter integrity or development. While there exists a number of tractography toolsets, these usually lack tools for preprocessing or to analyze diffusion properties along the fiber tracts. Currently, the field is in critical need of a coherent end-to-end toolset for performing an along-fiber tract analysis, accessible to non-technical neuroimaging researchers. The UNC-Utah NA-MIC DTI framework represents a coherent, open source, end-to-end toolset for atlas fiber tract based DTI analysis encompassing DICOM data conversion, quality control, atlas building, fiber tractography, fiber parameterization, and statistical analysis of diffusion properties. Most steps utilize graphical user interfaces (GUI) to simplify interaction and provide an extensive DTI analysis framework for non-technical researchers/investigators. We illustrate the use of our framework on a small sample, cross sectional neuroimaging study of eight healthy 1-year-old children from the Infant Brain Imaging Study (IBIS) Network. In this limited test study, we illustrate the power of our method by quantifying the diffusion properties at 1 year of age on the genu and splenium fiber tracts.

Diffusion-weighted imaging (DWI) is known to be prone to artifacts related to motion originating from subject movement, cardiac pulsation, and breathing, but also to mechanical issues such as table vibrations. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involves simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. The scientific community offers strong theoretical and experimental work on noise reduction and orientation distribution function (ODF) reconstruction techniques for HARDI data, where post-acquisition motion correction is widely performed, e.g., using the open-source DTIprep software (1), FSL (the FMRIB Software Library) (2), or TORTOISE (3). Nonetheless, effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk of introducing confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well-controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on a study of the impact of motion correction using four metrics that quantify (1) similarity of fiber orientation distribution functions (fODFs), (2) deviation of local fiber orientations, (3) global brain connectivity via graph diffusion distance (GDD), and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.

Sensory experience during early development can shape the central nervous system and this is thought to influence adult perceptual skills. In the auditory system, early induction of conductive hearing loss (CHL) leads to deficits in central auditory coding properties in adult animals, and this is accompanied by diminished perceptual thresholds. In contrast, a brief regimen of auditory training during development can enhance the perceptual skills of animals when tested in adulthood. Here, we asked whether a brief period of training during development could compensate for the perceptual deficits displayed by adult animals reared with CHL. Juvenile gerbils with CHL, and age-matched controls, were trained on a frequency modulation (FM) detection task for 4 or 10 days. The performance of each group was subsequently assessed in adulthood, and compared to adults with normal hearing (NH) or adults raised with CHL that did not receive juvenile training. We show that as juveniles, both CHL and NH animals display similar FM detection thresholds that are not immediately impacted by the perceptual training. However, as adults, detection thresholds and psychometric function slopes of these animals were significantly improved. Importantly, CHL adults with juvenile training displayed thresholds that approached NH adults. Additionally, we found that hearing impaired animals trained for 10 days displayed adult thresholds closer to untrained adults than those trained for 4 days. Thus, a relatively brief period of auditory training may compensate for the deleterious impact of hearing deprivation on auditory perception on the trained task.

Given the disproportionately high rates of obesity-related morbidity among low-income, ethnic minority youth, obesity prevention in this population is critical. Prior efforts to curb childhood obesity have had limited public health impact. The present study evaluates an innovative approach to obesity prevention by promoting foundational parenting and child behavioral regulation. This pre-post intervention study evaluated an enhanced version of ParentCorps with 91 families of pre-Kindergarten students in low-income, urban communities. Assessments included tests of knowledge and parent report. Consistent with findings from two randomized controlled trials of ParentCorps, parent knowledge and use of foundational parenting practices increased and child behavior problems decreased. Child nutrition knowledge and physical activity increased and television watching decreased; for boys, sleep problems decreased. Comparable benefits occurred for children at high risk for obesity based on child dysregulation, child overweight, and parent overweight. Results support a "whole child," family-centered approach to health promotion in early childhood.

Alzheimer's disease is a neurodegenerative disorder that is the most common cause of dementia in the elderly today. One of the earliest reported signs of Alzheimer's disease is olfactory dysfunction, which may manifest in a variety of ways. The present study sought to address this issue by investigating odor coding in the anterior piriform cortex, the primary cortical region involved in higher order olfactory function, and how it relates to performance on olfactory behavioral tasks. An olfactory habituation task was performed on cohorts of transgenic and age-matched wild-type mice at 3, 6 and 12 months of age. These animals were then anesthetized and acute, single-unit electrophysiology was performed in the anterior piriform cortex. In addition, in a separate group of animals, a longitudinal odor discrimination task was conducted from 3-12 months of age. Results showed that while odor habituation was impaired at all ages, Tg2576 performed comparably to age-matched wild-type mice on the olfactory discrimination task. The behavioral data mirrored intact anterior piriform cortex single-unit odor responses and receptive fields in Tg2576, which were comparable to wild-type at all age groups. The present results suggest that odor processing in the olfactory cortex and basic odor discrimination is especially robust in the face of amyloid beta precursor protein (AbetaPP) over-expression and advancing amyloid beta (Abeta) pathology. Odor identification deficits known to emerge early in Alzheimer's disease progression, therefore, may reflect impairments in linking the odor percept to associated labels in cortical regions upstream of the primary olfactory pathway, rather than in the basic odor processing itself.

Recent advances in neuroimaging methods have made accessible new ways of disentangling the complex interplay between genetic and environmental factors that influence structural brain development. In recent years, research investigating associations between socioeconomic status (SES) and brain development have found significant links between SES and changes in brain structure, especially in areas related to memory, executive control, and emotion. This review focuses on studies examining links between structural brain development and SES disparities of the magnitude typically found in developing countries. We highlight how highly correlated measures of SES are differentially related to structural changes within the brain.