This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The morphology of the human brain is exceptionally complex; reflecting a myriad of inextricably intertwined systems of neuronal cell bodies, axons, and other components. Groupings of neural components that share common structural or functional properties comprise the structural and functional neuroanatomic framework of the brain. Characterization of the morphologic properties of the brain and its component parts, as enabled by state-of-the-art magnetic resonance imaging (MRI) is exceptionally well suited to permit a quantitative study of the parameters relevant to the structural and functional makeup of the human brain in vivo. The goal of this grant is to continue to develop tools and methods for the precise quantitative analysis of brain morphology in health and disease, and to disseminate the tools and results of the application of these tools to the neuroscience community as a whole. Specifically, we will 1) extend our previously developed pixel segmentation and morphological quantification methods, continuing our efforts to develop a unified neuroanatomic segmentation framework and transition these tools to clinical applications on a routinely available software platform; 2) continue our previously developed methods to characterize shape and shape change metrics in normal subjects and pathological patient populations; and 3) dissemination of segmentation tools and comparison methods, as well as the results of image segmentation and volumetric analysis to the community as a whole using the World Wide Web.This application continues to take advantage of several unique aspects that distinguishes it from other related work. First, a unified framework for segmentation and classification in support of a neurologically-based anatomic morphology has emerged. Second, this unified framework incorporates the multispectral nature of MRI data. Third, this framework intrinsically includes estimates of the underlying uncertainty associated with the segmentation and classification process, which supports a rational assessment of sensitivity of a given method. Fourth, this approach expands upon traditional 'static' image analysis by incorporation of shape-based analysis for anomaly detection. In addition, we have identified a number of clinical application areas which, in addition to fostering enhanced analytic capabilities to studies in these areas, permits us to optimize the operational efficiency of the resulting analysis. Specifically, the segmentation, classification and shape analysis of MRI data in patients with stroke and Huntington's disease, as welt as the appropriate normative populations, provide a vital testbed for the evaluation of the clinical utility of these morphological analysis techniques.
| Green, Shulamite A; Hernandez, Leanna M; Bowman, Hilary C et al. (2018) Sensory over-responsivity and social cognition in ASD: Effects of aversive sensory stimuli and attentional modulation on neural responses to social cues. Dev Cogn Neurosci 29:127-139 |
| Yang, Yaling; Joshi, Shantanu H; Jahanshad, Neda et al. (2017) Neural correlates of proactive and reactive aggression in adolescent twins. Aggress Behav 43:230-240 |
| Dennis, Emily L; Rashid, Faisal; Faskowitz, Josh et al. (2017) MAPPING AGE EFFECTS ALONG FIBER TRACTS IN YOUNG ADULTS. Proc IEEE Int Symp Biomed Imaging 2017:101-104 |
| Walsh, Christine M; Ruoff, Leslie; Walker, Kathleen et al. (2017) Sleepless Night and Day, the Plight of Progressive Supranuclear Palsy. Sleep 40: |
| Green, Shulamite A; Hernandez, Leanna; Bookheimer, Susan Y et al. (2017) Reduced modulation of thalamocortical connectivity during exposure to sensory stimuli in ASD. Autism Res 10:801-809 |
| Kodumuri, Nishanth; Sebastian, Rajani; Davis, Cameron et al. (2016) The association of insular stroke with lesion volume. Neuroimage Clin 11:41-45 |
| Kamins, Joshua; Giza, Christopher C (2016) Concussion-Mild Traumatic Brain Injury: Recoverable Injury with Potential for Serious Sequelae. Neurosurg Clin N Am 27:441-52 |
| Agis, Daniel; Goggins, Maria B; Oishi, Kumiko et al. (2016) Picturing the Size and Site of Stroke With an Expanded National Institutes of Health Stroke Scale. Stroke 47:1459-65 |
| Levine, Andrew J; Soontornniyomkij, Virawudh; Achim, Cristian L et al. (2016) Multilevel analysis of neuropathogenesis of neurocognitive impairment in HIV. J Neurovirol 22:431-41 |
| Flournoy, John C; Pfeifer, Jennifer H; Moore, William E et al. (2016) Neural Reactivity to Emotional Faces May Mediate the Relationship Between Childhood Empathy and Adolescent Prosocial Behavior. Child Dev 87:1691-1702 |
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