2000 |
Zielinski, Brandon A |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
Auditory-Visual Integration in Speech Perception
This research will aid our understanding of the functional organization and specialization of the cerebral cortex in humans and its role in sensory perception. In particular, it will aid our understanding of primary and nonprimary auditory cortex and of the neurobiological mechanisms underlying the processing of speech sounds. In addition to identifying the neural mechanisms underlying the McGurk effect, which is relevant to much investigation in linguistics and other studies of speech processing, this research will contribute to our understanding of auditory-visual integration processes in normal and atypical speech perception and of more general principles of auditory- visual integration. Additionally, this research will aid our understanding of the fundamental principles of cross-modal integration and multimodal sensory perception, and will identify neuroanatomical substrates and neurobiological mechanisms which may be involved in these processes. The understanding of neurobiological mechanisms of human brain function, and the evolution of these mechanisms is our long-range goal. Ultimately, this research will aid in the understanding of major dysfunctions of speech and hearing such as sensory and phonological aphasia, and will enable us to design and implement more appropriate therapeutic approaches to neurological impairments based upon fundamental principles of speech processing. In addition, employing functional magnetic resonance imaging (fMRI) to identify neural mechanisms of speech perception permits both the direct correlation of function with anatomy and repeated studies in the same individual. Thus, it will undoubtedly prove to be extremely useful in presurgical mapping, determining hemispheric dominance in epilepsy patients, and monitoring recovery from stroke or cerebral trauma. Additionally, the use of fMRI in these experiments would aid in establishing this methodology as a powerful clinical tool, an application that would have a profound impact on clinical care.
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1 |
2014 — 2017 |
Zielinski, Brandon A. |
K08Activity Code Description: To provide the opportunity for promising medical scientists with demonstrated aptitude to develop into independent investigators, or for faculty members to pursue research aspects of categorical areas applicable to the awarding unit, and aid in filling the academic faculty gap in these shortage areas within health profession's institutions of the country. |
Brain Network Development in Normal and Autistic Children
PROJECT SUMMARY / ABSTRACT [This proposal is designed to facilitate the career development and transition to independence of Brandon A. Zielinski, M.D., Ph.D. At the conclusion of the award term, Dr. Zielinski will be a fully independent investigator, poised to build a rigorous, broad-based research laboratory that will make substantial contributions to diagnosis, prognosis, treatment, and understanding of childhood neurological disorders by probing functional and structural connectivity abnormalities in large-scale brain networks using innovative neuroimaging methods. Although Dr. Zielinski has extensive mentored experience in functional and structural MRI research, he is in need of further training in specific methodologies relating to MRI data acquisition and processing (particularly DTI), technical aspects of structural and functional MRI, integration of complex multimodal neuroimaging data, neuropsychological assessment of normal and autistic children, and multidimensional statistics. This proposal will provide intensive and multifaceted mentored training experience through which he will acquire in-depth understanding in all of these areas. Under this award, he will conduct comprehensive neuroimaging research requiring subject assessment, data acquisition, processing, and management, advanced statistical analysis, and integration of complex neuroimaging and neurobehavioral datasets. Dr. Zielinski will be supported by a mentorship team with extensive and complementary expertise in all of these areas. Through this proposal, he will obtain the depth as well as breadth of knowledge, skill, and experience required to become an exceptional independent researcher, and a leader in his field. Structure begets function in the human brain, yet the structure-function interrelationships of human brain networks remain unknown. This proposal seeks to establish that large-scale brain networks reflect conserved intrinsic patterns of correlated functional activity, white matter fiber connectivity, and gray matter morphology shared by neural neighborhoods separated by long distances. Major goals are to identify and characterize functional and structural brain networks in children, and to determine how large-scale network patterns emerge in early human development. Accumulating evidence suggests that autism is a network-based disease, and that abnormalities in network structure may underlie the abnormal brain function at the core of the disease. Discovery of early network abnormalities in autism will provide a new framework for understanding this complex illness and lead to new pathways for diagnosis and treatment. We propose to combine an emerging neuroimaging technique (structural covariance MRI, scMRI) with established advanced neuroimaging techniques (functional connectivity MRI, fcMRI, and diffusion tensor imaging, DTI) in order to identify and characterize the brain's fundamental large-scale network architecture. This innovative approach will enable development of a structure-function model of network organization in the human brain synthesizing gray matter structure, white matter structure, and brain network function. Applying this approach in children will provide a foundation for understanding emergence of large-scale brain networks involved in specific domains of human cognition, greatly impacting our understanding of human growth and development. Furthermore, identifying normal neurodevelopmental patterns will advance our ability to detect perturbations of these systems in conditions of neurologic dysfunction and disease, enabling innovative approaches to optimization, preservation, and recovery of function in neurologically affected children. Discovering the unique bioimaging phenotype of autism could profoundly impact our ability to detect, diagnose, and treat this devastating condition. This work will form the basis of a synergistic and fundamental model of human brain organization and development with broad application to human health and disease, fueling Dr. Zielinski for the duration of his career.]
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0.957 |