The objective of the project is to accelerate discovery and a new program for multidisciplinary interaction across cognitive neuroscience, human neuroimaging and medicine at the University of Washington (UW). The project uses the infrastructure of the Integrated Brain Imaging Center to partner with existing established Centers and groups whose scientific programs can immediately investigate basic and translational questions in neurodegenerative disease, brain aging, epilepsy, and rehabilitation of paralysis with new systems neuroimaging approaches. The UW is a premier biomedical research institution and a particularly strong institutional setting for using imaging to elucidate biological mechanisms and biomarkers of disease, and for conducting translational studies. The theme of this proposal is the application of emerging systems neuroimaging approaches to key basic problems in neurologic disease pathophysiology, and key translational settings. One project cluster centers around novel uses of systems neuroimaging and MR spectroscopy to understand mechanisms in degenerative disease (Alzheimer disease, Parkinson disease). One goal is to understand and detect the early vulnerability of the default mode network in Alzheimer disease. For this work, we will use two subject groups: well characterized mild cognitive impairment, which often reflects incipient Alzheimer disease, and aging individuals who have been rigorously stratified with respect to their cognitive trajectories in midlife and old age. A second goal is to understand cognitive impairments in Parkinson disease, which arise in the setting of disturbances primarily in ascending systems. A third goal is understanding factors governing prognosis for language and other cognitive impairments after epilepsy surgery. A second cluster project cluster is driven by outstanding UW expertise in human neurophysiology, electrophysiology and sensorimotor engineering, and focuses on integration of imaging with electrophysiology to understand the neurophysiologic dynamics of clinically relevant large scale systems (default mode network, dorsal attentional network), and to improve brain-computer interfaces for rehabilitation of paralysis. For each collaboration we propose an initial high impact study and future directions.

Public Health Relevance

This project will develop new collaborative scientific teams at the University of Washington to work in partnership with the Integrated Brain Imaging Center and apply new imaging methods to degenerative dementia, brain aging, epilepsy, and rehabilitation of paralysis. One cluster of projects will investigate the biological basis of early Alzheimer disease, disorders of attention and concentration in Parkinson disease, and language problems in epilepsy surgery. A second cluster of projects will used EEG and imaging to understand signaling in brain systems and how to extract signals for controlling brain-computer interfaces. )

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
High Impact Research and Research Infrastructure Programs—Multi-Yr Funding (RC4)
Project #
1RC4NS073008-01
Application #
8047111
Study Section
Special Emphasis Panel (ZRG1-BDCN-A (55))
Program Officer
Babcock, Debra J
Project Start
2010-09-30
Project End
2013-08-31
Budget Start
2010-09-30
Budget End
2013-08-31
Support Year
1
Fiscal Year
2010
Total Cost
$4,784,830
Indirect Cost
Name
University of Washington
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Boord, Peter; Madhyastha, Tara M; Askren, Mary K et al. (2017) Executive attention networks show altered relationship with default mode network in PD. Neuroimage Clin 13:1-8
Chaovalitwongse, W Art; Won, Daehan; Seref, Onur et al. (2017) Network Optimization of Functional Connectivity Within Default Mode Network Regions to Detect Cognitive Decline. IEEE Trans Neural Syst Rehabil Eng 25:1079-1089
Lee, Adél; Särkkä, Aila; Madhyastha, Tara M et al. (2017) Characterizing cross-subject spatial interaction patterns in functional magnetic resonance imaging studies: A two-stage point-process model. Biom J 59:1352-1381
Wang, Sijia; Peterson, Daniel J; Gatenby, J C et al. (2017) Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI. Front Neuroinform 11:17
Askren, Mary K; McAllister-Day, Trevor K; Koh, Natalie et al. (2016) Using Make for Reproducible and Parallel Neuroimaging Workflow and Quality-Assurance. Front Neuroinform 10:2
Gaiteri, Chris; Chen, Mingming; Szymanski, Boleslaw et al. (2015) Identifying robust communities and multi-community nodes by combining top-down and bottom-up approaches to clustering. Sci Rep 5:16361
Madhyastha, Tara M; Askren, Mary K; Boord, Peter et al. (2015) Cerebral perfusion and cortical thickness indicate cortical involvement in mild Parkinson's disease. Mov Disord 30:1893-900
Madhyastha, Tara M; Askren, Mary K; Zhang, Jing et al. (2015) Group comparison of spatiotemporal dynamics of intrinsic networks in Parkinson's disease. Brain 138:2672-86
Tungaraza, Rosalia L; Mehta, Sonya H; Haynor, David R et al. (2015) Anatomically informed metrics for connectivity-based cortical parcellation from diffusion MRI. IEEE J Biomed Health Inform 19:1375-83
Madhyastha, Tara M; Askren, Mary K; Boord, Peter et al. (2015) Dynamic connectivity at rest predicts attention task performance. Brain Connect 5:45-59

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