We seek sponsorship from the NIH to support a new and innovative program in the fundamentals and applications of neuroimaging. It is premised on the belief that neuroscientists of tomorrow are likely to require mastery of neuroimaging methods and principles in their work to address the growing burden of neurological disease and to perform the studies that will best advance our understanding of human behavior and cognition. This application includes both T-90 and R-90 components for our pre-doctoral students. The UCLA Comprehensive Neuroimaging Training Program (NITP) seeks to train pre-doctoral students in principles of neuroimaging that are fundamental - common to most or all neuroimaging - in recognition of the rapid changes that have occurred and will continue in imaging technology. They will be exposed to an unusually complete range of imaging approaches from cellular to whole brain, from structural to dynamic and inclusive of advanced multi-modality imaging. Our students will be full participants in the neurosciences interdepartmental program at UCLA, but will benefit from additional specialized course work and experience. The NITP will be both complementary to, and participatory in, existing programs in neurosciences and computational biology already well-established at UCLA. The students will benefit from the large and experience neuroimaging faculty and from courses newly-developed for this program. Responsive to the Short Course opportunities the NITP will sponsor an annual one-week fellowship in functional neuroimaging and an outreach program where the faculty and trainees will deliver content to local schools. We also will hold an annual seminar, directed principally to the lay audience, intended to educate the public on the results and important limitations of neuroimaging. Each of these short course programs will serve important educational objectives for the NITP students, who will serve as facilitators and instructors. ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Interdisciplinary Research Training Award (T90)
Project #
5T90DA022768-03
Application #
7488878
Study Section
Special Emphasis Panel (ZEY1-VSN (02))
Program Officer
Grant, Steven J
Project Start
2006-09-30
Project End
2011-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
3
Fiscal Year
2008
Total Cost
$175,119
Indirect Cost
Name
University of California Los Angeles
Department
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Kerr, Wesley T; Janio, Emily A; Braesch, Chelsea T et al. (2018) An objective score to identify psychogenic seizures based on age of onset and history. Epilepsy Behav 80:75-83
Kerr, Wesley T; Janio, Emily A; Braesch, Chelsea T et al. (2017) Identifying psychogenic seizures through comorbidities and medication history. Epilepsia 58:1852-1860
Kerr, Wesley T; Janio, Emily A; Braesch, Chelsea T et al. (2017) Diagnostic implications of review-of-systems questionnaires to differentiate epileptic seizures from psychogenic seizures. Epilepsy Behav 69:69-74
Kerr, Wesley T; Janio, Emily A; Le, Justine M et al. (2016) Diagnostic delay in psychogenic seizures and the association with anti-seizure medication trials. Seizure 40:123-6
Ching, Christopher R K; Hua, Xue; Hibar, Derrek P et al. (2015) Does MRI scan acceleration affect power to track brain change? Neurobiol Aging 36 Suppl 1:S167-77
Suthana, Nanthia A; Parikshak, Neelroop N; Ekstrom, Arne D et al. (2015) Specific responses of human hippocampal neurons are associated with better memory. Proc Natl Acad Sci U S A 112:10503-8
Douglas, Pamela K; Pisani, Maureen; Reid, Rory et al. (2014) Method for simultaneous fMRI/EEG data collection during a focused attention suggestion for differential thermal sensation. J Vis Exp :e3298
Schreiner, Matthew J; Karlsgodt, Katherine H; Uddin, Lucina Q et al. (2014) Default mode network connectivity and reciprocal social behavior in 22q11.2 deletion syndrome. Soc Cogn Affect Neurosci 9:1261-7
Kerr, Wesley T; Douglas, Pamela K; Anderson, Ariana et al. (2014) The utility of data-driven feature selection: re: Chu et al. 2012. Neuroimage 84:1107-10
LeMoyne, Robert; Kerr, Wesley T; Zanjani, Kevin et al. (2014) Implementation of an iPod wireless accelerometer application using machine learning to classify disparity of hemiplegic and healthy patellar tendon reflex pair. J Med Imaging Health Inform 4:21-28

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