| NSF Org: |
DMS Division Of Mathematical Sciences |
| Recipient: |
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| Initial Amendment Date: | February 11, 2014 |
| Latest Amendment Date: | May 22, 2018 |
| Award Number: | 1352213 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Gabor Szekely
DMS Division Of Mathematical Sciences MPS Directorate for Mathematical and Physical Sciences |
| Start Date: | July 1, 2014 |
| End Date: | June 30, 2020 (Estimated) |
| Total Intended Award Amount: | $400,000.00 |
| Total Awarded Amount to Date: | $400,000.00 |
| Funds Obligated to Date: |
FY 2015 = $83,788.00 FY 2016 = $89,703.00 FY 2017 = $91,175.00 FY 2018 = $50,741.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
660 S MILL AVENUE STE 204 TEMPE AZ US 85281-3670 (480)965-5479 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
P O Box 1804 Tempe AZ US 85287-1804 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
STATISTICS, Division Co-Funding: CAREER |
| Primary Program Source: |
01001516DB NSF RESEARCH & RELATED ACTIVIT 01001617DB NSF RESEARCH & RELATED ACTIVIT 01001718DB NSF RESEARCH & RELATED ACTIVIT 01001819DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.049 |
ABSTRACT
Understanding functions of the human brain is a very challenging yet crucially important task. To advance knowledge about brain functions, pioneering technologies such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS) have been widely used in neuroimaging experiments. Focusing on such neuroimaging studies, the investigator identifies optimal and efficient experimental designs to allow researchers to collect informative data for rendering precise and valid statistical inference on human brain functions. Specifically, the investigator will develop fundamental theories to provide insights and guidance on selecting optimal designs for fMRI studies. He will also develop efficient computational tools for obtaining designs for modern fMRI experiments with sophisticated experimental settings and/or advanced statistical analysis methods. Various practical situations will be considered. These will include cases where (i) the experimental subject's probabilistic behavior needs to be taken into account at the design stage; (ii) the hemodynamic response function, which models the subject's brain activity in response to a brief mental stimulus, can vary over time; and (iii) flexible statistical approaches such as semi- and non-parametric methods are considered for a better interpretation of the rather complex neuroimaging data. In addition to the popularly used fMRI, the investigator will obtain and study high-quality designs for experiments utilizing some other pioneering brain mapping techniques such as EEG and fNIRS.
The research results will allow researchers to select experimental designs to improve the quality of neuroimaging experiments for studying brain functions. They will benefit society by facilitating the use of pioneering brain mapping technologies in advancing knowledge about some terrifying brain disorders such as Alzheimer's disease, and about how the brains work when we learn, remember and make decisions. To further broaden the impact of the research, the investigator will provide free, user-friendly software packages for researchers and practitioners to easily obtain high-quality neuroimaging experimental designs. In addition, new courses on design of experiments will be developed. These courses will help students to gain practically useful knowledge and skills on design and analysis of modern scientific experiments.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Functional brain imaging studies, such as functional magnetic resonance imaging (fMRI) experiments, and functional near-infrared spectroscopy (fNIRS) experiments, allow researchers to gain important insights into how the human brain works. These studies are widely conducted to understand the inner working of our brain, and some brain disorders such as Alzheimer’s disease, epilepsy and traumatic brain injury. Due to the complexity of the human brain, sophisticated statistical methods are almost always needed for extracting useful information from the collected data. A key first step to the success of such statistical inference is to select a high-quality experimental design for these brain imaging studies to allow the collection of the most informative data at minimum cost. This, however, is a challenging task, and not much work has previously been done. This project involves a systematic research on optimal experimental designs to provide novel statistical design theory, and practically useful approaches to guide the selection of high-quality designs for modern functional brain imaging experiments, and to improve the quality of statistical analysis results in these studies.
In this project, the PI and his collaborators developed some fundamental theories for optimal experimental designs for functional brain imaging studies. These results provide rather general rules, and in-depth insights into optimal brain imaging experimental designs to help avoid the use of inefficient designs, and to guide the selection of good designs. Several new classes of optimal designs are identified in this project to largely enhance the library of high-quality designs for functional brain imaging studies. The PI also developed some very efficient computational approaches, and user-friendly computer programs for experimenters to generate good designs for brain imaging studies that have complex structures. These research results are made publicly available to allow researchers and practitioners to select or obtain the designs best suited to their studies. To increase the broader impacts, the PI has been disseminating important findings of this research through conference presentations, and journal publications. Moreover, the PI developed new courses that cover the important findings of this research. He also trains graduate students on conducting research on this and related areas to foster future workforce.
Last Modified: 08/30/2020
Modified by: Ming-Hung Kao
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