Functional neuroimaging studies of the human brain have become increasingly important in the understanding of normal and pathological processes of cognition. Sophisticated statistical analytic frameworks have been developed to locate signal change and define brain networks involved in various tasks. However, in subtle cognitive impairment-e.g., exposure-related illness, early stages of degenerative diseases, injury, secondary illness following adjuvant therapy for cancer-these methods tend to have low sensitivity for detecting small changes in brain states resulting from mild brain dysfunction. An understanding of disease mechanism or progression of subtle cognitive dysfunction requires a novel statistical analytic framework with improved sensitivity to measure small changes in brain states. We have developed an innovative methodology that we successfully applied in measures of regional cerebral blood flow experiments. These methods use well established spatial modeling procedures, new to the functional brain imaging field, to derive statistically optimal spatial summaries within effective resolution groups or "kriging", shown by preliminary studies to improve signal detection sensitivity and mitigate the multiple testing burden. Within this new spatial modeling framework, we propose to extend the kriging methodology to fMRI and EEG, modify existing techniques for characterizing brain networks of connectivity (e.g., kriging-based independent components analysis), and integrate the imaging modalities using a statistical classifier based on derived inputs of data driven effective resolution groups. Our primary goal is to develop this analysis framework to provide insight into the neurophysiological mechanisms of mild cognitive dysfunction. Achieving this goal may suggest treatments to alleviate symptoms, prevent progression, or at minimum, provide an informed clinical management of cognitively impaired patients.

Public Health Relevance

Cognitive impairment is a major health concern, affecting people of all ages. Causes range from traumatic injury to toxin exposures, including chemotherapy for cancer treatment, to degenerative diseases. Mechanisms of damage or disease remain difficult to establish using current methods in functional brain imaging studies due to an inability to measure very small changes in brain states. We propose a new analytic framework using existing technology to improve the ability to measure subtle changes important in the understanding of disease pathology of impaired cognition and to greatly facilitate the integration of information from several imaging modalities with potential implications for clinical management and treatment.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21EB014563-01
Application #
8229843
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Pai, Vinay Manjunath
Project Start
2012-04-01
Project End
2013-01-31
Budget Start
2012-04-01
Budget End
2013-01-31
Support Year
1
Fiscal Year
2012
Total Cost
$173,138
Indirect Cost
$56,472
Name
University of Texas Sw Medical Center Dallas
Department
Other Clinical Sciences
Type
Schools of Medicine
DUNS #
800771545
City
Dallas
State
TX
Country
United States
Zip Code
75390