Functional and Anatomic Image Analysis and Biostatistics Core
Project Leader: Nikos Makris, MD, PhD
The overarching goal of the Functional and Anatomic Image Analysis and Biostatistics Core is to provide a common neuroimaging anatomical, functional, statistical, modeling and neuroinformatics framework to be used by the Projects to facilitate structure/function, inter-paradigm, and inter-species analyses as well as databasing and data sharing across Projects. Functional MRI (fMRI) can provide information about both the location of cortical and subcortical areas involved in the response to acupuncture, and dynamic information relating to the temporal interrelationships of these areas. In addition, conventional MRI provides an exquisite view of structural neuroanatomy. Thus the goal of this Core is to provide a reproducible and efficient means for obtaining, analyzing, testing and reporting the resultant structural and functional data. Data derived from different imaging modalities need to be integrated. Each one of these will result in a host of measures, which represent a quantitative dimension vector and can be used to elucidate the structural underpinnings of the structural, functional, behavioral and clinical dimension vector statistically. The combination of cortical, subcortical gray and white matter fiber tract measurements will allow us to perform quantitative neural systems analysis with particular emphasis on the limbic and paralimbic systems, the autonomic system, the pain neuromatrix, the corticostriatal system and the Default mode network. The framework provided by the neural systems and the observation of their structural and functional properties creates a unique opportunity to perform quantitative modeling (such as structural equation mobeling or Granger's causality analysis) of these observations. Furthermore, the multimodal nature of the data requires a modeling approach to integrate the information across the different imaging modalities. |
