2008 Summer Project Week:fMRIconnectivity
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Key Investigators
- MIT: Bryce Kim, Polina Golland
- BWH: Jungsu Oh, Marek Kubicki
Objective
Our objective is to study functional connectivity of schizophrenia patients versus normal with unsupervised data-driven analysis methods, such as ICA and clustering.
Approach, Plan
Our approach for investigating functional connectivity of schizophrenia patients is to apply probabilistic independent component analysis (PICA) and clustering based on Gaussian mixture model (GMM).
Our plan for the project week is to first run such data-driven analysis methods on the data and then perform group analysis. We will also compare the results between PICA and GMM and investigate the factors that contribute to the differences.
Progress
We have applied standard fMRI preprocessing steps on the data and regressed out the effects of white matter and ventricles. We have also customized PICA for our analysis purpose and written GMM tools.
References
- Fletcher, P.T., Tao, R., Jeong, W.-K., Whitaker, R.T., "A Volumetric Approach to Quantifying Region-to-Region White Matter Connectivity in Diffusion Tensor MRI," to appear Information Processing in Medical Imaging (IPMI) 2007.
