An Overview, Challenges, and Future Directions - SAMSI
An Overview, Challenges, and Future Directions - SAMSI
An Overview, Challenges, and Future Directions - SAMSI
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Experiments Models Connectivity Prediction Summary<br />
Bayesian spatial hierarchical model<br />
[Derado et al., 2012, Statistical Methods in Medical Research].<br />
Notation<br />
We developed a Bayesian spatial hierarchical model for predicting<br />
follow-up neural activity based on baseline functional neuroimaging<br />
data <strong>and</strong> other patient characteristics.<br />
Model borrows strength from spatial correlations present in the data.<br />
Let i = 1, . . . , n denote subjects, v = 1, . . . , V voxels, g = 1, . . . , G<br />
regions.<br />
Let Y (v) denote the regional cerebral blood flow (rCBF) (a proxy for<br />
brain activity) at voxel v.<br />
(<br />
) T<br />
Let Y ig (v) = Y ig (v) (1) , Y ig (v) (2) , (1)=baseline, (2)=follow-up.<br />
F. D. Bowman (Emory University) <strong>SAMSI</strong>: NDA RTP, NC 59 / 77
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