Abstract

The complementary spatial, temporal and specificity advantages of MRI, EEG, MEG, PET and DOT for functional brain imaging motivate interest in multimodal functional brain imaging. State-variable dynamical systems modeling of neural activity and its relation to local hemodynamics further coupled with autonomic physiology offers enhanced spatiotemporal resolution and insight into physiological signals and mechanisms. However, such a model also implies an explosion of state dimension. We discuss strategies for controlling this high dimensionality based on subspace approaches applied to the observed data and the model structure, and also describe some implications for understanding human brain function.

Notes

Poster presented at the 2006 Thrust R2A Multi-View Tomographic Methods Conference

Keywords

Multimodal Functional Brain Imaging, MRI, EEG, MEG, PET, DOT, brain

Subject Categories

Brain mapping, Diagnostic imaging

Disciplines

Biomedical Engineering and Bioengineering

Publisher

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

Publication Date

2006

Rights Holder

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

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