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MICCAI
2008
Springer

Discovering Structure in the Space of Activation Profiles in fMRI

11 years 2 months ago
Discovering Structure in the Space of Activation Profiles in fMRI
We present a method for discovering patterns of activation observed through fMRI in experiments with multiple stimuli/tasks. We introduce an explicit parameterization for the profiles of activation and represent fMRI time courses as such profiles using linear regression estimates. Working in the space of activation profiles, we design a mixture model that finds the major activation patterns along with their localization maps and derive an algorithm for fitting the model to the fMRI data. The method enables functional group analysis independent of spatial correspondence among subjects. We validate this model in the context of category selectivity in the visual cortex, demonstrating good agreement with prior findings based on hypothesis-driven methods.
Danial Lashkari, Ed Vul, Nancy Kanwisher, Polin
Added 06 Nov 2009
Updated 06 Nov 2009
Type Conference
Year 2008
Where MICCAI
Authors Danial Lashkari, Ed Vul, Nancy Kanwisher, Polina Golland
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