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Karl-Heinz Nenning: Analysis of fMRI data using functional parcellation and functional connectivity

Spezifikationsvortrag DA

What
  • Presentation
When Nov 10, 2009
from 05:15 pm to 05:35 pm
Where Sem 183/2
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Functional MRI is a powerful non-invasive tool to analyze the relationship between stimulus and activation of brain areas by means of the BOLD (blood oxygenlevel dependent) signal. Since there are always anatomical and functional differences between brains of subjects, usually spatial normalization to a reference space and spatially smoothing of the data is used.

Without placing any a priori constraints, data driven parcellation methods can be used to delineate homogenous and connected regions of the brain. Furthermore significant data reduction is achieved which alleviates further processing.

The goal of this master thesis is to implement a parcellation method based on spectral clustering to analyze fMRI data of phantom pain patients which are treated with mirror therapy. It should be used to detect functional connectivity patterns of the fMRI data, which leads to a delineation of the interactivity and the functional meaning of the parcels.
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