Connectivity-Driven Parcellation Methods for the Human Cerebral Cortex

In this thesis, we present robust and fully-automated methods for the subdivision of the entire human cerebral cortex based on connectivity information. Our contributions are four-fold: First, we propose a clustering approach to delineate a cortical parcellation that provides a reliable abstraction of the brain's functional organisation... (read more)

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