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MRI brain parcellation based on data-driven methods

One of the Lab’s research interest is the use of brain connectivity information (and, in particular, in combining structural and functional connectivity information) to perform data-driven parcellation of the brain (i.e. sub-division of the brain structures into well-define parcels or regions of meaningful anatomical or functional significance).

For example, we have recently demonstrated how the combination of structural connectivity, functional connectivity and dynamic connectivity can be exploited to parcellate the corpus callosum (one of the largest white matters structures in the human brain) (see figure). This white matter parcellation can be subsequently used, in combination with diffusion MRI fibre-tracking, to achieve cortical segregation (see figure). All these results are obtained in a data-driven way, without having to rely on a prior assumption of how the white matter or cerebral cortex is subdivided. Our Lab will continue to develop and optimise these type of connectivity-based parcellation methods, as well as to assess their role in various neurological disorders.

Reference:
Calamante F, Smith RE, Liang X, Zalesky A, Connelly A. Track-weighted dynamic functional connectivity (TWdFC): a new method to study dynamic connectivity. In Proc. Annual Meeting of the Intl. Soc. Mag. Reson. Med. (ISMRM) 24 (2016), Singapore, p. 308.
 

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