Скачать с ютуб OHBM2022 Functional connectivity parcellation - Ruby Kong в хорошем качестве

OHBM2022 Functional connectivity parcellation - Ruby Kong

Resting-state functional connectivity has shown great promise as a tool for parcellating the human brain into functional areas and networks. Until recently, most parcellations have relied on data averaged across many individuals. However, such group-level parcellations might obscure biologically meaningful individual-specific features. In this educational course, we will first introduce resting-state fMRI. We will then discuss several approaches (e.g., boundary mapping and clustering) for estimating network-level and areal-level brain parcellations at the group-level, as well as in individuals. We will also outline a systematic approach for assessing the quality of brain parcellations based on FACT (function, architectonics, connectivity and topography). After that, we will provide a comparison of various group-level and individual-specific parcellations with a particular focus on the behavioral relevance of individual-specific parcellation features not visible in group-level parcellations. Finally, we will briefly discuss individual-specific gradients and compare gradients with parcellations for behavioral prediction. Article discussed https://www.physiology.org/doi/full/1... (Yeo et al. 2011) https://www.sciencedirect.com/science... (Power et al. 2011) https://academic.oup.com/cercor/artic... (Gordon et al. 2016) https://academic.oup.com/cercor/artic... (Schaefer et al. 2017) https://www.cell.com/neuron/fulltext/... (Gordon et al. 2017) https://academic.oup.com/cercor/advan... (Kong et al. 2018) Software employed https://github.com/ThomasYeoLab/CBIG https://fsl.fmrib.ox.ac.uk/fsl/fslwiki https://surfer.nmr.mgh.harvard.edu/ Data available at https://db.humanconnectome.org https://openfmri.org/