000916043 001__ 916043
000916043 005__ 20230713130859.0
000916043 0247_ $$2Handle$$a2128/33147
000916043 037__ $$aFZJ-2022-05889
000916043 041__ $$aEnglish
000916043 1001_ $$0P:(DE-Juel1)170074$$aReuter, Niels$$b0$$ufzj
000916043 245__ $$aPainting the Brain by Numbers: Introducing an open-source approach to automated regional connectivity-based parcellation$$f- 2021-07-02
000916043 260__ $$c2022
000916043 300__ $$a161 p.
000916043 3367_ $$2DataCite$$aOutput Types/Dissertation
000916043 3367_ $$2ORCID$$aDISSERTATION
000916043 3367_ $$2BibTeX$$aPHDTHESIS
000916043 3367_ $$02$$2EndNote$$aThesis
000916043 3367_ $$0PUB:(DE-HGF)11$$2PUB:(DE-HGF)$$aDissertation / PhD Thesis$$bphd$$mphd$$s1671182612_19774
000916043 3367_ $$2DRIVER$$adoctoralThesis
000916043 502__ $$aDissertation, Heinrich Heine Universitat Dusseldorf, 2022$$bDissertation$$cHeinrich Heine Universitat Dusseldorf$$d2022$$o2022-03-03
000916043 500__ $$aGrants that are not listed:  - Deutsche Forschungsgemeinschaft (DFG, EI 816/11-1)  - National Institute of Mental Health (R01-MH074457)  - The Helmholtz Portfolio Theme "Supercomputing and Modelling for the Human Brain"Selecting a POF topic appears to be mandatory, but my work was done under the previous POF period.
000916043 520__ $$aRegional connectivity-based parcellation (rCBP) is a widely used procedure for investigating the structural and functional differentiation within a region-of-interest (ROI) based on its long-range connectivity. No standardized software or guidelines currently exist for applying rCBP, making the method only accessible to those who develop their own tools. A historical background to rCBP has been provided in chapter 1, which continues with the aim of this work: introducing CBPtools, an open-source software package implementing rCBP. The chapter concludes by detailing various methods and concepts associated with the rCBP procedure.CBPtools is a Python (version 3.5+) package that allows users to run an extensively evaluated rCBP analysis workflow on a given ROI. It currently supports two modalities: resting-state functional connectivity and structural connectivity based on diffusion-weighted imaging, along with support for custom connectivity matrices. Analysis parameters are customizable, and the workflow can be scaled to many subjects using a parallel processing environment. Parcellation results with corresponding validity metrics are provided as textual and graphical output. Thus, CBPtools provides a simple plug-and-play yet customizable way to conduct rCBP analyses. Chapter two discusses architectural choices, scope, and software dependencies, followed by a thorough description of all implemented features as well as a step-by-step guide through the processing pipeline.In chapter three we demonstrate the utility of CBPtools using a voluminous data set on an average compute-cluster infrastructure by performing rCBP on three ROIs prominently featured in parcellation literature. A side-project on the investigation of potential issues regarding outliers in the data set is added as chapter four.In closing we discuss our findings, provide recommendations, and suggest future extensions to the CBPtools software in chapters five and six. CBPtools is capable of reproducing parcellations found in existing literature. It offers flexibility in terms of customization while remaining easy to use. By providing an open-source software we aim to promote reproducible and comparable rCBP analyses and, importantly, make the rCBP procedure readily available.
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000916043 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x2
000916043 8564_ $$uhttps://juser.fz-juelich.de/record/916043/files/Painting%20the%20Brain%20by%20Numbers.pdf$$yOpenAccess
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