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@PHDTHESIS{Reuter:916043,
author = {Reuter, Niels},
title = {{P}ainting the {B}rain by {N}umbers: {I}ntroducing an
open-source approach to automated regional
connectivity-based parcellation},
school = {Heinrich Heine Universitat Dusseldorf},
type = {Dissertation},
reportid = {FZJ-2022-05889},
pages = {161 p.},
year = {2022},
note = {Grants 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.; Dissertation,
Heinrich Heine Universitat Dusseldorf, 2022},
abstract = {Regional 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.},
cin = {INM-7},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {5235 - Digitization of Neuroscience and User-Community
Building (POF4-523) / 5251 - Multilevel Brain Organization
and Variability (POF4-525) / HBP SGA2 - Human Brain Project
Specific Grant Agreement 2 (785907)},
pid = {G:(DE-HGF)POF4-5235 / G:(DE-HGF)POF4-5251 /
G:(EU-Grant)785907},
typ = {PUB:(DE-HGF)11},
url = {https://juser.fz-juelich.de/record/916043},
}