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@ARTICLE{Pais:904388,
author = {Pais, Patricia and Mateo, Celine and Pan, Wen-Ju and
Acland, Ben and Kleinfeld, David and Snyder, Lawrence H. and
Yu, Xin and Keilholz, Shella},
title = {{C}ontribution of animal models toward understanding
resting state functional connectivity},
journal = {NeuroImage},
volume = {245},
issn = {1053-8119},
address = {Orlando, Fla.},
publisher = {Academic Press},
reportid = {FZJ-2021-05958},
pages = {118630 -},
year = {2021},
abstract = {Functional connectivity, which reflects the spatial and
temporal organization of intrinsic activity throughout the
brain, is one of the most studied measures in human
neuroimaging research. The noninvasive acquisition of
resting state functional magnetic resonance imaging
(rs-fMRI) allows the characterization of features designated
as functional networks, functional connectivity gradients,
and time-varying activity patterns that provide insight into
the intrinsic functional organization of the brain and
potential alterations related to brain dysfunction.
Functional connectivity, hence, captures dimensions of the
brain's activity that have enormous potential for both
clinical and preclinical research. However, the mechanisms
underlying functional connectivity have yet to be fully
characterized, hindering interpretation of rs-fMRI studies.
As in other branches of neuroscience, the identification of
the neurophysiological processes that contribute to
functional connectivity largely depends on research
conducted on laboratory animals, which provide a platform
where specific, multi-dimensional investigations that
involve invasive measurements can be carried out. These
highly controlled experiments facilitate the interpretation
of the temporal correlations observed across the brain.
Indeed, information obtained from animal experimentation to
date is the basis for our current understanding of the
underlying basis for functional brain connectivity. This
review presents a compendium of some of the most critical
advances in the field based on the efforts made by the
animal neuroimaging community.},
cin = {INM-4},
ddc = {610},
cid = {I:(DE-Juel1)INM-4-20090406},
pnm = {5253 - Neuroimaging (POF4-525)},
pid = {G:(DE-HGF)POF4-5253},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:34644593},
UT = {WOS:000714763700003},
doi = {10.1016/j.neuroimage.2021.118630},
url = {https://juser.fz-juelich.de/record/904388},
}