% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Bottenhorn:845833,
author = {Bottenhorn, Katherine L and Flannery, Jessica S and
Boeving, Emily R and Riedel, Michael C and Eickhoff, Simon
and Sutherland, Matthew T and Laird, Angela R},
title = {{C}ooperating yet distinct brain networks engaged during
naturalistic paradigms: {A} meta-analysis of functional
{MRI} results},
journal = {Network neuroscience},
volume = {3},
number = {1},
issn = {2472-1751},
address = {Cambridge, MA},
publisher = {The MIT Press},
reportid = {FZJ-2018-03040},
pages = {27-48},
year = {2019},
note = {This study was supported by awards from the National
Institute of Drug Abuse (U01-DA041156, K01-DA037819,
U24-DA039832, R01DA041353), the National Institute of Mental
Health (R56-MH097870),and the National Science Foundation
(1631325 and REAL DRL-1420627). The authors declare no
competing financial interests},
abstract = {Cognitive processes do not occur by pure insertion and
instead depend on the full complement of co-occurring mental
processes, including perceptual and motor functions. As
such, there is limited ecological validity to human
neuroimaging experiments that use highly controlled tasks to
isolate mental processes of interest. However, a growing
literature shows how dynamic, interactive tasks have allowed
researchers to study cognition as it more naturally occurs.
Collective analysis across such neuroimaging experiments may
answer broader questions regarding how naturalistic
cognition is biologically distributed throughout the brain.
We applied an unbiased, data-driven, meta-analytic approach
that uses k-means clustering to identify core brain networks
engaged across the naturalistic functional neuroimaging
literature. Functional decoding allowed us to, then,
delineate how information is distributed between these
networks throughout the execution of dynamical cognition in
realistic settings. This analysis revealed six recurrent
patterns of brain activation, representing sensory,
domain-specific, and attentional neural networks that
support the cognitive demands of naturalistic paradigms.
Though gaps in the literature remain, these results suggest
that naturalistic fMRI paradigms recruit a common set of
networks that that allow both separate processing of
different streams of information and integration of relevant
information to enable flexible cognition and complex
behavior.},
cin = {INM-7},
ddc = {610},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {574 - Theory, modelling and simulation (POF3-574)},
pid = {G:(DE-HGF)POF3-574},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:30793072},
UT = {WOS:000449591500002},
doi = {10.1162/netn_a_00050},
url = {https://juser.fz-juelich.de/record/845833},
}