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@INPROCEEDINGS{Weis:911682,
author = {Weis, Susanne},
title = {{M}ovies in the {M}agnet: {N}aturalistic {V}iewing for
phenotype prediction},
reportid = {FZJ-2022-04937},
year = {2022},
abstract = {In recent years, most research on phenotype prediction from
functional connectivity (FC) of the brain has been based on
resting state (RS) data, where participants lie in the
scanner without any particular task or any external
stimulation. However, one of the major drawbacks of this
approach is that, in the absence of a task, RS FC is
influenced by the spontaneous thoughts of the participant
and is therefore badly standardized. To address this
limitation, naturalistic viewing (NV), during which
participants are presented with movie clips while inside the
scanner, has been suggested as an emerging tool for the
study of individual differences. By closer mimicking
conditions under which the brain naturally operates, NV
promises to capture more ecologically valid neuronal
responses and thereby increase prediction accuracies.
Furthermore, by choosing stimuli to match the phenotype of
interest, it might be possible to manipulate brain state to
further increase predictive power. I will discuss recent
results from our group addressing the question whether
phenotype prediction based on NV is indeed superior to RS
based predictions. },
month = {Jun},
date = {2022-06-14},
organization = {20th Brain Connectivity Workshop
- „20 years of Brain Connectivity
Research: Breakthroughs in
understanding mechanisms and predicting
function“, Düsseldorf (online
event), 14 Jun 2022 - 14 Jun 2022},
subtyp = {Other},
cin = {INM-7},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {5252 - Brain Dysfunction and Plasticity (POF4-525)},
pid = {G:(DE-HGF)POF4-5252},
typ = {PUB:(DE-HGF)6},
url = {https://juser.fz-juelich.de/record/911682},
}