2018
DOI: 10.1016/j.neuroimage.2017.11.046
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Resting-state functional connectivity remains unaffected by preceding exposure to aversive visual stimuli

Abstract: While much is known about immediate brain activity changes induced by the confrontation with emotional stimuli, the subsequent temporal unfolding of emotions has yet to be explored. To investigate whether exposure to emotionally aversive pictures affects subsequent resting-state networks differently from exposure to neutral pictures, a resting-state fMRI study implementing a two-group repeated-measures design in healthy young adults (N = 34) was conducted. We focused on investigating (i) patterns of amygdala w… Show more

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Cited by 9 publications
(7 citation statements)
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“…Before turning to the novel aspects of the present study, we first sought to root our individual differences analyses in a replication of past work of group-level amygdala RSFC patterns (Geissmann et al, 2018). First, pre-encoding resting-state networks resembled those previously reported (Roy et al, 2009;Geissmann et al, 2018), with positive RSFC of the bilateral amygdala with large swaths of ventromedial and dorsomedial prefrontal cortex (PFC), temporal lobes, orbital and inferior PFC (Fig.…”
Section: Resting-state Fmri Resultsmentioning
confidence: 70%
See 1 more Smart Citation
“…Before turning to the novel aspects of the present study, we first sought to root our individual differences analyses in a replication of past work of group-level amygdala RSFC patterns (Geissmann et al, 2018). First, pre-encoding resting-state networks resembled those previously reported (Roy et al, 2009;Geissmann et al, 2018), with positive RSFC of the bilateral amygdala with large swaths of ventromedial and dorsomedial prefrontal cortex (PFC), temporal lobes, orbital and inferior PFC (Fig.…”
Section: Resting-state Fmri Resultsmentioning
confidence: 70%
“…We first examined group-level pre-encoding (Z Pre ) amygdala RSFC maps as a comparison to prior work characterizing RSFC networks of the amygdala. For comparison with previous work reporting few changes in the amygdala RSFC following emotion picture viewing (Geissmann et al, 2018), next we examined overall pre-to postencoding increases in amygdala RSFC (Z Post Ͼ Z Pre masked with Z Post thresholded at p Ͻ 0.005). These first two analyses were used to establish our group findings before exploring the novel inter-individual difference questions central to the purpose of the current study.…”
Section: Resting-state Fmri Analysesmentioning
confidence: 99%
“…Omission of NR in the derivation of FC maps from dual regression can prevent a potential source of error whose impact cannot be gauged precisely without knowledge of the exact spatial distributions of signals within the fMRI data. Rather than include all spatial maps from group ICA as spatial priors (Abram et al, ; Filippini et al, ; Geissmann et al, ; Muetzel et al, ; Pannekoek et al, ; Rueter, Abram, MacDonald, Rustichini, & DeYoung, ; Smith et al, ), some dual regression studies omit spatial priors thought to represent noise (Baggio et al, ; Fan et al, ; Giorgio, Zhang, Costantino, De Stefano, & Frezzotti, ; Ishaque et al, ; Klaassens et al, ; Schumacher et al, ); however, the remaining “nuisance” spatial maps may still reduce FC map accuracy, through mechanisms described in this article: Appendix A shows an example where DRA quality scores did not improve after omitting only spatial priors thought to represent structured noise. Reduction of NR to a small number that are highly consistent in spatial distributions across all subjects/sessions might avoid these pitfalls, provided that denoising procedures do not remove the signal corresponding to these NR from the fMRI data.…”
Section: Discussionmentioning
confidence: 99%
“…Our linear regression procedures are based on the equation boldY=b1X1+b2X2+b3X3++bnXn+normalc+boldε, where the best approximation for the values of vector Y (the dependent variable, representing the spatial map for a given time point or the vector time course for a given voxel) for a given set of vectors { X 1 , X 2 , … X n } (n independent variables, representing either spatial maps or time courses) is found by choosing the set of regression coefficients {b 1 , b 2 , … b n } that minimize the sum of squares of the residual values in vector ε . We say that the independent variables are being regressed onto the dependent variable, borrowing terminology from Huettel et al (), recognizing that no consensus for such terminology yet exists in the dual regression literature (Abram et al, ; Baggio et al, ; Chahine, Richter, Wolter, Goya‐Maldonado, & Gruber, ; Geissmann et al, ; Ishaque et al, ; Muetzel et al, ; Odish et al, ; Pannekoek et al, ; Smith et al, ). Our dependent and independent variables are always mean centered prior to regression (making the terms orthogonal and uncorrelated synonymous); and to ensure that mean values for independent variables predict the mean value for the dependent variable, c is set to zero.…”
Section: Theorymentioning
confidence: 99%
“…A exibição de stímulos visuais estáticos é um método amplamente empregado para induzir a emoção de alegria e medo em condições experimentais (Geissmann et al, 2018). Em boa parte dos estudos, os estímulos visuais capazes de induzir estas emoções são retirados da International Affective Picture Systema (IAPS - Lang et al, 2008) ou de bases de dado validadas contendo faces humanas expressando alegria (Ebner et al, 2010).…”
Section: Estímulos Visuais Estáticosunclassified