2020
DOI: 10.1093/texcom/tgaa025
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Neural Responses to Reward in a Gambling Task: Sex Differences and Individual Variation in Reward-Driven Impulsivity

Abstract: Previous work suggests sex differences in reward sensitivity. However, it remains unclear how men and women differ in the neural processes of reward-driven impulsivity. With a data set of 968 subjects (502 women) curated from the Human Connectome Project, we investigated sex differences in regional activations to reward and to punishment in a gambling task. Individual variations in reward-driven impulsivity were quantified by the difference in reaction time (RT) between reward and punishment blocks in the gamb… Show more

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Cited by 22 publications
(8 citation statements)
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“…Further, women appear to be more loss aversive than men [ 70 ], and it remains to be seen to what extent loss aversion can be captured by punishment sensitivity and how sex differences in loss aversion may account for the current findings. More studies with multiple behavioral paradigms [ 71 ] are warranted to investigate these issues.…”
Section: Discussionmentioning
confidence: 99%
“…Further, women appear to be more loss aversive than men [ 70 ], and it remains to be seen to what extent loss aversion can be captured by punishment sensitivity and how sex differences in loss aversion may account for the current findings. More studies with multiple behavioral paradigms [ 71 ] are warranted to investigate these issues.…”
Section: Discussionmentioning
confidence: 99%
“…As with our recent study of the HCP data ( Li et al, 2020 ), imaging data were analyzed with Statistical Parametric Mapping (SPM8, Welcome Department of Imaging Neuroscience, University College London, U.K.). Standard image preprocessing was performed.…”
Section: Methodsmentioning
confidence: 99%
“…We followed the same published routines in our earlier studies 28 , 29 . Imaging data were preprocessed using SPM8.…”
Section: Methodsmentioning
confidence: 99%
“…We modeled the BOLD signals to identify 2-back and 0-back responses. We followed our previous routine in image data modeling 28 , 29 . A statistical analytical block design was constructed for each individual subject, using a general linear model (GLM) by convolving the canonical hemodynamic response function (HRF) with a boxcar function in SPM.…”
Section: Methodsmentioning
confidence: 99%