2021
DOI: 10.1016/j.neuroimage.2021.117725
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The neural substrates of subliminal attentional bias and reduced inhibition in individuals with a higher BMI: A VBM and resting state connectivity study

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Cited by 9 publications
(6 citation statements)
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“…Neuroimaging studies exploring the relationship between food cue-reactivity and obesity in adults have consistently found reward regions (e.g., OFC) and VN ( 42 44 ). Individuals with higher BMI had altered resting-state FC in OFC and visual areas ( 45 ), which was correlated with food bias ( 46 ). It should be noted that the variability of FC for a given region measures the temporal variability of FC between this given region and the rest of the regions of the brain across time windows.…”
Section: Discussionmentioning
confidence: 99%
“…Neuroimaging studies exploring the relationship between food cue-reactivity and obesity in adults have consistently found reward regions (e.g., OFC) and VN ( 42 44 ). Individuals with higher BMI had altered resting-state FC in OFC and visual areas ( 45 ), which was correlated with food bias ( 46 ). It should be noted that the variability of FC for a given region measures the temporal variability of FC between this given region and the rest of the regions of the brain across time windows.…”
Section: Discussionmentioning
confidence: 99%
“…Osimo et al reported that the gray matter density of several frontal regions was positively related to the 2D GNG performance. This statistical correlation suggested that frontal morphology could directly influence attentional behaviors, with a great possibility to improve attention by neural modulation [ 76 ]. Silva et al discovered that anodal electrical stimulation on the frontal lobe could effectively modulate the attentional orientation and execution, which was demonstrated in the behavioral scores in professional 2D tasks [ 77 ].…”
Section: Discussionmentioning
confidence: 99%
“…Self-disgust, physical self-disgust, and behavioral self-disgust were treated as variables of interest, respectively. Age, sex, and total brain volume (TBV) were entered as covariates of no interest in three general linear models-factors are commonly controlled in VBM analyses (Kong et al, 2020;Osimo et al, 2021;Vartanian et al, 2020). TBV data were calculated using the REX Toolbox (http://web.mit.edu/swg/software.htm).…”
Section: Image Data Analysismentioning
confidence: 99%