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Salient stimuli can capture attention in a bottom-up manner; however, this attentional capture can be suppressed in a top-down manner. It has been shown that individuals with high working memory capacity (WMC) can suppress salient‑but-irrelevant distractors better than those with low WMC; however, neural substrates underlying this difference remain unclear. To examine this, participants with high or low WMC (high-/low-WMC, n = 44/44) performed a visual search task wherein a color singleton item served as a salient distractor, and underwent structural and resting-state functional magnetic resonance imaging scans. Behaviorally, the color singleton distractor generally reduced the reaction time (RT). This RT benefit (ΔRT) was higher in the high-WMC group relative to the low-WMC group, indicating the superior distractor suppression ability of the high-WMC group. Moreover, leveraging voxel-based morphometry analysis, gray matter morphology (volume and deformation) in the ventral attention network (VAN) was found to show the same, positive associations with ΔRT in both WMC groups. However, correlations of the opposite sign were found between ΔRT and gray matter morphology in the frontoparietal (FPN)/default mode network (DMN) in the two WMC groups. Furthermore, resting-state functional connectivity analysis centering on regions with a structural-behavioral relationship found that connections between the left orbital and right superior frontal gyrus (hubs of DMN and VAN, respectively) was correlated with ΔRT in the high-WMC group (but not in the low-WMC group). Collectively, our work present shared and distinct neuroanatomical substrates of distractor suppression in high- and low-WMC individuals. Furthermore, intrinsic connectivity of the brain network hubs in high-WMC individuals may account for their superior ability in suppressing salient distractors. [ABSTRACT FROM AUTHOR]

Selective attention, the ability to filter relevant from a sea of sensory information, relies on the prioritization of goal-relevant information (target facilitation) and the suppression of goal-irrelevant information (distractor suppression). Although several lines of evidence have shown that target facilitation and distractor suppression were mediated by distinct mechanisms, the underlying neural substrates remain unclear. To address this question, we acquired structural and resting-state magnetic resonance imaging scans, as well as behavioral data from a modified Posner cueing task. Specifically, the location of a target (Target Cue, TC) and a distractor (Distractor Cue, DC) was either cued in advance to separately trigger target facilitation and distractor suppression, or no predictive information was provided, serving as a baseline. We combined voxel-based morphometry (VBM) and resting-state functional connectivity (rsFC) analyses to explore the neural correlates of behavioral benefits, yielding the following results. First, behavioral data showed faster responses to TC and DC conditions compared to baseline, the benefits of which were named TC-benefit and DC-benefit. Second, the VBM analysis revealed that the gray matter volume (GMV) in the superior frontal (SFG) and postcentral gyrus inversely correlated with individual TC-benefit, while the GMV in the superior parietal lobe, middle frontal gyrus, and angular gyrus inversely correlated with individual DC-benefit, indicating that target facilitation and distractor suppression was associated with the GMV of distinct and distributed regions in the frontoparietal cortex. Third, the rsFC analysis with the SFG as a seed region further found distinct patterns of rsFC for target facilitation and distractor suppression. Specifically, individual TC-benefit were positively correlated with distributed connections between the SFG and brain regions, mainly within the ventral attention and somato-motor network; but individual DC-benefit were positively correlated with centralized connections between the SFG and brain regions, mainly within the frontoparietal, dorsal attention and ventral attention network. Finally, a multiple linear regression analysis showed that the GMV and rsFC could jointly explain individual differences in TC- and DC-benefit. Taken together, these results provided neural evidence for different structural and functional substrates underlying target facilitation and distractor suppression. ∙ Location cue of a distractor or target quickened search responses (DC/TC-benefit). ∙Neural substrates of DC/TC-benefit were explored using VBM and rsFC analyses. ∙Both GMV and rsFC analysis revealed distinct neural correlates of DC/TC-benefit. ∙GMV and rsFC together explained over 80% of individual variations in DC/TC-benefit. [ABSTRACT FROM AUTHOR]

• Distractor suppression (DS) was measured using visual search task. • Using functional connectivity between large anatomical regions to predict DS. • Prefrontal-temporal, insula-limbic, parietal-occipital connections were key to DS. • The model could also predict daily distractibility in an independent sample. Distractor suppression (DS) is crucial in goal-oriented behaviors, referring to the ability to suppress irrelevant information. Current evidence points to the prefrontal cortex as an origin region of DS, while subcortical, occipital, and temporal regions are also implicated. The present study aimed to examine the contribution of communications between these brain regions to visual DS. To do it, we recruited two independent cohorts of participants for the study. One cohort participated in a visual search experiment where a salient distractor triggering distractor suppression to measure their DS and the other cohort filled out a Cognitive Failure Questionnaire to assess distractibility in daily life. Both cohorts collected resting-state functional magnetic resonance imaging (rs-fMRI) data to investigate function connectivity (FC) underlying DS. First, we generated predictive models of the DS measured in visual search task using resting-state functional connectivity between large anatomical regions. It turned out that the models could successfully predict individual's DS, indicated by a significant correlation between the actual and predicted DS (r = 0.32, p < 0.01). Importantly, Prefrontal-Temporal, Insula-Limbic and Parietal-Occipital connections contributed to the prediction model. Furthermore, the model could also predict individual's daily distractibility in the other independent cohort (r = –0.34, p < 0.05). Our findings showed the efficiency of the predictive models of distractor suppression encompassing connections between large anatomical regions and highlighted the importance of the communications between attention-related and visual information processing regions in distractor suppression. Current findings may potentially provide neurobiological markers of visual distractor suppression. [ABSTRACT FROM AUTHOR]