认知控制与显著性加工在类别注意选择中的分工与协同机制OACHSSCD

Category-based attentional selection(CAS)enables the visual system to prioritize objects that share an abstract,semantic label.For example,"tools,""letters,"or"animals."Yet how cognitive load and salience processing jointly sculpt this high-level form of attention remains unclear.Here we combined a Majority Function Task(MFT)with a visual Oddball manipulation in a fully crossed 2(load:low 3:0 vs.high 2:1 ratio)×2(salience level:standard 80%vs.Oddball 20%)×2(salience relevance:task-relevant vs.task-irrelevant)design.Twenty-nine right-handed adults(24 women;18−27 yrs)performed 768 trials while BOLD signals were recorded in a 3 T scanner;eye position was concurrently monitored to rule out overt shifts. Inverse-efficiency scores(IES=RT/accuracy)confirmed the expected main effect of load,but also revealed a three-way interaction:under high load,task-relevant Oddballs produced the largest cost(Cohen’s d=0.81),whereas task-irrelevant Oddballs caused a moderate,load-dependent slowdown.This pattern supports a resource-competition account in which maintaining a category template and suppressing conspicuous distractors draw on a common,finite pool. Whole-brain GLM revealed a functional division of effects.Cognitive load(high>low)boosted activity throughout the dorsal control network,including bilateral superior parietal lobule(SPL),dorsal lateral prefrontal cortex(DLPFC)and insula,whereas salience level(Oddball>standard)preferentially recruited ventral salience nodes,including right angular gyrus,bilateral anterior insula and caudate nucleus.By contrast,salience relevance(task-relevant vs.task-irrelevant)produced no reliable univariate clusters,mirroring the absence of a pure relevance main effect in local BOLD amplitude.To test whether relevance information was nonetheless encoded in spatial patterns,we performed multivariate pattern analysis(MVPA).A linear support-vector machine trained on voxels that were jointly responsive to load and salience distinguished the eight experimental conditions with 86.83%accuracy(t=73.57,p<.001).Weight-map inspection showed that the right superior occipital/parieto-occipital junction and right pre-central gyrus contributed most strongly but not exclusively,suggesting rPOJ and FEF serve as a convergence hub together with premotor nodes.Thus,although relevance does not manifest as a simple amplitude shift,it is robustly represented in distributed activation patterns and in the connectivity of a posterior occipito-parietal hub,highlighting a pattern-based,network-level code that reconciles the dorsal−ventral division of labor with successful category-based attentional selection. These converging results indicate that CAS operates through a layered priority architecture:dorsal control regions inject goal-related gain,ventral salience regions register statistical deviance,and rPOJ/FEF synergistically re-weights both streams to rebalance priority values when resources are scarce.Taken together,our findings extend priority-map theory into the semantic domain and demonstrate that cognitive load is a key moderator of how salience relevance shapes the competition between dorsal and ventral attention systems. By isolating where(dorsal vs.ventral)and how(pattern vs.amplitude)cognitive load and salience relevance interact,the study refines dual-route models of attention and identifies rPOJ and FEF as pivotal hubs for balancing task demands against environmental conspicuity,that is,a mechanism likely critical for real-world scenarios that call for rapid category-based decisions under pressure.