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控制感对损失注意捕获的双路径调节机制：基于选择和基于结果的控制差异
杨二莹, 贺佳, 胡艳梅, 吕文宇, 李梦笛
心理科学 ›› 2026, Vol. 49 ›› Issue (4) : 860-873.
PDF(2381 KB)
PDF(2381 KB)
控制感对损失注意捕获的双路径调节机制：基于选择和基于结果的控制差异
Dual-Pathway Modulation of Sense of Control on Loss-Driven Attentional Capture: Differences Between Choice-based and Outcome-based Control
控制感能否影响损失注意捕获尚存争议，且其调控机制亦有待探明。研究1和2结合行为实验、眼动追踪技术和分层漂移扩散模型系统考察该问题。实验任务分为两个阶段：首先在联结学习阶段通过转盘游戏建立颜色与损失的关联，随后在测验阶段采用额外单例范式考察损失关联干扰物的注意捕获效应。研究1通过改变按键反应和转盘停止的因果联系来操纵基于选择的控制。结果显示，高控制（vs.低控制）条件下搜索反应时更慢、瞳孔直径更大、首次注视潜伏期更短、注视持续时间更长、漂移率（v）更低、非决策时间（t）更长。研究2通过改变按键结果和预期损失的匹配程度来操纵基于结果的控制。结果显示，高控制（vs.低控制）条件下搜索正确率最低，对目标的注视持续时间最短。上述结果揭示了两种控制对损失注意捕获的差异性调节机制：基于选择的控制同时调节早期注意定向与晚期注意维持；而基于结果的控制主要影响晚期注意维持。
The influence of sense of control on loss-driven attentional capture remains a topic of debate, and the underlying regulatory mechanisms are still not fully understood. While some studies have shown that loss-related stimuli can automatically capture attention, others have failed to replicate these findings. Investigating whether and how loss-related information captures attention is essential for understanding the cognitive foundations of adaptive human behavior. Sense of control influences both attentional selection and the mitigation of loss threats. Therefore, it is likely a significant factor in modulating attentional capture related to losses.
This study utilized eye-tracking technology and applied the Hierarchical Drift Diffusion Model (HDDM) to computationally model behavioral data. The aim was to investigate the cognitive and computational mechanisms by which choice-based and outcome-based control influence loss-driven attentional capture. In Experiment 1, choice-based control was manipulated by altering the causal relationship between keypress responses and the stopping of a roulette wheel. During the associative learning phase, participants established associations between different colors and outcomes of high loss, low loss, or no loss through a roulette game. In the following test phase, the additional singleton paradigm was employed to assess the attentional capture effect of loss-associated distractors. The two key variables manipulated in Experiment 1 were the degree of control and the level of loss. In the high control condition, the roulette wheel stopped immediately on the loss score selected by the participant upon keypress. In the low-control condition, it continued spinning for a period before forcibly stopping at a computer-selected loss value. The available loss options were “-50 points,” “-5 points,” and “0 points,” corresponding to high-loss, low-loss, and no-loss outcomes, respectively. Behavioral results indicated slower search response times in the high-control condition compared to the low-control condition, suggesting a stronger attentional capture effect. Eye-tracking data showed larger pupil diameters, shorter first-fixation latencies, and longer fixation durations in the high-control condition, indicating heightened arousal levels, faster early attentional orienting, and enhanced late attentional maintenance. HDDM results revealed a lower drift rate (v) and longer non-decision time (t) in the high-control condition, reflecting a slower evidence accumulation speed during decision-making and extended stimulus encoding and response organization outside the decision process.
In Experiment 2, outcome-based control was manipulated by varying the alignment between keypress outcomes and expected losses, while ensuring a causal relation between the keypress responses and the stopping of the roulette wheel. The proportion of trials in which the outcome matched expectations was set at 100%, 75%, or 50% to correspond to high, medium, and low control, respectively. The total loss decreased as the degree of control increased. The results indicated that search accuracy was lowest and fixation durations on the target were shortest in the high-control condition compared to the low-control condition, suggesting a trade-off between processing precision and speed. HDDM results indicated that reaction times were primarily constrained by the non-decision time (t) parameter, which was not influenced by the degree of control.
These findings suggest that sense of control modulates loss-driven attentional capture through a dual-path mechanism: (1) Choice-based control enhances attentional capture by accelerating early attentional orienting and prolonging late attentional maintenance; and (2) Outcome-based control influences attentional selection by balancing processing speed and precision during late attentional maintenance. This framework sheds light on the dynamic processes through which sense of control regulates loss-driven attentional capture. Future research could further investigate its biological basis using cognitive neuroscience techniques, combined with computational neural modeling to examine predictive pathways from neural activity to behavioral responses. Additionally, studies could explore the interaction between choice-based and outcome-based control in influencing loss-driven attentional capture and compare their relative contributions to this modulation..
loss / control / attentional capture / eye-tracking / drift-diffusion model
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When stimuli are associated with reward outcome, their visual features acquire high attentional priority such that stimuli possessing those features involuntarily capture attention. Whether a particular feature is predictive of reward, however, will vary with a number of contextual factors. One such factor is spatial location: for example, red berries are likely to be found in low-lying bushes, whereas yellow bananas are likely to be found on treetops. In the present study, I explore whether the attentional priority afforded to reward-associated features is modulated by such location-based contingencies. The results demonstrate that when a stimulus feature is associated with a reward outcome in one spatial location but not another, attentional capture by that feature is selective to when it appears in the rewarded location. This finding provides insight into how reward learning effectively modulates attention in an environment with complex stimulus-reward contingencies, thereby supporting efficient foraging.
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Pupil diameter was monitored during picture viewing to assess effects of hedonic valence and emotional arousal on pupillary responses. Autonomic activity (heart rate and skin conductance) was concurrently measured to determine whether pupillary changes are mediated by parasympathetic or sympathetic activation. Following an initial light reflex, pupillary changes were larger when viewing emotionally arousing pictures, regardless of whether these were pleasant or unpleasant. Pupillary changes during picture viewing covaried with skin conductance change, supporting the interpretation that sympathetic nervous system activity modulates these changes in the context of affective picture viewing. Taken together, the data provide strong support for the hypothesis that the pupil's response during affective picture viewing reflects emotional arousal associated with increased sympathetic activity.
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Allocating attentional resources to currently relevant information in a dynamically changing environment is critical to goal-directed behavior. Previous studies in nonhuman primates (NHPs) have demonstrated modulation of neural representations of stimuli, in particular visual categorizations, by behavioral significance in the lateral prefrontal cortex. In the human brain, a network of frontal and parietal regions, the "multiple demand" (MD) system, is involved in cognitive and attentional control. To test for the effect of behavioral significance on categorical discrimination in the MD system in humans, we adapted a previously used task in the NHP and used multivoxel pattern analysis for fMRI data. In a cued-detection categorization task, participants detected whether an image from one of two target visual categories was present in a display. Our results revealed that categorical discrimination is modulated by behavioral relevance, as measured by the distributed pattern of response across the MD network. Distinctions between categories with different behavioral status (e.g., a target and a nontarget) were significantly discriminated. Category distinctions that were not behaviorally relevant (e.g., between two targets) were not discriminated. Other aspects of the task that were orthogonal to the behavioral decision did not modulate categorical discrimination. In a high visual region, the lateral occipital complex, modulation by behavioral relevance was evident in its posterior subregion but not in the anterior subregion. The results are consistent with the view of the MD system as involved in top-down attentional and cognitive control by selective coding of task-relevant discriminations. Significance statement: Control of cognitive demands fundamentally involves flexible allocation of attentional resources depending on a current behavioral context. Essential to such a mechanism is the ability to select currently relevant information and at the same time filter out information that is irrelevant. In an fMRI study, we measured distributed patterns of activity for objects from different visual categories while manipulating the behavioral relevance of the categorical distinctions. In a network of frontal and parietal cortical regions, the multiple-demand (MD) network, patterns reflected category distinctions that were relevant to behavior. Patterns could not be used to make task-irrelevant category distinctions. These findings demonstrate the ability of the MD network to implement complex goal-directed behavior by focused attention.Copyright © 2015 the authors 0270-6474/15/3512383-11$15.00/0.
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G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
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To what extent do we learn from the positive versus negative outcomes of our decisions? The neuromodulator dopamine plays a key role in these reinforcement learning processes. Patients with Parkinson's disease, who have depleted dopamine in the basal ganglia, are impaired in tasks that require learning from trial and error. Here, we show, using two cognitive procedural learning tasks, that Parkinson's patients off medication are better at learning to avoid choices that lead to negative outcomes than they are at learning from positive outcomes. Dopamine medication reverses this bias, making patients more sensitive to positive than negative outcomes. This pattern was predicted by our biologically based computational model of basal ganglia-dopamine interactions in cognition, which has separate pathways for "Go" and "NoGo" responses that are differentially modulated by positive and negative reinforcement.
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We report 3 experiments examining the effects of positive versus negative valence and perceptual load in determining attention capture by irrelevant emotional distractors. Participants performed a letter search task searching for 1 of 2 target letters (X or N) in conditions of either low perceptual load (circular nontarget letters) or high perceptual load (angular nontarget letters that are similar to the target letters). On 25% of the trials an irrelevant emotional distractor was presented at the display center and participants were instructed to ignore it. The distractor stimulus was either positive or negative and was selected from 3 different classes: IAPS pictures of erotica or mutilated bodies (Experiment 1), happy or angry faces (Experiment 2), and faces associated with gain or loss in a prior value-learning phase involving a betting game (Experiment 3). The results showed a consistent pattern of interaction of load and valence across the 3 experiments. Irrelevant emotional distractors produced interference effects on search reaction time (RT) in conditions of low load, with no difference between negative and positive valence. High perceptual load, however, consistently reduced interference from the negative-valence distractors, but had no effect on the positive-valence distractors. As these results were consistently found across 3 different categories of emotional distractors, they suggest the general conclusion that attentional capture by irrelevant emotional distractors depends on both their valence and the level of perceptual load in the task and highlight the special status of distractors associated with pleasure.(c) 2016 APA, all rights reserved).
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Changes in pupil diameter that reflect effort and other cognitive factors are often interpreted in terms of the activity of norepinephrine-containing neurons in the brainstem nucleus locus coeruleus (LC), but there is little direct evidence for such a relationship. Here, we show that LC activation reliably anticipates changes in pupil diameter that either fluctuate naturally or are driven by external events during near fixation, as in many psychophysical tasks. This relationship occurs on as fine a temporal and spatial scale as single spikes from single units. However, this relationship is not specific to the LC. Similar relationships, albeit with delayed timing and different reliabilities across sites, are evident in the inferior and superior colliculus and anterior and posterior cingulate cortex. Because these regions are interconnected with the LC, the results suggest that non-luminance-mediated changes in pupil diameter might reflect LC-mediated coordination of neuronal activity throughout some parts of the brain. Copyright © 2016 Elsevier Inc. All rights reserved.
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A typical scene contains many different objects that, because of the limited processing capacity of the visual system, compete for neural representation. The competition among multiple objects in visual cortex can be biased by both bottom-up sensory-driven mechanisms and top-down influences, such as selective attention. Functional brain imaging studies reveal that, both in the absence and in the presence of visual stimulation, biasing signals due to selective attention can modulate neural activity in visual cortex in several ways. Although the competition among stimuli for representation is ultimately resolved within visual cortex, the source of top-down biasing signals derives from a network of areas in frontal and parietal cortex.
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Most organisms facing a choice between multiple stimuli will look repeatedly at them, presumably implementing a comparison process between the items' values. Little is known about the nature of the comparison process in value-based decision-making or about the role of visual fixations in this process. We created a computational model of value-based binary choice in which fixations guide the comparison process and tested it on humans using eye-tracking. We found that the model can quantitatively explain complex relationships between fixation patterns and choices, as well as several fixation-driven decision biases.
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Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries an opportunity cost--that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternative explanations for both the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across sub-disciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternative models might be empirically distinguished.
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This article presents a comprehensive survey of research concerning interactions between associative learning and attention in humans. Four main findings are described. First, attention is biased toward stimuli that predict their consequences reliably (). This finding is consistent with the approach taken by Mackintosh (1975) in his attentional model of associative learning in nonhuman animals. Second, the strength of this attentional bias is modulated by the value of the outcome (). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that may result in increased attention to stimuli (Pearce & Hall, 1980), receives less support. This suggests that hybrid models of associative learning, incorporating the mechanisms of both the Mackintosh and Pearce-Hall theories, may not be required to explain data from human participants. Rather, a simpler model, in which attention to stimuli is determined by how strongly they are associated with significant outcomes, goes a long way to account for the data on human attentional learning. The last main finding, and an exciting area for future research and theorizing, is that and modulate both deliberate attentional focus, and more automatic attentional capture. The automatic influence of learning on attention does not appear to fit the traditional view of attention as being either or. Rather, it suggests a new kind of “derived” attention.PsycINFO Database Record (c) 2016 APA, all rights reserved
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Using functional MRI, we examined how the affective experience of choice, the means by which individuals exercise control, is modulated by the valence of potential outcomes (gains, losses). When trials involved potential gains, participants reported liking cues predicting a choice opportunity better than cues predicting no choice opportunity--an effect that corresponded with blood-oxygen-level-dependent (BOLD) increases in ventral striatum (VS) activity. Surprisingly, no differences were observed between choice and no-choice cues when participants anticipated potential losses. Individual differences in subjective choice preference in the loss condition, however, corresponded to choice-related BOLD activity in VS. We conducted a second experiment to examine whether monetary losses were perceived differently in the context of simultaneous gains. When losses occurred in the absence of gains, participants showed an increased affective experience of choice--they reported greater liking of choice than no-choice trials, and VS activity was greater for choice than for no-choice cues. Collectively, the findings suggest that the affective experience of choice involves reward-processing circuitry when people anticipate appetitive and aversive outcomes, but the choice experience may be sensitive to context and individual differences.
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It is nearly 10 years since Patrick Haggard and colleagues first reported the 'intentional binding' effect (Haggard, Clark, & Kalogeras, 2002). The intentional binding effect refers to the subjective compression of the temporal interval between a voluntary action and its external sensory consequence. Since the first report, considerable interest has been generated and a fascinating array of studies has accumulated. Much of the interest in intentional binding comes from the promise to shed light on human agency. In this review we survey studies on intentional binding, focusing, in particular, on the link between intentional binding and the sense of agency (the experience of controlling action to influence events in the environment). We suggest that, whilst it is yet to be fully explicated, the link between intentional binding and the sense of agency is compelling. We conclude by considering outstanding questions and future directions for research on intentional binding.Copyright © 2011 Elsevier Inc. All rights reserved.
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A subcortical pathway through the superior colliculus and pulvinar to the amygdala is commonly assumed to mediate the non-conscious processing of affective visual stimuli. We review anatomical and physiological data that argue against the notion that such a pathway plays a prominent part in processing affective visual stimuli in humans. Instead, we propose that the primary role of the amygdala in visual processing, like that of the pulvinar, is to coordinate the function of cortical networks during evaluation of the biological significance of affective visual stimuli. Under this revised framework, the cortex has a more important role in emotion processing than is traditionally assumed.
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In real-life situations, we are often required to recognize our own movements among movements originating from other people. In social situations, these movements are often correlated (for example, when dancing or walking with others) adding considerable difficulty to self-recognition. Studies from visual search have shown that visual attention can selectively highlight specific features to make them more salient. Here, we used a novel visual search task employing virtual reality and motion tracking to test whether visual attention can use efferent information to enhance self-recognition of one's movements among four or six moving avatars. Active movements compared to passive movements allowed faster recognition of the avatar moving like the subject. Critically, search slopes were flat for the active condition but increased for passive movements, suggesting efficient search for active movements. In a second experiment, we tested the effects of using the participants' own movements temporally delayed as distractors in a self-recognition discrimination task. We replicated the results of the first experiment with more rapid self-recognition during active trials. Importantly, temporally delayed distractors increased reaction times despite being more perceptually different than the spatial distractors. The findings demonstrate the importance of agency in self-recognition and self-other discrimination from movement in social settings.
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Environmental stimuli and objects, including rewards, are often processed sequentially in the brain. Recent work suggests that the phasic dopamine reward prediction-error response follows a similar sequential pattern. An initial brief, unselective and highly sensitive increase in activity unspecifically detects a wide range of environmental stimuli, then quickly evolves into the main response component, which reflects subjective reward value and utility. This temporal evolution allows the dopamine reward prediction-error signal to optimally combine speed and accuracy.
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The dorsal anterior cingulate cortex (dACC) has a near-ubiquitous presence in the neuroscience of cognitive control. It has been implicated in a diversity of functions, from reward processing and performance monitoring to the execution of control and action selection. Here, we propose that this diversity can be understood in terms of a single underlying function: allocation of control based on an evaluation of the expected value of control (EVC). We present a normative model of EVC that integrates three critical factors: the expected payoff from a controlled process, the amount of control that must be invested to achieve that payoff, and the cost in terms of cognitive effort. We propose that dACC integrates this information, using it to determine whether, where and how much control to allocate. We then consider how the EVC model can explain the diverse array of findings concerning dACC function. Copyright © 2013 Elsevier Inc. All rights reserved.
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It is well known that salient yet task irrelevant stimuli may capture our eyes independent of our goals and intentions. The present study shows that a task-irrelevant stimulus that is previously associated with high monetary reward captures the eyes much stronger than that very same stimulus when previously associated with low monetary reward. We conclude that reward changes the salience of a stimulus such that a stimulus that is associated with high reward becomes more pertinent and therefore captures the eyes above and beyond its physical salience. Because the stimulus capture the eyes and disrupts goal-directed behavior we argue that this effect is automatic not driven by strategic, top-down control.Copyright © 2012 Elsevier Ltd. All rights reserved.
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The feeling of control is a fundamental aspect of human experience and accompanies our voluntary actions all the time. However, how the sense of control interacts with wider perception, cognition, and behavior remains poorly understood. This study focused on how controlling an external object influences the allocation of attention. Experiment 1 examined attention to an object that is under a different level of control from the others. Participants searched for a target among multiple distractors on screen. All the distractors were partially under the participant's control (50% control level), and the search target was either under more or less control than the distractors. The results showed that, against this background of partial control, visual attention was attracted to an object only if it was more controlled than other available objects and not if it was less controlled. Experiment 2 examined attention allocation in contexts of either perfect control or no control over most of the objects. Specifically, the distractors were under either perfect (100%) control or no (0%) control, and the search target had one of six levels of control varying from 0% to 100%. When differences in control between the distractors and the target were small, visual attention was now more strongly drawn to search targets that were less controlled than distractors, rather than more controlled, suggesting attention to objects over which one might be losing control. Experiment 3 studied the events of losing or gaining control as opposed to the states of having or not having control. ERP measures showed that P300 amplitude proportionally encoded the magnitude of both increases and decreases in degree of control. However, losing control had more marked effects on P170 and P300 than gaining an equivalent degree of control, indicating high priority for efficiently detecting failures of control. Overall, our results suggest that controlled objects preferentially attract attention in uncontrolled environments. However, once control has been registered, the brain becomes highly sensitive to subsequent loss of control. Our findings point toward careful perceptual monitoring of degree of one's own agentic control over external objects. We suggest that control has intrinsic cognitive value because perceptual systems are organized to detect it and, once it has been acquired, to maintain it.
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