Relative saliency affects attentional capture and suppression of color and face singleton distractors: evidence from event-related potential studies.

Prior research has yet to fully elucidate the impact of varying relative saliency between target and distractor on attentional capture and suppression, along with their underlying neural mechanisms, especially when social (e.g. face) and perceptual (e.g. color) information interchangeably serve as singleton targets or distractors, competing for attention in a search array. Here, we employed an additional singleton paradigm to investigate the effects of relative saliency on attentional capture (as assessed by N2pc) and suppression (as assessed by PD) of color or face singleton distractors in a visual search task by recording event-related potentials. We found that face singleton distractors with higher relative saliency induced stronger attentional processing. Furthermore, enhancing the physical salience of colors using a bold color ring could enhance attentional processing toward color singleton distractors. Reducing the physical salience of facial stimuli by blurring weakened attentional processing toward face singleton distractors; however, blurring enhanced attentional processing toward color singleton distractors because of the change in relative saliency. In conclusion, the attentional processes of singleton distractors are affected by their relative saliency to singleton targets, with higher relative saliency of singleton distractors resulting in stronger attentional capture and suppression; faces, however, exhibit some specificity in attentional capture and suppression due to high social saliency.

Modality-specific effects of threat on self-motion perception.

BACKGROUND: Threat and individual differences in threat-processing bias perception of stimuli in the environment. Yet, their effect on perception of one's own (body-based) self-motion in space is unknown. Here, we tested the effects of threat on self-motion perception using a multisensory motion simulator with concurrent threatening or neutral auditory stimuli. RESULTS: Strikingly, threat had opposite effects on vestibular and visual self-motion perception, leading to overestimation of vestibular, but underestimation of visual self-motions. Trait anxiety tended to be associated with an enhanced effect of threat on estimates of self-motion for both modalities. CONCLUSIONS: Enhanced vestibular perception under threat might stem from shared neural substrates with emotional processing, whereas diminished visual self-motion perception may indicate that a threatening stimulus diverts attention away from optic flow integration. Thus, threat induces modality-specific biases in everyday experiences of self-motion.

Reward-modulated attention deployment is driven by suppression, not attentional capture.

One driving factor for attention deployment towards a stimulus is its associated value due to previous experience and learning history. Previous visual search studies found that when looking for a target, distractors associated with higher reward produce more interference (e.g., longer response times). The present study investigated the neural mechanism of such value-driven attention deployment. Specifically, we were interested in which of the three attention sub-processes are responsible for the interference that was repeatedly observed behaviorally: enhancement of relevant information, attentional capture by irrelevant information, or suppression of irrelevant information. We replicated earlier findings showing longer response times and lower accuracy when a target competed with a high-reward compared to a low-reward distractor. We also found a spatial gradient of interference: behavioral performance dropped with increasing proximity to the target. This gradient was steeper for high- than low-reward distractors. Event-related potentials of the EEG signal showed the reason for the reward-induced attentional bias: High-reward distractors required more suppression than low-reward distractors as evident in larger Pd components. This effect was only found for distractors near targets, showing the additional filtering needs required for competing stimuli in close proximity. As a result, fewer attentional resources can be distributed to the target when it competes with a high-reward distractor, as evident in a smaller target-N2pc amplitude. The distractor-N2pc, indicative of attentional capture, was neither affected by distance nor reward, showing that attentional capture alone cannot explain interference by stimuli of high value. In sum our results show that the higher need for suppression of high-value stimuli contributes to reward-modulated attention deployment and increased suppression can prevent attentional capture of high-value stimuli.

On the reliability of value-modulated attentional capture: An online replication and multiverse analysis.

Stimuli predicting rewards are more likely to capture attention, even when they are not relevant to our current goals. Individual differences in value-modulated attentional capture (VMAC) have been associated with various psychopathological conditions in the scientific literature. However, the claim that this attentional bias can predict individual differences requires further exploration of the psychometric properties of the most common experimental paradigms. The current study replicated the VMAC effect in a large online sample (N = 182) and investigated the internal consistency, with a design that allowed us to measure the effect during learning (rewarded phase) and after acquisition, once feedback was omitted (unrewarded phase). Through the rewarded phase there was gradual increase of the VMAC effect, which did not decline significantly throughout the unrewarded phase. Furthermore, we conducted a reliability multiverse analysis for 288 different data preprocessing specifications across both phases. Specifications including more blocks in the analysis led to better reliability estimates in both phases, while specifications that removed more outliers also improved reliability, suggesting that specifications with more, but less noisy, trials led to better reliability estimates. Nevertheless, in most instances, especially those considering fewer blocks of trials, reliability estimates fell below the minimum recommended thresholds for research on individual differences. Given the present results, we encourage researchers working on VMAC to take into account reliability when designing studies aimed at capturing individual differences and provide recommendations to improve methodological practices.

Reliability of individual differences in distractor suppression driven by statistical learning.

A series of recent studies has demonstrated that attentional selection is modulated by statistical regularities, even when they concern task-irrelevant stimuli. Irrelevant distractors presented more frequently at one location interfere less with search than distractors presented elsewhere. To account for this finding, it has been proposed that through statistical learning, the frequent distractor location becomes suppressed relative to the other locations. Learned distractor suppression has mainly been studied at the group level, where individual differences are treated as unexplained error variance. Yet these individual differences may provide important mechanistic insights and could be predictive of cognitive and real-life outcomes. In the current study, we ask whether in an additional singleton task, the standard measures of attentional capture and learned suppression are reliable and stable at the level of the individual. In an online study, we assessed both the within- and between-session reliability of individual-level measures of attentional capture and learned suppression. We show that the measures of attentional capture, but not of distractor suppression, are moderately stable within the same session (i.e., split-half reliability). Test-retest reliability over a 2-month period was found to be moderate for attentional capture but weak or absent for suppression. RT-based measures proved to be superior to accuracy measures. While producing very robust findings at the group level, the predictive validity of these RT-based measures is still limited when it comes to individual-level performance. We discuss the implications for future research drawing on inter-individual variation in the attentional biases that result from statistical learning.

Attention to Stimuli of Learned versus Innate Biological Value Relies on Separate Neural Systems.

The neural bases of attention, a set of neural processes that promote behavioral selection, is a subject of intense investigation. In humans, rewarded cues influence attention, even when those cues are irrelevant to the current task. Because the amygdala plays a role in reward processing, and the activity of amygdala neurons has been linked to spatial attention, we reasoned that the amygdala may be essential for attending to rewarded images. To test this possibility, we used an attentional capture task, which provides a quantitative measure of attentional bias. Specifically, we compared reaction times (RTs) of adult male rhesus monkeys with bilateral amygdala lesions and unoperated controls as they made a saccade away from a high- or low-value rewarded image to a peripheral target. We predicted that: (1) RTs will be longer for high- compared with low-value images, revealing attentional capture by rewarded stimuli; and (2) relative to controls, monkeys with amygdala lesions would exhibit shorter RT for high-value images. For comparison, we assessed the same groups of monkeys for attentional capture by images of predators and conspecifics, categories thought to have innate biological value. In performing the attentional capture task, all monkeys were slowed more by high-value relative to low-value rewarded images. Contrary to our prediction, amygdala lesions failed to disrupt this effect. When presented with images of predators and conspecifics, however, monkeys with amygdala lesions showed significantly diminished attentional capture relative to controls. Thus, separate neural pathways are responsible for allocating attention to stimuli with learned versus innate value.SIGNIFICANCE STATEMENT Valuable objects attract attention. The amygdala is known to contribute to reward processing and the encoding of object reward value. We therefore examined whether the amygdala is necessary for allocating attention to rewarded objects. For comparison, we assessed the amygdala's contribution to attending to objects with innate biological value: predators and conspecifics. We found that the macaque amygdala is necessary for directing attention to images with innate biological value, but not for directing attention to recently learned reward-predictive images. These findings indicate that the amygdala makes selective contributions to attending to valuable objects. The data are relevant to mental health disorders, such as social anxiety disorders and small animal phobias, that arise from biased attention to select categories of objects.

Electrophysiological correlates of attentional capture in joint action.

In joint action, agents are assumed to represent their partner's task to optimize joint performance. However, the neurophysiological processes underlying the processing of the partner's task have not been widely investigated. Pairs of participants were asked to perform a joint version of a visual search task in either a cooperative or a competitive social context. During the task, one agent's neural activity was recorded using electroencephalography (EEG). The alpha-lateralization index was calculated as [(contralateral - ipsilateral)/(contralateral + ipsilateral)] × 100 to examine attentional selection or suppression of the laterally presented stimulus. A negative alpha-lateralization indicates lower alpha-band power over the contralateral sites compared with the ipsilateral sites and was related to attentional selection. A positive alpha-lateralization indicates higher alpha-band power over the contralateral sites compared with the ipsilateral sites and was related to attentional suppression. Behavioural results showed impeded search performance when the partner target was present. Furthermore, EEG time-frequency results showed that the partner target induced a negative parieto-occipital alpha-lateralization, indicating that it captured attention, when the agent target was absent. When the agent target was present, the parieto-occipital alpha-lateralization index was negative for laterally presented partner target in the cooperative and positive in the competitive social context, indicative of attentional capture in the cooperative condition and suppression of the partner target in the competitive condition. In sum, our study showed that humans tune their attentional processing towards a partner target in a joint action task. This attentional tuning was shown to be affected by social context and the presence of the agent's own target.

Visual Distraction's "Silver Lining": Distractor Suppression Boosts Attention to Competing Stimuli.

Efficient search of the environment requires that people attend to the desired elements in a scene and ignore the undesired ones. Recent research has shown that this endeavor can benefit from the ability to proactively suppress distractors with known features, but little is known about the mechanisms that produce the suppression. We show here in five experiments (N = 120 college students) that, surprisingly, identification of a sought-for target is enhanced when it is grouped with a suppressed distractor compared with when it is in a different perceptual group. The results show that the suppressive mechanism not only downweights undesired elements but also enhances responses to task-relevant elements in competition for attention with the distractor, fine tuning the suppression. The findings extend the understanding of how people efficiently process their visual world.

Reward functioning from an attentional perspective and obsessive-compulsive symptoms-an eye-tracking study.

BACKGROUND: Recently, a novel approach to obsessive-compulsive disorder has emerged, implicating altered reward functioning in the disorder. Yet, no study to date has directly examined the attentional aspect of reward functioning in participants with obsessive-compulsive (OC) symptoms, with past research mostly relying on reaction-time-based tasks. METHODS: A reward-based value-modulated attentional capture task was completed by a sample of nonclinical student participants-44 with high (HOC) and 48 with low (LOC) levels of OC symptoms. We measured the extent to which high and low reward-signaling distractors captured attention and impaired performance on the task, resulting in a lower possibility of obtaining a monetary reward. Attentional capture was indexed via fixation data, and further explored using saccade data. RESULTS: Both groups performed more poorly when a high-reward signaling distractor was present, compared to when a low-reward signaling distractor was present. Importantly, this difference was significantly greater in the HOC group, and was found to be driven by the specific effects of reward-signaling distractors. Similar results emerged when exploring saccade data, and remained significant after controlling for both addiction-related compulsivity and depressive symptoms. CONCLUSIONS: Current findings suggest that attentional reward-related functioning may be associated with OC symptoms. Different aspects of reward functioning, including attention, should be further explored and incorporated into future research and clinical endeavors.

Common and Unique Inhibitory Control Signatures of Action-Stopping and Attentional Capture Suggest That Actions Are Stopped in Two Stages.

The ability to stop an already initiated action is paramount to adaptive behavior. Much scientific debate in the field of human action-stopping currently focuses on two interrelated questions. (1) Which cognitive and neural processes uniquely underpin the implementation of inhibitory control when actions are stopped after explicit stop signals, and which processes are instead commonly evoked by all salient signals, even those that do not require stopping? (2) Why do purported (neuro)physiological signatures of inhibition occur at two different latencies after stop signals? Here, we address both questions via two preregistered experiments that combined measurements of corticospinal excitability, EMG, and whole-scalp EEG. Adult human subjects performed a stop signal task that also contained "ignore" signals: equally salient signals that did not require stopping but rather completion of the Go response. We found that both stop- and ignore signals produced equal amounts of early-latency inhibition of corticospinal excitability and EMG, which took place ∼150 ms following either signal. Multivariate pattern analysis of the whole-scalp EEG data further corroborated that this early processing stage was shared between stop- and ignore signals, as neural activity following the two signals could not be decoded from each other until a later time period. In this later period, unique activity related to stop signals emerged at frontocentral scalp sites, reflecting an increased stop signal P3. These findings suggest a two-step model of action-stopping, according to which an initial, universal inhibitory response to the saliency of the stop signal is followed by a slower process that is unique to outright stopping.SIGNIFICANCE STATEMENT Humans often have to stop their ongoing actions when indicated by environmental stimuli (stop signals). Successful action-stopping requires both the ability to detect these salient stop signals and to subsequently inhibit ongoing motor programs. Because of this tight entanglement of attentional control and motor inhibition, identifying unique neurophysiological signatures of action-stopping is difficult. Indeed, we report that recently proposed early-latency signatures of motor inhibition during action-stopping are also found after salient signals that do not require stopping. However, using multivariate pattern analysis of scalp-recorded neural data, we also identified subsequent neural activity that uniquely distinguished action-stopping from saliency detection. These results suggest that actions are stopped in two stages: the first common to all salient events and the second unique to action-stopping.