Attentional set and explicit expectations of perceptual load determine flanker interference.

Task-irrelevant stimuli often capture our attention despite our best efforts to ignore them. It has been noted that tasks involving perceptually complex displays can lead to reduced interference from distractors. The mechanism behind this effect is debated, with some accounts emphasizing the "perceptual load" of the stimuli themselves and others emphasizing the role of proactive control. Here, in three experiments, we investigated the roles of perceptual load, proactive control, and reward motivation in determining distractor interference. Participants performed a visual search task of high, low, or intermediate load, with flanking task-irrelevant distractors. Each trial was preceded by a cue indicating the level of perceptual load (Experiments 1-3) as well as the potential reward that could be earned (Experiments 2 and 3). In all three experiments, the attentional set induced by the preceding trial and cued proactive expectation of perceptual load interacted to determine flanker interference, which was significant for all trial types except trials cued as high load which were also preceded by high load. These effects were not modulated by reward motivation, although in the final experiment reward did significantly improve performance overall. Thus, successful distractor exclusion does not depend upon motivation or load per se but does require an expectation of high load. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The dynamics of statistical learning in visual search and its interaction with salience processing: An EEG study.

Visual attention can be guided by statistical regularities in the environment, that people implicitly learn from past experiences (statistical learning, SL). Moreover, a perceptually salient element can automatically capture attention, gaining processing priority through a bottom-up attentional control mechanism. The aim of our study was to investigate the dynamics of SL and if it shapes attentional target selection additively with salience processing, or whether these mechanisms interact, e.g. one gates the other. In a visual search task, we therefore manipulated target frequency (high vs. low) across locations while, in some trials, the target was salient in terms of colour. Additionally, halfway through the experiment, the high-frequency location changed to the opposite hemifield. EEG activity was simultaneously recorded, with a specific interest in two markers related to target selection and post-selection processing, respectively: N2pc and SPCN. Our results revealed that both SL and saliency significantly enhanced behavioural performance, but also interacted with each other, with an attenuated saliency effect at the high-frequency target location, and a smaller SL effect for salient targets. Concerning processing dynamics, the benefit of salience processing was more evident during the early stage of target selection and processing, as indexed by a larger N2pc and early-SPCN, whereas SL modulated the underlying neural activity particularly later on, as revealed by larger late-SPCN. Furthermore, we showed that SL was rapidly acquired and adjusted when the spatial imbalance changed. Overall, our findings suggest that SL is flexible to changes and, combined with salience processing, jointly contributes to establishing attentional priority.

Separate and overlapping mechanisms of statistical regularities and salience processing in the occipital cortex and dorsal attention network.

Attention selects behaviorally relevant inputs for in-depth processing. Beside the role of traditional signals related to goal-directed and stimulus-driven control, a debate exists regarding the mechanisms governing the effect of statistical regularities on attentional selection, and how these are integrated with other control signals. Using a visuo-spatial search task under fMRI, we tested the joint effects of statistical regularities and stimulus-driven salience. We found that both types of signals modulated occipital activity in a spatially specific manner. Salience acted primarily by reducing the attention bias towards the target location when associated with irrelevant distractors, while statistical regularities reduced this attention bias when the target was presented at a low probability location, particularly at the lower levels of the visual hierarchy. In addition, we found that both statistical regularities and salience activated the dorsal frontoparietal network. Additional exploratory analyses of functional connectivity revealed that only statistical regularities modulated the inter-regional coupling between the posterior parietal cortex and the occipital cortex. These results show that statistical regularities and salience signals are both spatially represented at the occipital level, but that their integration into attentional processing priorities relies on dissociable brain mechanisms.

Integrated effects of top-down attention and statistical learning during visual search: An EEG study.

The present study aims to investigate how the competition between visual elements is solved by top-down and/or statistical learning (SL) attentional control (AC) mechanisms when active together. We hypothesized that the "winner" element that will undergo further processing is selected either by one AC mechanism that prevails over the other, or by the joint activity of both mechanisms. To test these hypotheses, we conducted a visual search experiment that combined an endogenous cueing protocol (valid vs. neutral cue) and an imbalance of target frequency distribution across locations (high- vs. low-frequency location). The unique and combined effects of top-down control and SL mechanisms were measured on behaviour and amplitudes of three evoked-response potential (ERP) components (i.e., N2pc, P1, CNV) related to attentional processing. Our behavioural results showed better performance for validly cued targets and for targets in the high-frequency location. The two factors were found to interact, so that SL effects emerged only in the absence of top-down guidance. Whereas the CNV and P1 only displayed a main effect of cueing, for the N2pc we observed an interaction between cueing and SL, revealing a cueing effect for targets in the low-frequency condition, but not in the high-frequency condition. Thus, our data support the view that top-down control and SL work in a conjoint, integrated manner during target selection. In particular, SL mechanisms are reduced or even absent when a fully reliable top-down guidance of attention is at play.

Proactively Adjusting Stopping: Response Inhibition is Faster when Stopping Occurs Frequently.

People are able to stop actions before they are executed, and proactively slow down the speed of going in line with their expectations of needing to stop. Such slowing generally increases the probability that stopping will be successful. Surprisingly though, no study has clearly demonstrated that the speed of stopping (measured as the stop-signal reaction time, SSRT) is reduced by such proactive adjustments. In addition to a number of studies showing non-significant effects, the only study that initially had observed a clear effect in this direction found that it was artifactually driven by a confounding variable (specifically, by context-independence violations, which jeopardize the validity of the SSRT estimation). Here, we tested in two well-powered and well-controlled experiments whether the SSRT is shorter when stopping is anticipated. In each experiment, we used a Stop-Signal Task, in which the stop-trial frequency was either high (50%) or low (20%). Our results robustly show that the SSRT was shorter when stop signals were more anticipated (i.e., in the high-frequent condition) while carefully controlling for context-independence violations. Hence, our study is first to demonstrate a clear proactive benefit on the speed of stopping, in line with an ability to emphasize going or stopping, by trading off the speed of both.

A pupillometric investigation of state regulation in adults scoring high versus low on ADHD symptomatology.

According to the state regulation deficit (SRD) account, ADHD is associated with difficulties regulating tonic arousal levels, which may be due to inefficient effort allocation. We aimed to test the SRD account by using a target detection task with three different event rates (ER; 700 ms, 1800 ms, 6000 ms), in order to manipulate the tonic arousal state and its effects on performance and pupil indices in adults with high (n = 40) versus low (n = 36) ADHD symptom levels. In an additional condition, a fast ER (700 ms) was accompanied by auditory white noise (WN), to further increase tonic arousal level. The ER manipulation had a clear effect on RT and variability of RT. These effects were more pronounced for the high-ADHD group, especially for variability of RT with decreasing ER, suggestive of deficient upregulation of a tonic arousal state in that group, in line with their self-reported SRDs in daily life. Adding WN to the fast condition led to more errors, however similarly for both groups. Contrary to our predictions, the ER manipulation had no effect on tonic pupil size (as a measure of tonic arousal). Phasic pupil amplitude (as a measure of cognitive effort) linearly increased with decreasing ER, suggesting more effort allocation during slower ERs. WN decreased phasic pupil amplitude, but had no impact on tonic pupil size. Importantly, however, no ADHD-related differences were present for the pupil indices. In conclusion, adults with elevated levels of ADHD symptoms reported more SRDs in daily life and showed a performance pattern that suggests difficulties in upregulating but not downregulating the tonic arousal state. Surprisingly, these findings were not accompanied by group differences in pupillometric indices. This casts some doubts on the relationship between these measures of autonomic nervous system activity and state regulation, in particular in the context of ADHD symptomatology.

Effects of top-down and bottom-up attention on post-selection posterior contralateral negativity.

We examined the effect of combined top-down and bottom-up attentional control sources in easy and difficult visual search tasks. Applying a new analysis on previously acquired data, we focused on the sustained posterior contralateral negativity (SPCN) and the response-locked posterior contralateral negativity (RLpcN), to better understand processes following target selection. We used the signed-area approach to measure the negative area, where the signal was either locked to the target or the response onsets. We further split the RLpcN into an early and a late segment to capture the dynamics of selection and post-selection processes. In Experiment 1, participants reported the orientation of a uniquely tilted target. In Experiment 2, participants reported the position of a small gap within the uniquely tilted target. In both experiments, endogenous cues manipulated top-down attention (valid vs. neutral), and salient color singletons (either the target or a distractor) manipulated bottom-up attention. We hypothesized that the SPCN and the later segment of the RLpcN would be modulated by task difficulty and target salience, as they are associated with post-selection processes, such as response selection and working memory. The early segment of the RLpcN was hypothesized to be modulated by the cueing manipulation and presence of a salient distractor, as they affect target selection. An effect of distractor presence was observed on the early segment of the RLpcN, and our results further supported the hypotheses regarding the SPCN and the later segment of the RLpcN, providing novel insights into post-selection processes in visual search.

Computational Investigations of Learning and Synchronization in Cognitive Control.

Complex cognition requires binding together of stimulus, action, and other features, across different time scales. Several implementations of such binding have been proposed in the literature, most prominently synaptic binding (learning) and synchronization. Biologically plausible accounts of how these different types of binding interact in the human brain are still lacking. To this end, we adopt a computational approach to investigate the impact of learning and synchronization on both behavioral (reaction time, error rate) and neural (θ power) measures. We train four models varying in their ability to learn and synchronize for an extended period of time on three seminal action control paradigms varying in difficulty. Learning, but not synchronization, proved essential for behavioral improvement. Synchronization however boosts performance of difficult tasks, avoiding the computational pitfalls of catastrophic interference. At the neural level, θ power decreases with practice but increases with task difficulty. Our simulation results bring new insights in how different types of binding interact in different types of tasks, and how this is translated in both behavioral and neural metrics.

The influence of pupil responses on subjective brightness perception.

When the pupil dilates, the amount of light that falls onto the retina increases. However, in daily life, this does not make the world look brighter. Here we asked whether pupil size (resulting from active pupil movement) influences subjective brightness in the absence of indirect cues that, in daily life, support brightness constancy. We measured the subjective brightness of a tester stimulus relative to a referent as a function of pupil size during tester presentation. In Experiment 1, we manipulated pupil size through a secondary working-memory task (larger pupils with higher load and after errors). We found some evidence that the tester was perceived as darker, rather than brighter, when pupils were larger. In Experiment 2, we presented a red or blue display (larger pupils following red displays). We again found that the tester was perceived as darker when pupils were larger. We speculate that the visual system takes pupil size into account when making brightness judgments. Finally, we highlight the challenges associated with manipulating pupil size. In summary, the current study (as well as a recent pharmacological study on the same topic by another team) is intriguing first steps towards understanding the role of pupil size in brightness perception.

Dynamic causal interactions between occipital and parietal cortex explain how endogenous spatial attention and stimulus-driven salience jointly shape the distribution of processing priorities in 2D visual space.

Visuo-spatial attention prioritizes the processing of relevant inputs via different types of signals, including current goals and stimulus salience. Complex mixtures of these signals engage in everyday life situations, but little is known about how these signals jointly modulate distributed patterns of activity across the occipital regions that represent visual space. Here, we measured spatio-topic, quadrant-specific occipital activity during the processing of visual displays containing both task-relevant targets and salient color-singletons. We computed spatial bias vectors indexing the effect of attention in 2D space, as coded by distributed activity in the occipital cortex. We found that goal-directed spatial attention biased activity towards the target and that salience further modulated this endogenous effect: salient distractors decreased the spatial bias, while salient targets increased it. Analyses of effective connectivity revealed that the processing of salient distractors relied on the modulation of the bidirectional connectivity between the occipital and the posterior parietal cortex, as well as the modulation of the lateral interactions within the occipital cortex. These findings demonstrate that goal-directed attention and salience jointly contribute to shaping processing priorities in the occipital cortex and highlight that multiple functional paths determine how spatial information about these signals is distributed across occipital regions.

Investigating the relationship between background luminance and self-reported valence of auditory stimuli.

The present study investigated the effect of background luminance on the self-reported valence ratings of auditory stimuli, as suggested by some earlier work. A secondary aim was to better characterise the effect of auditory valence on pupillary responses, on which the literature is inconsistent. Participants were randomly presented with sounds of different valence categories (negative, neutral, and positive) obtained from the IADS-E database. At the same time, the background luminance of the computer screen (in blue hue) was manipulated across three levels (i.e., low, medium, and high), with pupillometry confirming the expected strong effect of luminance on pupil size. Participants were asked to rate the valence of the presented sound under these different luminance levels. On a behavioural level, we found evidence for an effect of background luminance on the self-reported valence rating, with generally more positive ratings as background luminance increased. Turning to valence effects on pupil size, irrespective of background luminance, interestingly, we observed that pupils were smallest in the positive valence and the largest in negative valence condition, with neutral valence in between. In sum, the present findings provide evidence concerning a relationship between luminance perception (and hence pupil size) and self-reported valence of auditory stimuli, indicating a possible cross-modal interaction of auditory valence processing with completely task-irrelevant visual background luminance. We furthermore discuss the potential for future applications of the current findings in the clinical field.

An EEG study of the combined effects of top-down and bottom-up attentional selection under varying task difficulty.

We examined the effect of combined top-down and bottom-up attentional control sources, using known attention-related EEG components that are thought to reflect target selection (N2pc) and distractor suppression (PD ). We used endogenous cues (valid vs. neutral) for top-down attentional control, and salience in the form of color singletons (either the target or a distractor) for bottom-up attentional control in visual search. Crucially, in two experiments, the task was of increasing difficulty, reporting the orientation of a tilted target (Experiment 1), or the position of a small gap within the target among tilted non-targets (Experiment 2). Our results showed strong cueing effects on RT and accuracy in both experiments, demonstrating a general facilitation of responses to validly cued targets. Whereas the processing of salient targets was not improved compared with non-salient targets, the presence of a salient distractor consistently worsened performance. The N2pc and PD were only observed in trials where targets were preceded by neutral cues in Experiment 1, and for validly cued targets and salient neutrally cued targets in Experiment 2. A cueing effect was found on the PD in Experiment 1, showing an amplitude reduction in trials where the target was validly cued. These results support the idea that bottom-up attentional allocation occurs only when top-down allocation of attention is absent or inefficient. Therefore, these results indicate that attentional selection and suppression during visual search are both influenced by top-down cueing and give support to theories that focus on the interaction between the two types of attention.

Guiding spatial attention by multimodal reward cues.

Our attention is constantly captured and guided by visual and/or auditory inputs. One key contributor to selecting relevant information from the environment is reward prospect. Intriguingly, while both multimodal signal processing and reward effects on attention have been widely studied, research on multimodal reward signals is lacking. Here, we investigated this using a Posner task featuring peripheral cues of different modalities (audiovisual/visual/auditory), reward prospect (reward/no-reward), and cue-target stimulus-onset asynchronies (SOAs 100-1,300 ms). We found that audiovisual and visual reward cues (but not auditory ones) enhanced cue-validity effects, albeit with different time courses (Experiment 1). While the reward-modulated validity effect of visual cues was pronounced at short SOAs, the effect of audiovisual reward cues emerged at longer SOAs. Follow-up experiments exploring the effects of visual (Experiment 2) and auditory (Experiment 3) reward cues in isolation showed that reward modulated performance only in the visual condition. This suggests that the differential effect of visual and auditory reward cues in Experiment 1 is not merely a result of the mixed cue context, but confirms that visual reward cues have a stronger impact on attentional guidance in this paradigm. Taken together, it seems that adding an auditory reward cue to the inherently dominant visual one led to a shift/extension of the validity effect in time - instead of increasing its amplitude. While generally being in line with a multimodal cuing benefit, this specific pattern highlights that different reward signals are not simply combined in a linear fashion but lead to a qualitatively different process.

State regulation in adults scoring high versus low on ADHD symptomatology: A pupillometry study.

OBJECTIVE: According to the state regulation deficit account, attention deficit/hyperactivity disorder (ADHD) is associated with difficulties in maintaining an optimal level of cognitive arousal. As the precise locus of this problem is yet unknown, the present study investigated this through behavioral and pupillometry indices. METHOD: Adults scoring high versus low on ADHD symptomatology carried out a target detection task at three event rate (ER) levels. Phasic pupil dilation was used as an index of cognitive effort, and tonic pupil size as an index of tonic arousal. RESULTS: Performance and self-reports indicated state regulation difficulties in the high-ADHD group. Phasic pupil dilation was increased during slow ER, indicating additional effort allocation. Surprisingly, tonic pupil size was smallest in the fast ER, and group effects were absent for both pupil measures. CONCLUSION: The high-ADHD group showed state regulation difficulties despite similar levels of additional effort allocation as reflected by phasic pupil responses. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Neural underpinnings of valence-action interactions triggered by cues and targets in a rewarded approach/avoidance task.

Incentive-valence signals have a large impact on our actions in everyday life. While it is intuitive (and most often beneficial) to approach positive and avoid negative stimuli, these prepotent response tendencies can also be maladaptive, as exemplified by clinical conditions such as overeating or pathological gambling. We have recently shown that targets associated with monetary incentives can trigger such valence-action biases (target condition), and that these are absent when valence and action information are provided by advance cues (cue condition). Here, we explored the neural correlates underlying the absence of the behavioral bias in this condition using fMRI. Specifically, we tested in how far valence and action information are integrated at all in the cue condition (where no behavioral biases are observed), assessing activity at the moment of the cue (mainly preparation) and the target (mainly implementation). The cue-locked data was dominated by main effects of valence with increased activity for incentive versus no-incentive cues in a network including anterior insula, premotor cortex, (mostly ventral) striatum (voxel-wise analysis), and across five predefined regions of interest (ROI analysis). Only one region, the anterior cingulate cortex, featured a valence-action interaction, with increased activity for win-approach compared to no-incentive-approach cues. The target-locked data revealed a different interaction pattern with increased activity in loss-approach as compared to win-approach targets in the cerebellum (voxel-wise) and across all ROIs. For comparison, the uncued target condition (target-locked data only) featured valence and action main effects (incentive > no-incentive targets; approach > avoid targets), but no interactions. The results resonate with the common observations that performance benefits after incentive-valence cues are promoted by increased preparatory control. Moreover, the data provide support for the idea that valence and action information are integrated according to an evolutionary benefit (cue-locked), requiring additional neural resources to implement non-intuitive valence-action mappings (target-locked).

Theta and alpha power across fast and slow timescales in cognitive control.

Theta and alpha frequency neural oscillations are important for learning and cognitive control, but their exact role has remained obscure. In particular, it is unknown whether they operate at similar timescales, and whether they support different cognitive processes. We recorded EEG in 30 healthy human participants while they performed a learning task containing both novel (block-unique) and repeating stimuli. We investigated behavior and electrophysiology at both fast (i.e., within blocks) and slow (i.e., between blocks) timescales. Behaviorally, both response time and accuracy improved (respectively decrease and increase) over both fast and slow timescales. However, on the spectral level, theta power significantly decreased along the slow timescale, whereas alpha power significantly increased along the fast timescale. We thus demonstrate that theta and alpha both play a role during learning, but operate at different timescales. This result poses important empirical constraints for theories on learning, cognitive control, and neural oscillations.

Face the (trigger) failure: Trigger failures strongly drive the effect of reward on response inhibition.

Response inhibition is typically understood as the ability to stop inappropriate actions and is often investigated using the stop-signal task, in which a go response, triggered by a go signal, has to be inhibited upon the onset of a stop signal. In this task, response inhibition has been formalized as a race between a go and a stop process, which allows the latency of the stop process (stop-signal reaction time; SSRT) to be estimated. Yet, non-parametric SSRT estimations assume that the stop process is initiated without fail, which appears problematic as it is known that participants fail to do so on a subset of trials ("trigger failures"). Importantly, non-parametric methods systematically overestimate SSRT when trigger failures are present, and a growing literature is demonstrating that reported SSRT differences between groups and individuals are also (or rather) driven by differential trigger-failure rates. In the present study, we extend this line of research to a within-individual manipulation, namely the influence of reward on stop performance. We first reanalyzed four data sets of studies that had reported a facilitating effect of stimulus-based reward on SSRTs. Reanalyzing this data, we found that reward decreased the rates of trigger failures. When accounting for these differential trigger-failure rates, the effect of reward on SSRTs (i.e., stop latency) appeared to be virtually abolished. We then conducted a preregistered online follow-up study, implementing a typical block-based reward manipulation. The results of this study indicated simultaneous reward effects on trigger-failure rates and on SSRT. In sum, the present results indicate that trigger failures are an important source of variance in response inhibition, dovetailing with an evolving multicomponential view of response inhibition.

Comparing the motivational value of rewards and losses in an EEG-pupillometry study.

We found earlier that performance-contingent rewards lead to faster performance than equivalent losses [Carsten, Hoofs, Boehler, & Krebs, 2019. Motivation Science, 5(3). http://dx.doi.org/10.1037/mot0000117]. Here, we further tested the hypothesis that motivation to gain rewards is higher than to avoid losses, even when incentive values are matched. As implicit markers of motivation, we assessed electroencephalography (EEG) focusing on the P3 after target and feedback onset, and the Feedback-Related Negativity (FRN), as well as simultaneously recorded pupil size. Comparing only reward and loss prospect trials in Experiment 1, we found no consistent differences in behavior and electrophysiological markers of motivation, although pupil data suggested higher arousal after feedback in potential-loss trials. Including additional no-incentive trials in Experiment 2, we found consistent evidence that motivation to gain rewards was higher than to avoid losses: In line with behavior, the target-P3 was most pronounced for reward-related stimuli, followed by loss and no-incentive ones. This same ranking was found in the P3 and the FRN after positive outcomes (i.e., reward, avoided loss, and correct feedback in no-incentive trials). Negative outcomes featured a different pattern in line with the pupil response, which suggests that losses are emotionally salient events, without invigorating behavior proportionally. In sum, these findings suggest that the motivation to gain rewards is more pronounced than motivation to avoid equivalent losses, at least in tasks promoting transient increases in attention triggered by incentive prospect. These motivational differences may arise as avoided losses are not profitable in the long term, in contrast to gained rewards.

Effects of nicotine on pupil size and performance during multiple-object tracking in non-nicotine users.

Nicotine has been commonly used in pyschopharmacological studies, showing its benefits as a pharmacological stimulant on cognitive performance. In the current study, we investigated the effects of 2 mg (Experiment 1) and 4 mg (Experiment 2) of nicotine on performance on a multiple-object-tracking task. Participants were young non-smoking adults with no pre-existing attentional deficits. Nicotine and placebo were administered through nicotine and nicotine-free taste-matched chewing gum, respectively. Additionally, we compared pupil size between nicotine and placebo conditions in both experiments. Although we found that pupil size was considerably smaller in the nicotine conditions, nicotine administration did not appear to facilitate behavioural performance. We speculate that nicotine might enhance performance only for certain cognitive functions, and only for specific populations, such as nicotine-deprived smokers.

Are all behavioral reward benefits created equally? An EEG-fMRI study.

Reward consistently boosts performance in cognitive tasks. Although many different reward manipulations exist, systematic comparisons are lacking. Reward effects on cognitive control are usually studied using monetary incentive delay (MID; cue-related reward information) or stimulus-reward association (SRA; target-related reward information) tasks. While for MID tasks, evidence clearly implicates reward-triggered global increases in proactive control, it is unclear how reward effects arise in SRA tasks, and in how far such mechanisms overlap during task preparation and target processing. Here, we address these questions with simultaneous EEG-fMRI using a Stroop task with four different block types. In addition to MID and SRA blocks, we used an SRA-task modification with reward-irrelevant cues (C-SRA) and regular reward-neutral Stroop-task blocks. Behaviorally, we observed superior performance for all reward conditions compared to Neutral, and more pronounced reward effects in the SRA and C-SRA blocks, compared to MID blocks. The fMRI data showed similar reward effects in value-related areas for events that signaled reward availability (MID cues and (C-)SRA targets), and comparable reward modulations in cognitive-control regions for all targets regardless of block type. This result pattern was echoed by the EEG data, showing clear markers of valuation and cognitive control, which only differed during task preparation, whereas reward-related modulations during target processing were again comparable across block types. Yet, considering only cue-related fMRI data, C-SRA cues triggered preparatory control processes beyond reward-unrelated MID cues, without simultaneous modulations in typical reward areas, implicating enhanced task preparation that is not directly driven by a concurrent neural reward-anticipation response.