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.

Electrophysiological Indices of Distractor Processing in Visual Search Are Shaped by Target Expectations.

Although in many cases salient stimuli capture attention involuntarily, it has been proposed recently that under certain conditions, the bottom-up signal generated by such stimuli can be proactively suppressed. In support of this signal suppression hypothesis, ERP studies have demonstrated that salient stimuli that do not capture attention elicit a distractor positivity (PD), a putative neural index of suppression. At the same time, it is becoming increasingly clear that regularities across preceding search episodes have a large influence on attentional selection. Yet to date, studies in support of the signal suppression hypothesis have largely ignored the role of selection history on the processing of distractors. The current study addressed this issue by examining how electrophysiological markers of attentional selection (N2pc) and suppression (PD) elicited by targets and distractors, respectively, were modulated when the search target randomly varied instead of being fixed across trials. Results showed that although target selection was unaffected by this manipulation, both in terms of manual response times, as well as in terms of the N2pc component, the PD component was reliably attenuated when the target features varied randomly across trials. This result demonstrates that the distractor PD, which is typically considered the marker of selective distractor processing, cannot unequivocally be attributed to suppression only, as it also, at least in part, reflects the upweighting of target features.

The Electrophysiological Markers of Statistically Learned Attentional Enhancement: Evidence for a Saliency-based Mechanism.

It is well established that attention can be sharpened through the process of statistical learning (e.g., visual search becomes faster when targets appear at high-relative-to-low probability locations). Although this process of statistically learned attentional enhancement differs behaviorally from the well-studied top-down and bottom-up forms of attention, relatively little work has been done to characterize the electrophysiological correlates of statistically learned attentional enhancement. It thus remains unclear whether statistically learned enhancement recruits any of the same cognitive mechanisms as top-down or bottom-up attention. In the current study, EEG data were collected while participants searched for an ambiguous unique shape in a visual array (the additional singleton task). Unbeknownst to the participants, targets appeared more frequently in one location in space (probability cuing). Encephalographic data were then analyzed in two phases: an anticipatory phase and a reactive phase. In the anticipatory phase preceding search stimuli onset, alpha lateralization as well as the Anterior Directing Attention Negativity and Late Directing Attention Positivity components-signs of preparatory attention known to characterize top-down enhancement-were tested. In the reactive phase, the N2pc component-a well-studied marker of target processing-was examined following stimuli onset. Our results showed that statistically learned attentional enhancement is not characterized by any of the well-known anticipatory markers of top-down attention; yet targets at high probability locations did reliably evoke larger N2pc amplitudes, a finding that is associated with bottom-up attention and saliency. Overall, our findings are consistent with the notion that statistically learned attentional enhancement increases the perceptual salience of items appearing at high-probability locations relative to low-probability locations.

Statistical Learning Within Objects.

Research has recently shown that efficient selection relies on the implicit extraction of environmental regularities, known as statistical learning. Although this has been demonstrated for scenes, similar learning arguably also occurs for objects. To test this, we developed a paradigm that allowed us to track attentional priority at specific object locations irrespective of the object's orientation in three experiments with young adults (all Ns = 80). Experiments 1a and 1b established within-object statistical learning by demonstrating increased attentional priority at relevant object parts (e.g., hammerhead). Experiment 2 extended this finding by demonstrating that learned priority generalized to viewpoints in which learning never took place. Together, these findings demonstrate that as a function of statistical learning, the visual system not only is able to tune attention relative to specific locations in space but also can develop preferential biases for specific parts of an object independently of the viewpoint of that object.

Long-term memory retrieval bypasses working memory.

For decades, it has been assumed that when humans retrieve information from long-term memory (LTM), information need first to be brought back into working memory (WM). However, as WM capacity is limited, it is unclear what happens if information from LTM needs to be retrieved while WM is fully engaged? To address this question, observers had to retrieve colors from LTM while WM storage capacity was fully engaged. The behavioral results showed that retrieving information from LTM is possible even when WM capacity is fully occupied. Additional evidence from electroencephalogram (EEG) confirmed that WM was fully engaged as the suppression of alpha oscillation reached its maximum when memorizing the maximum amount of information into WM; yet the suppression in alpha oscillation was even further amplified when items were retrieved simultaneously from LTM, providing a neural signature of additional LTM retrieval capacity above and beyond the maximum WM capacity. Together, our findings indicate that information retrieved from LTM does not always have to be brought back into WM, but instead might be accessed through a different mechanism when WM is fully engaged.

Multivariate analysis of EEG activity indexes contingent attentional capture.

An extensive body of work has shown that attentional capture is contingent on the goals of the observer: Capture is strongly reduced or even eliminated when an irrelevant singleton stimulus does not match the target-defining properties (Folk et al., 1992). There has been a long-standing debate on whether attentional capture can be explained by goal-driven and/or stimulus-driven accounts. Here, we shed further light on this matter by using EEG activity (raw EEG and alpha power) to provide a time-resolved index of attentional orienting towards salient stimuli that either matched or did not match target-defining properties. A search display containing the target stimulus was preceded by a spatially uninformative singleton cue that either matched the color of the upcoming target (contingent cues), or that appeared in an irrelevant color (non-contingent cues). Multivariate analysis of raw EEG and alpha power revealed preferential tuning to the location of both contingent and non-contingent cues, with a stronger bias towards contingent than non-contingent cues. The time course of these effects, however, depended on the neural signal. Raw EEG data revealed attentional orienting towards the contingent cue early on in the trial (>156 ms), while alpha power revealed sustained spatial selection in the cued locations at a later moment in the trial (>250 ms). Moreover, while raw EEG showed stronger capture by contingent cues during this early time window, an advantage for contingent cues arose during a later time window in alpha band activity. Thus, our findings suggest that raw EEG activity and alpha-band power tap into distinct neural processes that index separate aspects of covert spatial attention.

Learning in Visual Regions as Support for the Bias in Future Value-Driven Choice.

Reinforcement learning can bias decision-making toward the option with the highest expected outcome. Cognitive learning theories associate this bias with the constant tracking of stimulus values and the evaluation of choice outcomes in the striatum and prefrontal cortex. Decisions however first require processing of sensory input, and to date, we know far less about the interplay between learning and perception. This functional magnetic resonance imaging study (N = 43) relates visual blood oxygen level-dependent (BOLD) responses to value beliefs during choice and signed prediction errors after outcomes. To understand these relationships, which co-occurred in the striatum, we sought relevance by evaluating the prediction of future value-based decisions in a separate transfer phase where learning was already established. We decoded choice outcomes with a 70% accuracy with a supervised machine learning algorithm that was given trial-by-trial BOLD from visual regions alongside more traditional motor, prefrontal, and striatal regions. Importantly, this decoding of future value-driven choice outcomes again highlighted an important role for visual activity. These results raise the intriguing possibility that the tracking of value in visual cortex is supportive for the striatal bias toward the more valued option in future choice.

Statistical distractor learning modulates perceptual sensitivity.

The present study used perceptual sensitivity (d') to determine the spatial distribution of attention in displays in which participants have learned to suppress a location that is most likely to contain a distractor. Participants had to indicate whether a horizontal or a vertical line, which was shown only briefly before it was masked, was present within a target shape. Critically, the target shape could be accompanied by a singleton distractor color, which when present appeared with a high probability at one display location. The results show that perceptual sensitivity was reduced for locations likely to contain a distractor, as d' was lower for this location than for all other locations in the display. We also found that the presence of an irrelevant color singleton reduced the gain for input at the target location, particularly when the irrelevant singleton was close to the target singleton. We conclude that, through the repeated encounter with a distractor at a particular location, the weights within the attentional priority map are changed such that the perceptual sensitivity for objects presented at that location is reduced relative to all other locations. This reduction of perceptual sensitivity signifies that this location competes less for attention than all other locations.

Correction: How pupil responses track value-based decision-making during and after reinforcement learning.

[This corrects the article DOI: 10.1371/journal.pcbi.1006632.].

Dopaminergic medication reduces striatal sensitivity to negative outcomes in Parkinson's disease.

Reduced levels of dopamine in Parkinson's disease contribute to changes in learning, resulting from the loss of midbrain neurons that transmit a dopaminergic teaching signal to the striatum. Dopamine medication used by patients with Parkinson's disease has previously been linked to behavioural changes during learning as well as to adjustments in value-based decision-making after learning. To date, however, little is known about the specific relationship between dopaminergic medication-driven differences during learning and subsequent changes in approach/avoidance tendencies in individual patients. Twenty-four Parkinson's disease patients ON and OFF dopaminergic medication and 24 healthy controls subjects underwent functional MRI while performing a probabilistic reinforcement learning experiment. During learning, dopaminergic medication reduced an overemphasis on negative outcomes. Medication reduced negative (but not positive) outcome learning rates, while concurrent striatal blood oxygen level-dependent responses showed reduced prediction error sensitivity. Medication-induced shifts in negative learning rates were predictive of changes in approach/avoidance choice patterns after learning, and these changes were accompanied by systematic striatal blood oxygen level-dependent response alterations. These findings elucidate the role of dopamine-driven learning differences in Parkinson's disease, and show how these changes during learning impact subsequent value-based decision-making.

Neural Dynamics of Reward-Induced Response Activation and Inhibition.

Reward-predictive stimuli can increase an automatic response tendency, which needs to be counteracted by effortful response inhibition when this tendency is inappropriate for the current task. Here we investigated how the human brain implements this dynamic process by adopting a reward-modulated Simon task while acquiring EEG and fMRI data in separate sessions. In the Simon task, a lateral target stimulus triggers an automatic response tendency of the spatially corresponding hand, which needs to be overcome if the activated hand is opposite to what the task requires, thereby delaying the response. We associated high or low reward with different targets, the location of which could be congruent or incongruent with the correct response hand. High-reward targets elicited larger Simon effects than low-reward targets, suggesting an increase in the automatic response tendency induced by the stimulus location. This tendency was accompanied by modulations of the lateralized readiness potential over the motor cortex, and was inhibited soon after if the high-reward targets were incongruent with the correct response hand. Moreover, this process was accompanied by enhanced theta oscillations in medial frontal cortex and enhanced activity in a frontobasal ganglia network. With dynamical causal modeling, we further demonstrated that the connection from presupplementary motor area (pre-SMA) to right inferior frontal cortex (rIFC) played a crucial role in modulating the reward-modulated response inhibition. Our results support a dynamic neural model of reward-induced response activation and inhibition, and shed light on the neural communication between reward and cognitive control in generating adaptive behaviors.

Anticipatory Distractor Suppression Elicited by Statistical Regularities in Visual Search.

Salient yet irrelevant objects often capture our attention and interfere with our daily tasks. Distraction by salient objects can be reduced by suppressing the location where they are likely to appear. The question we addressed here was whether suppression of frequent distractor locations is already implemented beforehand, in anticipation of the stimulus. Using EEG, we recorded cortical activity of human participants searching for a target while ignoring a salient distractor. The distractor was presented more often at one location than at any other location. We found reduced capture for distractors at frequent locations, indicating that participants learned to avoid distraction. Critically, we found evidence for "proactive suppression" as already "prior to display onset," there was enhanced power in parieto-occipital alpha oscillations contralateral to the frequent distractor location-a signal known to occur in anticipation of irrelevant information. Locked to display onset, ERP analysis showed a distractor suppression-related distractor positivity (PD) component for this location. Importantly, this PD was found regardless of whether distracting information was presented at the frequent location. In addition, there was an early PD component representing an early attentional index of the frequent distractor location. Our results show anticipatory (proactive) suppression of frequent distractor locations in visual search already starting prior to display onset.

Discriminating between anticipatory and visually triggered saccades: measuring minimal visual saccadic response time using luminance.

We describe a novel behavioral method to accurately discriminate anticipatory (i.e., saccades not generated by visual input) from visually triggered saccades and to identify the minimal visual saccadic reaction time (SRT). This method can be used to calculate a feasible lower bound cutoff for latencies of visually triggered saccades within a certain experimental context or participant group. We apply this method to compute the minimal visual SRT for two different saccade target luminance levels. Three main findings are presented: 1) the minimal visual SRT for all participants was 46 ms shorter for bright targets than for dim targets, 2) the transition from non-visually triggered to visually triggered saccades occurred abruptly, independent of target luminance, and 3) although the absolute minimal visual SRTs varied between participants, the response pattern (response to bright targets being faster than to dim targets) was consistent across participants. These results are consistent with variability in saccadic and neural responses to luminance as has been reported in monkeys. On the basis of these results, we argue that differences in the minimal visual SRT can easily occur when stimuli vary in luminance or other saliency features. Applying an absolute cutoff (i.e., 70-90 ms) that approaches the minimal neuronal conduction delays, which is general practice in many laboratories, may result in the wrongful inclusion of saccades that are not visually triggered. It is suggested to assess the lower SRT bound for visually triggered saccades when piloting an experimental setup and before including saccades based on particular latency criteria. NEW & NOTEWORTHY We successfully developed an anticipation paradigm to discriminate between anticipatory and visually triggered saccades by measuring the minimal visual saccadic response time (SRT). We show that the 70- to 90-ms lower bound cutoff for visually triggered saccades should be applied in a flexible way and that the transitional interval is very short. The paradigm can be employed to investigate the effects of different stimulus features, experimental conditions, and participant groups on the minimal visual SRT in humans.

Capture and Control: Working Memory Modulates Attentional Capture by Reward-Related Stimuli.

Physically salient but task-irrelevant distractors can capture attention in visual search, but resource-dependent, executive-control processes can help reduce this distraction. However, it is not only physically salient stimuli that grab our attention: Recent research has shown that reward history also influences the likelihood that stimuli will capture attention. Here, we investigated whether resource-dependent control processes modulate the effect of reward on attentional capture, much as for the effect of physical salience. To this end, we used eye tracking with a rewarded visual search task and compared performance under conditions of high and low working memory load. In two experiments, we demonstrated that oculomotor capture by high-reward distractor stimuli is enhanced under high memory load. These results highlight the role of executive-control processes in modulating distraction by reward-related stimuli. Our findings have implications for understanding the neurocognitive processes involved in real-life conditions in which reward-related stimuli may influence behavior, such as addiction.

How pupil responses track value-based decision-making during and after reinforcement learning.

Cognition can reveal itself in the pupil, as latent cognitive processes map onto specific pupil responses. For instance, the pupil dilates when we make decisions and these pupil size fluctuations reflect decision-making computations during and after a choice. Surprisingly little is known, however, about how pupil responses relate to decisions driven by the learned value of stimuli. This understanding is important, as most real-life decisions are guided by the outcomes of earlier choices. The goal of this study was to investigate which cognitive processes the pupil reflects during value-based decision-making. We used a reinforcement learning task to study pupil responses during value-based decisions and subsequent decision evaluations, employing computational modeling to quantitatively describe the underlying cognitive processes. We found that the pupil closely tracks reinforcement learning processes independently across participants and across trials. Prior to choice, the pupil dilated as a function of trial-by-trial fluctuations in value beliefs about the to-be chosen option and predicted an individual's tendency to exploit high value options. After feedback a biphasic pupil response was observed, the amplitude of which correlated with participants' learning rates. Furthermore, across trials, early feedback-related dilation scaled with value uncertainty, whereas later constriction scaled with signed reward prediction errors. These findings show that pupil size fluctuations can provide detailed information about the computations underlying value-based decisions and the subsequent updating of value beliefs. As these processes are affected in a host of psychiatric disorders, our results indicate that pupillometry can be used as an accessible tool to non-invasively study the processes underlying ongoing reinforcement learning in the clinic.

Spatially Selective Alpha Oscillations Reveal Moment-by-Moment Trade-offs between Working Memory and Attention.

Current theories assume a functional role for covert attention in the maintenance of spatial information in working memory. Consistent with this view, both the locus of attention and positions stored in working memory can be decoded based on the topography of oscillatory alpha-band (8-12 Hz) activity on the scalp. Thus far, however, alpha modulation has been studied in isolation for covert attention and working memory tasks. Here, we applied an inverted spatial encoding model in combination with EEG to study the temporal dynamics of spatially specific alpha activity during a task that required observers to visually select a target location while maintaining another independently varying location in working memory. During the memory delay period, alpha-based spatial tuning functions shifted from the position stored in working memory to the covertly attended position and back again after the attention task was completed. The findings provide further evidence for a common oscillatory mechanism in both the selection and the maintenance of relevant spatial visual information and demonstrate the dynamic trade-off in prioritization between two spatial tasks.

To look or not to look? Reward, selection history, and oculomotor guidance.

The current eye-tracking study examined the influence of reward on oculomotor performance, and the extent to which learned stimulus-reward associations interacted with voluntary oculomotor control with a modified paradigm based on the classical antisaccade task. Participants were shown two equally salient stimuli simultaneously: a gray and a colored circle, and they were instructed to make a fast saccade to one of them. During the first phase of the experiment, participants made a fast saccade toward the colored stimulus, and their performance determined a (cash) bonus. During the second, participants made a saccade toward the gray stimulus, with no rewards available. On each trial, one of three colors was presented, each associated with high, low or no reward during the first phase. Results from the first phase showed improved accuracy and shorter saccade latencies on high-reward trials, while those from the second replicated well-known effects typical of the antisaccade task, namely, decreased accuracy and increased latency during phase II, even despite the absence of abrupt asymmetric onsets. Crucially, performance differences between phases revealed longer latencies and less accurate saccades during the second phase for high-reward trials, compared with the low- and no-reward trials. Further analyses indicated that oculomotor capture by reward signals is mainly found for saccades with short latencies, while this automatic capture can be overridden through voluntary control with longer ones. These results highlight the natural flexibility and adaptability of the attentional system, and the role of reward in modulating this plasticity. NEW & NOTEWORTHY Typically, in the antisaccade task, participants need to suppress an automatic orienting reflex toward a suddenly appearing peripheral stimulus. Here, we introduce an alternative antisaccade task without such abrupt onsets. We replicate well-known antisaccade effects (more errors and longer latencies), demonstrating the role of reward in developing selective oculomotor biases. Results highlight how reward and selection history facilitate developing automatic biases from goal-driven behavior, and they suggest that this process responds to individual differences in impulsivity.

Clinical pain and functional network topology in Parkinson's disease: a resting-state fMRI study.

Pain is an important non-motor symptom in Parkinson's disease (PD), but its underlying pathophysiological mechanisms are still unclear. Research has shown that functional connectivity during the resting-state may be involved in persistent pain in PD. In the present cross-sectional study, 24 PD patients (both during on and off medication phase) and 27 controls participated. We assessed pain with the colored analogue scale and the McGill pain questionnaire. We examined a possible pathophysiological mechanism with resting-state fMRI using functional network topology, i.e., the architecture of functional connections. We took betweenness centrality (BC) to assess hubness, and global efficiency (GE) to assess integration of the network. We aimed to (1) assess the differences between PD patients and controls with respect to pain and resting-state network topology, and (2) investigate how resting-state network topology (BC and GE) is associated with clinical pain in both PD patients and controls. Results show that PD patients experienced more pain than controls. GE of the whole brain was higher in PD patients (on as well as off medication) compared to healthy controls. GE of the specialized pain network was also higher in PD patients compared to controls, but only when patients were on medication. BC of the pain network was lower in PD patients off medication compared to controls. We found a positive association between pain and GE of the pain network in PD patients off medication. For healthy controls, a negative association was found between pain and GE of the pain network, and also between pain and BC of the pain network. Our results suggest that functional network topology differs between PD patients and healthy controls, and that this topology can be used to investigate the underlying neural mechanisms of pain symptoms in PD.

Eye abduction reduces but does not eliminate competition in the oculomotor system.

Although it is well established that there is a tight coupling between covert attention and the eye movement system there is an ongoing controversy whether this relationship is functional. Previous studies demonstrated that disrupting the ability to execute an eye movement interferes with the allocation of covert attention. One technique that prevents the execution of an eye movement involves the abduction of the eye in the orbit while presenting the stimuli outside of the effective oculomotor range (Craighero, Nascimben, & Fadiga, 2004). Although eye abduction is supposed to disrupt activation of the oculomotor program responsible for the shift of covert attention, this crucial assumption has never been tested experimentally. In the present study we used saccadic curvature to examine whether eye abduction eliminates the target-distractor competition in the oculomotor system. We experimentally reduced the ability to execute saccades by abducting the eye by 30° (monocular vision). This way the peripheral part of the temporal hemifield was located outside the oculomotor range. Participants made a vertical eye movement while on some trials a distractor was shown either inside or outside of the oculomotor range. The curvature away from distractors located outside the oculomotor range was reduced, but not completely eliminated. This confirms that eye abduction influences the activation of the oculomotor program, but points to the fact that other forms of motor planning, such as head movements are also represented in the oculomotor system. The results are in line with the idea that covert attention is an emerging property of movement planning, but is not restricted to saccade planning.

The influence of distractors on express saccades.

It is well known that regular target-driven saccades are affected by the presence of close and remote distractors. Distractors close to the target affect the saccade landing position (known as the global effect), while remote distractors prolong saccade latencies to the target (known as the remote-distractor effect). Little is known about whether a different population of saccades known as express saccades (saccades with very short latencies between 80 and 130 ms) is similarly affected by close and remote distractors, as these saccades are considered to be the result of advanced preparation of an oculomotor program toward the target. We designed a task in which we were able to generate a large number of express saccades, as evidenced by a separate and very early peak in the saccade-latency distribution-a distribution that was different from that of regular saccades. Our results show that irrelevant and unexpected visual input had a large effect on express saccades. We found a global and a remote-distractor effect which were similar to those seen in regular saccades. Even though our findings confirm the existence of very-short-latency saccades in humans, it is questionable whether they represent a different population of saccades, as they were equally affected by the presence of distractors as are regular saccades.