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Reward modulates oculomotor competition between differently valued stimuli
... Dans un premier temps, nous allons nous intéresser aux interactions entre la saillance et l'histoire de récompense, puis, dans un second temps, nous présenterons les interactions entre le modèle attentionnel et l'histoire de récompense.-Interaction entre la saillance perceptive et l'histoire de récompense : D'après certains auteurs, l'histoire de récompense agirait de façon similaire à la saillance bottom-up d'un stimulus, en guidant de manière involontaire et précoce, la sélection des informations (e.g.,Bucker et al., 2015 ;. En revanche, ces deux sources de signaux (e.g., saillance induite par la récompense et saillance perceptive) sont bien distinctes l'une de l'autre et leurs interactions déterminent ensemble la sélection attentionnelle des informations.Tout d'abord, nous avons déjà mentionné le fait que l'histoire de récompense peut potentialiser les effets de capture par des distracteurs saillants (e.g.,Anderson et al., 2011a ;Le Pelley et al., 2015). ...
... Néanmoins, nous allons voir que certaines études ont commencé à mettre en évidence une modulation de la capture attentionnelle par la récompense, dès lors que des conditions expérimentales contraignent plus fermement une sélection guidée par le modèle attentionnel top-down. Ces études suggèrent alors qu'il soit possible d'éviter, de façon top-down, une distraction par la récompense dans certaines conditions (lesquelles étant encore mal définies, et que notre travail s'attachera justement à éclaircir).2.3 La distraction par l'histoire de récompense est-elle évitable ?Selon plusieurs auteurs(Bucker et al., 2015 ;MacLean & Giesbrecht, 2015b), l'influence de l'histoire de récompense sur la sélection attentionnelle serait tellement précoce qu'elle échapperait à tout processus de contrôle top-down et pourrait, à ce titre, être considérée comme inévitable et automatique (e.g.,Anderson, 2015a ;Jahfari & Theeuwes, 2017 ;Krebs, Boehler, Egner, & Woldorff, 2011 ;Le Pelley, Mitchell, Beesley, George, & Wills, 2016 ;Marchner & Preuschhof, 2018 ;Pearson et al., 2015 ;. Cependant, selon nous, cette proposition est encore insuffisamment étayée par les données de la littérature. ...
... Ce biais attentionnel semble très persistant dans le temps, puisqu'il était observé chez des participants testés plusieurs jours(Della Libera & Chelazzi, 2009 ;MacLean & Giesbrecht, 2015b, 2015a voire plusieurs mois(Anderson & Yantis, 2013) après l'apprentissage associatif entre un stimulus et une récompense. Par ailleurs, plus la récompense associée à ce distracteur était élevée, plus l'effet de capture attentionnelle était important(Anderson & Halpern, 2017 ;Anderson et al., 2011b ;Anderson & Yantis, 2013 ;Bucker et al., 2015 ;Le Pelley et al., 2015 ;. ...
Au quotidien, notre attention sélective nous permet de sélectionner les informations pertinentes au regard de notre tâche et d'ignorer celles qui ne le sont pas, afin de maintenir un comportement cohérent avec nos buts. Néanmoins, dans certaines situations, un stimulus complètement non-pertinent peut capturer notre attention contre notre volonté et, de ce fait, produire un phénomène de distraction. La distraction a initialement été considérée comme essentiellement dépendante de la saillance perceptive des distracteurs. Cependant, de récentes études ont mis en évidence que les stimuli associés à l'obtention d'une récompense (i.e., disposant d'une histoire de récompense) sont également susceptibles de produire des effets de distraction particulièrement robustes et persistants (indépendamment de leur pertinence pour la tâche en cours et de leur saillance perceptive). Parallèlement, tout un autre champ de recherche a été consacré à l’étude du contrôle attentionnel qui peut être mis en place afin de prévenir une distraction par des stimuli visuellement saillants. Cependant, à ce jour, très peu de travaux ont tenté de manipuler la qualité du contrôle attentionnel qui peut être instauré pour éviter la distraction par des stimulus associés à une récompense. L'objectif de notre travail était donc de déterminer si, et si oui, dans quelles conditions, ces distracteurs pouvaient être ignorés efficacement ou, au contraire, pouvaient résister au contrôle attentionnel. Dans sept études, nous avons associé des stimuli visuels initialement neutres à une récompense (monétaire ou sociale) afin d’étudier leur impact sur les performances lorsqu’ils apparaissaient comme distracteurs dans des tâches recherche visuelle. Nous avons manipulé la qualité du contrôle attentionnel en faisant varier les contraintes perceptives (i.e., charge perceptive : Études 1 et 2), cognitives (i.e., charge cognitive : Étude 3) ou sensorielles (i.e., dégradation sensorielle : Études 4-7) imposées par la tâche. Nous avons mis en évidence que l'interférence provoquée par un distracteur associé à une forte récompense monétaire, contrairement à celle provoquée par des distracteurs uniquement saillants, peut résister à l'augmentation de la charge perceptive (Étude 1). L'analyse des potentiels cérébraux évoqués par ces distracteurs (Etude 2) suggère que cet effet puisse résulter d’une capture attentionnelle (N2pc) accrue en charge perceptive faible et d’une suppression attentionnelle (Pd) moins efficace en charge perceptive forte pour ces distracteurs. Contrairement à nos attentes, aucun effet de la récompense n'a été observé dans l’étude manipulant la charge cognitive (Étude 3), nous conduisant à proposer que notre manipulation ait pu drainer les ressources cognitives nécessaires à l'apprentissage de l’association distracteur-récompense. Ensuite, nous avons montré que l'augmentation de la pression temporelle (Étude 4-5), réputée pour favoriser la sélection précoce d'une cible, peut au contraire, dans certaines conditions, entrainer une plus grande difficulté à ignorer les distracteurs. Pour autant, dans ces conditions, le simple fait que des distracteurs récompensés puissent apparaître semble impacter encore plus négativement la sélection d'une cible que la pression temporelle elle-même. Enfin, nos deux dernières études (Études 6-7) ont mobilisé un cadre expérimental plus écologique, impliquant la recherche de cibles dans des photographies de scènes routières prises du point de vue d’un conducteur d’automobile et l’apparition de distracteurs récompensés sur l’écran d’un smartphone présent dans l’habitacle. Nous avons mis en évidence que la dégradation sensorielle de la cible (via une augmentation de l'intensité du brouillard) entraine une distraction plus importante pour des distracteurs associés à une récompense sociale, en particulier pour les personnes présentant un niveau élevé de FoMO (Fear of Missing Out ; peur de manquer une expérience sociale). [...]
... Subsequently, we investigated the impact of these value-based objects on attentional control. Studies have shown that reward-linked targets capture attention more easily than neutral targets (Bucker et al., 2015;Theeuwes & Belopolsky, 2012), but few studies have examined the effect of punishment-based targets on attention or in sports. In Experiment 2, we associated reward and punishment values with distractors to induce reward/punishment pressure and tested the effect of the value-based distractors five distinct areas, including the dartboard, scoreboard, reward target, punishment target, and neutral target. ...
... Due to the experimental design involving both rewards and punishments, the compensation In addition, attentional engagement with the money board was greater than that with all other targets in the learning step, indicating that money-related goals are more attractive. For attentional disengagement, time pressure made it more difficult to disengage from the task-irrelevant targets, which was in line with Experiment 3. The hypothesis was based on previous studies (Bucker et al., 2015;Mine & Saiki, 2015;Vromen et al., 201) that investigated attention control using cognitive tasks and asked participants only to respond to targets and distractors. However, this experiment used a motor task, which required much more effort than a simple cognitive task. ...
The present research aimed to examine the effect of time pressure and reward-punishment pressure on attention control in two distinct processes: attentional engagement and attentional disengagement. Study 1 employed a dart-throw task to explore the effects of time pressure (Experiment 1) and reward-punishment pressure (Experiment 2) on attention control. The findings revealed that (a) time pressure did not significantly impact attentional engagement or attentional disengagement toward either task-relevant nor task-irrelevant targets; (b) reward/punishment pressure resulted in reduced attentional engagement towards task-irrelevant targets; and (c) compared to punishment pressure, reward pressure led to longer attentional disengagement from task-irrelevant targets. In Study 2, two virtual reality shooting tasks (Experiment 3 and Experiment 4) were conducted using the same design as Study 1, with a repetition rate of 50%. The findings showed that (a) time pressure did not impact attentional engagement, but led longer attentional disengagement; (b) attentional disengagement from the scoreboard was longer in the TP condition than in the NTP condition, while attentional disengagement from the target was shorter; (c) reward pressure induced attentional disengagement from both task-relevant and task-irrelevant targets. Through a mini meta-analysis that synthesized the results, it was determined that the impairment of attention control was primarily manifested through attentional disengagement. This study provides empirical support for attention control theory in the field of sports and offers a direct measurement method for assessing attention in sporting contexts.
... Furthermore, VDAC has been shown to persist for as long as 9 months after learning the original association without any additional reinforcement (Anderson & Yantis, 2013). In the absence of reinforcement, it is expected that a previously conditioned response to a reward-predictive stimulus would cease (e.g., Pavlov, 2010), and yet, when VDAC is reported, there is often no significant reduction in the impairment over the course of test (Anderson et al., 2011b;Anderson & Yantis, 2012Bucker et al., 2015;Failing & Theeuwes, 2014;Rothkirch et al., 2013;Sali et al., 2014;Sha & Jiang, 2016;Stankevich & Geng, 2014;, although occasionally such an effect has been observed (Anderson et al., 2011a(Anderson et al., , 2016Asutay & Västfjäll, 2016;Sali et al., 2018). These findings suggest that reward learning creates an unusually persistent change in attentional priority that is biased in favor of formerly reward associated features even when no longer predictive of reward. ...
... In Experiments 4 and 5 absent trials where neither the previously rewarded or non-rewarded features were presented as Table 1 Non-exhaustive list of value-driven attention(al) capture (VDAC) literature using paradigms with the key features of the test paradigms investigated in the current study. Excluded were studies where rewards were still available at test (e.g., Bucker et al., 2015;Munneke et al., 2015), and studies showing trial-to-trial effects of reward (Hickey et al., 2010a(Hickey et al., , b, 2011. The former was excluded as the presence of rewards at test makes it unclear whether extinction learning is taking place, and the latter as trial-to-trial effects may be at least in part due to priming. ...
Visual features previously associated with reward can capture attention even when task-irrelevant, a phenomenon known as value-driven attention capture (VDAC). VDAC persists without reinforcement, unlike other forms of learning, where removing reinforcement typically leads to extinction. In five experiments, factors common to many studies were manipulated to examine their impact on VDAC and its extinction. All experiments included learning and test phases. During learning, participants completed a visual search task during which one of two target colors was associated with a reward, and the other with no reward. During test, 1 week later, participants completed another visual search task in which the reward association was not reinforced. When a rewarded feature remained task-relevant (Experiment 1), VDAC was observed. When the rewarded feature was made task-irrelevant (Experiments 2–5) there was no evidence of a VDAC effect, except when the target feature was physically salient and there was a reduction in the frequency of exposure to the reward-associated feature (Experiment 5). We failed to find evidence of VDAC in Experiments 2–4, suggesting that VDAC may depend on the demands of the task resulting in vulnerability to VDAC. When VDAC was observed, extinction was also observed. This indicates that VDAC is subject to extinction as would be expected from an effect driven by reinforcement learning.
... Prior studies have also shown that reward contingencies can speed up saccades (Bendiksby & Platt, 2006;Kawagoe et al., 1998;Takikawa et al., 2002;Yamamoto et al., 2013). Similar results have been obtained in studies using human observers (Bucker, Silvis, Donk, & Theeuwes, 2015;Milstein & Dorris, 2007;Theeuwes & Belopolsky, 2012). For example, in Chen and colleagues' study, participants were cued to make saccades to the left or right and were also cued to whether or not the trial would be a reward trial. ...
... Previous studies have investigated direction and speed of saccades towards a previously reward-associated object as an index of valuedriven attentional capture (A.J. Kim and Anderson, 2019;Anderson & Yantis, 2012;Bucker et al., 2015;H. Kim and Anderson, 2019;Le Pelley et al., 2015;Milstein & Dorris, 2007;Milstein & Dorris, 2011;Theeuwes & Belopolsky, 2012), but the reward association is never assigned to the eye movement itself. ...
... Target objects associated with relatively high reward during a training session invoke more oculomotor capture compared to objects previously associated with low reward when presented as a task-irrelevant distractor in a subsequent test session. Oculomotor capture due to reward-based selection history has been observed when participants are unconstrained where to look at (Anderson & Yantis, 2012;Bucker, Silvis, Donk, & Theeuwes, 2015) or when instructed to search for a target defined by a different feature than the one previously associated with reward ). ...
... In the case of reward, it seems that although reward-based selection history biases competition above and beyond bottom-up and top-down processes, much of the evidence to date suggests that it does so in a similar way as physical salience. This is corroborated by behavioral and neuronal evidence showing that reward is interrelated with the physical salience of a stimulus (e.g., Wang et al., 2013), creates plastic changes in stimulus representations (e.g., Hickey et al., 2010a;, and affects selection as early as traditional manipulations of physical salience (e.g., Bucker, Silvis, et al., 2015;. Thus, in light of the current evidence, reward learning induces plastic changes in stimulus representations, which are evident as early in visual hierarchy as the (extra)striate visual cortex. ...
Visual attention enables us to selectively prioritize or suppress information in the environment. Prominent models concerned with the control of visual attention differentiate between goal-directed, top-down and stimulus-driven, bottom-up control, with the former determined by current selection goals and the latter determined by physical salience. In the current review, we discuss recent studies that demonstrate that attentional selection does not need to be the result of top-down or bottom-up processing but, instead, is often driven by lingering biases due to the "history" of former attention deployments. This review mainly focuses on reward-based history effects; yet other types of history effects such as (intertrial) priming, statistical learning and affective conditioning are also discussed. We argue that evidence from behavioral, eye-movement and neuroimaging studies supports the idea that selection history modulates the topographical landscape of spatial "priority" maps, such that attention is biased toward locations having the highest activation on this map.
... A separate case of learning involves pairing the perception of neutral images with reward or punishment-which is known to affect binocular oculomotor competition both in human (Bucker et al., 2015) and in non-human primates (Ghazizadeh et al., 2016). Along these lines, Wilbertz et al. (2014) and Marx and Einh€ auser (2015) showed that perceptual conditioning affects the duration of dominance periods in binocular rivalry. ...
Substantial experimental, theoretical, and computational insights into sensory processing have been derived from the phenomena of perceptual multistability—when two or more percepts alternate or switch in response to a single sensory input. Here, we review a range of findings suggesting that alternations can be seen as internal choices by the brain responding to values. We discuss how elements of external, experimenter-controlled values and internal, uncertainty- and aesthetics-dependent values influence multistability. We then consider the implications for the involvement in switching of regions, such as the anterior cingulate cortex, which are more conventionally tied to value-dependent operations such as cognitive control and foraging.
... This is likely because we do not readily think of oculomotor actions (i.e., saccades; in the following oculomotor actions and saccades are used as synonyms) as typical means to generate effects in the environment to achieve a specific goal, even though recent technologies support that aspect, e.g., gaze-based software menu control, camera autofocus, or gaze-based communication software for motor impaired patients (Slobodenyuk, 2016). Several studies have shown that expected reward affects where people look (Bucker, Silvis, Donk, & Theeuwes, 2015;Hickey & van Zoest, 2012;Schütz, Trommershäuser, & Gegenfurtner, 2012;Theeuwes & Belopolsky, 2012) as well as how quickly they do so (Dunne, Ellison, & Smith, 2015;Lauwereyns, Watanabe, Coe, & Hikosaka, 2002;Milstein & Dorris, 2007;Rothkirch, Ostendorf, Sax, & Sterzer, 2013;Watanabe, Lauwereyns, & Hikosaka, 2003). Hence, reward can serve as a goal that determines oculomotor actions. ...
Humans use their eyes not only as visual input devices to perceive the environment, but also as an action tool in order to generate intended effects in their environment. For instance, glances are used to direct someone else's attention to a place of interest, indicating that gaze control is an important part of social communication. Previous research on gaze control in a social context mainly focused on the gaze recipient by asking how humans respond to perceived gaze (gaze cueing). So far, this perspective has hardly considered the actor’s point of view by neglecting to investigate what mental processes are involved when actors decide to perform an eye movement to trigger a gaze response in another person. Furthermore, eye movements are also used to affect the non-social environment, for instance when unlocking the smartphone with the help of the eyes. This and other observations demonstrate the necessity to consider gaze control in contexts other than social communication whilst at the same time focusing on commonalities and differences inherent to the nature of a social (vs. non-social) action context. Thus, the present work explores the cognitive mechanisms that control such goal-oriented eye movements in both social and non-social contexts. The experiments presented throughout this work are built on pre-established paradigms from both the oculomotor research domain and from basic cognitive psychology. These paradigms are based on the principle of ideomotor action control, which provides an explanatory framework for understanding how goal-oriented, intentional actions come into being. The ideomotor idea suggests that humans acquire associations between their actions and the resulting effects, which can be accessed in a bi-directional manner: Actions can trigger anticipations of their effects, but the anticipated resulting effects can also trigger the associated actions. According to ideomotor theory, action generation involves the mental anticipation of the intended effect (i.e., the action goal) to activate the associated motor pattern. The present experiments involve situations where participants control the gaze of a virtual face via their eye movements. The triggered gaze responses of the virtual face are consistent to the participant’s eye movements, representing visual action effects. Experimental situations are varied with respect to determinants of action-effect learning (e.g., contingency, contiguity, action mode during acquisition) in order to unravel the underlying dynamics of oculomotor control in these situations. In addition to faces, conditions involving changes in non-social objects were included to address the question of whether mechanisms underlying gaze control differ for social versus non-social context situations. The results of the present work can be summarized into three major findings. 1. My data suggest that humans indeed acquire bi-directional associations between their eye movements and the subsequently perceived gaze response of another person, which in turn affect oculomotor action control via the anticipation of the intended effects. The observed results show for the first time that eye movements in a gaze-interaction scenario are represented in terms of their gaze response in others. This observation is in line with the ideomotor theory of action control. 2. The present series of experiments confirms and extends pioneering results of Huestegge and Kreutzfeldt (2012) with respect to the significant influence of action effects in gaze control. I have shown that the results of Huestegge and Kreutzfeldt (2012) can be replicated across different contexts with different stimulus material given that the perceived action effects were sufficiently salient. 3. Furthermore, I could show that mechanisms of gaze control in a social gaze-interaction context do not appear to be qualitatively different from those in a non-social context. All in all, the results support recent theoretical claims emphasizing the role of anticipation-based action control in social interaction. Moreover, my results suggest that anticipation-based gaze control in a social context is based on the same general psychological mechanisms as ideomotor gaze control, and thus should be considered as an integral part rather than as a special form of ideomotor gaze control.
... The influence of reward-learning on free-choice priming was evident in the faster responses (in the choice data in Experiment 1 and 2, and RT data in Experiment 2). Both neurophysiological and behavioral evidence exists to suggest that reward drives attentional selection by modulating saliency of the perceptual representations of reward-associated stimuli (Hickey et al., 2010;Bucker et al., 2015;Failing and Theeuwes, 2018). Such saliencybased effects are expected to be short-lived. ...
While it is known that reward induces attentional prioritization, it is not clear what effect reward-learning has when associated with stimuli that are not fully perceived. The masked priming paradigm has been extensively used to investigate the indirect impact of brief stimuli on response behavior. Interestingly, the effect of masked primes is observed even when participants choose their responses freely. While classical theories assume this process to be automatic, recent studies have provided evidence for attentional modulations of masked priming effects. Most such studies have manipulated bottom-up or top-down modes of attentional selection, but the role of “newer” forms of attentional control such as reward-learning and selection history remains unclear. In two experiments, with number and arrow primes, we examined whether reward-mediated attentional selection modulates masked priming when responses are chosen freely. In both experiments, we observed that primes associated with high-reward lead to enhanced free-choice priming compared to primes associated with no-reward. The effect was seen on both proportion of choices and response times, and was more evident in the faster responses. In the slower responses, the effect was diminished. Our study adds to the growing literature showing the susceptibility of masked priming to factors related to attention and executive control.
... That is, past regularities in search context and selection behavior can be implicitly or explicitly learned and can drive the deployment of attention when these regularities are subsequently encountered again. The influence of selection history has, among others, been demonstrated in studies investigating intertrial priming (Kristjánsson & Campana, 2010;Maljkovic & Nakayama, 1994, 2000, reward (Bucker, Silvis, Donk, & Theeuwes, 2015;Bucker & Theeuwes, 2017;Chelazzi, Perlato, Santandrea, & Della Libera, 2013;Della Libera, Perlato, & Chelazzi, 2011;Failing, Nissens, Pearson, Le Pelley, & Theeuwes, 2015;Failing & Theeuwes, 2014;Hickey, Chelazzi, & Theeuwes, 2010;Preciado, Munneke, & Theeuwes, 2017a, 2017b, and fear conditioning (Nissens, Failing, & Theeuwes, 2017;Schmidt, Belopolsky, & Theeuwes, 2015;see Failing & Theeuwes, 2018 for a review). ...
The present study investigated how statistical regularities present in the display affected the time courses associated with salience-driven and goal-driven visual selection. In two experiments, participants were instructed to make a speeded saccade toward a prespecified target that was presented simultaneously with a distractor among multiple homogeneously oriented background lines. The distractor was presented more often at one location than at all other locations. We found that the statistical regularity regarding the distractor location affected visual selection very early, modulating the time courses associated with both salience-driven and goal-driven selection. These results suggest that statistical learning induces a continuous bias in visual selection, operating above and beyond salience-driven and goal-driven control. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
... Other research using similar methods found semantic information (e.g., categorical information of a scene or an item) associated with a reward also captures an individual's attention (Failing & Theeuwes, 2015;Hickey, Kaiser, & Peelen, 2015). Reward items not only capture individual's covert attention but also draw individual's eye movements (e.g., Bucker, Silvis, Donk, & Theeuwes, 2015;, showing overt attentional shift (attentional orienting). What's more, the N2pc elicited by reward distractors precedes that elicited by the target, suggesting reward distractors capture attention before the target, which provides neurophysiological evidence for reward-associated attentional capture (Qi, Zeng, Ding, & Li, 2013). ...
Previous research has revealed the influence of reward associations on attentional selection and control. The attentional network can be divided into three components according to its function: Alerting, orienting, and executive control. In the current research, we used training-test procedure and attention network test variant to investigate the effects of color-based reward associations on alerting (Experiment 1), orienting (Experiment 2), executive control (Experiment 3), as well as the interactions among these three networks (Experiment 4). The findings were as follows: Compared with colors previously associated with low reward, colors previously associated with high reward trigger stronger alerting and orienting effects (Experiments 1 and 2), and they had stronger interference effects when functioning as features of flanker distractor (Experiment 3). More importantly, reward associations had only a positive impact on the interaction of orienting by executive control but not on the interaction of alerting by executive control (Experiment 4). In summary, reward associations have different effects on the three attentional networks and can enhance the interaction of orienting by executive control.
... It is generally believed that spatial priority maps may encode the priority of individual visual locations by combining signals, including the individual's goal (Folk & Remington, 2008;Leber & Egeth, 2006), the visual object's saliency (Theeuwes, 1992(Theeuwes, , 2010, past selection history (Awh, Belopolsky, & Theeuwes, 2012;Failing & Theeuwes, 2018;Theeuwes, 2018), reward association, and other possible sources influencing the object's saliency (Bourgeois, Chelazzi, & Vuilleumier, 2016;Bucker, Silvis, Donk, & Theeuwes, 2015;Bucker & Theeuwes, 2017;Chelazzi, Perlato, Santandrea, & Libera, 2013;Hickey, Chelazzi, & Theeuwes, 2010;Della Libera, Perlato, & Chelazzi, 2011;Failing & Theeuwes, 2018;Nissens, Failing, & Theeuwes, 2016;Schmidt, Belopolsky, & Theeuwes, 2015). As a result, the weight of each location within the map will determine the priority of selection, assuming that the location with the highest weight is selected first, followed by the next highest weight, etc. ...
People are sensitive to regularities in the environment. Recent studies employing the additional singleton paradigm showed that a singleton distractor that appeared more often in one specific location than in all other locations may lead to attentional suppression of high-probability distractor locations. This in turn effectively reduced the attentional capture effect by the salient distractor singleton. However, in basically all of these previous studies, the probability that the salient distractor was presented at this specific location was relatively high (i.e., 65%; or a ratio of 13:1 between high- and low-probability locations). The question we addressed here was whether participants still can learn the regularities in the display even when these regularities are quite subtle. We systematically manipulated the ratio of the distractor appearing at the high- and low-probability location from 2:1 to 8:1. We asked the question whether the suppression effect would depend on the probabilities of the distractor appearing in the high-probability location. The results showed that the suppression of the high-probability location was linearly related to the high-low-probability ratio. In other words, the more evidence that a distractor appears more often at a particular location, the stronger the suppression. This indicates that the distribution of attention is optimally adapted to the statistical regularities present in the display.
... In another study, Theeuwes and Belopolsky (2012) used a variant of the oculomotor capture task and demonstrated that eye movements are affected by reward-based selection history in a very similar way. They found that observers made more erroneous saccades to an abrupt onset stimulus during a reward-free test session if the color of that onset stimulus was previously associated with a high reward compared to when it was associated with a low reward during the training session (see also Anderson & Yantis, 2012;Bucker, Silvis, Donk & Theeuwes, 2015). ...
In this Element, a framework is proposed in which it is assumed that visual selection is the result of the interaction between top-down, bottom-up and selection-history factors. The Element discusses top-down attentional engagement and suppression, bottom-up selection by abrupt onsets and static singletons as well as lingering biases due to selection-history entailing priming, reward and statistical learning. We present an integrated framework in which biased competition among these three factors drives attention in a winner-take-all-fashion. We speculate which brain areas are likely to be involved and how signals representing these three factors feed into the priority map which ultimately determines selection.
... For example, repeated selection of a stimulus or feature biases attention on a transient, intertrial timescale without engaging top-down or bottom-up attention (Kruijne & Meeter, 2016;Maljkovic & Nakayama, 1994;Sha, Remington, & Jiang, 2017;Theeuwes, 2018). More persistent changes to attentional priority for frequently selected items can also occur when features or stimuli are associated with consistent reward contingencies (Anderson, Laurent, & Yantis, 2011;Bucker, Silvis, Donk, & Theeuwes, 2015;Chelazzi et al., 2014;Failing & Theeuwes, 2018;Gong & Li, 2014;Libera & Chelazzi, 2006) or presented in nonrandom, predictive patterns (Chun & Jiang, 1998;Jiang, Sha, & Remington, 2015;Sha et al., 2017;Turk-Browne, Scholl, Chun, & Johnson, 2009). ...
When repeatedly selected features have predictive value, an observer can learn to prioritize them. However, relatively little is known about the mechanisms underlying this persistent statistical learning. In two experiments, we investigated the boundary conditions of statistical learning. Each task included a training phase where targets appeared more frequently in one of two target colors, followed by a test phase where targets appeared equally in both colors. A posttest survey probed awareness of target color probability differences. Experiment 1 tested whether statistical learning requires the predictive feature to be inherently bound to the target. Participants searched for a horizontal or vertical line among diagonal distractors and reported its length (long or short). In the bound condition, targets and distractors were colored, whereas targets were presented in white font and surrounded by colored boxes in the unbound condition. Experiment 2 tested whether reducing task difficulty by simplifying the judgment (horizontal or vertical) would eliminate statistical learning. The results suggested that statistical learning is robust to manipulations of binding, but is attenuated when task difficulty is reduced. Finally, we found evidence that explicit awareness may contribute to statistical learning, but its effects are small and require large sample sizes for adequate detection. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
... This is likely because we do not readily think of oculomotor action as a typical means to generate effects in the environment to achieve a specific goal even though recent technologies support that aspect, e.g., gaze-based software menu control, camera autofocus, or gaze-based communication software for motor-impaired patients (Slobodenyuk, 2016). Several studies have shown that expected reward affects where people look (Bucker, Silvis, Donk, & Theeuwes, 2015;Hickey & van Zoest, 2012;Schütz, Trommershäuser, & Gegenfurtner, 2012;Theeuwes & Belopolsky, 2012) as well as how quickly they do so (Dunne, Ellison, & Smith, 2015;Lauwereyns, Watanabe, Coe, & Hikosaka, 2002;Milstein & Dorris, 2007;Rothkirch, Ostendorf, Sax, & Sterzer, 2013;Watanabe, Lauwereyns, & Hikosaka, 2003). Hence, reward can serve as a goal that determines oculomotor actions. ...
Gaze control is an important component of social communication, e.g. to direct someone’s attention. While previous research on gaze interaction has mainly focused on the gaze recipient by asking how humans respond to perceived gaze (gaze cueing), we address the actor’s point of view by asking how actors control their own eye movements to trigger a gaze response in others. Specifically, we investigate whether gaze responses of a (virtual) interaction partner are anticipated and thereby affect oculomotor control. Building on a pre-established paradigm for addressing anticipation-based motor control in non-social contexts, participants were instructed to alternately look at two faces on the screen, which consistently responded to the participant’s gaze with either direct or averted gaze. We tested whether this gaze response of the targeted face is already anticipated prior to the participant’s eye movement by displaying a task-irrelevant visual stimulus (prior to the execution of the target saccade), which was either congruent, incongruent, or unrelated to the subsequently perceived gaze. In addition to schematic and photographic faces, we included conditions involving changes in non-social objects. Overall, we observed congruency effects (as an indicator of anticipation of the virtual other’s gaze response to one’s own gaze) for both social and non-social stimuli, but only when the perceived changes were sufficiently salient. Temporal dynamics of the congruency effects were comparable for social and non-social stimuli, suggesting that similar mechanisms underlie anticipation-based oculomotor control. The results support recent theoretical claims emphasizing the role of anticipation-based action control in social interaction.
... The results show that previously rewarded stimulus -even when the stimulus is non-salient -captures attention and interferes for search for the target. These results are well established both in covert [37][38][39][40] and overt search [41,42]. ...
... Most of these studies however have compared rewarded to unrewarded behavior and did not include different levels of reward. When rewards of different magnitudes can be obtained, saccade endpoints are closer to high than to low reward targets 36 and maximize gain 33 , the microsaccade rate scales with value 37 and saccade vigor decreases with advanced discounting of rewards 16,38 . Here, looking at saccade latencies without interleaved choices (Experiment 1 & 3), we found no significant evidence for a direct influence of value in two out of three conditions. ...
When humans have to choose between different options, they can maximize their payoff by choosing the option that yields the highest reward. Information about reward is not only used to optimize decisions but also for movement preparation to minimize reaction times to rewarded targets. Here, we show that this is especially true in contexts in which participants additionally have to choose between different options. We probed eye movement preparation by measuring saccade latencies to differently rewarded single targets (single-trial) appearing left or right from fixation. In choice-trials, both targets were displayed and participants were free to decide for one target to receive the corresponding reward. In blocks without choice-trials, single-trial latencies were not or only weakly affected by reward. With choice-trials present, the influence of reward increased with the proportion and difficulty of choices and decreased when a cue indicated that no choice will be necessary. Choices caused a delay in subsequent single-trial responses to the non-chosen option. Taken together, our results suggest that reward affects saccade preparation mainly when the outcome is uncertain and depends on the participants’ behavior, for instance when they have to choose between targets differing in reward.
... Thus, when reward is congruent with the current task demands, the reward outcome that is associated with a stimulus can increase its attentional priority to improve behavioural performance. In addition, several studies have shown that stimuli that have been associated with a high, compared to low, reward receive attentional priority even if they become completely task-irrelevant and rewards are no longer delivered (e.g., Anderson, Laurent, & Yantis, 2011a, 2011bBucker, Silvis, Donk, & Theeuwes, 2015;Della Libera & Chelazzi, 2006Failing & Theeuwes, 2014;MacLean, Diaz, & Giesbrecht, 2016;Moher, Anderson, & Song, 2015;Pool, Brosch, Delplanque, & Sander, 2014;Roper, Vecera, & Vaidya, 2014;. Typically, these studies make use of a training-test phase design, such that certain target stimulus features are coupled to the delivery of high and low reward in the training phase, while that same stimulus features are presented as distractors in the following test phase during which rewards are no longer delivered. ...
It has been shown that pure Pavlovian associative reward learning can elicit value-driven attentional capture. However, in previous studies, task-irrelevant and response-independent reward-signalling stimuli hardly competed for visual selective attention. Here we put Pavlovian reward learning to the test by manipulating the extent to which bottom-up (Experiment 1) and top-down (Experiment 2) processes were involved in this type of learning. In Experiment 1, the stimulus, the colour of which signalled the magnitude of the reward given, was presented simultaneously with another randomly coloured stimulus, so that it did not capture attention in a stimulus-driven manner. In Experiment 2, observers performed an attentionally demanding RSVP-task at the centre of the screen to largely tax goal-driven attentional resources, while a task-irrelevant and response-independent stimulus in the periphery signalled the magnitude of the reward given. Both experiments showed value-driven attentional capture in a non-reward test phase, indicating that the reward-signalling stimuli were imbued with value during the Pavlovian reward conditioning phases. This suggests that pure Pavlovian reward conditioning can occur even when (1) competition prevents attention being automatically allocated to the reward-signalling stimulus in a stimulus-driven manner, and (2) attention is occupied by a demanding task, leaving little goal-driven attentional resources available to strategically select the reward-signalling stimulus. The observed value-driven attentional capture effects appeared to be similar for observers who could and could not explicitly report the stimulus–reward contingencies. Altogether, this study provides insight in the conditions under which mere stimulus–reward contingencies in the environment can be learned to affect future behaviour.
... In line with the selection history component described in the model of Awh et al. (2012), behavioral research has shown attentional orienting to the location of a non-salient cue that had acquired value through reward learning (Failing & Theeuwes, 2014). Similarly, eye movements have been observed to land closer to high compared to low reward-signaling distractors (Bucker, Silvis, Donk, & Theeuwes, 2015;McCoy & Theeuwes, 2016). It has recently been suggested that reward learning of particular locations relies upon spatial priority maps, specifically when multiple potential targets compete for attention . ...
Recent research on the impact of location-based reward on attentional orienting has indicated that reward factors play an influential role in spatial priority maps. The current study investigated whether and how reward associations based on spatial location translate from overt eye movements to covert attention. If reward associations can be tied to locations in space, and if overt and covert attention rely on similar overlapping neuronal populations, then both overt and covert attentional measures should display similar spatial-based reward learning. Our results suggest that location- and reward-based changes in one attentional domain do not lead to similar changes in the other. Specifically, although we found similar improvements at differentially rewarded locations during overt attentional learning, this translated to the least improvement at a highly rewarded location during covert attention. We interpret this as the result of an increased motivational link between the high reward location and the trained eye movement response acquired during learning, leading to a relative slowing during covert attention when the eyes remained fixated and the saccade response was suppressed. In a second experiment participants were not required to keep fixated during the covert attention task and we no longer observed relative slowing at the high reward location. Furthermore, the second experiment revealed no covert spatial priority of rewarded locations. We conclude that the transfer of location-based reward associations is intimately linked with the reward-modulated motor response employed during learning, and alternative attentional and task contexts may interfere with learned spatial priorities.
... In the test phase, however, the reward signal becomes detrimental to the task demands: not only is reward no longer available, but the previously rewarded stimulus is also rendered a distractor that competes with a new target for selection. This approach is now welldocumented in the literature on covert (Anderson, Laurent, & Yantis, 2011;Della Libera & Chelazzi, 2006Failing & Theeuwes, 2014;Hickey, Chelazzi, & Theeuwes, 2010) as well as overt visual search Bucker, Silvis, Donk, & Theeuwes, 2015;. The vast majority of these studies converge onto similar findings: selection benefits for rewardassociated stimuli during a training phase turn into behavioral costs (i.e., interference in search time) when these stimuli subsequently compete with a new target for selection, even if they are explicitly no longer predictive of reward. ...
Previous research has shown that attentional selection is affected by reward contingencies: previously selected and rewarded stimuli continue to capture attention even if the reward contingencies are no longer in place. In the current study, we investigated whether attentional selection also is affected by stimuli that merely signal the magnitude of reward available on a given trial but, crucially, have never had instrumental value. In a series of experiments, we show that a stimulus signaling high reward availability captures attention even when that stimulus is and was never physically salient or part of the task set, and selecting it is harmful for obtaining reward. Our results suggest that irrelevant reward-signaling stimuli capture attention, because participants have learned about the relationship between the stimulus and reward. Importantly, we only observed learning after initial attentional prioritization of the reward signaling stimulus. We conclude that nonsalient, task-irrelevant but reward-signaling stimuli can affect attentional selection above and beyond top-down or bottom-up attentional control, however, only after such stimuli were initially prioritized for selection.
Electronic supplementary material
The online version of this article (doi:10.3758/s13414-017-1376-8) contains supplementary material, which is available to authorized users.
... The effects of rewards often linger after rewards are no longer available [33] and this effect can be spatially localized with high precision [34]. In the present study, after the penalty condition was removed, participants accelerated the saccades towards targets near the penalty sector about as abruptly as they had decelerated them at the onset of the penalty phase ( Fig 3A). ...
People use eye movements extremely effectively to find objects of interest in a cluttered visual scene. Distracting, task-irrelevant attention capturing regions in the visual field should be avoided as they jeopardize the efficiency of search. In the current study, we used eye tracking to determine whether people are able to avoid making saccades to a predetermined visual area associated with a financial penalty, while making fast and accurate saccades towards stimuli placed near the penalty area. We found that in comparison to the same task without a penalty area, the introduction of a penalty area immediately affected eye movement behaviour: the proportion of saccades to the penalty area was immediately reduced. Also, saccadic latencies increased, but quite modestly, and mainly for saccades towards stimuli near the penalty area. We conclude that eye movement behaviour is under efficient cognitive control and thus quite flexible: it can immediately be adapted to changing environmental conditions to improve reward outcome.
... In addition, several studies have shown that reward associated stimuli are prioritized, even when reward features become completely task-irrelevant in a context where the actual rewards are no longer delivered (e.g., Anderson et al. 2011aAnderson et al. , 2011bBucker, Silvis, Donk, & Theeuwes, 2015;Della Libera & Chelazzi, 2006;2009;Failing & Theeuwes, 2014;MacLean, Diaz, & Giesbrecht, 2016). Typically, these studies make use of (1) an initial training phase in which target features are associated with high and low reward-value, and (2) a test phase in which the previously reward signaling target features become distractor features and rewards are no longer delivered. ...
Recent evidence shows that distractors that signal high compared to low reward availability elicit stronger attentional capture, even when this is detrimental for task-performance. This suggests that simply correlating stimuli with reward administration, rather than their instrumental relationship with obtaining reward, produces value-driven attentional capture. However, in previous studies, reward delivery was never response independent, as only correct responses were rewarded, nor was it completely task-irrelevant, as the distractor signaled the magnitude of reward that could be earned on that trial. In two experiments, we ensured that associative reward learning was completely response independent by letting participants perform a task at fixation, while high and low rewards were automatically administered following the presentation of task-irrelevant colored stimuli in the periphery (Experiment 1) or at fixation (Experiment 2). In a following non-reward test phase, using the additional singleton paradigm, the previously reward signaling stimuli were presented as distractors to assess truly task-irrelevant value driven attentional capture. The results showed that high compared to low reward-value associated distractors impaired performance, and thus captured attention more strongly. This suggests that genuine Pavlovian conditioning of stimulus-reward contingencies is sufficient to obtain value-driven attentional capture. Furthermore, value-driven attentional capture can occur following associative reward learning of temporally and spatially task-irrelevant distractors that signal the magnitude of available reward (Experiment 1), and is independent of training spatial shifts of attention towards the reward signaling stimuli (Experiment 2). This confirms and strengthens the idea that Pavlovian reward learning underlies value driven attentional capture.
... Stimuli associated with high reward have been shown to receive attentional priority over equally salient competing stimuli associated with low or no reward (e.g., Bucker, Silvis, Donk, &Theeuwes, 2015;Failing & Theeuwes, 2014;Kiss, Driver, & Eimer, 2009;Krebs, Boehler, Egner, & Woldorff, 2011;Stankevich & Geng, 2015), disregarding an exogenously driven bias based on the physical salience of the stimuli. Furthermore, distractors associated with high reward have been shown to capture attention to a greater extent than distracters associated with low or no reward when observers are searching for targets in a goal-directed manner (e.g., Anderson, Laurent, & Yantis, 2011a, b;Bucker, Belopolsky, & Theeuwes, 2015;Bucker & Theeuwes, 2016;Failing, Nissens, Pearson, Le Pelley, & Theeuwes, 2015;Lee & Shomstein, 2013;Le Pelley, Pearson, Griffiths, & Beesley, 2015). ...
In two experiments, we utilized an exogenous cueing task in which different-colored abrupt-onset cues were associated with an appetitive (gain of 10 cents), aversive (loss of 5 cents), or neutral (no gain or loss) outcome. Reward delivery did not depend on performance, but instead the specific exogenous cues were always followed by their corresponding outcome in a classical-conditioning-like manner. Compared to neutral cues and independent of cue-target delay, the results of Experiment 1 showed that appetitive cues strengthened attentional capture, whereas aversive cues reduced attentional capture. The data revealed that both appetitive and aversive cues initially facilitated responding at the validly cued location. At the long cue-target delays, however, this facilitation effect at the validly cued location remained present for gain-associated cues while it reversed for loss-associated cues. The results of Experiment 2 confirmed these findings by showing that both neutral and aversive cues initially facilitated responding at the cued location and that, at long cue-target delays, aversive cues elicited stronger reorienting away from the cued location as compared to neutral cues. Together these findings indicate that all abrupt-onset cues initially capture attention independent of their outcome association. Yet, if time passes, attention remains lingering at the location of gain-associated cues, whereas attention is released and reoriented away from the location of loss-associated cues. Altogether, we show that associating the color of an abrupt-onset cue with an appetitive or aversive outcome can modulate attentional deployment following exogenous cueing.
... Furthermore, even when the stimulus no longer predicted reward, the learned value of the reward increased exogenous capture of the eyes above and beyond that driven by salience alone. Similarly, Bucker et al. (2015) observed that objects previously associated with a higher reward attracted the eyes in a stronger fashion than those associated with low or no monetary rewards. When rewards were no longer delivered, the bias found to higher-reward targets persisted. ...
The eye movement system is sensitive to reward. However, whilst the eye movement system is extremely flexible, the extent to which changes to oculomotor behavior induced by reward paradigms persist beyond the training period or transfer to other oculomotor tasks is unclear. To address these issues we examined the effects of presenting feedback that represented small monetary rewards to spatial locations on the latency of saccadic eye movements, the time-course of learning and extinction of the effects of rewarding saccades on exogenous spatial attention and oculomotor inhibition of return. Reward feedback produced a relative facilitation of saccadic latency in a stimulus driven saccade task which persisted for three blocks of extinction trials. However, this hemifield-specific effect failed to transfer to peripheral cueing tasks. We conclude that rewarding specific spatial locations is unlikely to induce long-term, systemic changes to the human oculomotor or attention systems.
The last ten years of attention research have witnessed a revolution, replacing a theoretical dichotomy (top-down vs. bottom-up control) with a trichotomy (biased by current goals, physical salience, and selection history). This third new mechanism of attentional control, selection history, is multifaceted. Some aspects of selection history must be learned over time whereas others reflect much more transient influences. A variety of different learning experiences can shape the attention system, including reward, aversive outcomes, past experience searching for a target, target‒non-target relations, and more. In this review, we provide an overview of the historical forces that led to the proposal of selection history as a distinct mechanism of attentional control. We then propose a formal definition of selection history, with concrete criteria, and identify different components of experience-driven attention that fit within this definition. The bulk of the review is devoted to exploring how these different components relate to one another. We conclude by proposing an integrative account of selection history centered on underlying themes that emerge from our review.
Preview benefit refers to faster search for a target when a subset of distractors is seen prior to the search display. We investigated whether reward modulates this effect. Participants identified a target among non-targets on each trial. On “preview” trials, placeholders occupied half the search array positions prior to the onset of the full array. On “non-preview” trials, no placeholders preceded the full search array. On preview trials, the target could appear at either a placeholder position (old-target-location condition) or a position where no placeholder had been (new-target-location condition). Critically, the colour of the stimulus array indicated whether participants would earn reward for a correct response. We found a typical preview benefit, but no evidence that reward modulated this effect, despite a manipulation check showing that stimuli in the reward-signaling colour tended to capture attention on catch trials. The results suggest that reward learning does not modulate the preview benefit.
The traditional distinction between exogenous and endogenous attentional control has recently been enriched with an additional mode of control, termed as reward history. Recent findings have indicated that previously rewarded stimuli capture more attention than their physical attributes would predict. However, an important question is whether reward-based learning (or value-driven) attentional control is fully automatic or driven by strategic, top-down control? Most researchers suggest value-driven attentional control is fully automatic, not driven by strategic, top-down control. Although previous studies have examined the phenomenon of value-driven attention capture, few studies have distinguished early attentional orienting and later attentional disengagement in the value-driven attentional control process. Therefore, the present study employed a modified spatial cueing paradigm to disentangle attentional orienting and disengagement and manipulated the goal-relevance of reward distractors to investigate the characteristics of value-driven attentional control. In Experiment 1, rewarded distractors were goal-relevant, and we would expect the prioritized orienting to and the delayed disengagement from rewarded distractors (compared with no-reward distractors) to be evident when both were goal-relevant (i.e., part of the target-set); In Experiment 2, rewarded distractors were not goal-relevant, and we would expect prioritized orienting to and delayed disengagement from rewarded distractors (compared with no-reward distractors) not to be evident when both were not goal-relevant.
Forty-eight participants (Experiment 1: 24; Experiment 2: 24) with normal or corrected-to-normal vision were tested. During the training phase, the four positions in the search display were all circles of different colors (such as red, green, blue, cyan, orange, and yellow). Targets were defined as a red or a green circle, exactly one of which was presented on every trial. Inside the target, a white line segment was oriented either vertically or horizontally, and inside each of the nontargets, a white line segment was tilted at 45° to the left or to the right. The feedback display informed participants of the reward earned (+10, +0) on the previous trial, as well as total reward accumulated thus far according to their responses. During the test phase, each trial started with the presentation of the fixation display (900 ms), which was followed immediately by the cue display (100 ms). After the cue display, the fixation display was presented again (100 ms), followed by the target display (100 ms). The target display was followed by a gray screen (until response). The feedback display at test informed participants only whether their response on the previous trial was correct. That is, no reward was provided during the test phase.
Results showed that: (1) Across Experiments 1 and 2, we observed the significant main effects of reward. ( 2) In the test phase in Experiment 1, rewarded distractors were goal-relevant and we observed prioritized orienting to and delayed disengagement from rewarded distractors (compared with no-reward distractors) be evident; in Experiment 2, rewarded distractors were not goal-relevant, and we observed prioritized orienting to and delayed disengagement from rewarded distractors (compared with no-reward distractors) not be evident.
The present findings demonstrate that: (1) In the training phase, participants have learned the effect of reward. (2) In the test phase, orienting to and disengagement from rewarded stimuli are modulated by current top-down goals. These findings provide a new perspective on the domain of attention to rewarded stimuli by indicating that even the early orienting of attention to rewarded stimuli is contingent on current top-down goals, suggesting early orienting to rewarded stimuli to be more complex and cognitively involved than previously hypothesized.
Value-driven attentional capture refers to the automatic and involuntary guidance of attention to stimuli that are associated with value. Often this form of attentional selection is based on learned associations between a stimulus and a received (monetary) reward. The rationale is that associating a stimulus with a reward boosts its representation on an attentional priority map, biasing attention towards selection of this stimulus. The work presented here investigates how and to what extent value-signaling distractors capture attention when participants are provided with prior information concerning the target's location. In a series of experiments using a classic visual search paradigm, we provided the participants with a 100% valid cue concerning the target location. At the moment the target appeared at the cued location, a salient and reward-associated distractor appeared elsewhere in the display. The results show that under changing experimental conditions (such as the likelihood of obtaining reward), presenting participants with value-signaling distractors resulted in two distinct modes of value-driven capture, relying on different underlying attentional mechanisms. The first, indirect mechanism of attentional control refers to the observation that participants abandon the top-down set for target location in favor of reward-seeking behavior, leading to capture by all singleton stimuli that may represent value. The second, direct mechanism of value-driven attentional control concerns the observation that valued, but not non-valued distractors break through the focus of attention and capture attention, despite participants not engaging in reward-seeking behavior. In the current work we investigate the properties and experimental conditions leading to direct and indirect value-driven attentional guidance. Importantly, as classic saliency-driven attentional capture does not occur under focused attentional conditions, we conclude that rewarded stimuli appear to be more strongly manifested on a priority map leading to enhanced and distinctive means of attentional guidance.
Meeting abstract presented at VSS 2016
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 (learned predictiveness). 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 (learned value). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that uncertainty 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 learned predictiveness and learned value 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 goal-directed or stimulus-driven. Rather, it suggests a new kind of “derived” attention.
Motivational stimuli such as rewards elicit adaptive responses and influence various cognitive functions. Notably, increasing evidence suggests that stimuli with particular motivational values can strongly shape perception and attention. These effects resemble both selective top-down and stimulus-driven attentional orienting, as they depend on internal states but arise without conscious will, yet they seem to reflect attentional systems that are functionally and anatomically distinct from those classically associated with frontoparietal cortical networks in the brain. Recent research in human and nonhuman primates has begun to reveal how reward can bias attentional selection, and where within the cognitive system the signals providing at-tentional priority are generated. This review aims at describing the different mechanisms sustaining motivational attention, their impact on different behavioral tasks, and current knowledge concerning the neural networks governing the integration of motivational influences on attentional behavior.
Cognitive control covers a broad range of cognitive functions, but its research and theories typically remain tied to a single domain. Here we outline and review an associative learning perspective on cognitive control in which control emerges from associative networks containing perceptual, motor, and goal representations. Our review identifies 3 trending research themes that are shared between the domains of conflict adaptation, task switching, response inhibition, and attentional control: Cognitive control is context-specific, can operate in the absence of awareness, and is modulated by reward. As these research themes can be envisaged as key characteristics of learning, we propose that their joint emergence across domains is not coincidental but rather reflects a (latent) growth of interest in learning-based control. Associative learning has the potential for providing broad-scaled integration to cognitive control theory, and offers a promising avenue for understanding cognitive control as a self-regulating system without postulating an ill-defined set of homunculi. We discuss novel predictions, theoretical implications, and immediate challenges that accompany an associative learning perspective on cognitive control.
In the present study, we investigated the conditions in which rewarded distractors have the ability to capture attention, even when attention is directed toward the target location. Experiment 1 showed that when the probability of obtaining reward was high, all salient distractors captured attention, even when they were not associated with reward. This effect may have been caused by participants suboptimally using the 100%-valid endogenous location cue. Experiment 2 confirmed this result by showing that salient distractors did not capture attention in a block in which no reward was expected. In Experiment 3, the probability of the presence of a distractor was high, but it only signaled reward availability on a low number of trials. The results showed that those very infrequent distractors that signaled reward captured attention, whereas the distractors (both frequent and infrequent ones) not associated with reward were simply ignored. The latter experiment indicates that even when attention is directed to a location in space, stimuli associated with reward break through the focus of attention, but equally salient stimuli not associated with reward do not.
Participant's were required to make a saccade to a uniquely colored target while ignoring the presentation of an onset distractor. The results provide evidence for a competitive integration model of saccade programming that assumes endogenous and exogenous saccades are programmed in a common saccade map. The model incorporates a lateral interaction structure in which saccade-related activation at a specific location spreads to neighboring locations but inhibits distant locations. In addition, there is top-down, location-specific inhibition of locations to which the saccade should not go. The time course of exogenous and endogenous activation in the saccade map can explain a variety of eye movement data, including endpoints, latencies, and trajectories of saccades and the well-known global effect.
In certain situations, the endpoint of an eye movement is not positioned on the centre of a target element, but deviates in the direction of another element. This phenomenon has been termed 'the global effect' and has proven to constitute a valuable measure of various processes that control and influence our oculomotor behavior. The goal of the current review is to provide insight in the factors that determine where the eyes land. We will focus on the fundamental characteristics of the global effect and discuss the various domains in which the global effect has been applied. The global effect appears to be best explained in terms of a weighted average of activity in a saccade map.
Salient stimuli and stimuli associated with reward have the ability to attract both
attention and the eyes. The current study exploited the effects of reward on the wellknown
global effect in which two objects appear simultaneously in close spatial
proximity. Participants always made saccades to a predefined target, while the colour of
a nearby distractor signalled the reward available (high/low) for that trial. Unlike
previous reward studies, in the current study these distractors never served as targets. We
show that participants made fast saccades towards the target. However, saccades landed
significantly closer to the high compared to the low reward signalling distractor. This
reward effect was already present in the first block and remained stable throughout the
experiment. Instead of landing exactly in between the two stimuli (i.e., the classic global
effect), the fastest eye movements landed closer towards the reward signalling distractor.
Results of a control experiment, in which no distractor-reward contingencies were
present, confirmed that the observed effects were driven by reward and not by physical
salience. Furthermore, there were trial-by-trial reward priming effects in which saccades
landed significantly closer to the high instead of the low reward signalling distractor
when the same distractor was presented on two consecutive trials. Together the results
imply that a reward signalling stimulus that was never part of the task set has an
automatic effect on the oculomotor system.
Classic spatial cueing experiments have demonstrated that salient cues have the ability to summon attention as evidenced by performance benefits when the cue validly indicates the target location and costs when the cue is invalid. Here we show that nonsalient cues that are associated with reward also have the ability to capture attention. We demonstrate performance costs and benefits in attentional orienting towards a nonsalient cue that acquired value through reward learning. The present study provides direct evidence that stimuli associated with reward have the ability to exogenously capture spatial attention independent of task-set, goals and salience.
It is thought that reward-induced motivation influences perceptual, attentional, and cognitive control processes to facilitate behavioral performance. In this study, we investigated the effect of reward-induced motivation on exogenous attention orienting and inhibition of return (IOR). Attention was captured by peripheral onset cues that were nonpredictive for the target location. Participants performed a target discrimination task at short (170 ms) and long (960 ms) cue-target stimulus onset asynchronies. Reward-induced motivation was manipulated by exposing participants to low- and high-reward blocks. Typical cue facilitation effects on initial orienting were observed for both the low- and high-reward conditions. However, IOR was found only for the high-reward condition. This indicates that reward-induced motivation has a clear effect on reorienting and inhibitory processes following the initial capture of attention, but not on initial exogenous orienting that is considered to be exclusively automatic and stimulus-driven. We suggest that initial orienting is completely data-driven, not affected by top-down motivational processes, while reorienting and the accompanying IOR effect involve motivational top-down processes. To support this, we showed that reward-induced motivational processes and top-down control processes co-act in order to improve behavioral performance: High-reward-induced motivation caused an increase in top-down cognitive control, as signified by posterror slowing. Moreover, we show that personality trait propensity to reward-driven behavior (BAS-Drive scale) was related to reward-triggered behavioral changes in top-down reorienting, but not to changes in automatic orienting.
Investigating eye movements has been a promising approach to uncover the role of visual working memory in early attentional processes. Prior research has already demonstrated that eye movements in search tasks are more easily drawn toward stimuli that show similarities to working memory content, as compared with neutral stimuli. Previous saccade tasks, however, have always required a selection process, thereby automatically recruiting working memory. The present study was an attempt to confirm the role of working memory in oculomotor selection in an unbiased saccade task that rendered memory mechanisms irrelevant. Participants executed a saccade in a display with two elements, without any instruction to aim for one particular element. The results show that when two objects appear simultaneously, a working memory match attracts the first saccade more profoundly than do mismatch objects, an effect that was present throughout the saccade latency distribution. These findings demonstrate that memory plays a fundamental biasing role in the earliest competitive processes in the selection of visual objects, even when working memory is not recruited during selection.
Visual selective attention is the brain function that modulates ongoing processing of retinal input in order for selected representations to gain privileged access to perceptual awareness and guide behavior. Enhanced analysis of currently relevant or otherwise salient information is often accompanied by suppressed processing of the less relevant or salient input. Recent findings indicate that rewards exert a powerful influence on the deployment of visual selective attention. Such influence takes different forms depending on the specific protocol adopted in the given study. In some cases, the prospect of earning a larger reward in relation to a specific stimulus or location biases attention accordingly in order to maximize overall gain. This is mediated by an effect of reward acting as a type of incentive motivation for the strategic control of attention. In contrast, reward delivery can directly alter the processing of specific stimuli by increasing their attentional priority, and this can be measured even when rewards are no longer involved, reflecting a form of reward-mediated attentional learning. As a further development, recent work demonstrates that rewards can affect attentional learning in dissociable ways depending on whether rewards are perceived as feedback on performance or instead are registered as random-like events occurring during task performance. Specifically, it appears that visual selective attention is shaped by two distinct reward-related learning mechanisms: one requiring active monitoring of performance and outcome, and a second one detecting the sheer association between objects in the environment (whether attended or ignored) and the more-or-less rewarding events that accompany them. Overall this emerging literature demonstrates unequivocally that rewards "teach" visual selective attention so that processing resources will be allocated to objects, features and locations which are likely to optimize the organism's interaction with the surrounding environment and maximize positive outcome.
Stimuli that have previously been associated with the delivery of reward involuntarily capture attention when presented as unrewarded and task-irrelevant distractors in a subsequent visual search task. It is unknown how long such effects of reward learning on attention persist. One possibility is that value-driven attentional biases are plastic and constantly evolve to reflect only recent reward history. According to such a mechanism of attentional control, only consistently reinforced patterns of attention allocation persist for extended periods of time. Another possibility is that reward learning creates enduring changes in attentional priority that can persist indefinitely without further learning. Here we provide evidence for an enduring effect of reward learning on attentional priority: stimuli previously associated with reward in a training phase capture attention when presented as irrelevant distractors over half a year later, without the need for further reward learning. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
Our gaze tends to be directed to objects previously associated with rewards. Such object values change flexibly or remain stable. Here we present evidence that the monkey substantia nigra pars reticulata (SNr) in the basal ganglia represents stable, rather than flexible, object values. After across-day learning of object-reward association, SNr neurons gradually showed a response bias to surprisingly many visual objects: inhibition to high-valued objects and excitation to low-valued objects. Many of these neurons were shown to project to the ipsilateral superior colliculus. This neuronal bias remained intact even after >100 d without further learning. In parallel with the neuronal bias, the monkeys tended to look at high-valued objects. The neuronal and behavioral biases were present even if no value was associated during testing. These results suggest that SNr neurons bias the gaze toward objects that were consistently associated with high values in one's history.
Argues that automaticity and skill are closely related but are not identical. Automatic processes are components of skill, but skill is more than the sum of the automatic components. Automaticity and skill are similar in that both are learned through practice. Implications are discussed for (1) current studies of the co-occurrence of properties of automaticity, (2) the relation between multiple resources and automaticity, and (3) the relation between control and automaticity. It is concluded that many of the issues in automaticity may be resolved or at least revised by considering the role that automatic processes play in performing a skill. (French abstract) (3 p ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Covert shifts of attention precede and direct overt eye movements to stimuli that are task relevant or physically salient. A growing body of evidence suggests that the learned value of perceptual stimuli strongly influences their attentional priority. For example, previously rewarded but otherwise irrelevant and inconspicuous stimuli capture covert attention involuntarily. It is unknown, however, whether stimuli also draw eye movements involuntarily as a consequence of their reward history. Here, we show that previously rewarded but currently task-irrelevant stimuli capture both attention and the eyes. Value-driven oculomotor capture was observed during unconstrained viewing, when neither eye movements nor fixations were required, and was strongly related to individual differences in visual working memory capacity. The appearance of a reward-associated stimulus came to evoke pupil dilation over the course of training, which provides physiological evidence that the stimuli that elicit value-driven capture come to serve as reward-predictive cues. These findings reveal a close coupling of value-driven attentional capture and eye movements that has broad implications for theories of attention and reward learning.
Three visual-search experiments tested whether the preattentive parallel stage can-selectively guide the attentive stage to
a particular known-to-be-relevant target feature. Subjects searched multielement displays for a salient green circle that
had a unique form when surrounded by green nontarget squares or had a unique color when surrounded by red nontarget circles.
In the distractor conditions, a salient item in the other dimension was present as well. As an extension of earlier findings
(Theeuwes, 1991), the results showed that complete top-down selectivity toward a particular feature was not possible, not
even after extended and consistent practice. The results reveal that selectivity depends on the relative discriminability
of the stimulus dimensions: the presence of an irrelevant item with a unique color interferes with parallel search for a unique
form, and vice versa.
Visual attention is captured by physically salient stimuli (termed salience-based attentional capture), and by otherwise task-irrelevant stimuli that contain goal-related features (termed contingent attentional capture). Recently, we reported that physically nonsalient stimuli associated with value through reward learning also capture attention involuntarily (Anderson, Laurent, & Yantis, PNAS, 2011). Although it is known that physical salience and goal-relatedness both influence attentional priority, it is unknown whether or how attentional capture by a salient stimulus is modulated by its associated value. Here we show that a physically salient, task-irrelevant distractor previously associated with a large reward slows visual search more than an equally salient distractor previously associated with a smaller reward. This magnification of salience-based attentional capture by learned value extinguishes over several hundred trials. These findings reveal a broad influence of learned value on involuntary attentional capture.
Attention selects which aspects of sensory input are brought to awareness. To promote survival and well-being, attention prioritizes stimuli both voluntarily, according to context-specific goals (e.g., searching for car keys), and involuntarily, through attentional capture driven by physical salience (e.g., looking toward a sudden noise). Valuable stimuli strongly modulate voluntary attention allocation, but there is little evidence that high-value but contextually irrelevant stimuli capture attention as a consequence of reward learning. Here we show that visual search for a salient target is slowed by the presence of an inconspicuous, task-irrelevant item that was previously associated with monetary reward during a brief training session. Thus, arbitrary and otherwise neutral stimuli imbued with value via associative learning capture attention powerfully and persistently during extinction, independently of goals and salience. Vulnerability to such value-driven attentional capture covaries across individuals with working memory capacity and trait impulsivity. This unique form of attentional capture may provide a useful model for investigating failures of cognitive control in clinical syndromes in which value assigned to stimuli conflicts with behavioral goals (e.g., addiction, obesity).
Reward-related mesolimbic dopamine steers animal behavior, creating automatic approach toward reward-associated objects and avoidance of objects unlikely to be beneficial. Theories of dopamine suggest that this reflects underlying biases in perception and attention, with reward enhancing the representation of reward-associated stimuli such that attention is more likely to be deployed to the location of these objects. Using measures of behavior and brain electricity in male and female humans, we demonstrate this to be the case. Sensory and perceptual processing of reward-associated visual features is facilitated such that attention is deployed to objects characterized by these features in subsequent experimental trials. This is the case even when participants know that a strategic decision to attend to reward-associated features will be counterproductive and result in suboptimal performance. Other results show that the magnitude of visual bias created by reward is predicted by the response to reward feedback in anterior cingulate cortex, an area with strong connections to dopaminergic structures in the midbrain. These results demonstrate that reward has an impact on vision that is independent of its role in the strategic establishment of endogenous attention. We suggest that reward acts to change visual salience and thus plays an important and undervalued role in attentional control.
While numerous studies have explored the mechanisms of reward-based decisions (the choice of action based on expected gain), few have asked how reward influences attention (the selection of information relevant for a decision). Here we show that a powerful determinant of attentional priority is the association between a stimulus and an appetitive reward. A peripheral cue heralded the delivery of reward or no reward (these cues are termed herein RC+ and RC-, respectively); to experience the predicted outcome, monkeys made a saccade to a target that appeared unpredictably at the same or opposite location relative to the cue. Although the RC had no operant associations (did not specify the required saccade), they automatically biased attention, such that an RC+ attracted attention and an RC- repelled attention from its location. Neurons in the lateral intraparietal area (LIP) encoded these attentional biases, maintaining sustained excitation at the location of an RC+ and inhibition at the location of an RC-. Contrary to the hypothesis that LIP encodes action value, neurons did not encode the expected reward of the saccade. Moreover, at odds with an adaptive decision process, the cue-evoked biases interfered with the required saccade, and these biases increased rather than abating with training. After prolonged training, valence selectivity appeared at shorter latencies and automatically transferred to a novel task context, suggesting that training produced visual plasticity. The results suggest that reward predictors gain automatic attentional priority regardless of their operant associations, and this valence-specific priority is encoded in LIP independently of the expected reward of an action.
Efficient goal-directed behavior in a crowded world is crucially mediated by visual selective attention (VSA), which regulates deployment of cognitive resources toward selected, behaviorally relevant visual objects. Acting as a filter on perceptual representations, VSA allows preferential processing of relevant objects and concurrently inhibits traces of irrelevant items, thus preventing harmful distraction. Recent evidence showed that monetary rewards for performance on VSA tasks strongly affect immediately subsequent deployment of attention; a typical aftereffect of VSA (negative priming) was found only following highly rewarded selections. Here we report a much more striking demonstration that the controlled delivery of monetary rewards also affects attentional processing several days later. Thus, the propensity to select or to ignore specific visual objects appears to be strongly biased by the more or less rewarding consequences of past attentional encounters with the same objects.
Three visual-search experiments tested whether the preattentive parallel stage can selectively guide the attentive stage to a particular known-to-be-relevant target feature. Subjects searched multielement displays for a salient green circle that had a unique form when surrounded by green nontarget squares or had a unique color when surrounded by red nontarget circles. In the distractor conditions, a salient item in the other dimension was present as well. As an extension of earlier findings (Theeuwes, 1991), the results showed that complete top-down selectivity toward a particular feature was not possible, not even after extended and consistent practice. The results reveal that selectivity depends on the relative discriminability of the stimulus dimensions: the presence of an irrelevant item with a unique color interferes with parallel search for a unique form, and vice versa.
Three visual search experiments tested whether top-down selectivity toward particular stimulus dimensions is possible during preattentive parallel search. Subjects viewed multielement displays in which two salient items, each unique in a different dimension--that is, color and intensity (Experiment 1) or color and form (Experiments 2 and 3)--were simultaneously present. One of the dimensions defined the target; the other dimension served as distractor. The results indicate that when search is performed in parallel, top-down selectivity is not possible. These findings suggest that preattentive parallel search is strongly automatic, because it satisfies both the load-insensitivity and the unintentionality criteria of automaticity.
The length of initial voluntary saccades to a target were measured in three experiments. It was found that saccade length varied as a function of the number, locus and distance of non-target stimuli present in the visual field. Eye movements tended to be directed toward the “center of gravity” of the stimuli close to the target. These systematic changes seem to be independent of task requirements for acuity. Some implications are discussed.
Bartlett viewed thinking as a high level skill exhibiting ballistic properties that he called its “point of no return”. This paper explores one aspect of cognition through the use of a simple model task in which human subjects are asked to commit attention to a position in visual space other than fixation. This instruction is executed by orienting a covert (attentional) mechanism that seems sufficiently time locked to external events that its trajectory can be traced across the visual field in terms of momentary changes in the efficiency of detecting stimuli. A comparison of results obtained with alert monkeys, brain injured and normal human subjects shows the relationship of this covert system to saccadic eye movements and to various brain systems controlling perception and motion. In accordance with Bartlett's insight, the possibility is explored that similar principles apply to orienting of attention toward sensory input and orienting to the semantic structures used in thinking.
Participants were required to make a saccade to a uniquely colored target while ignoring the presentation of an onset distractor. The results provide evidence for a competitive integration model of saccade programming that assumes endogenous and exogenous saccades are programmed in a common saccade map. The model incorporates a lateral interaction structure in which saccade-related activation at a specific location spreads to neighboring locations but inhibits distant locations. In addition, there is top-down, location-specific inhibition of locations to which the saccade should not go. The time course of exogenous and endogenous activation in the saccade map can explain a variety of eye movement data, including endpoints, latencies, and trajectories of saccades and the well-known global effect.
When saccadic eye movements are made in a search task that requires selecting a target from distractors, the movements show greater curvature in their trajectories than similar saccades made to single stimuli. To test the hypothesis that this increase in curvature arises from competitive interactions between saccade goals occurring near the time of movement onset, we performed single-unit recording and microstimulation experiments in the superior colliculus (SC). We found that saccades that ended near the target but curved toward a distractor were accompanied by increased presaccadic activity of SC neurons coding the distractor site. This increased activity occurred approximately 30 ms before saccade onset and was abruptly quenched on saccade initiation. The magnitude of increased activity at the distractor site was correlated with the amount of curvature toward the distractor. In contrast, neurons coding the target location did not show any significant difference in discharge for curved versus straight saccades. To determine whether this pattern of SC discharge is causally related to saccade curvature, we performed a second series of experiments using electrical microstimulation. Monkeys made saccades to single visual stimuli presented without distractors, and we stimulated sites in the SC that would have corresponded to distractor sites in the search task. The stimulation was subthreshold for evoking saccades, but when its temporal structure mimicked the activity recorded for curved saccades in search, the subsequent saccades to the visual target showed curvature toward the location coded by the stimulation site. The effect was larger for higher stimulation frequencies and when the stimulation site was in the same colliculus as the representation of the visual target. These results support the hypothesis that the increased saccade curvature observed in search arises from rivalry between target and distractor goals and are consistent with the idea that the SC is involved in the competitive neural interactions underlying saccade target selection.
Four experiments were conducted to investigate the role of stimulus-driven control in saccadic eye movements. Participants were required to make a speeded saccade toward a predefined target presented concurrently with multiple nontargets and possibly 1 distractor. Target and distractor were either equally salient (Experiments 1 and 2) or not (Experiments 3 and 4). The results uniformly demonstrated that fast eye movements were completely stimulus driven, whereas slower eye movements were goal driven. These results are in line with neither a bottom-up account nor a top-down notion of visual selection. Instead, they indicate that visual selection is the outcome of 2 independent processes, one stimulus driven and the other goal driven, operating in different time windows.
We investigated the saccade decision process by examining activity recorded in the frontal eye field (FEF) of monkeys performing 2 separate visual search experiments in which there were errors in saccade target choice. In the first experiment, the difficulty of a singleton search task was manipulated by varying the similarity between the target and distractors; errors were made more often when the distractors were similar to the target. On catch trials in which the target was absent the monkeys occasionally made false alarm errors by shifting gaze to one of the distractors. The second experiment was a popout color visual search task in which the target and distractor colors switched unpredictably across trials. Errors occurred most frequently on the first trial after the switch and less often on subsequent trials. In both experiments, FEF neurons selected the saccade goal on error trials, not the singleton target of the search array. Although saccades were made to the same stimulus locations, presaccadic activation and the magnitude of selection differed across trial conditions. The variation in presaccadic selective activity was accounted for by the variation in saccade probability across the stimulus-response conditions, but not by variations in saccade metrics. These results suggest that FEF serves as a saccade probability map derived from the combination of bottom-up and top-down influences. Peaks on this map represent the behavioral relevance of each item in the visual field rather than just reflecting saccade preparation. This map in FEF may correspond to the theoretical salience map of many models of attention and saccade target selection.
To evaluate the effect of an abstract motivational incentive on top-down mechanisms of visual spatial attention, 10 subjects engaged in a target detection task and responded to targets preceded by spatially valid (predictive), invalid (misleading) or neutral central cues under three different incentive conditions: win money (WIN), lose money (LOSE), and neutral (neither gain nor lose). Activation in the posterior cingulate cortex was correlated with visual spatial expectancy, defined as the degree to which the valid cue benefited performance as evidenced by faster reaction times compared to non-directional cues. Winning and losing money enhanced this relationship via overlapping but independent limbic mechanisms. In addition, activity in the inferior parietal lobule was correlated with disengagement (the degree to which invalid cues diminished performance). This relationship was also enhanced by monetary incentives. Finally, incentive enhanced the relationship of activation in the visual cortex to visual spatial expectancy and disengagement for both types of incentive (WIN and LOSE). These results show that abstract incentives enhance neural processing within the attention network in a process- and valence-selective manner. They also show that different cognitive and motivational mechanisms may produce a common effect upon unimodal cortices in order to enhance processing to serve the current behavioral goal.
Although both attention and motivation affect behavior, how these 2 systems interact is currently unknown. To address this question, 2 experiments were conducted in which participants performed a spatially cued forced-choice localization task under varying levels of motivation. Participants were asked to indicate the location of a peripherally cued target while ignoring a distracter. Motivation was manipulated by varying magnitude and valence (reward and punishment) of an incentive linked to task performance. Attention was manipulated via a peripheral cue, which correctly predicted the presence of a target stimulus on 70% of the trials. Taken together, our findings revealed that the signal detection measure, reflecting perceptual sensitivity, increased as a function of incentive value during both valid and invalid trials. In addition, trend analyses revealed a linear increase in detection sensitivity as a function of incentive magnitude for both reward and punishment conditions. Our results suggest that elevated motivation leads to improved efficiency in orienting and reorienting of exogenous spatial attention and that one mechanism by which attention and motivation interact involves the sharpening of attention during motivationally salient conditions.
In addition to their well-known role in skeletal movements, the basal ganglia control saccadic eye movements (saccades) by means of their connection to the superior colliculus (SC). The SC receives convergent inputs from cerebral cortical areas and the basal ganglia. To make a saccade to an object purposefully, appropriate signals must be selected out of the cortical inputs, in which the basal ganglia play a crucial role. This is done by the sustained inhibitory input from the substantia nigra pars reticulata (SNr) to the SC. This inhibition can be removed by another inhibition from the caudate nucleus (CD) to the SNr, which results in a disinhibition of the SC. The basal ganglia have another mechanism, involving the external segment of the globus pallidus and the subthalamic nucleus, with which the SNr-SC inhibition can further be enhanced. The sensorimotor signals carried by the basal ganglia neurons are strongly modulated depending on the behavioral context, which reflects working memory, expectation, and attention. Expectation of reward is a critical determinant in that the saccade that has been rewarded is facilitated subsequently. The interaction between cortical and dopaminergic inputs to CD neurons may underlie the behavioral adaptation toward purposeful saccades.
A spatial-temporal model of saccadic control is proposed which predicts saccadic responses to complex spatial and temporal target configurations and is close to underlying physiological structures. The model consists of an afferent preprcessing stage organized in parallel channels and a Spatial-Temporal Translator which evalutes the oculomotor error signal by determining the center of gravity of the visual input signals. It is demonstrated that spatial preprocessing forms an important part in oculomotor control.
The basal ganglia are equipped with inhibitory and disinhibitory mechanisms that enable a subject to choose valuable objects and actions. Notably, a value can be determined flexibly by recent experience or stably by prolonged experience. Recent studies have revealed that the head and tail of the caudate nucleus selectively and differentially process flexible and stable values of visual objects. These signals are sent to the superior colliculus through different parts of the substantia nigra so that the animal looks preferentially at high-valued objects, but in different manners. Thus, relying on short-term value memories, the caudate head circuit allows the subject's gaze to move expectantly to recently valued objects. Relying on long-term value memories, the caudate tail circuit allows the subject's gaze to move automatically to previously valued objects. The basal ganglia also contain an equivalent parallel mechanism for action values. Such flexible-stable parallel mechanisms for object and action values create a highly adaptable system for decision making.
When objects in a visual scene are positioned in close proximity, eye movements to these objects tend to land at an intermediate location between the objects (i.e. the global effect). This effect is most pronounced for short latency saccades and is therefore believed to be reflexive and dominantly controlled by bottom-up information. At longer latencies this effect can be modulated by top-down factors. The current study established the time course at which top-down information starts to have an influence on bottom-up averaging. In a standard global effect task two peripheral stimuli (a red and a green abrupt onset) were positioned within an angular distance of 20°. In the condition in which observers received no specific target instruction, the eyes landed in between the red and green element establishing the classic global effect. However, when observers were instructed to make a saccade to the red element during a whole block or when the target color varied from trial-to-trial (red or green), a clear effect of the target instruction on the accuracy of the landing position of the primary saccade was found. With increasing saccade latencies, the eyes landed closer to the instructed target. Crucially, however, this effect was even seen for the shortest saccade latencies (as early as 200 ms), suggesting that saccade averaging is affected early on by top-down processes.
Choosing valuable objects is critical for survival, but their values may change flexibly or remain stable. Therefore, animals should be able to update the object values flexibly by recent experiences and retain them stably by long-term experiences. However, it is unclear how the brain encodes the two conflicting forms of values and controls behavior accordingly. We found that distinct circuits of the primate caudate nucleus control behavior selectively in the flexible and stable value conditions. Single caudate neurons encoded the values of visual objects in a regionally distinct manner: flexible value coding in the caudate head and stable value coding in the caudate tail. Monkeys adapted in both conditions by looking at objects with higher values. Importantly, inactivation of each caudate subregion disrupted the high-low value discrimination selectively in the flexible or stable context. This parallel complementary mechanism enables animals to choose valuable objects in both flexible and stable conditions.
A goal-directed action aiming at an incentive outcome, if repeated, becomes a skill that may be initiated automatically. We now report that the tail of the caudate nucleus (CDt) may serve to control a visuomotor skill. Monkeys looked at many fractal objects, half of which were always associated with a large reward (high-valued objects) and the other half with a small reward (low-valued objects). After several daily sessions, they developed a gaze bias, looking at high-valued objects even when no reward was associated. CDt neurons developed a response bias, typically showing stronger responses to high-valued objects. In contrast, their responses showed no change when object values were reversed frequently, although monkeys showed a strong gaze bias, looking at high-valued objects in a goal-directed manner. The biased activity of CDt neurons may be transmitted to the oculomotor region so that animals can choose high-valued objects automatically based on stable reward experiences.
The capacity to predict future events permits a creature to detect, model, and manipulate the causal structure of its interactions
with its environment. Behavioral experiments suggest that learning is driven by changes in the expectations about future salient
events such as rewards and punishments. Physiological work has recently complemented these studies by identifying dopaminergic
neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient
and rewarding events. Taken together, these findings can be understood through quantitative theories of adaptive optimizing
control.
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.
Prominent models of attentional control assert a dichotomy between top-down and bottom-up control, with the former determined by current selection goals and the latter determined by physical salience. This theoretical dichotomy, however, fails to explain a growing number of cases in which neither current goals nor physical salience can account for strong selection biases. For example, equally salient stimuli associated with reward can capture attention, even when this contradicts current selection goals. Thus, although 'top-down' sources of bias are sometimes defined as those that are not due to physical salience, this conception conflates distinct--and sometimes contradictory--sources of selection bias. We describe an alternative framework, in which past selection history is integrated with current goals and physical salience to shape an integrated priority map.
Observers make rapid eye movements to examine the world around them. Before an eye movement is made, attention is covertly shifted to the location of the object of interest. The eyes typically will land at the position at which attention is directed. Here we report that a goal-directed eye movement toward a uniquely colored object is disrupted by the appearance of a new but task-irrelevant object, unless subjects have a sufficient amount of time to focus their attention on the location of the target prior to the appearance of the new object. In many instances, the eyes started moving toward the new object before gaze started to shift to the color-singleton target. The eyes often landed for a very short period of time time (25-150 ms) near the new object. The results suggest parallel programming of two saccades: one voluntary, goal-directed eye movement toward the color-singleton target and one stimulus-driven eye movement reflexively elicited by the appearance of the new object. Neuroanatomical structures responsible for parallel programming of saccades saccades are discussed.
When two elements are presented closely aligned, the average saccade endpoint will generally be located in between these two elements. This 'global effect' has been explained in terms of the center of gravity account which states that the saccade endpoint is based on the relative saliency of the different elements in the visual display. In the current study, we tested one of the implications of the center of gravity account: when two elements are presented closely aligned with the same size and the same distance from central fixation, the saccade should land on the intermediate location, irrespective of the stimulus size. To this end, two equally-sized elements were presented simultaneously and participants were required to execute an eye movement to the visual information presented on the display. Results showed that the strongest global effect was observed in the condition with smaller stimuli, whereas the saccade averaging was weaker when larger stimuli were presented. In a second experiment, in which only one element was presented, we observed that the width of the distribution of saccade endpoints is influenced by stimulus size in that the distribution is broader with smaller stimuli. We conclude that perfect saccade averaging is not always the default response by the oculomotor system. There appears to be a tendency to initiate an eye movement towards one of the visual elements, which becomes stronger with increasing stimulus size. This effect might be explained by an increased uncertainty in target localization for smaller stimuli, resulting in a higher probability of the merging of two stimulus representations into one representation.
The dip test measures multimodality in a sample by the maximum difference, over all sample points, between the empirical distribution function, and the unimodal distribution function that minimizes that maximum difference. The uniform distribution is the asymptotically least favorable unimodal distribution, and the distribution of the test statistic is determined asymptotically and empirically when sampling from the uniform.
Short-latency saccades to targets among nontarget backgrounds are often directed to the center of the entire (target + nontarget) stimulus configuration. This "averaging" or "center-of-gravity" tendency has been attributed to an automatic, reflexive saccadic response to a poorly-resolved visual signal. We investigated the role of high-level processes by varying the probability of the target appearing in one of two locations. Subjects were asked to make a saccade to a target "+" located above-right or above-left of a central fixation point. A nontarget ("x") was in the other location (directional separation = 30 deg). The mean latencies were short (180-230 msec) in accordance with instructions. Mean saccadic direction was shifted to the right by 24-52% of the directional separation of the stimulus pair as the probability of the target appearing on the right increased from 0.2 to 0.8. The difference in saccadic directions as a function of the actual target location was small and independent of probability, showing that probability introduced a bias without affecting the discriminability of the target from the nontarget. The effect of probability was reduced when the discrimination of the target from the nontarget was easier (square vs triangle), and abolished (saccadic accuracy near perfect with the same average latencies) when the target was presented alone. The results show that the direction of short-latency saccades, initiated before the target has been distinguished from a nearby nontarget, is based on the prior history of target locations and expectations about the future location of the target. High-level plans can account for effects of nontargets on saccades. To infer that a reflexive sensorimotor averaging mechanism exists solely on the basis of observed saccadic "centering" tendencies is unwarranted.
Four experiments are reported in which saccadic eye movements are examined when the eye moves to targets in peripheral vision which consist of two discrete stimuli. It is found that under a variety of conditions, the saccade amplitude is such that the saccade lands at an intermediate position between the stimuli. This result has been termed the global effect and is interpreted as an influence of the global target configuration on the saccade amplitude. It is suggested that this phenomenon may be explicable in terms of activity in an ensemble of cells with large receptive fields. The experiments demonstrate the global effect in the situations of rapid automatic tracking, scanning for target detail and comparison of target configurations. The effect depends in a systematic quantitative manner on the properties of the visual stimuli. This may be loosely described by saying the saccade is directed to the centre of gravity of the target configuration. The saccades are however in general directed closer to the near target than predicted by the geometric centre of gravity. Although the effect appears in a similar form in all the conditions tested, minor differences do occur. It is also shown that the effect shows a dependence on the latency of the saccade, being most pronounced for saccades with short latencies. It is suggested that this may be a consequence of the dynamics of visual information processing.
1. The first experiment of this study determined the effects of low-frequency stimulation of the monkey superior colliculus on spontaneous saccades in the dark. Stimulation trains, subthreshold for eliciting short-latency fixed-vector saccades, were highly effective at biasing the metrics (direction and amplitude) of spontaneous movements. During low-frequency stimulation, the distribution of saccade metrics was biased toward the direction and amplitude of movements induced by suprathreshold stimulation of the same collicular location. 2. Low-frequency stimulation biased the distribution of saccade metrics but did not initiate movements. The distribution of intervals between stimulation onset and the onset of the next saccade did not differ significantly from the distribution of intervals between an arbitrary point in time and the onset of the next saccade under unstimulated conditions. 3. Results of our second experiment indicate that low-frequency stimulation also influenced the metrics of visually guided saccades. The magnitude of the stimulation-induced bias increased as stimulation current or frequency was increased. 4. The time course of these effects was analyzed by terminating stimulation immediately before, during, or after visually guided saccades. Stimulation trains terminated at the onset of a movement were as effective as stimulation trains that continued throughout the movement. No effects were observed if stimulation ended 40-60 ms before the movement began. 5. These results show that low-frequency collicular stimulation can influence the direction and amplitude of spontaneous or visually guided saccades without initiating a movement. These data are compatible with the hypothesis that the collicular activity responsible for specifying the horizontal and vertical amplitude of a saccade differs from the type of collicular activity that initiates a saccade.
The capacity to predict future events permits a creature to detect, model, and manipulate the causal structure of its interactions with its environment. Behavioral experiments suggest that learning is driven by changes in the expectations about future salient events such as rewards and punishments. Physiological work has recently complemented these studies by identifying dopaminergic neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient and rewarding events. Taken together, these findings can be understood through quantitative theories of adaptive optimizing control.
In addition to their well-known role in skeletal movements, the basal ganglia control saccadic eye movements (saccades) by means of their connection to the superior colliculus (SC). The SC receives convergent inputs from cerebral cortical areas and the basal ganglia. To make a saccade to an object purposefully, appropriate signals must be selected out of the cortical inputs, in which the basal ganglia play a crucial role. This is done by the sustained inhibitory input from the substantia nigra pars reticulata (SNr) to the SC. This inhibition can be removed by another inhibition from the caudate nucleus (CD) to the SNr, which results in a disinhibition of the SC. The basal ganglia have another mechanism, involving the external segment of the globus pallidus and the subthalamic nucleus, with which the SNr-SC inhibition can further be enhanced. The sensorimotor signals carried by the basal ganglia neurons are strongly modulated depending on the behavioral context, which reflects working memory, expectation, and attention. Expectation of reward is a critical determinant in that the saccade that has been rewarded is facilitated subsequently. The interaction between cortical and dopaminergic inputs to CD neurons may underlie the behavioral adaptation toward purposeful saccades.
Motor sequence learning is a process whereby a series of elementary movements is re-coded into an efficient representation for the entire sequence. Here we show that human subjects learn a visuomotor sequence by spontaneously chunking the elementary movements, while each chunk acts as a single memory unit. The subjects learned to press a sequence of 10 sets of two buttons through trial and error. By examining the temporal patterns with which subjects performed a visuomotor sequence, we found that the subjects performed the 10 sets as several clusters of sets, which were separated by long time gaps. While the overall performance time decreased by repeating the same sequence, the clusters became clearer and more consistent. The cluster pattern was uncorrelated with the distance of hand movements and was different across subjects who learned the same sequence. We then split a learned sequence into three segments, while preserving or destroying the clusters in the learned sequence, and shuffled the segments. The performance on the shuffled sequence was more accurate and quicker when the clusters in the original sequence were preserved than when they were destroyed. The results suggest that each cluster is processed as a single memory unit, a chunk, and is necessary for efficient sequence processing. A learned visuomotor sequence is hierarchically represented as chunks that contain several elementary movements. We also found that the temporal patterns of sequence performance transferred from the nondominant to dominant hand, but not vice versa. This may suggest a role of the dominant hemisphere in storage of learned chunks. Together with our previous unit-recording and imaging studies that used the same learning paradigm, we predict specific roles of the dominant parietal area, basal ganglia, and presupplementary motor area in the chunking.
The salience map is a crucial concept for many theories of visual attention. On this map, each object in the scene competes for selection - the more conspicuous the object, the greater its representation, and the more likely it will be chosen. In recent years, the firing patterns of single neurons have been interpreted using this framework. Here, we review evidence showing that the expression of salience is remarkably similar across structures, remarkably different across tasks, and modified in important ways when the salient object is consistent with the goals of the participant. These observations have important ramifications for theories of attention. We conclude that priority--the combined representation of salience and relevance--best describes the firing properties of neurons.
It is generally agreed that saccade deviations away from a distractor location represent inhibition in the oculomotor system. By systematically manipulating the location of a distractor we tested whether the inhibition of the distractor is coded coarsely or fine-grained. Results showed that the location of a distractor had an effect on the saccade trajectories, suggesting that the amount of inhibition observed depends on the location of the distractor. More specifically, the vertical distance of the distractor from fixation seems to be a determining factor. These findings have important implications for models that account for inhibition in the target selection process and the areas that could underlie inhibitory influences on the superior colliculus (SC), like the frontal eye fields (FEF) and the dorsolateral prefrontal cortex (dlPFC). Finally, the initial direction and the endpoint of a saccade were found to be strongly correlated, which contradicts recent models proposing that the initial saccade direction and saccade endpoint are unrelated.