Browsing by Author "Theeuwes, Jan"
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- Attentional suppression is in place before display onsetPublication . Huang, C.; Donk, Mieke; Theeuwes, JanRecent studies have shown that observers can learn to suppress a location that is most likely to contain a distractor. The current study investigates whether the statistically learned suppression is already in place, before, or implemented exactly at the moment participants expect the display to appear. Participants performed a visual search task in which a distractor was presented more frequently at the high-probability location (HPL) in a search display. Occasionally, the search display was replaced by a probe display in which participants needed to detect a probe ofset. The temporal relationship between the probe display and the search display was manipulated by varying the stimulus onset asynchronies (SOAs) in the probe task. In this way, the attentional distribution in space was probed before, exactly at, or after the moment when the search display was expected to be presented. The results showed a statistically learned suppression at the HPL, as evidenced by faster and more accurate search when a distractor was presented at this location. Crucially, irrespective of the SOA, probe detection was always slower at the HPL than at the low-probability locations, indicating that the spatial suppression induced by statistical learning is proactively implemented not just at the moment the display is expected, but prior to display onset. We conclude that statistical learning afects the weights within the priority map relatively early in time, well before the availability of the search display
- Electrophysiological indices of distractor processing in visual search are shaped by target expectationsPublication . Van Moorselaar, Dirk; Huang, Changrun; Theeuwes, JanAlthough in many cases salient stimuli capture attention involuntarily, it has been proposed recently that under certain conditions, the bottom–up signal generated by such stimuli can be proactively suppressed. In support of this signal suppression hypothesis, ERP studies have demonstrated that salient stimuli that do not capture attention elicit a distractor positivity (PD), a putative neural index of suppression. At the same time, it is becoming increasingly clear that regularities across preceding search episodes have a large influence on attentional selection. Yet to date, studies in support of the signal suppression hypothesis have largely ignored the role of selection history on the processing of distractors. The current study addressed this issue by examining how electrophysiological markers of attentional selection (N2pc) and suppression (PD) elicited by targets and distractors, respectively, were modulated when the search target randomly varied instead of being fixed across trials. Results showed that although target selection was unaffected by this manipulation, both in terms of manual response times, as well as in terms of the N2pc component, the PD component was reliably attenuated when the target features varied randomly across trials. This result demonstrates that the distractor PD, which is typically considered the marker of selective distractor processing, cannot unequivocally be attributed to suppression only, as it also, at least in part, reflects the upweighting of target features.
- Learning to suppress a location does not depend on knowing which locationPublication . Gao, Ya; Theeuwes, JanThe present study investigated whether explicit knowledge and awareness regarding the regularities present in the display afects statistical learning (SL) in visual search. Participants performed the additional singleton paradigm in which a salient distractor was presented much more often in one location than in all other locations. Previous studies have shown that participants learn this regularity as the location that is most likely to contain a distractor becomes suppressed relative to all other locations. In the current study, after each trial, participants had to either indicate the location of the distractor or the location of the target. Those participants that reported the distractor location, were very much aware of the regularity present in the display. However, participants that reported the target location were basically unaware of the regularity regarding the distractor. The results showed no diference between these groups in the amount of suppression of the high-probability location. This indicates that regardless of whether participants had explicit knowledge or not, the suppression was basically the same. We conclude that explicit knowledge and awareness does not contribute to learning to suppress a location. This conclusion is consistent with the notion that statistical learning is automatic, operating without conscious efort or awareness.
- Learning to suppress a location is configuration-dependentPublication . Gao, Ya; De Waard, Jasper; Theeuwes, JanWhere and what we attend is very much determined by what we have encountered in the past. Recent studies have shown that people learn to extract statistical regularities in the environment resulting in attentional suppression of locations that were likely to contain a distractor, efectively reducing the amount of attentional capture. Here, we asked whether this suppression efect due to statistical learning is dependent on the specifc confguration within which it was learned. The current study employed the additional singleton paradigm using search arrays that had a confguration consisting of set sizes of either four or 10 items. Each confguration contained its own high probability distractor location. If learning would generalize across set size confgurations, both high probability locations would be suppressed equally, regardless of set size. However, if learning to suppress is dependent on the confguration within which it was learned, one would expect only suppression of the high probability location that matched the confguration within which it was learned. The results show the latter, suggesting that implicitly learned suppression is confguration-dependent. Thus, we conclude that the high probability location is learned within the confguration context within which it is presented
- Pinging the brain to reveal the hidden attentional priority map using encephalographyPublication . Duncan, Dock H.; van Moorselaar, Dirk; Theeuwes, JanAttention has been usefully thought of as organized in priority maps – putative maps of space where attentional priority isweighted across spatial regions in a winner-take-all competition for attentional deployment. Recent work has highlighted the influence of past experiences on the weighting of spatial priority – called selection history. Aside from being distinct from more wellstudied, top-down forms of attentional enhancement, little is known about the neural substrates of history-mediated attentional priority. Using a task known to induce statistical learning of target distributions, in an EEG study we demonstrate that this otherwise invisible, latent attentional priority map can be visualized during the intertrial period using a ‘pinging’ technique in conjunction with multivariate pattern analyses. Our findings not only offer a method of visualizing the history-mediated attentional priority map, but also shed light on the underlying mechanisms allowing our past experiences to influence future behavior.
- Self-explaining roads: Effects of road design on speed choicePublication . Theeuwes, Jan; Snell, Joshua; Koning, Trisha; Bucker, BernoOne of the leading principles for road design is the notion of Self-Explaining Roads (SER). According to this notion, the design and layout of the road environment should automatically elicit behavior that is appropriate for that type of road. The current study investigated the effects of the road environment (i.e., the presence of particular road elements such as the presence/absence of edge lines, and a physical separation between driving lanes) on driving speed choice in the Netherlands for roads in- and outside the city limits (ICL and OCL). A total of 462 participants (all car drivers) were exposed to either 152 ICL or 152 OCL pictures of road environments for either a short (300 ms in Experiment 1, 200 ms in Experiment 2) or long duration (1500 ms) and indicated as fast as possible which speed they would drive given the road environment they viewed. All images were labeled with respect to the presence or absence of particular road elements. A linear mixed model was used to determine the effects of road elements on speed choice and response time. The results showed that the presence of certain road elements impacted the speed chosen. For example, inside the city limits, relative to no bicycle lane, a bicycle lane painted on the road reduced driving speed while a separate bike lane increased the speed chosen. Also, central line markings (relative to no line marking) and a road made of asphalt (relative to pavers) were associated with higher speeds. Outside city limits, having multiple lanes (versus one lane) was related to higher speeds and having two driving directions without separation (versus a one-way road) was related to lower speed choices. Importantly, exposure duration (200 /300 ms versus 1500 ms) only had a marginal effect, indicating that road users generally only need a brief glimpse of the road to be able to decide what speed to drive. Consistent with the principles of SER, we conclude that categorization and the associated speed decision is fast, operating within a single glance and is impacted by the road elements present in the environment. Finally, we believe our method constitutes a valuable tool in road design, as it allows one to efficiently and effectively gauge the impact of various road elements in large population samples.
- Spatial enhancement due to statistical learning tracks the estimated spatial probabilityPublication . Zhang, Yuanyuan; Yang, Yihan; Wang, Benchi; Theeuwes, JanIt is well known that attentional selection is sensitive to the regularities presented in the display. In the current study we employed the additional singleton paradigm and systematically manipulated the probability that the target would be presented in one particular location within the display (probabilities of 30%, 40%, 50%, 60%, 70%, 80%, and 90%). The results showed the higher the target probability, the larger the performance benefit for high- relative to low-probability locations both when a distractor was present and when it was absent. We also showed that when the difference between high- and low-probability conditions was relatively small (30%) participants were not able to learn the contingencies. The distractor presented at a highprobability target location caused more interference than when presented at a low-probability target location. Overall, the results suggest that attentional biases are optimized to the regularities presented in the display tracking the experienced probabilities of the locations that were most likely to contain a target. We argue that this effect is not strategic in nature nor the result of repetition priming. Instead, we assume that through statistical learning the weights within the spatial priority map are adjusted optimally, generating the efficient selection priorities.
- Spatial transfer of object-based statistical learningPublication . Van Moorselaar, Dirk; Theeuwes, JanA large number of recent studies have demonstrated that efcient attentional selection depends to a large extent on the ability to extract regularities present in the environment. Through statistical learning, attentional selection is facilitated by directing attention to locations in space that were relevant in the past while suppressing locations that previously were distracting. The current study shows that we are not only able to learn to prioritize locations in space but also locations within objects independent of space. Participants learned that within a specifc object, particular locations within the object were more likely to contain relevant information than other locations. The current results show that this learned prioritization was bound to the object as the learned bias to prioritize a specifc location within the object stayed in place even when the object moved to a completely diferent location in space. We conclude that in addition to spatial attention prioritization of locations in space, it is also possible to learn to prioritize relevant locations within specifc objects. The current fndings have implications for the inferred spatial priority map of attentional weights as this map cannot be strictly retinotopically organized· · ·
- Statistical learning of distractor locations is dependent on task contextPublication . De Waard, Jasper; Van Moorselaar, Dirk; Bogaerts, Louisa; Theeuwes, JanThrough statistical learning, humans can learn to suppress visual areas that often contain distractors. Recent findings suggest that this form of learned suppression is insensitive to context, putting into question its real-life relevance. The current study presents a different picture: we show contextdependent learning of distractor-based regularities. Unlike previous studies which typically used background cues to differentiate contexts, the current study manipulated task context. Specifically, the task alternated from block to block between a compound search and a detection task. In both tasks, participants searched for a unique shape, while ignoring a uniquely colored distractor item. Crucially, a different high-probability distractor location was assigned to each task context in the training blocks, and all distractor locations were made equiprobable in the testing blocks. In a control experiment, participants only performed a compound search task such that the contexts were made indistinguishable, but the high-probability locations changed in exactly the same way as in the main experiment. We analyzed response times for different distractor locations and show that participants can learn to suppress a location in a context-dependent way, but suppression from previous task contexts lingers unless a new high-probability location is introduced.
- Statistical learning of motor preparationPublication . Theeuwes, Jan; Huang, Changrun; Frings, Christian; Van Moorselaar, DirkStatistical learning, the process of extracting regularities from the environment, is one of the most fundamental abilities playing an essential role in almost all aspects of human cognition. Previous studies have shown that attentional selection is biased toward locations that are likely to contain a target and away from locations that are likely to contain a distractor. The current study investigated whether participants can also learn to extract that a specific motor response is more likely when the target is presented at specific locations within the visual field. To that end, the additional singleton paradigm was adapted such that when the singleton target was presented at one specific location, one response (e.g., right index finger) was more likely than the other (e.g., right middle finger) and the reverse was true for another location. The results show that participants learned to extract that a particular motor response is more likely when the singleton target (which was unrelated to the response) was presented at a specific location within the visual field. The results also suggest that it is the location of the target and not its shape that is associated with the biased response. This learning cannot be considered as being top-down or conscious as participants showed little, if any, awareness of the response biases present. The results are discussed in terms of the event coding theory. The study increases the scope of statistical learning and shows how individuals adapt automatically, without much awareness, to the regularities present in the environment.