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- 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.
- What to expect where and when: how statistical learning drives visual selectionPublication . Theeuwes, Jan; Bogaerts, Louisa; van Moorselaar, DirkInexistente
- 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.
- 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· · ·
- Visual statistical learning requires attentionPublication . Duncan, Dock H.; Van Moorselaar, Dirk; Theeuwes, JanABSTRACT: Statistical learning is a person’s ability to automatically learn environmental regularities through passive exposure. Since the earliest studies of statistical learning in infants, it has been debated exactly how “passive” this learning can be (i.e., whether attention is needed for learning to occur). In Experiment 1 of the current study, participants performed a serial feature search task where they searched for a target shape among heterogenous nontarget shapes. Unbeknownst to the participants, one of these nontarget shapes was presented much more often in location. Even though the regularity concerned a nonsalient, nontarget item that did not receive any attentional priority during search, participants still learned its regularity (responding faster when it was presented at this high-probability location). While this may suggest that not much, if any, attention is needed for learning to occur, follow-up experiments showed that if an attentional strategy (i.e., color subset search or exogenous cueing) effectively prevents attention from being directed to this critical regularity, incidental learning is no longer observed. We conclude that some degree of attention to a regularity is needed for visual statistical learning to occur.
- 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.
- 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
- Transfer of statistical learning between tasksPublication . Van Moorselaar, Dirk; Theeuwes, JanRecent studies have shown that observers can learn to suppress locations in the visual field with a high distractor probability. Here, we investigated whether this learned suppression resulting from a spatial distractor imbalance transfers to a completely different search task that does not contain any distractors. Observers performed the additional singleton task and learned to suppress the location that was likely to contain a color singleton distractor. Within a block, the additional singleton task would randomly switch to a T-among-L task where observers searched in parallel (Experiment 1) or serially (Experiment 2) for a T among Ls. The upcoming search was either unpredictable (Experiment 1/2A) or cued (Experiment 1/2B). The results show that there was transfer of learning from one to the other task as the learned suppression stayed in place after the switch regardless of whether the T-among-L task was performed via parallel or serial search. Moreover, cueing that the task would switch had no effect on performance. The current findings indicate that implicit learned biases are rather inflexible and remain in place even when the task and the required search strategy are dramatically different and even when participants can anticipate that a change in the search required is imminent. This transfer of the suppression to a different task is consistent with the notion that suppression is proactively applied. Because the location is already suppressed proactively, that is, before display onset, regardless which display and task is presented, the suppressed location competes less for attention than all other locations.
- 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.
- 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.