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