Through experience, humans can learn to suppress locations that frequently contain distracting stimuli. However, the neural mechanism underlying learned suppression remains largely unknown. In this study, we combined steady-state visually evoked potentials (SSVEPs) with event-related potentials (ERPs) to investigate the mechanism behind statistically learned spatial suppression. Twenty-four male and female human participants performed a version of the additional singleton search task in which one location contained a distractor stimulus frequently. The search stimuli constantly flickered on-and-off the screen, resulting in steady state entrainment. Prior to search onset, no differences in the SSVEP response were found, though a post-hoc analysis did reveal proactive alpha lateralization. Following search onset, clear evoked differences in both the SSVEP and ERP signals emerged at the suppressed location relative to all other locations. Crucially, the early timing of these evoked modulations suggests that learned distractor suppression occurs at the initial stages of visual processing. Significance Statement Often times a distractor (e.g. a colorful yet irrelevant billboard on a highway) becomes easier to ignore after you’ve encountered it several times. This learned suppression is an important component of the human visual system which is otherwise highly salience driven. In a series of EEG experiments, we used SSVEPs and ERPs to study how learning changes attention towards salient distracting stimuli when these distractors appear frequently at specific locations. We found converging evidence that learning alters the early evoked responses to these stimuli. Our results indicate that through learning, early neural responses to distracting stimuli are changed.

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.

email: J.Theeuwes@vu.nl 2 abstract The current review presents an integrated tripartite framework for understanding attentional control, emphasizing the interaction and competition among top-down, bottom-up, and selection-history influences. It focuses on attentional capture which refers to conditions in which salient objects or events receive attentional priority even when they are inconsistent with the goals, tasks, and intentions of the observer. The review describes which components of the tripartite framework are in play when distraction by salient objects is prevented and the conditions in which there is no control over the occurrence of attentional capture. It is concluded that attentional capture can be controlled in a proactive way mainly by implicit statistical learning mechanisms associated with selection history. Current and lingering controversies regarding the control of attentional capture are discuss 3

Statistical 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 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 looked 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 non-salient 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, a follow-up experiment showed that if, during search, no attention is directed to this regularity, incidental learning is no longer seen; suggesting that at least some attention to the critical regularity is needed for learning to occur. We conclude that some degree of attention to a regularity is needed for visual statistical learning to occur.