The central visual field is essential for activities like reading and face recognition. However, the impact of peripheral vision loss on daily activities is profound. While the importance of central vision is well established, the contribution of peripheral vision to spatial attention is less clear. In this study, we introduced a \"mouse-eye\" method as an alternative to traditional gaze-contingent eye tracking. We found that even in tasks requiring central vision, peripheral vision contributes to implicit attentional learning. Participants searched for a T among Ls, with the T appearing more often in one visual quadrant. Earlier studies showed that participants\' awareness of the T location probability was not essential for their ability to learn. When we limited the visible area around the mouse cursor, only participants aware of the target\'s location probability showed learning; those unaware did not. Adding placeholders in the periphery did not restore implicit attentional learning. A control experiment showed that when participants were allowed to see all items while searching and moving the mouse to reveal the target\'s color, both aware and unaware participants acquired location probability learning. Our results underscore the importance of peripheral vision in implicitly guided attention. Without peripheral vision, only explicit, but not implicit, attentional learning prevails.

This study investigated the impact of target template variation or consistency on attentional bias in location probability learning. Participants conducted a visual search task to find a heterogeneous shape among a homogeneous set of distractors. The target and distractor shapes were either fixed throughout the experiment (target-consistent group) or unpredictably varied on each trial (target-variant group). The target was often presented in one possible search region, unbeknownst to the participants. When the target template was consistent throughout the biased visual search, spatial attention was persistently biased toward the frequent target location. However, when the target template was inconsistent and varied during the biased search, the spatial bias was attenuated so that attention was less prioritized to a frequent target location. The results suggest that the alternative use of target templates may interfere with the emergence of a persistent spatial bias. The regularity-based spatial bias depends on the number of attentional shifts to the frequent target location, but also on search-relevant contexts.

Attention is tuned towards locations that frequently contain a visual search target (location probability learning; LPL). Peripheral vision, covering a larger field than the fovea, often receives information about the target. Yet what is the role of peripheral vision in attentional learning? Using gaze-contingent eye tracking, we examined the impact of simulated peripheral vision loss on location probability learning. Participants searched for a target T among distractor Ls. Unbeknownst to them, the T appeared disproportionately often in one quadrant. Participants searched with either intact vision or \"tunnel vision,\" restricting the visible search items to the central 6.7º (in diameter) of the current gaze. When trained with tunnel vision, participants in Experiment 1 acquired LPL, but only if they became explicitly aware of the target\'s location probability. The unaware participants were not faster finding the target in high-probability than in low-probability locations. When trained with intact vision, participants in Experiment 2 successfully acquired LPL, regardless of whether they were aware of the target\'s location probability. Thus, whereas explicit learning may proceed with central vision alone, implicit LPL is strengthened by peripheral vision. Consistent with Guided Search (Wolfe, 2021), peripheral vision supports a nonselective pathway to guide visual search.

Daily activities often occur in familiar environments, affording us an opportunity to learn. Laboratory studies have shown that people readily acquire an implicit spatial preference for locations that frequently contained a search target in the past. These studies, however, have focused on group characteristics, downplaying the significance of individual differences. In a pre-registered study, we examined the stability of individual differences in two variants of an implicit location probability learning (LPL) task. We tested the possibility that individual differences were stable in variants that shared the same search process, but not in variants involving different search processes. In Experiment 1, participants performed alternating blocks of T-among-Ls and 5-among-2s search tasks. Unbeknownst to them, the search target appeared disproportionately often in one region of space; the high-probability regions differed between the two tasks. LPL transferred between the two tasks. In addition, individuals who showed greater LPL in the T-task also did so in the 5-task and vice versa. In Experiment 2, participants searched for either a camouflaged-T against background noise or a well-segmented T among well-segmented Ls. These two tasks produced task-specific learning that did not transfer between tasks. Moreover, individual differences in learning did not correlate between tasks. Thus, LPL is associated with stable individual differences across variants, but only when the variants share common search processes.

Growing evidence has shown that attention can be habit-like, unconsciously and persistently directed toward locations that have frequently contained search targets in the past. The attentional preference typically arises when the eye gaze aligns with the attended location. Here we tested whether this spatial alignment is necessary for the acquisition of a search habit. To divert eye movements away from an attended location, we used gaze-contingent eye tracking, restricting the visible portion of the screen to an area opposite to the current gaze. Participants searched for a T target amidst a circular array of L distractors. Unbeknownst to them, the target appeared more frequently in one screen quadrant. Despite fixating on a location diametrically opposite to the visible, attended region, participants acquired probability cuing, producing quicker responses when the target appeared in the high-probability quadrant. They also showed a speed advantage in the diagonal quadrant. The attentional preference for the high-probability quadrant persisted during a testing phase in which the target\'s location was unbiased, but only when participants continued to search with the restricted view. These results indicate that a search habit can be acquired even when participants are required to look away from the high-probability locations. The finding suggests that the learned search habit is not solely a result of oculomotor learning.

Statistical knowledge of a target\'s location may benefit visual search, and rapidly understanding the changes in regularity would increase the adaptability in visual search situations where fast and accurate performance is required. The current study tested the sources of statistical knowledge-explicitly-given instruction or experience-driven learning-and whether they affect the speed and location spatial attention is guided. Participants performed a visual search task with a statistical regularity to bias one quadrant (\"old-rich\" condition) in the training phase, followed by another quadrant (\"new-rich\" condition) in the switching phase. The \"instruction\" group was explicitly instructed on the regularity, whereas the \"no-instruction\" group was not. It was expected that the instruction group would rely on goal-driven attention (using regularities with explicit top-down knowledge), and the no-instruction group would rely on habit-like attention (learning regularities through repetitive experiences) in visual search. Compared with the no-instruction group, the instruction group readjusted spatial attention following the regularity switch more rapidly. The instruction group showed greater attentional bias toward the new-rich quadrant than the old-rich quadrant; however, the no-instruction group showed a similar extent of attentional bias to two rich quadrants. The current study suggests that the source of statistical knowledge can affect attentional allocation. Moreover, habit-like attention, a different type of attentional source than goal-driven attention, is relatively implicit and inflexible.

Location probability learning-the acquisition of an attentional bias toward locations that frequently contained a search target-shows many characteristics of a search habit. To what degree does it depend on oculomotor control, as might be expected if habit-like attention is grounded in eye movements? Here, we examined the impact of a spatially incompatible oculomotor signal on location probability learning (LPL). On each trial of a visual search task, participants first saccaded toward a unique C-shape, whose orientation determined whether participants should continue searching for a T target among L distractors. The C-shape often appeared in one, \"C-rich\" quadrant that differed from where the T was frequently located. Experiment 1 showed that participants acquired LPL toward the high-probability, \"T-rich\" quadrant, an effect that persisted in an unbiased testing phase. Participants were also faster finding the target in the vicinity of the C-shape, but this effect did not persist after the C-shape was removed. Experiment 2 found that the C-shape affected search only when it was task-relevant. Experiment 3 replicated and extended the findings of Experiment 1 using eye tracking. Thus, location probability learning is robust in the face of a spatially incompatible saccade, demonstrating partial independence between experience-guided attention and goal-driven oculomotor control. The findings are in line with the modular view of attention, which conceptualizes the search habit as a high-level process abstracted from eye movements.

Some eye diseases, especially macular degeneration, can cause central vision loss (CVL), impairing goal-driven guidance of attention. Does CVL also affect implicit, experience-driven attention? We investigated how simulated central scotomas affected young adults\' ability to prioritize locations frequently containing visual search targets (location probability learning). Participants searched among distractor letter \'L\'s for a target \'T\' that appeared more often in one screen quadrant than others. To dissociate potential impairments to statistical learning of target locations and attentional guidance, two experiments each included search with and without simulated scotomas. Experiment 1 successfully induced probability learning in a no-scotoma phase. When participants later searched both with and without simulated scotomas, they showed persistent, statistically equivalent spatial biases in both no-scotoma and scotoma search. Experiment 2 trained participants with a central scotoma. While Experiment 1\'s participants acquired probability learning regardless of their self-reported awareness of the target\'s location probability, in Experiment 2 only aware participants learned to bias attention to the high probability region. Similarly, learning with a scotoma affected search with no scotoma in aware but not unaware participants. Together, these results show that simulated central vision loss interferes with the acquisition of implicitly learned location probability learning, supporting a role of central vision in implicit spatial attentional biases.

We tested whether implicit learning causes shifts of spatial attention in advance of or in response to stimulus onset. Participants completed randomly interspersed trials of letter search, which involved reporting the orientation of a T among Ls, and scene search, which involved identifying which of four scenes was from a target category (e.g., forest). In Experiment 1, an initial phase more often contained target letters in one screen quadrant, while the target scenes appeared equally often in all quadrants. Participants persistently prioritized letter targets in the more probable region, but the implicitly learned preference did not affect the unbiased scene task. In Experiment 2, the spatial probabilities of the scene and letter tasks reversed. Participants unaware of the probability manipulation acquired only a spatial bias to scene targets in the more probable region, with no effect on letter search. Instead of recruiting baseline shifts of spatial attention prior to stimulus onset, implicit learning of target probability yields task-dependent shifts of spatial attention following stimulus onset. Such shifts may involve attentional behaviors unique to certain task contexts.

The visual environment contains predictable information - \"statistical regularities\" - that can be used to aid perception and attentional allocation. Here we investigate the role of statistical learning in facilitating search tasks that resemble medical-image perception. Using faux X-ray images, we employed two tasks that mimicked two problems in medical-image perception: detecting a target signal that is poorly segmented from the background; and discriminating a candidate anomaly from benign signals. In the first, participants searched a heavily camouflaged target embedded in cloud-like noise. In the second, the noise opacity was reduced, but the target appeared among visually similar distractors. We tested the hypothesis that learning may be task-specific. To this end, we introduced statistical regularities by presenting the target disproportionately more frequently in one region of the space. This manipulation successfully induced incidental learning of the target\'s location probability, producing faster search when the target appeared in the high-probability region. The learned attentional preference persisted through a testing phase in which the target\'s location was random. Supporting the task-specificity hypothesis, when the task changed between training and testing, the learned priority did not transfer. Eye tracking showed fewer, but longer, fixations in the detection than in the discrimination task. The observation of task-specificity of statistical learning has implications for theories of spatial attention and sheds light on the design of effective training tasks.