Learning In Visual Search Research Articles

Emotional modulation of statistical learning in visual search

Emotional modulation of statistical learning in visual search

The dynamics of statistical learning in visual search and its interaction with salience processing: An EEG study

Visual attention can be guided by statistical regularities in the environment, that people implicitly learn from past experiences (statistical learning, SL). Moreover, a perceptually salient element can automatically capture attention, gaining processing priority through a bottom-up attentional control mechanism. The aim of our study was to investigate the dynamics of SL and if it shapes attentional target selection additively with salience processing, or whether these mechanisms interact, e.g. one gates the other. In a visual search task, we therefore manipulated target frequency (high vs. low) across locations while, in some trials, the target was salient in terms of colour. Additionally, halfway through the experiment, the high-frequency location changed to the opposite hemifield. EEG activity was simultaneously recorded, with a specific interest in two markers related to target selection and post-selection processing, respectively: N2pc and SPCN. Our results revealed that both SL and saliency significantly enhanced behavioural performance, but also interacted with each other, with an attenuated saliency effect at the high-frequency target location, and a smaller SL effect for salient targets. Concerning processing dynamics, the benefit of salience processing was more evident during the early stage of target selection and processing, as indexed by a larger N2pc and early-SPCN, whereas SL modulated the underlying neural activity particularly later on, as revealed by larger late-SPCN. Furthermore, we showed that SL was rapidly acquired and adjusted when the spatial imbalance changed. Overall, our findings suggest that SL is flexible to changes and, combined with salience processing, jointly contributes to establishing attentional priority.

What is the Role of Spatial Attention in Statistical Learning During Visual Search?

Our ability to learn the regularities embedded in our environment is a fundamental aspect of our cognitive system. Does such statistical learning depend on attention? Research on this topic is scarce and has yielded mixed findings. In this preregistered study, we examined the role of spatial attention in statistical learning, and specifically in learned distractor-location suppression. This phenomenon refers to the finding that during visual search, participants are better at ignoring a salient distractor at a high-probability location than at low-probability locations - a bias persisting long after the probability imbalance has ceased. Participants searched for a shape-singleton target and a color-singleton distractor was sometimes present. During the learning phase, the color-singleton distractor was more likely to appear in the high-probability location than in the low-probability locations. Crucially, we manipulated spatial attention by having the experimental group focus their attention on the target's location in advance of the search display, using a 100%-informative spatial precue, while the control group was presented with a neutral, uninformative cue. During the subsequent test phase, the color-singleton distractor was equally likely to appear at any location and there were no cues. As expected, the results for the neutral-cue group replicated previous findings. Crucially, for the informative-cue group, interference from the distractor was minimal when attention was diverted from it (during learning) and no statistical learning was observed during test. Intertrial priming accounted for the small statistical-learning effect found during learning. These findings show that statistical learning in visual search requires attention.

No evidence for spatial suppression due to across-trial distractor learning in visual search

Previous studies have shown that during visual search, participants are able to implicitly learn across-trial regularities regarding target locations and use these to improve search performance. The present study asks whether such across-trial visual statistical learning also extends to the location of salient distractors. In Experiments 1 and 2, distractor regularities were paired so that a specific distractor location was 100% predictive of another specific distractor location on the next trial. Unlike previous findings that employed target regularities, the current results show no difference in search times between predictable and unpredictable trials. In Experiments 3–5 the distractor location was presented in a structured order (a sequence) for one group of participants, while it was presented randomly for the other group. Again, there was no learning effect of the across-trial regularities regarding the salient distractor locations. Across five experiments, we demonstrated that participants were unable to exploit across-trial spatial regularities regarding the salient distractors. These findings point to important boundary conditions for the modulation of visual attention by statistical regularities and they highlight the need to differentiate between different types of statistical regularities.

Statistical learning in visual search reflects distractor rarity, not only attentional suppression

In visual search tasks, salient distractors may capture attention involuntarily, but interference can be reduced when the salient distractor appears more frequently on one out of several possible positions. The reduction was attributed to attentional suppression of the high-probability position. However, all previous studies on this topic compared performance on the high-probability position to the remaining positions, which had a low probability of containing the distractor. Therefore, it is not clear whether the difference resulted from reduced interference on the high-probability position or from increased interference on the low-probability positions. To decide between these alternatives, we compared high-probability and low-probability with equal-probability positions. Consistent with attentional suppression, interference was reduced on the high-probability position compared with equal-probability positions. However, there was also an increase in interference on low-probability positions compared with equal-probability positions. The increase is in line with previous reports of boosted interference when distractors are rare. Our results show that the experimental design used in previous research is insufficient to separate effects of attentional suppression and those of distractor rarity.

Distributed attention beats the down-side of statistical context learning in visual search.

Spatial attention can be deployed with a narrower focus to process individual items or distributed relatively broadly to process larger parts of a scene. This study investigated how focused- versus distributed-attention modes contribute to the adaptation of context-based memories that guide visual search. In two experiments, participants were either required to fixate the screen center and use peripheral vision for search (“distributed attention”), or they could freely move their eyes, enabling serial scanning of the search array (“focused attention”). Both experiments consisted of an initial learning phase and a subsequent test phase. During learning, participants searched for targets presented either among repeated (invariant) or nonrepeated (randomly generated) spatial layouts of distractor items. Prior research showed that repeated encounters of invariant display arrangements lead to long-term context memory about these arrays, which can then come to guide search (contextual-cueing effect). The crucial manipulation in the test phase was a change of the target location within an otherwise constant distractor layout, which has previously been shown to abolish the cueing effect. The current results replicated these findings, although importantly only when attention was focused. By contrast, with distributed attention, the cueing effect recovered rapidly and attained a level comparable to the initial effect (before the target location change). This indicates that contextual cueing can adapt more easily when attention is distributed, likely because a broad attentional set facilitates the flexible updating of global (distractor-distractor), as compared to more local (distractor-target), context representations—allowing local changes to be incorporated more readily.

How Attentional Guidance and Response Selection Boost Contextual Learning: Evidence from Eye Movement.

The contextual cueing effect (CCE) refers to the learned association between predictive configuration and target location, speeding up response times for targets. Previous studies have examined the underlying processes (initial perceptual process, attentional guidance, and response selection) of CCE but have not reached a general consensus on their contributions to CCE. In the present study, we used eye tracking to address this question by analyzing the oculomotor correlates of context-guided learning in visual search and eliminating indefinite response factors during response priming. The results show that both attentional guidance and response selection contribute to contextual learning.

Evolution of decision weights and eye movements through learning in visual search

Evolution of decision weights and eye movements through learning in visual search

Statistical learning in visual search is easier after experience with noise than overcoming previous learning

ABSTRACTThis study compared adaptation to novel statistical learning following different environmental changes. Three groups of participants completed training with a visual search task. For the Consistent-first group, targets and distractors appeared in predefined spatial locations. For the Random-first group training contained no regularity and for the Mixed-first group training consisted of both consistent and random conditions. During the test phase, all groups received identical consistent and random conditions. Contrary to previous findings we did not observe statistical learning shutdown following experience with random visual search: a contextual-cueing effect was observed for all groups. However the effect was not stable in the Mixed-first group, suggesting an ongoing adjustment process. We conclude that initiating learning after experience with noise (i.e., random search) is easier than overcoming previous learning (i.e., encountering previously learned layouts). We argue that our cognitive system is sensitive to changes in the visual input and is actively searching for regularity even when it is absent.

視覚探索における意識的・無意識的学習効果の違い(視聴覚技術,ヒューマンインターフェース)

視覚探索における意識的・無意識的学習効果の違い(視聴覚技術,ヒューマンインターフェース)

Representing Color Ensembles

Colors are rarely uniform, yet little is known about how people represent color distributions. We introduce a new method for studying color ensembles based on intertrial learning in visual search. Participants looked for an oddly colored diamond among diamonds with colors taken from either uniform or Gaussian color distributions. On test trials, the targets had various distances in feature space from the mean of the preceding distractor color distribution. Targets on test trials therefore served as probes into probabilistic representations of distractor colors. Test-trial response times revealed a striking similarity between the physical distribution of colors and their internal representations. The results demonstrate that the visual system represents color ensembles in a more detailed way than previously thought, coding not only mean and variance but, most surprisingly, the actual shape (uniform or Gaussian) of the distribution of colors in the environment.

Contextual cueing in 3D visual search depends on representations in planar-, not depth-defined space.

Learning of spatial inter-item associations can speed up visual search in everyday life, an effect referred to as contextual cueing (Chun & Jiang, 1998). Whereas previous studies investigated contextual cueing primarily using 2D layouts, the current study examined how 3D depth influences contextual learning in visual search. In two experiments, the search items were presented evenly distributed across front and back planes in an initial training session. In the subsequent test session, the search items were either swapped between the front and back planes (Experiment 1) or between the left and right halves (Experiment 2) of the displays. The results showed that repeated spatial contexts were learned efficiently under 3D viewing conditions, facilitating search in the training sessions, in both experiments. Importantly, contextual cueing remained robust and virtually unaffected following the swap of depth planes in Experiment 1, but it was substantially reduced (to nonsignificant levels) following the left-right side swap in Experiment 2. This result pattern indicates that spatial, but not depth, inter-item variations limit effective contextual guidance. Restated, contextual cueing (even under 3D viewing conditions) is primarily based on 2D inter-item associations, while depth-defined spatial regularities are probably not encoded during contextual learning. Hence, changing the depth relations does not impact the cueing effect.

Neural correlates of context-dependent feature conjunction learning in visual search tasks.

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc.

Object-based implicit learning in visual search: Perceptual segmentation constrains contextual cueing

In visual search, detection of a target is faster when it is presented within a spatial layout of repeatedly encountered nontarget items, indicating that contextual invariances can guide selective attention (contextual cueing; Chun & Jiang, 1998). However, perceptual regularities may interfere with contextual learning; for instance, no contextual facilitation occurs when four nontargets form a square-shaped grouping, even though the square location predicts the target location (Conci & von Mühlenen, 2009). Here, we further investigated potential causes for this interference-effect: We show that contextual cueing can reliably occur for targets located within the region of a segmented object, but not for targets presented outside of the object's boundaries. Four experiments demonstrate an object-based facilitation in contextual cueing, with a modulation of context-based learning by relatively subtle grouping cues including closure, symmetry, and spatial regularity. Moreover, the lack of contextual cueing for targets located outside the segmented region was due to an absence of (latent) learning of contextual layouts, rather than due to an attentional bias towards the grouped region. Taken together, these results indicate that perceptual segmentation provides a basic structure within which contextual scene regularities are acquired. This in turn argues that contextual learning is constrained by object-based selection.

Object-based Implicit Learning in Visual Search: Perceptual Segmentation constrains Contextual Cueing

Object-based Implicit Learning in Visual Search: Perceptual Segmentation constrains Contextual Cueing

Medial temporal lobe-dependent repetition suppression and enhancement due to implicit vs. explicit processing of individual repeated search displays.

Using visual search, functional magnetic resonance imaging (fMRI) and patient studies have demonstrated that medial temporal lobe (MTL) structures differentiate repeated from novel displays—even when observers are unaware of display repetitions. This suggests a role for MTL in both explicit and, importantly, implicit learning of repeated sensory information (Greene et al., 2007). However, recent behavioral studies suggest, by examining visual search and recognition performance concurrently, that observers have explicit knowledge of at least some of the repeated displays (Geyer et al., 2010). The aim of the present fMRI study was thus to contribute new evidence regarding the contribution of MTL structures to explicit vs. implicit learning in visual search. It was found that MTL activation was increased for explicit and, respectively, decreased for implicit relative to baseline displays. These activation differences were most pronounced in left anterior parahippocampal cortex (aPHC), especially when observers were highly trained on the repeated displays. The data are taken to suggest that explicit and implicit memory processes are linked within MTL structures, but expressed via functionally separable mechanisms (repetition-enhancement vs. -suppression). They further show that repetition effects in visual search would have to be investigated at the display level.

Figure-ground segmentation determines contextual learning in visual search

Figure-ground segmentation determines contextual learning in visual search

Attention prioritization as a mechanism underlying context-guided learning in visual search

Attention prioritization as a mechanism underlying context-guided learning in visual search

Short and long term learning in visual search: An unexpected interference

Short and long term learning in visual search: An unexpected interference

Distance-from-target dynamics during visual search

Tseng, Y. C., & Li, C. S. (2004). Oculomotor correlates of context-guided learning in visual search. Perception & Psychophysics, 66, 1368–1378 noted that visual search with eye movements may be characterized by a search phase in which fixations do not move towards the target, followed by a phase in which fixations move steadily towards the target. They speculated that the phases are related to memory and recognition processes. Human visual search and Monte Carlo simulations are described towards an explanation. Distance-from-target dynamics were demonstrated to be sensitive to geometric constraints and therefore do not provide a solution to the question of memory in visual search. Finally, it is concluded that the specific distance-from-target dynamics noted by Tseng, Y. C., & Li, C. S. (2004). Oculomotor correlates of context-guided learning in visual search. Perception & Psychophysics, 66, 1368–1378 are parsimoniously explained by random walks that were initialized at the centre of their stimulus displays.