Feature-based Attention Research Articles

Social norm learning alters feature-based visual attention: Evidence from steady-state visual evoked potentials.

Dating back to the seminal studies of Sherif (1935), there is robust evidence that social norm learning is able to shape perceptual decision making in a persistent manner. But what mechanisms underlie this effect? Here, we propose the new attentional alignment hypothesis. According to this hypothesis, norm learning alters feature-based visual attention. In particular, we hypothesize that norm learning increases visual attention toward norm-congruent relative to norm-incongruent stimulus features. Using steady-state visual evoked potentials, our results show for the first time that norm learning can persistently alter early attentional processes in the visual cortex. As predicted by the attentional alignment hypothesis, individuals' feature-based attention was tuned toward norm-congruent and away from norm-incongruent features. This bias persisted even when norm information was no longer available. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evidence for an age-related decline in feature-based attention

ABSTRACT Feature-based attention allows to efficiently guide attention to relevant information in the visual scene, but unambiguous empirical evidence on age-related effects is still limited. In this study, young and older participants performed a two-alternative forced choice task in which a response was selected based on a task-relevant number (=target) presented alone or with a task-irrelevant letter (=neutral distracter) or number (=compatible/incompatible distracter). Participants were required to select the target based on color. To compare the behavioral interference of the distracters between the age groups, data were modeled with a hierarchical drift-diffusion model. The results revealed that decreases in the rate at which information was collected in the conditions with versus without a distracter were more pronounced in the older than young age group when the distracter was compatible or incompatible. Our findings are consistent with an age-related decline in the ability to filter out distracters based on features.

Dissociating different temporal stages of emotional word processing by feature-based attention

Negative emotional content is prioritized across different stages of information processing as reflected by different components of the event-related potential (ERP). In this preregistered study (N = 40), we investigated how varying the attentional focus allows us to dissociate the involvement of specific ERP components in the processing of negative and neutral words. Participants had to discriminate the orientation of lines overlaid onto the words, the word type (adjective/noun), or the emotional content (negative/neutral). Thus, attention was either not focused on words (distraction task), non-emotional aspects, or the emotional relevance of words. Regardless of the task, there were no significant differences between negative and neutral words for the P1, N1, or P2 components. In contrast, interactions between emotion and task were observed for the early posterior negativity (EPN) and late positive potential (LPP). EPN differences were absent during the distraction task but were present in the other two tasks. LPP emotion differences were found only when attention was directed to the emotional content of words. Our study adds to the evidence that early ERP components do not reliably separate negative and neutral words. However, results show that mid-latency and late stages of emotion processing are separable by different attention tasks. The EPN represents a stage of attentional enhancement of negative words given sufficient attentional resources. Differential activations during the LPP stage are associated with more elaborative processing of the emotional meaning of words.

Feature-based Attentional Amplitude Modulations of the Steady-state Visual Evoked Potentials Reflect Blood Oxygen Level Dependent Changes in Feature-sensitive Visual Areas.

Recent EEG studies have investigated basic principles of feature-based attention by means of frequency-tagged random dot kinematograms in which different colors are simultaneously presented at different temporal frequencies to elicit steady-state visual evoked potentials (SSVEPs). These experiments consistently showed global facilitation of the to-be-attended random dot kinematogram-a basic principle of feature-based attention. SSVEP source estimation suggested that posterior visual cortex from V1 to area hMT+/V5 is broadly activated by frequency-tagged stimuli. What is presently unknown is whether the feature-based attentional facilitation of SSVEPs is a rather unspecific neural response including all visual areas that follow the "on/off," or whether SSVEP feature-based amplitude enhancements are driven by activity in visual areas most sensitive to a specific feature, such as V4v in the case of color. Here, we leverage multimodal SSVEP-fMRI recordings in human participants and a multidimensional feature-based attention paradigm to investigate this question. Attending to shape produced significantly greater SSVEP-BOLD covariation in primary visual cortex compared with color. SSVEP-BOLD covariation during color selection increased along the visual hierarchy, with greatest values in areas V3 and V4. Importantly, in area hMT+/V5, we found no differences between shape and color selection. Results suggest that SSVEP amplitude enhancements in feature-based attention is not an unspecific enhancement of neural activity in all visual areas following the "on/off." These findings open new avenues to investigating neural dynamics of competitive interactions in specific visual areas sensitive to a certain feature in a more economical way and better temporal resolution compared with fMRI.

A source for category-induced global effects of feature-based attention in human prefrontal cortex

Global effects of feature-based attention (FBA) are generally limited to stimuli sharing the same or similar features, as hypothesized in the "feature-similarity gain model." Visual perception, however, often reflects categories acquired via experience/learning; whether the global-FBA effect can be induced by the categorized features remains unclear. Here, human subjects were trained to classify motion directions into two discrete categories and perform a classical motion-based attention task. We found a category-induced global-FBA effect in both the middle temporal area (MT+) and frontoparietal areas, where attention to a motion direction globally spread to unattended motion directions within the same category, but not to those in a different category. Effective connectivity analysis showed that the category-induced global-FBA effect in MT+ was derived by feedback from the inferior frontal junction (IFJ). Altogether, our study reveals a category-induced global-FBA effect and identifies a source for this effect in human prefrontal cortex, implying that FBA is of greater ecological significance than previously thought.

Early sensory gain control is dominated by obligatory and global feature-based attention in top-down shifts of combined spatial and feature-based attention.

What are the dynamics of global feature-based and spatial attention, when deployed together? In an attentional shifting experiment, flanked by three control experiments, we investigated neural temporal dynamics of combined attentional shifts. For this purpose, orange- and blue-frequency-tagged spatially overlapping Random Dot Kinematograms were presented in the left and right visual hemifield to elicit continuous steady-state-visual-evoked-potentials. After being initially engaged in a fixation cross task, participants were at some point in time cued to shift attention to one of the Random Dot Kinematograms, to detect and respond to brief coherent motion events, while ignoring all such events in other Random Dot Kinematograms. The analysis of steady-state visual-evoked potentials allowed us to map time courses and dynamics of early sensory-gain modulations by attention. This revealed a time-invariant amplification of the to-be attended color both at the attended and the unattended side, followed by suppression for the to-be-ignored color at attended and unattended sides. Across all experiments, global and obligatory feature-based selection dominated early sensory gain modulations, whereas spatial attention played a minor modulatory role. However, analyses of behavior and neural markers such as alpha-band activity and event-related potentials to target- and distractor-event processing, revealed clear modulations by spatial attention.

Feature-based attention has a spatial gradient

Feature-based attention has a spatial gradient

Feature-based attention modulates population spatial frequency tuning

Feature-based attention modulates population spatial frequency tuning

A screening method for visual attention disabilities in cerebral palsy with periventricular leukomalacia

PurposePatients with periventricular leukomalacia (PVL) have been reported to have a variety of complications; however, whether these involve impaired visual attention disabilities remains unclear. Therefore, this study aimed to investigate the presence or absence and degree of visual attention disabilities in patients with PVL and propose a screening test that would allow anyone to check for visual attention disabilities easily. MethodsThe study participants were 14 patients with PVL and seven controls with dyskinetic cerebral palsy. All participants performed three types of visual attention tasks: spatial attention tasks, feature-based attention tasks, and object-based attention tasks. The participants also performed counting tasks to determine how many squares of the same size and color could be counted (up to nine). Receiver operating characteristic analysis was used to calculate cutoff values, with disability as the objective variable and the value of the counting task as the explanatory variable. ResultsThe results revealed that patients with PVL often had visual attention disabilities, as indicated by a significant reduction in tasks requiring divided attention. Visual attention disabilities could be detected by a score of ≤8 in the square counting task. ConclusionsThese findings suggest that family members and teachers of patients with PVL can easily screen for visual attention disabilities at home and school to improve mobility precautions in patients with this disability.

Feature-based attention warps the perception of visual features

Selective attention improves sensory processing of relevant information but can also impact the quality of perception. For example, attention increases visual discrimination performance and at the same time boosts apparent stimulus contrast of attended relative to unattended stimuli. Can attention also lead to perceptual distortions of visual representations? Optimal tuning accounts of attention suggest that processing is biased towards “off-tuned” features to maximize the signal-to-noise ratio in favor of the target, especially when targets and distractors are confusable. Here, we tested whether such tuning gives rise to phenomenological changes of visual features. We instructed participants to select a color among other colors in a visual search display and subsequently asked them to judge the appearance of the target color in a 2-alternative forced choice task. Participants consistently judged the target color to appear more dissimilar from the distractor color in feature space. Critically, the magnitude of these perceptual biases varied systematically with the similarity between target and distractor colors during search, indicating that attentional tuning quickly adapts to current task demands. In control experiments we rule out possible non-attentional explanations such as color contrast or memory effects. Overall, our results demonstrate that selective attention warps the representational geometry of color space, resulting in profound perceptual changes across large swaths of feature space. Broadly, these results indicate that efficient attentional selection can come at a perceptual cost by distorting our sensory experience.

The Architecture of Object-Based Attention

The allocation of attention to objects raises several intriguing questions: What are objects, how does attention access them, what anatomical regions are involved? Here, we review recent progress in the field to determine the mechanisms underlying object-based attention. First, findings from unconscious priming and cueing suggest that the preattentive targets of object-based attention can be fully developed object representations that have reached the level of identity. Next, the control of object-based attention appears to come from ventral visual areas specialized in object analysis that project downward to early visual areas. How feedback from object areas can accurately target the object's specific locations and features is unknown but recent work in autoencoding has made this plausible. Finally, we suggest that the three classic modes of attention may not be as independent as is commonly considered, and instead could all rely on object-based attention. Specifically, studies show that attention can be allocated to the separated members of a group-without affecting the space between them-matching the defining property of feature-based attention. At the same time, object-based attention directed to a single small item has the properties of space-based attention. We outline the architecture of object-based attention, the novel predictions it brings, and discuss how it works in parallel with other attention pathways.

Temporal attention

Attention, that is, the ability to focus processing resources on a specific part of sensory input, is often thought of as being mainly allocated in space, toward specific objects or modalities. However, attention can also be allocated within time. Temporal attention can be induced implicitly, that is, through learning of temporal regularities between at least two events, or explicitly, by the active instruction to attend to a specific time point. Moreover, temporal attention can be induced via external rhythmic stimulation. Many studies throughout the last 120 years have shown that, irrespective of the way temporal attention is induced, it facilitates processing of upcoming events. Based on early findings measuring reaction time, researchers initially assumed that temporal attention primarily accelerates motor processing. Within the last 20 years, however, more and more evidence has emerged supporting the view that temporal attention facilitates perceptual processing. Moreover, temporal attention may even interact with other attentional domains such as spatial attention or feature-based attention. In the present article, we summarize classical as well as current findings and theoretical accounts on how temporal attention affects perceptual processing. Furthermore, we sketch current challenges and open questions in research on temporal attention.

A Multimodal 3-D Detector With Attention From the Corresponding Modal

Robust 3D detection based on camera-LiDAR fusion has become a research focus for autonomous driving. Despite the extensive efforts invested, it remains an extremely challenging task to effectively establish fine-grained corresponding relations between different modalities and achieve complementary multimodal fusion free of interference. To these ends, we propose a multimodal 3D detector termed as CFFNet, mainly consisting of a multimodal feature extraction backbone network and a corresponding feature-based attention fusion (CFAF) module. Specifically, the multimodal feature extraction backbone is devised to build a simple yet effective cross-modal correspondence by unifying multimodal features into a shared bird’s eye view (BEV) space. Expressive and noise-suppressed image BEV features are generated from pseudo image voxels, whose depth information is estimated with range-wise attention drawn from LiDAR BEV features. With the prominent heterogeneity of multimodal features taken into consideration, the CFAF module performs a discriminative fusion targeted at informative and contributive features retained in different modalities. The fusion is accomplished by element-wisely reweighting image BEV features with attention generated from differential features of LiDAR. The multimodal feature extraction backbone and CFAF module are both evaluated and proved to offer significant performance gains separately and together. Evaluations conducted on the KITTI 3D object detection dataset show that the proposed CFFNet achieves state-of-the-art performance.

Event-Related Potentials Index Prediction Error Signalling During Perceptual Processing of Emotional Facial Expressions

Humans use socially relevant stimuli to guide perceptual processing of the surrounding environment, with emotional stimuli receiving preferential attention due to their social importance. Predictive coding theory asserts this cognitive process occurs efficiently by combining predictions about what is to be perceived with incoming sensory information, generating prediction errors that are then used to update future predictions. Recent evidence has identified differing neural activity that demonstrates how spatial and feature-based attention may interact with prediction, yet how emotion-guided attention may influence this relationship remains unknown. In the present study, participants viewed a display of two faces in which attention, prediction, and emotion were manipulated, and responded to a face expressing a specific emotion (anger or happiness). The N170 was found to be enhanced by unpredictable as opposed to predictable stimuli, indicating that it indexes general prediction error signalling processes. The N300 amplitudes were also enhanced by unpredictable stimuli, but they were also affected by the attentional status of angry but not happy faces, suggesting that there are differences in prediction error processes indexed by the N170 and N300. Overall, the findings suggest that the N170 and N300 both index violations of expectation for spatial manipulations of stimuli in accordance with prediction error responding processes.

Space- and feature-based attention operate both independently and interactively within latent components of perceptual decision making.

Top-down visual attention filters undesired stimuli while selected information is afforded the lion's share of limited cognitive resources. Multiple selection mechanisms can be deployed simultaneously, but how unique influences of each combine to facilitate behavior remains unclear. Previously, we failed to observe an additive perceptual benefit when both space-based attention (SBA) and feature-based attention (FBA) were cued in a sparse display (Liang & Scolari, 2020): FBA was restricted to higher order decision-making processes when combined with a valid spatial cue, whereas SBA additionally facilitated target enhancement. Here, we introduced a series of design modifications across three experiments to elicit both attention mechanisms within signal enhancement while also investigating the impacts on decision making. First, we found that when highly reliable spatial and feature cues made unique contributions to search (experiment 1), or when each cue component was moderately reliable (experiments 2a and 2b), both mechanisms were deployed independently to resolve the target. However, the same manipulations produced interactive attention effects within other latent decision-making components that depended on the probability of the integrated cueing object. Time spent before evidence accumulation was reduced and responses were more conservative for the most likely pre-cue combination-even when it included an invalid component. These data indicate that selection mechanisms operate on sensory signals invariably in an independent manner, whereas a higher-order dependency occurs outside of signal enhancement.

Global attentional selection of visual features is not associated with selective modulation of posterior alpha-band activity.

Attending to a single feature, such as color or motion, leads to global modulation of neural processing associated with the representation of the attended features. Alpha-band modulations are hypothesized to be a marker (and even a mechanism) of the modulation of neural processing. By adopting a previously used attentional shifting paradigm, we examined whether alpha-band dynamics are linked to sustained Feature-Based-Attentional (FBA) selection. For this purpose, we presented task-irrelevant flickering random dot kinematograms (RDKs) in the periphery that either did or did not share the to-be-attended color of centrally presented task-relevant RDKs and should thus be subject to global FBA selection. Steady-state visual evoked potentials (SSVEPs) and alpha-band activity associated with these task-irrelevant RDKs were analyzed to quantify FBA modulation. Overall, the SSVEP results replicated previous findings: relative to a pre-cue baseline, SSVEP amplitudes for peripheral RDKs were significantly enhanced when these RDKs shared the to-be-attended color of the central RDKs and were not modulated when they shared the centrally to-be-ignored color. Nevertheless, there were no differences in alpha-band amplitude modulations between signals recorded contralateral to the RDKs sharing the centrally attended color and RDKs sharing the centrally ignored color. Hence, alpha-band modulations seem not to index the sustained global selection of attended over unattended feature values within the same feature dimension.

Efficient tuning of attention to narrow and broad ranges of task-relevant feature values

ABSTRACT Feature-based attention is the ability to select relevant information based on visual features, such as a particular colour or motion direction. In contrast to spatial attention, where the attentional focus has been shown to be flexibly adjustable to select small or large regions in space, it is unclear whether feature-based attention can be efficiently tuned to different feature ranges. Here, we establish that the focus of feature-based attention can be adjusted more broadly or narrowly to select currently relevant features. Participants attended to a set of target-coloured dots among distractor dots to detect brief decreases in luminance (Experiments 1a, 1b, 2) or bursts of coherent motion (Experiments 3a, 3b, 4), while varying the range of colours that the target dot spanned across trials. We found that while participants’ performance decreased with larger feature ranges to select, but remained at a relatively high level even at the largest colour range. Our findings suggest that broadening the focus of feature-based attention comes only at a small cost and that selecting large swaths of feature space is surprisingly efficient. These results are consistent with accounts that propose a flexible and generalized set of attentional mechanisms that act across both spatial and feature-based domains.

Combined influence of valence and statistical learning on the control of attention II: Evidence from within-domain additivity.

Attention is biased in favor of stimuli that signal either threat or reward; this experience-dependent attentional bias develops via associative learning and persists into extinction. Physically salient yet task-irrelevant stimuli are also prioritized by the attention system, but the attentional priority of a physically salient distractor can be suppressed when it appears in a location in which it has been frequently encountered in the past. Similar effects of statistical learning on distractor suppression have been observed for distractors appearing in a predictable color. A pair of recent studies demonstrate that statistically learned distractor suppression and valence-based attentional biases combine additively, suggesting independent influences of learning on attentional priority. One limitation of these prior studies, however, is that the effects of statistical learning were defined with respect to spatial attention and the effects of associative learning with respect to feature-based attention. A strong version of the independence account would predict additive influences on attention even when both sources of priority are represented within a single domain of attentional control, which we tested in the present study. The attentional priority of a distractor was elevated when its color was previously associated with electric shock and reduced when its shape was frequently encountered as a distractor in a prior training phase, with these two influences on priority combining additively. Our findings provide strong evidence for the idea that statistical learning and valance-based associative learning exert independent influences on the control of attention, which has implications for contemporary theories of selection history.

Exploring the distinct patterns of pupil dilation between space- and feature-based attention in a visual search task

Exploring the distinct patterns of pupil dilation between space- and feature-based attention in a visual search task

Reconstructing attended and unattended colors from human scalp electroencephalography

Human electroencephalography (EEG) studies have shown that attention enhances relevant over irrelevant visual features (e.g., Andersen et al., 2013). Such amplitude modulations have been a major focus of feature-based attention research, alongside recent studies showing that the spatial pattern of scalp-recorded EEG activity conveys critical information about different stimuli. To date, the majority of these studies have focused on decoding visual-spatial features (location, orientation). Here, we test whether color—a non-spatial feature—can be reconstructed from the scalp activity pattern using steady-state visual evoked potentials (SSVEPs) and inverted encoding modeling (IEM). Furthermore, we test how these color reconstructions vary across different types of feature-based attention tasks. Participants (N=17) performed two color-based attention tasks: 1) a non-competitive task, in which they monitored a single array of colored dots to detect a brief interval of coherent motion; 2) a selective attention task in which participants focused on target-colored dots among distractors to detect a brief luminance decrease. In the selective task, the target and distractor colors were either distinct (180° away on a CIELab colorwheel) or similar (63° away). Stimuli flickered at different frequencies to elicit separable SSVEPs that we used to generate color-selective response profiles based on their spatially distributed patterns. Across both tasks, we found that information about the target and distractor colors was reliably recovered from single trials with IEMs, confirming the usefulness of this technique for investigating feature representations. Model-based reconstructions in the selective attention task were stronger for more distinct colors, suggesting that perceptually similar features might elicit less informative SSVEP signals due to greater overlap in the neural populations that encode them. Broadly, our results demonstrate that SSVEPs along with IEMs can be used to investigate non-spatial visual features that may not be as well represented as spatial information in event-related potentials or alpha-band signals.