Target-distractor similarity predicts visual search efficiency but only for highly similar features.

A major constraining factor for attentional selection is the similarity between targets and distractors. When similarity is low, target items can be identified quickly and efficiently, whereas high similarity can incur large costs on processing speed. Models of visual search contrast a fast, efficient parallel stage with a slow serial processing stage where search times are strongly modulated by the number of distractors in the display. In particular, recent work has argued that the magnitude of search slopes should be inversely proportional to target-distractor similarity. Here, we assessed the relationship between target-distractor similarity and search slopes. In our visual search tasks, participants detected an oddball color target among distractors (Experiments 1 & 2) or discriminated the direction of a triangle in the oddball color (Experiment 3). We systematically varied the similarity between target and distractor colors (along a circular CIELAB color wheel) and the number of distractors in the search array, finding logarithmic search slopes that were inversely proportional to the number of items in the array. Surprisingly, we also found that searches were highly efficient (i.e., near-zero slopes) for targets and distractors that were extremely similar (≤20° in color space). These findings indicate that visual search is systematically influenced by target-distractor similarity across different processing stages. Importantly, we found that search can be highly efficient and entirely unaffected by the number of distractors despite high perceptual similarity, in contrast to the general assumption that high similarity must lead to slow and serial search behavior.

The effect of sports expertise on the performance of orienteering athletes' real scene image recognition and their visual search characteristics.

As a sport conducted in dynamically changing natural environments, orienteering places high demands on athletes' cognitive processing abilities and visual search efficiency. However, previous studies on orienteering have been primarily limited by the use of fixed stimulus materials on computer screens, which are unable to fully simulate authentic sports scenarios. To better understand the sports expertise of orienteering athletes in terms of their real scene image recognition performance and visual search characteristics, this study recruited 40 orienteering athletes, both experts and novices, as participants. By utilizing eye-tracking technology and setting observation points in real-world scenarios to conduct image recognition task tests, the ecological validity of the experiment was further enhanced. The results showed that the experts demonstrated a high level of accuracy and a short response time, with visual search characteristics including few saccade counts, low fixation frequency, concentrated fixation points, simple and clear fixation paths, and higher visual search efficiency. This study further reveals that long-term specialized training will lead to the formation of a unique cognitive structure related to the specific knowledge and long-term memory required by expert orienteering athletes, thereby promoting the development of expert advantage.

Bistable perception of symbolic numbers.

Numerals, that is, semantic expressions of numbers, enable us to have an exact representation of the amount of things. Visual processing of numerals plays an indispensable role in the recognition and interpretation of numbers. Here, we investigate how visual information from numerals is processed to achieve semantic understanding. We first found that partial occlusion of some digital numerals introduces bistable interpretations. Next, by using the visual adaptation method, we investigated the origin of this bistability in human participants. We showed that adaptation to digital and normal Arabic numerals, as well as homologous shapes, but not Chinese numerals, biases the interpretation of a partially occluded digital numeral. We suggest that this bistable interpretation is driven by intermediate shape processing stages of vision, that is, by features more complex than local visual orientations, but more basic than the abstract concepts of numerals.

Cracking the neural code for word recognition in convolutional neural networks.

Learning to read places a strong challenge on the visual system. Years of expertise lead to a remarkable capacity to separate similar letters and encode their relative positions, thus distinguishing words such as FORM and FROM, invariantly over a large range of positions, sizes and fonts. How neural circuits achieve invariant word recognition remains unknown. Here, we address this issue by recycling deep neural network models initially trained for image recognition. We retrain them to recognize written words and then analyze how reading-specialized units emerge and operate across the successive layers. With literacy, a small subset of units becomes specialized for word recognition in the learned script, similar to the visual word form area (VWFA) in the human brain. We show that these units are sensitive to specific letter identities and their ordinal position from the left or the right of a word. The transition from retinotopic to ordinal position coding is achieved by a hierarchy of "space bigram" unit that detect the position of a letter relative to a blank space and that pool across low- and high-frequency-sensitive units from early layers of the network. The proposed scheme provides a plausible neural code for written words in the VWFA, and leads to predictions for reading behavior, error patterns, and the neurophysiology of reading.

Functional interactions underlying visuospatial orthographic processes in Chinese reading.

As a logographic writing system, Chinese reading involves the processing of visuospatial orthographic (ORT) properties. However, this aspect has received relatively less attention in neuroimaging research, which has tended to emphasize phonological (PHO) and semantic (SEM) aspects in processing Chinese characters. Here, we compared the functional correlates supporting all these three processes in a functional MRI single-character reading study, in which 35 native Chinese adults were asked to make ORT, PHO, and SEM judgments in separate task-specific activation blocks. Our findings revealed increased involvement of the right hemisphere in processing Chinese visuospatial orthography, particularly evident in the right ventral occipito-temporal cortex (vOTC). Additionally, time course analysis revealed that the left superior parietal gyrus (SPG) was initially involved in SEM processing but contributed to the visuospatial processing of words in a later time window. Finally, ORT processing demonstrated stronger recruitment of left vOTC-SPG-middle frontal gyrus (MFG) functional connectivity compared to SEM processing. This functional coupling correlated with reduced regional engagement of the left vOTC and MFG, highlighting that visuospatial ORT processes in reading Chinese rely on functional interactions among key regions rather than local regional processes. In conclusion, these findings underscore visuospatial ORT processes as a distinctive feature of reading logographic characters.

On relative word length and transposed-word effects.

It is harder to decide that a sequence of words is ungrammatical when the ungrammaticality is created by transposing two words in a correct sentence (e.g., he wants green these apples), and it is harder to judge that two ungrammatical word sequences are different when the difference is created by transposing two words (e.g., green want these he apples-green these want he apples). In two experiments, we manipulated the relative length of the transposed words such that these words were either the same length (e.g., then you see can it) or different lengths (e.g., then you create can it). The same-length and different-length conditions were matched for syntactic category and word frequency. In Experiment 1 (speeded grammatical decision) we found no evidence for a modulation of transposed-word effects as a function of the relative length of the transposed words. We surmised that this might be due to top-down constraints being the main driving force behind the effects found in the grammatical decision task. However, this was also the case in Experiment 2 (same-different matching with ungrammatical sequences of words) where syntactic constraints were minimized. Given that skilled readers can read sentences composed of words of the same length, our results confirm that word length information alone is not used to encode the order of words in a sequence of words, and especially concerning the order of adjacent words in foveal/parafoveal vision. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effects of machine learning errors on human decision-making: manipulations of model accuracy, error types, and error importance.

This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and L-shaped distractors. They were tasked with categorizing each image as target present or target absent. In Experiment 1, they performed this task without the aid of ML outputs. In Experiments 2-5, they were shown images with bounding boxes, representing the output of an ML model. The outputs could be correct (hits and correct rejections), or they could be erroneous (false alarms and misses). Experiment 2 manipulated the overall accuracy of these mock ML outputs. Experiment 3 manipulated the proportion of different types of errors. Experiments 4 and 5 manipulated the importance of specific types of stimuli or model errors, as well as the framing of the task in terms of human or model performance. These experiments showed that model misses were consistently harder for participants to detect than model false alarms. In general, as the model's performance increased, human performance increased as well, but in many cases the participants were more likely to overlook model errors when the model had high accuracy overall. Warning participants to be on the lookout for specific types of model errors had very little impact on their performance. Overall, our results emphasize the importance of considering human cognition when determining what level of model performance and types of model errors are acceptable for a given task.

Cue relevance drives early quitting in visual search.

Irrelevant salient distractors can trigger early quitting in visual search, causing observers to miss targets they might otherwise find. Here, we asked whether task-relevant salient cues can produce a similar early quitting effect on the subset of trials where those cues fail to highlight the target. We presented participants with a difficult visual search task and used two cueing conditions. In the high-predictive condition, a salient cue in the form of a red circle highlighted the target most of the time a target was present. In the low-predictive condition, the cue was far less accurate and did not reliably predict the target (i.e., the cue was often a false positive). These were contrasted against a control condition in which no cues were presented. In the high-predictive condition, we found clear evidence of early quitting on trials where the cue was a false positive, as evidenced by both increased miss errors and shorter response times on target absent trials. No such effects were observed with low-predictive cues. Together, these results suggest that salient cues which are false positives can trigger early quitting, though perhaps only when the cues have a high-predictive value. These results have implications for real-world searches, such as medical image screening, where salient cues (referred to as computer-aided detection or CAD) may be used to highlight potentially relevant areas of images but are sometimes inaccurate.

Flicker adaptation improves acuity for briefly presented stimuli by reducing crowding.

Adaptation to flickering/dynamic noise improves visual acuity for briefly presented stimuli (Arnold et al., 2016). Here, we investigate whether such adaptation operates directly on our ability to see detail or by changing fixational eye movements and pupil size or by reducing visual crowding. Following earlier work, visual acuity was measured in observers who were either unadapted or who had adapted to a 60-Hz flickering noise pattern. Participants reported the orientation of a white tumbling-T target (four-alternative forced choice [4AFC], ⊤⊣⊥⊢). The target was presented for 110 ms either in isolation or flanked by randomly oriented T's (e.g., ⊣⊤⊢) followed by an isolated (+) or flanked (+++) mask, respectively. We measured fixation stability (using an infrared eye tracker) while observers performed the task (with and without adaptation). Visual acuity improved modestly (around 8.4%) for flanked optotypes following adaptation to flicker (mean, -0.038 ± 0.063 logMAR; p = 0.015; BF10 = 3.66) but did not when measured with isolated letters (mean, -0.008 ± 0.055 logMAR; p = 0.5; BF10 = 0.29). The magnitude of acuity improvement was associated with individuals' (unadapted) susceptibility to crowding (the ratio of crowded to uncrowded acuity; r = -0.58, p = 0.008, BF10 = 7.70) but to neither fixation stability nor pupil size. Confirming previous reports, flicker improved acuity for briefly presented stimuli, but we show that this was only the case for crowded letters. These improvements likely arise from attenuation of sensitivity to a transient low spatial frequency (SF) image structure (Arnold et al., 2016; Tagoh et al., 2022), which may, for example, reduce masking of high SFs by low SFs. We also suggest that this attenuation could reduce backward masking and so reduce foveal crowding.

The effects of different types of emotion words on emotion picture processing - evidence from event-related potential.

Emotional information can be seen everywhere in daily life. Research on emotional words often employs lexical decision tasks to judge the veracity of words, involving only superficial processing and not the deep processing of emotional significance. Therefore, the purpose of this study is to explore the effect of types of emotional words on the processing of emotional pictures. Participants were publicly recruited for a button-press experiment to discuss the impact of emotional words on the processing of emotional pictures from both behavioral and physiological mechanisms. The results of experiment 1 show: (a) in terms of reaction time, the processing speed for negative emotional words was slower, with longer reaction times; (b) In terms of accuracy, positive emotional words had a higher correct rate than negative emotional words. The results of experiment 2 found: (a) a significant main effect of emotional word type in the late processing stage; (b) a significant interaction between emotional word type and congruency. Previously presented emotional words affect the processing of subsequently presented emotional pictures, with differences in the processing of the four types of words, indicating a significant role of language in emotional processing.

Secondary capture: Salience information persistently drives attentional selection.

It is well known that attention is captured by salient objects or events. The notion that attention is attracted by salience information present in the visual field is also at the heart of many influential models of attention. These models typically posit a hierarchy of saliency, suggesting that attention progresses from the most to the least salient item in the visual field. However, despite the significance of this claim in various models, research on eye movements challenges the idea that search strictly follows this saliency hierarchy. Instead, eye-tracking studies have suggested that saliency information has a transient impact, only influencing the initial saccade toward the most salient object, and only if executed swiftly after display onset. While these findings on overt eye movements are important, they do not address covert attentional processes occurring before a saccade is initiated. In the current series of experiments, we explored whether there was evidence for secondary capture-whether attention could be captured by another salient item after the initial capture episode. To explore this, we utilized displays with multiple distractors of varying levels of saliency. Our primary question was whether two distractors with different saliency levels would disrupt search more than a single, highly salient distractor. Across three experiments, clear evidence emerged indicating that two distractors interfered more with search than a single salient distractor. This observation suggests that following initial capture, secondary capture by the next most salient distractor occurred. These findings collectively support the idea that covert attention traverses the saliency hierarchy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Measuring learning and attention to irrelevant distractors in contextual cueing.

Visual search usually improves with repeated exposure to a search display. Previous research suggests that such a "contextual cueing" effect may be supported even by aspects of the search display that participants have been explicitly asked to ignore. Based on this evidence, it has been suggested that the development of contextual cueing over trials does not depend on selective attention. In the present series of experiments, we show that the most common strategy used to prevent participants from paying attention to task-irrelevant distractors often results in suboptimal selection. Specifically, we show that visual search is slower when search displays include many irrelevant distractors. Eye-tracking data show that this happens, at least in part, because participants fixate on them. These results cast doubts on previous demonstrations that contextual cueing is independent of selective attention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Viewpoint adaptation revealed potential representational differences between 2D images and 3D objects.

For convenience and experimental control, cognitive science has relied largely on images as stimuli rather than the real, tangible objects encountered in the real world. Recent evidence suggests that the cognitive processing of images may differ from real objects, especially in the processing of spatial locations and actions, thought to be mediated by the dorsal visual stream. Perceptual and semantic processing in the ventral visual stream, however, has been assumed to be largely unaffected by the realism of objects. Several studies have found that one key difference accounting for differences between real objects and images is actability; however, less research has investigated another potential difference - the three-dimensional nature of real objects as conveyed by cues like binocular disparity. To investigate the extent to which perception is affected by the realism of a stimulus, we compared viewpoint adaptation when stimuli (a face or a kettle) were 2D (flat images without binocular disparity) vs. 3D (i.e., real, tangible objects or stereoscopic images with binocular disparity). For both faces and kettles, adaptation to 3D stimuli induced stronger viewpoint aftereffects than adaptation to 2D images when the adapting orientation was rightward. A computational model suggested that the difference in aftereffects could be explained by broader viewpoint tuning for 3D compared to 2D stimuli. Overall, our finding narrowed the gap between understanding the neural processing of visual images and real-world objects by suggesting that compared to 2D images, real and simulated 3D objects evoke more broadly tuned neural representations, which may result in stronger viewpoint invariance.

Predictions enable top-down pattern separation in the macaque face-processing hierarchy.

Distinguishing faces requires well distinguishable neural activity patterns. Contextual information may separate neural representations, leading to enhanced identity recognition. Here, we use functional magnetic resonance imaging to investigate how predictions derived from contextual information affect the separability of neural activity patterns in the macaque face-processing system, a 3-level processing hierarchy in ventral visual cortex. We find that in the presence of predictions, early stages of this hierarchy exhibit well separable and high-dimensional neural geometries resembling those at the top of the hierarchy. This is accompanied by a systematic shift of tuning properties from higher to lower areas, endowing lower areas with higher-order, invariant representations instead of their feedforward tuning properties. Thus, top-down signals dynamically transform neural representations of faces into separable and high-dimensional neural geometries. Our results provide evidence how predictive context transforms flexible representational spaces to optimally use the computational resources provided by cortical processing hierarchies for better and faster distinction of facial identities.

Retinotopy drives the variation in scene responses across visual field map divisions of the occipital place area.

The occipital place area (OPA) is a scene-selective region on the lateral surface of human occipitotemporal cortex that spatially overlaps multiple visual field maps, as well as portions of cortex that are not currently defined as retinotopic. Here we combined population receptive field modeling and responses to scenes in a representational similarity analysis (RSA) framework to test the prediction that the OPA's visual field map divisions contribute uniquely to the overall pattern of scene selectivity within the OPA. Consistent with this prediction, the patterns of response to a set of complex scenes were heterogeneous between maps. To explain this heterogeneity, we tested the explanatory power of seven candidate models using RSA. These models spanned different scene dimensions (Content, Expanse, Distance), low- and high-level visual features, and navigational affordances. None of the tested models could account for the variation in scene response observed between the OPA's visual field maps. However, the heterogeneity in scene response was correlated with the differences in retinotopic profiles across maps. These data highlight the need to carefully examine the relationship between regions defined as category-selective and the underlying retinotopy, and they suggest that, in the case of the OPA, it may not be appropriate to conceptualize it as a single scene-selective region.

Tracking the brain signature of (mis)spelled logotypes via letter transpositions and replacements.

All leading models of visual word recognition assume a hierarchical process that progressively converts the visual input into abstract letter and word representations. However, the results from recent behavioral studies suggest that the mental representations of words with a highly consistent visual format, such as logotypes, may comprise not only purely abstract information but also perceptual information. This hypothesis would explain why participants often misperceive transposed-letter misspellings with the original base words to a larger degree in logotypes (e.g., SASMUNG, but not SARVUNG, is perceived as SAMSUNG) than in common words. The present experiment examined the electrophysiological signature behind the identification of correctly spelled and misspelled logotypes (via letter transposition or replacement) in an ERP go/no-go semantic categorization experiment. Results showed that N400 amplitudes for transposed-letter misspelled logotypes (SASMUNG) and intact logotypes (SAMSUNG) did not differ significantly across various time windows (until 600 ms), whereas replacement-letter misspelled logotypes (SARVUNG) yielded consistently larger N400 amplitudes. These findings reveal that the mental representations of logotypes are particularly resistant to minor orthographic changes, which has important theoretical and applied (e.g., marketing) implications.

The visual statistical learning overcomes scene dissimilarity through an independent clustering process.

Contextual cueing is a phenomenon of visual statistical learning observed in visual search tasks. Previous research has found that the degree of deviation of items from its centroid, known as variability, determines the extent of generalization for that repeated scene. Introducing variability increases dissimilarity between multiple occurrences of the same repeated layout significantly. However, current theories do not explain the mechanisms that help to overcome this dissimilarity during contextual cue learning. We propose that the cognitive system initially abstracts specific scenes into scene layouts through an automatic clustering unrelated to specific repeated scenes, and subsequently uses these abstracted scene layouts for contextual cue learning. Experiment 1 indicates that introducing greater variability in search scenes leads to a hindering in the contextual cue learning. Experiment 2 further establishes that conducting extensive visual searches involving spatial variability in entirely novel scenes facilitates subsequent contextual cue learning involving corresponding scene variability, confirming that learning clustering knowledge precedes the contextual cue learning and is independent of specific repeated scenes. Overall, this study demonstrates the existence of multiple levels of learning in visual statistical learning, where item-level learning can serve as material for layout-level learning, and the generalization reflects the constraining role of item-level knowledge on layout-level knowledge.

Manipulating and measuring variation in deep neural network (DNN) representations of objects.

We explore how DNNs can be used to develop a computational understanding of individual differences in high-level visual cognition given their ability to generate rich meaningful object representations informed by their architecture, experience, and training protocols. As a first step to quantifying individual differences in DNN representations, we systematically explored the robustness of a variety of representational similarity measures: Representational Similarity Analysis (RSA), Centered Kernel Alignment (CKA), and Projection-Weighted Canonical Correlation Analysis (PWCCA), with an eye to how these measures are used in cognitive science, cognitive neuroscience, and vision science. To manipulate object representations, we next created a large set of models varying in random initial weights and random training image order, training image frequencies, training category frequencies, and model size and architecture and measured the representational variation caused by each manipulation. We examined both small (All-CNN-C) and commonly-used large (VGG and ResNet) DNN architectures. To provide a comparison for the magnitude of representational differences, we established a baseline based on the representational variation caused by image-augmentation techniques used to train those DNNs. We found that variation in model randomization and model size never exceeded baseline. By contrast, differences in training image frequency and training category frequencies caused representational variation that exceeded baseline, with training category frequency manipulations exceeding baseline earlier in the networks. These findings provide insights into the magnitude of representational variations that can be expected with a range of manipulations and provide a springboard for further exploration of systematic model variations aimed at modeling individual differences in high-level visual cognition.

Action Planning Renders Objects in Working Memory More Attentionally Salient.

A rapidly growing body of work suggests that visual working memory (VWM) is fundamentally action oriented. Consistent with this, we recently showed that attention is more strongly biased by VWM representations of objects when we plan to act on those objects in the future. Using EEG and eye tracking, here, we investigated neurophysiological correlates of the interactions between VWM and action. Participants (n = 36) memorized a shape for a subsequent VWM test. At test, a probe was presented along with a secondary object. In the action condition, participants gripped the actual probe if it matched the memorized shape, whereas in the control condition, they gripped the secondary object. Crucially, during the VWM delay, participants engaged in a visual selection task, in which they located a target as fast as possible. The memorized shape could either encircle the target (congruent trials) or a distractor (incongruent trials). Replicating previous findings, we found that eye gaze was biased toward the VWM-matching shape and, importantly, more so when the shape was directly associated with an action plan. Moreover, the ERP results revealed that during the selection task, future action-relevant VWM-matching shapes elicited (1) a stronger Ppc (posterior positivity contralateral), signaling greater attentional saliency; (2) an earlier PD (distractor positivity) component, suggesting faster suppression; (3) a larger inverse (i.e., positive) sustained posterior contralateral negativity in incongruent trials, consistent with stronger suppression of action-associated distractors; and (4) an enhanced response-locked positivity over left motor regions, possibly indicating enhanced inhibition of the response associated with the memorized item during the interim task. Overall, these results suggest that action planning renders objects in VWM more attentionally salient, supporting the notion of selection-for-action in working memory.

Trial history contributes to the optimal tuning of attention.

In visual search tasks, targets are difficult to find when they are similar to the surrounding nontargets. In this scenario, it is optimal to tune attention to target features that maximize the difference between target and nontargets. We investigated whether the optimal tuning of attention is driven by biases arising from previously attended stimuli (i.e., trial history). Consistent with the effects of trial history, we found that optimal tuning was stronger when a single target-nontarget relation was repeated than when two target-nontarget relations alternated randomly. Detailed analysis of blocks with random alternation showed that optimal tuning was stronger when the target-nontarget relation probed in the current trial matched the relation in the previous trial. We evaluated several mechanisms that may underlie the effects of trial history, such as priming of attentional set, switch costs, and sensory adaptation. However, none of the accounts was able to fully account for the pattern of results. (PsycInfo Database Record (c) 2024 APA, all rights reserved).