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Mean search times for each task in Experiment 1. When searching for the physically larg- er target item, search times where shorter when the target items was numerically large as well, compared to when it was numerically small. Error bars represent 95% confidence intervals for with- in-subject designs (Morey, 2008).
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The current study investigates an interaction between numbers and physical size (i.e. size congruity) in visual search. In three experiments, participants had to detect a physically large (or small) target item amongst physically small (or large) distractors in a search task comprising single- digit numbers. The relative numerical size of the digit...
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Theories of visual search assume that selection is driven by an active template representation of the target object. Earlier studies suggest that template activation occurs prior to search, but the temporal dynamics of such preactivation remain unclear. Two experiments employed microsaccades to track both general preparation (i.e., anticipation of...
It has been proposed that only one visual working memory (VWM) representation can be activated to influence perception directly, whereas other VWM representations are accessory items which have little influence on visual selection. The sole active VWM representation might reflect a fundamental bottleneck in the information processing of human being...
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Citations
... The association of numerical information with perception and action provides another illustrative example of this embodied principle of knowledge representation. For example, the processing of numerically small or large numbers interacts with the visual search and manual grasping of small or large objects [56,99]. Sensory and motor codes are consequently an integral part of the representations of semantic concepts, although these concepts appear abstract, such as numbers or mathematical relations. ...
Numbers are present in every part of modern society and the human capacity to
use numbers is unparalleled in other species. Understanding the mental and
neural representations supporting this capacity is of central interest to cognitive
psychology, neuroscience, and education. Embodied numerical cognition theory
suggests that beyond the seemingly abstract symbols used to refer to numbers,
their underlying meaning is deeply grounded in sensorimotor experiences, and
that our specific understanding of numerical information is shaped by actions
related to our fingers, egocentric space, and experiences with magnitudes in
everyday life. We propose a sensorimotor perspective on numerical cognition
in which number comprehension and numerical proficiency emerge from
grounding three distinct numerical core concepts: magnitude, ordinality, and
cardinality.
... Santens and Verguts (2011) proposed that the size-congruity effect stems from either early representational overlap (an early interaction account) or a late interaction account reflecting response competition. A variety of different techniques have been used to test between these competing accounts, including electrophysiological techniques (Schwarz & Heinze, 1998;Szűcs & Soltész, 2007, 2008, neuroimaging (Cohen Kadosh et al., 2007), computer mouse tracking , visual search (Krause et al., 2017;Sobel et al., 2016;Sobel et al., 2017), and mathematical modelling (Bowman & Faulkenberry, 2020;Faulkenberry et al., 2018). However, consistent conclusions have remained elusive; some studies support the early interaction account, whereas others support the late interaction account. ...
When people choose the physically larger of two numerals, they are often slower when relative physical size is incongruent with numerical magnitude. This size-congruity effect not only informs our understanding of mental representations of number, but also serves as an index for numerical ability in individuals. In this paper, we apply methods of Haaf and Rouder (2017) to examine the size-congruity effect through the lens of individual differences. We develop and compare hierarchical Bayesian mixed models with varying levels of constraint on the individual size-congruity effects. In three data sets, the winning model was one in which the size-congruity effect was constrained to be positive. This indicates that, at least in the context of a physical comparison task with Arabic numerals, everyone exhibits a positive size-congruity effect. We discuss these results in the context of measurement fidelity and theory-building in numerical cognition.
... Another factor that may have affected our results is the size of the stimuli. Smaller images or greater number of squares may had induced higher cognitive workload, as the size 675 of the stimuli affects visual search (63). ...
Background and objective:
The cognitive workload is an important component in performance psychology, ergonomics, and human factors. Publicly available datasets are scarce, making it difficult to establish new approaches and comparative studies. In this work, COLET-COgnitive workLoad estimation based on Eye-Tracking dataset is presented.
Methods:
Forty-seven (47) individuals' eye movements were monitored as they solved puzzles involving visual search activities of varying complexity and duration. The participants' cognitive workload level was evaluated with the subjective test of NASA-TLX and this score is used as an annotation of the activity. Extensive data analysis was performed in order to derive eye and gaze features from low-level eye recorded metrics, and a range of machine learning models were evaluated and tested regarding the estimation of the cognitive workload level.
Results:
The activities induced four different levels of cognitive workload. Multi tasking and time pressure have induced a higher level of cognitive workload than the one induced by single tasking and absence of time pressure. Multi tasking had a significant effect on 17 eye features while time pressure had a significant effect on 7 eye features. Both binary and multi-class identification attempts were performed by testing a variety of well-known classifiers, resulting in encouraging results towards cognitive workload levels estimation, with up to 88% correct predictions between low and high cognitive workload.
Conclusions:
Machine learning analysis demonstrated potential in discriminating cognitive workload levels using only eye-tracking characteristics. The proposed dataset includes a much higher sample size and a wider spectrum of eye and gaze metrics than other similar datasets, allowing for the examination of their relations with various cognitive states.
... study were of different lengths and categories. These differences may affect user performance because features such as the physical size and familiarity of target could guide attention in visual search(Krause, Bekkering, Pratt & Lindemann, 2017; Wolfe1 & Horowitz, 2017). Thus, in the present study, users can only use single gesture in every target search and the list length and category were controlled. ...
We compared three list scrolling gestures including sliding to scroll, moving a regular scrollbar, and scrolling through alphabetic index, in a name locating task on mobile phone. We found that scrolling through alphabetic index was the fastest independent of target locations. Moreover, for near-reaching targets RT was shorter for sliding to scroll than moving scrollbar, but it took sliding longer than moving scrollbar for far-reaching targets. Gesture evaluation scores of alphabetic index increased and those of sliding to scroll decreased over time. The different pre- and post-task rating patterns for gestures are due to their differential fatigue and emotional changes. The present study provides insights into users’ mental models for three list scrolling gestures and implications for future gesture design.
... Another factor that may have affected our results is the size of the stimuli. Smaller images or greater number of squares may had induced higher cognitive workload, as the size of the stimuli affects visual search [63] . ...
... A recent examination of the size congruity effect using these line-segment forms found evidence that the same interactions between physical symbol size and numeric magnitude persist with these closely equivalent symbols [13]. Specifically, participants were faster to find a physically larger number symbol when that symbol represented a larger numeric magnitude, even when the symbol's visual features are nearly identical to the distractors. ...
... Previous studies of numerosity on symbol comparison tasks, including visual search experiments (e.g., [27]), drew comparisons between markedly distinct visual stimuli, and did not control for possible confounds related to the physical similarity of comparison digits. The current experiment provides such control, using the ideal case of number symbol comparisons when the physical features of the stimuli are equivalent [13], and omitting the physical size manipulations that are typical of investigations using the size congruity effect. ...
In visual search tasks, physically large target stimuli are more easily identified among small distractors than are small targets among large distractors. The present study extends this finding by presenting preliminary evidence of a new search asymmetry: stimuli that symbolically represent larger magnitude are identified more easily among featurally equivalent distractors that represent smaller magnitude. Participants performed a visual search task using line-segment digits representing the numbers 2 and 5, and the numbers 6 and 9, as well as comparable non-numeric control stimuli. In three experiments, we found that search times are faster when the target is a digit that represents a larger magnitude than the distractor, although this pattern was not evident in one additional experiment. The results provide suggestive evidence that the magnitude of a number symbol can affect perceptual comparisons between number symbols, and that the semantic meaning of a target stimulus can systematically affect visual search.
... Previous studies have demonstrated that the processing of non-numerical symbolic stimuli, such as dice pattern (Nuerk, Wood, & Willmes, 2005), physical size (Krause, Bekkering, Pratt, & Lindemann, 2017), luminance levels (Fumarola et al., 2014), or tone (Rusconi, Kwan, Giordano, Umilta, & Butterworth, 2006), can elicit the SNARC effect. In the current study, we provided subjects with two comparison standards (i.e., 3 and 7), cued by one of two colored rectangles. ...
People respond to small numbers faster with the left hand and respond to large numbers faster with the right hand, a phenomenon known as the Spatial-Numerical Association of Response Codes (SNARC) effect. Whether the SNARC effect originates from culturally determined long-term experience or the task-set-influenced temporary associations among spaces, locations, and numerical magnitudes in working memory (WM) is still controversial. In the present study, we used a trisection paradigm in which numbers were divided into three categories (small: 1, 2; middle: 4, 5, 6; and large: 8, 9) to explore whether the central executive control can modulate the SNARC effect. Participants were serially presented with a cue and a target number. The cue denoted a task rule, which informed participants to compare the target number with either 3 or 7. The cue was either switched or repeated across trials. We found that the SNARC effects were observed in the cue-switching condition. In the cue-repeat condition, the SNARC effect disappeared. These findings suggest that the SNARC effect is modulated by set-shifting-related central executive control in WM, supporting the view that the SNARC effect is WM-dependent.
... Given the strong asymmetry in the perception of vertical and horizontal sizes, it is reasonable to ask whether a similar effect could be identified in non-symbolic numerical estimation. The fact that a significant body of literature indicates a link between spatial and numerical abilities (e.g., de Hevia, Vallar, & Girelli, 2008;Krause, Bekkering, Pratt, & Lindemann, 2017) also legitimates such a question. Many studies suggest that non-symbolic numerical estimation is affected by continuous quantities, such as the cumulative surface area (sum of areas) or convex hull (overall space occupied by the most lateral items) of the stimuli (Gebuis & Reynvoet, 2012a, 2012bLeibovich, Katzin, Harel, & Henik, 2017;but see DeWind, Adams, Platt, & Brannon, 2015;Cicchini, Anobile, & Burr, 2016;Park, Dewind, Woldorff, & Brannon, 2016 for a different perspective). ...
Many studies have investigated whether numerical and spatial abilities share similar cognitive systems. A novel approach to this issue consists of investigating whether the same perceptual biases underlying size illusions can be identified in numerical estimation tasks. In this study, we required adult participants to estimate the number of white dots in arrays made of white and black dots displayed in such a way as to generate horizontal–vertical illusions with inverted T and L configurations. In agreement with previous literature, we found that participants tended to underestimate the target numbers. However, in the presence of the illusory patterns, participants were less inclined to underestimate the number of vertically aligned white dots. This reflects the perceptual biases underlying horizontal–vertical illusions. In addition, we identified an enhanced illusory effect when participants observed vertically aligned white dots in the T shape compared to the L shape, a result that resembles the length bisection bias reported in the spatial domain. Overall, we found the first evidence that numerical estimation differs as a function of the vertical or horizontal displacement of the stimuli. In addition, the involvement of the same perceptual biases observed in spatial tasks supports the idea that spatial and numerical abilities share similar cognitive processes.
... It was also found that by Chandler that larger text leads to better accuracy and search time [19].Fleetwood and Byrne [20] studied the effects of icon size and border in visual search strategies through eye tracking experiments, and developed a corresponding model. In a study on numbers, Krause et al. [21] explored the interaction of physical size (size congruity) and numbers in a visual search process that involved either physically large or small distractors. They found a size congruity effect. ...
In order to correctly read and interpret interface information shown on the interface of vital signs monitor, the challenging problems of misreading and misinterpreting the information must be addressed. Therefore, a visual search experiment that the text characteristics of the interface is carried out in this study to categorize parameterized information and encode parameterized numbers on a monitoring interface. The interface of a centralized vital signs monitor is simulated, and target searching of information objects is carried out in an experiment with three sets of characteristic variables: font size, background and text color, and spacing and location of the parameterized information. The experimental results show that the relative spacing of the information elements on the interface should be not too large or small. When the spacing is 30px, 38px, 46px, and 86px, the visual search process requires a long period time and it is easy to misinterpret the information. With an increase in the spacing, the plotted visual search response to different font sizes is a V-shape, while the rate of accuracy becomes an inverted V-shape. Compared to a font size 35pt and 55pt, a font size of 45pt results in the highest search efficiency and rate of accuracy. However, the background color has no significant effect on target searching in terms of reaction time. The findings show that the results in this study can be used as a guideline for the interface design of visual monitoring systems with diverse characters and spacing.
... And yet, the fact that incongruity between the cue's meaning and color can affect visual search performance is surprising; whereas color is undoubtedly a guiding feature in visual search, an item's semantic associations are typically presumed not to guide search (Wolfe & Horowitz, 2004. Nevertheless, recent studies have shown that in a visual search for a numerical target, incongruity between numerical size and physical size (i.e., numerical Stroop;Dadon & Henik, 2017) can influence visual search performance (Krause, Bekkering, Pratt, & Lindemann, 2017;Sobel, Puri, & Faulkenberry, 2016). To explain how sensory-semantic incongruity can influence visual search performance even though semantic associations are probably not guiding features for visual search, the target's semantic feature (numerical size) is presumed not to influence the selection stage, during which the search items' visual feature (physical size) guides attention to select one item for further processing. ...
... Then, only after an item has been selected on the basis of its visual features, sensory-semantic incongruity influences the decision stage (Risko, Maloney, & Fugelsang, 2013;Sobel & Puri, 2018). To extend on experiments that have found a numerical Stroop effect in visual search (Krause et al., 2017;Sobel et al., 2016), here we sought to develop a visual search experiment in which incongruity between a target's meaning and color has the opportunity to influence the decision stage of processing. Next, we describe the rationale underlying each of our experimental design decisions. ...
... The University of Central Arkansas Institutional Review Board approved all experimental procedures, and we treated participants in accordance with the ethical guidelines stipulated by the American Psychological Association (2017). In light of recent studies that have revealed a numerical Stroop effect in visual search (Krause et al., 2017;Sobel et al., 2016), an effect with a similarly large d = 1.25 would require a minimum of 14 participants to achieve 80% power at an alpha of 0.05 (Bausell & Li, 2002). A total of 16 students (one male, 15 female) between 19 and 29 (M = 21.5) ...
The fact that the Stroop effect is replicated much more often than the reverse Stroop effect has been attributed to the notion that in the traditional paradigm, which requires a verbal response, responding to the visual color with a color name requires translation of the perceptual stimulus to a verbal code, while reading the word does not (Durgin, 2000). Alternatively, Blais and Besner (2006) argue that the relative robustness of the Stroop compared to the reverse Stroop effect can be predicted by the strength of association between the features and the processing typically associated with the task. Accordingly, if identification of the target’s color or the target word (as in the traditional Stroop paradigm) is more strongly associated with semantic processing than perceptual processing, the target’s meaning should interfere with identification of the target’s color more than the target’s color interferes with reporting the word. In contrast, if localization is more strongly associated with perceptual processing, the target’s color should interfere with localizing the target word more than vice versa. Participants viewed color words in either the congruent or incongruent ink color, and were asked to either identify the meaning of target words or their color (experiment 1), or localize target words among other words based on either word or visual color cues (experiment 2). Consistent with the strength-of-association explanation, the Stroop effect was larger than the reverse Stroop for identification, but smaller than the reverse Stroop for localization. Experiments 3 and 4 replicated the larger reverse compared to Stroop effect in localization, while also controlling for any contribution of faster overall RTs to the smaller Stroop interference in experiment 2. Thus, whereas the Stroop effect may dominate in identification tasks, the reverse Stroop effect appears to be reliably elicited by localization, supporting the strength-of-association account of Stroop interference.
