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22 results for “Visual search”
Dataset from: "Reward expectation facilitates context learning and attentional guidance in visual search"
<p>Dataset for Bergmann N, Koch D, Schubö A (2019). Reward expectation facilitates context learning and attentional guidance in visual search, <em>Journal of Vision</em>, 19(3). <a href="https://doi.org/10.1167/19.3.10">https://doi.org/10.1167/19.3.10</a></p>
PLAE web app enables powerful searching and multiple visualizations across one million unified single-cell ocular transcriptomes
<p>Supplementary Data for "PLAE web app enables powerful searching and multiple visualizations across one million unified single-cell ocular transcriptomes"</p> <p> </p>
Reward draws the eye, uncertainty holds the eye: Associative learning modulates distracter interference in visual search.
<p>Eye tracking data and statistical analysis of:</p> <p>Koenig, S., Kadel, H., Uengoer, M., Schubö, A., & Lachnit, H. (2017). Reward draws the eye, uncertainty holds the eye: Associative learning modulates distracter interference in visual search. <em>Frontiers in Behavioral Neuroscience</em>. doi: 10.3389/fnbeh.2017.00128.</p> <p> Abstract: Stimuli in our sensory environment differ with respect to their physical salience, but moreover may acquire motivational salience by association with reward. If we repeatedly observed that reward is available in the context of a particular cue, but absent in the context of another cue, the former typically attracts more attention than the latter. However, we also may encounter cues uncorrelated with reward. A cue with 50% reward contingency may induce an average reward expectancy, but at the same time induces high reward uncertainty. In the current experiment we examined how both values, reward expectancy and uncertainty, affected overt attention. Two different colors were established as predictive cues for low reward and high reward respectively. A third color was followed by high reward on 50% of the trials and thus induced uncertainty. Colors then were introduced as distractors during search for a shape target and we examined the relative potential of the color distractors to capture and hold the first fixation. We observed that capture frequency corresponded to reward expectancy while capture duration corresponded to uncertainty. The results may suggest that within trial, reward expectancy is represented at an earlier time window than uncertainty.</p>
Head-motion and eye-gaze behavior reveal audio-visual target search strategies - dataset
<p>Participants were tasked with finding a target stimulus in the presence of a number of auditory distractors. </p> <p>The target stimulus (audio-only, audio-visual or visual-only) was presented at the central position for 3 seconds, after which the stimulus was moved to one of 24 positions around the participant. The other 23 positions all contained a visual distractor and 0, 1, 2, 3, 5, 7 or 11 auditory distractors (evenly spaced). </p> <p>Based on the eye and headtracking data, we calculated the FOV and target localization time and the maximum headrotation into the wrong direction. </p> <p>FOV localization time: time it took to bring target within FOV. <br>Target localization time: From FOV to response.</p> <p>These datasets contain both the tracking data and the summarized data. </p> <p>Columns "av_stim_x_y" list for each of the 24 AV stimuli (which both served as the targets and distractors), the id, the angle at which it was present during the trial and the visual and audio status.</p> <p>FUNDING: </p> <p>The research was supported by the Centre for Applied Hearing<br>research (CAHR) through a research consortium agreement with<br>GN Resound, Oticon, and Widex. The funders had no role in<br>study design, data collection and analysis, decision to publish, or<br>preparation of the article.</p>
SubDiv17: A Dataset for Investigating Subjectivity in the Visual Diversification of Image Search Results
<p>This dataset facilitates the comparison of approaches aiming at the diversification of image search results. The dataset was explicitly designed for general-purpose, multi-topic queries and provides multiple ground truth annotations to allow for the exploration of the subjectivity aspect in the general task of diversification. The dataset provides images and their metadata retrieved from Flickr for around 200 complex queries. Additionally, to encourage experimentations (and cooperations) from different communities such as information and multimedia retrieval, a broad range of pre-computed descriptors is provided. The dataset was successfully validated during the MediaEval 2017 Retrieving Diverse Social Images task using 29 submitted runs. For more information, please see <a href="https://doi.org/10.1145/3204949.3208122">https://doi.org/10.1145/3204949.3208122</a>.</p>
Humans trade-off search costs and accuracy in a combined visual search and perceptual task
<p>Data as well as MATLAB code for model fitting and to generate ideal observer predictions for the following publication:</p> <p>Wagner, I., Henare, D., Tünnermann, J., Schubö, A., & Schütz, A., C. (accepted). Humans trade-off search costs and accuracy in a combined visual search and perceptual task. <em>Attention, Perception, & Psychophysics</em>.</p> <p>The archive "data" contains two .csv file with data of participants that were recorded in the two experimental conditions (single-target: dat_cond1.csv, double-target: dat_cond2.csv). Each row in the .csv files corresponds to one gaze shift that was detected for a given trial of a given participants in a given condition. For more information about what data is stored in which column, please consult the README.rtf file in the "data" archive.</p> <p>The archive "probabilistcGenerativeModel" contains script to fit the probabilistic generative model and to generate ideal observer predictions. Please consult the README.rtf file in the archive for more information.</p> <p>The file "supplement_tradeOffSearchCostsAndAccuracy.docx" is the supplementary material for the publication. The supplement contains an extensive formal description of the probabilistic generative model, and additional supplementary plots. This file corresponds to the supplement which is referenced on the publication website of this manuscript.</p> <p>For further questions, please contact:<br> Ilja.Wagner[at]psychol.uni-giessen.de or a.schuetz[at]uni.marburg.de</p>
Visual reinforcement shapes eye movements in visual search
<p>Dataset from the following publication:</p> <p>Paeye, C., Schütz, A. C., & Gegenfurtner, K. R. (2016). Visual reinforcement shapes eye movements in visual search. Journal of Vision, 16(10):15, 1–15, <a>doi:10.1167/16.10.15 <span></span></a><a></a></p>
Raw data of visual search parameters of individuals with normal trichromacy and colour vision deficiency
<p><strong><span>Background</span></strong><span>: Colour-related search tasks are common in many professional fields. The study investigated whether increasing chromatic saturation can enhance the visual performance of individuals with colour vision deficiency (CVD) in colour-related search tasks.</span></p> <p><strong><span>Methods</span></strong><span>: 10 normal trichromats (5M, 5F; Mean (SD) age: 23.1 (3.3) years) and 15 individuals with CVD [8 deutans and 7 protans identified by HRR plates] (14M, 1F; aged 28.6 (8.7) years) participated in this study. Four naturalistic sceneries of everyday tasks/ birds, animals, and flowers of 15 different colour combinations (1 pair of colours in each combination. e.g., 'brown/black' or 'red/green') were presented in 'low' saturation, 'original' (unaltered images) and 'high' saturation condition using the Psychopy program on a colour-calibrated monitor. On each trial, the subject was asked to identify a specific-coloured target. </span></p> <p><span><strong>Results</strong>: </span><span>Overall, the visual search performance index (expressed as product of accuracy and a reciprocal of reaction time (%correct*s<sup>-1</sup>) of the normal trichromats [Mean (SD):77.76% correct*s<sup>-1</sup> (16.32)] was significantly higher than CVD [45.71 % correct*s<sup>-1</sup> (18.95)] in the "original" test images (p = 0.001), but in individuals with CVD, there was no significant difference between 'original' [45.71 % correct*s<sup>-1</sup> (18.95)] and 'high' saturation condition ([47.43 % correct*s<sup>-1</sup> (20.07)]; p > 0.05). However, colour-wise, increased saturation showed improvements (≥ 10 %) in protans mainly for 'red' combinations with other colours such as white (i.e., 'red/white'), purple, orange, grey, green, brown, and black.</span></p> <p><strong><span>Conclusion</span></strong><span>:</span><span> The study suggests that increasing the saturation of certain colour combinations can potentially aid in the visual search performance of individuals with CVD. This knowledge will help in better counselling and management of the patients.</span></p>
Psychometric Testing and Cue Utilization During Cued Visual Search
ClinicalTrials.gov study NCT04964674. IPD Sharing: YES. Countries: 1. Publications: 2.
Raw data of visual search parameters of individuals with normal trichromacy and colour vision deficiency
Open the record for dataset details and reuse information.
Data from: Measuring visual search and distraction in immersive virtual reality
Open the record for dataset details and reuse information.
Supplementary material 1 from: Grimm-Seyfarth A, Zarzycka A, Nitz T, Heynig L, Weissheimer N, Lampa S, Klenke R (2019) Performance of detection dogs and visual searches for scat detection and discrimination amongst related species with identical diets. Nature Conservation 37: 81-98. https://doi.org/10.3897/natureconservation.37.48208
: Data type: statistical data
Negative emotions enhance memory-guided attention in a visual search task by increasing frontoparietal, insular, and parahippocampal cortical activity
<p>Previous literature has demonstrated that long-term memory representations guide the deployment of attentional resources during visual search in real-world pictures. However, it is currently unknown whether such a memory-guided visual search effect might be affected by the emotional context of the picture. Here, we addressed this question using functional magnetic resonance imaging (fMRI). Participants were asked to encode the position of a high-contrast target stimulus embedded in emotional (negative or positive) or neutral pictures. At retrieval, they performed a visual search for the target presented at the same location as encoding, but at a much lower contrast. Behavioral data showed that negative emotional pictures enhanced the effect of memory-guided attention, improving participants’ target detection performance. At the neural level, this effect was supported by increased activation in a large circuit of regions involving the dorsal and ventral frontoparietal cortex, insular and parahippocampal cortex. We propose that these regions might form an integrated neural circuit that is recruited to select and process previously encoded target locations (i.e., memory-guided attention sustained by the frontoparietal cortex) embedded in emotional contexts (i.e., emotional contexts recollection supported by the parahippocampal cortex and emotional monitoring supported by the insular cortex). Ultimately, these findings reveal that negative emotions can enhance memory-guided visual search performance by increasing neural activity in a large-scale brain circuit, contributing to disentangle the complex relationship between emotion, attention, and memory.</p>
Task Switching Behavior Between Target Templates During Visual Search in Healthy Adults
ClinicalTrials.gov study NCT05786651. IPD Sharing: YES. Countries: 1. Publications: 0.
Data from: The effect of mood state on visual search times for detecting a target in noise: an application of smartphone technology
The study of visual perception has largely been completed without regard to the influence that an individual's emotional status may have on their performance in visual tasks. However, there is a growing body of evidence to suggest that mood may affect not only creative abilities and interpersonal skills but also the capacity to perform low-level cognitive tasks. Here, we sought to determine whether rudimentary visual search processes are similarly affected by emotion. Specifically, we examined whether an individual's perceived happiness level affects their ability to detect a target in noise. To do so, we employed pop-out and serial visual search paradigms, implemented using a novel smartphone application that allowed search times and self-rated levels of happiness to be recorded throughout each twenty-four-hour period for two weeks. This experience sampling protocol circumvented the need to alter mood artificially with laboratory-based induction methods. Using our smartphone application, we were able to replicate the classic visual search findings, whereby pop-out search times remained largely unaffected by the number of distractors whereas serial search times increased with increasing number of distractors. While pop-out search times were unaffected by happiness level, serial search times with the maximum numbers of distractors (n = 30) were significantly faster for high happiness levels than low happiness levels (p = 0.02). Our results demonstrate the utility of smartphone applications in assessing ecologically valid measures of human visual performance. We discuss the significance of our findings for the assessment of basic visual functions using search time measures, and for our ability to search effectively for targets in real world settings.
Eye Movements in Visual Search
ClinicalTrials.gov study NCT05472961. IPD Sharing: YES. Countries: 1. Publications: 0.
SSVEP and Distractor Processing During Visual Search
ClinicalTrials.gov study NCT05633238. IPD Sharing: YES. Countries: 1. Publications: 0.
Isolating and Mitigating Sequentially Dependent Perceptual Errors in Clinical Visual Search
ClinicalTrials.gov study NCT04332783. IPD Sharing: YES. Countries: 1. Publications: 0.
Task Switching Between Target Templates During Visual Search in Healthy Adults
ClinicalTrials.gov study NCT05709743. IPD Sharing: YES. Countries: 1. Publications: 0.
An Investigation of Attentional and Inhibitory Processes During Active Visual Search in Humans
ClinicalTrials.gov study NCT06587113. IPD Sharing: YES. Countries: 1. Publications: 0.
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