MouseView.js: Reliable and valid attention tracking in web-based experiments using a cursor-directed aperture

Anwyl-Irvine, Alexander; Armstrong, Thomas J.; Dalmaijer, Edwin S.

doi:10.31234/osf.io/rsdwg

Cited by 6 publications

(8 citation statements)

References 35 publications

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“…By moving their cursor around, participants can continuously uncover small sections of the target image at a time, imitating foveation. MouseView measures have been shown to significantly predict real human fixation measures (Anwyl-Irvine et al, 2021). In the current experiment, all MouseView images were presented at a size of 500 × 500 pixels with an aperture of 5% of the viewing window.…”

Section: Methodsmentioning

confidence: 99%

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The Visual Mandela Effect as Evidence for Shared and Specific False Memories Across People

Prasad

Bainbridge

2022

Psychol Sci

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The Mandela effect is an Internet phenomenon describing shared and consistent false memories for specific icons in popular culture. The visual Mandela effect is a Mandela effect specific to visual icons (e.g., the Monopoly Man is falsely remembered as having a monocle) and has not yet been empirically quantified or tested. In Experiment 1 ( N = 100 adults), we demonstrated that certain images from popular iconography elicit consistent, specific false memories. In Experiment 2 ( N = 60 adults), using eye-tracking-like methods, we found no attentional or visual differences that drive this phenomenon. There is no clear difference in the natural visual experience of these images (Experiment 3), and these errors also occur spontaneously during recall (Experiment 4; N = 50 adults). These results demonstrate that there are certain images for which people consistently make the same false-memory error, despite the majority of visual experience being the canonical image.

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Section: Methodsmentioning

confidence: 99%

“…Procedure. To determine how people viewed these images, we used MouseView, a mouse-tracking method analogous to eye tracking (Anwyl-Irvine et al, 2021). Generally, a target image is obscured by a white overlay, and MouseView creates a circular aperture that moves with the computer mouse to reveal the image underneath it (Fig.…”

Section: Methodsmentioning

confidence: 99%

The Visual Mandela Effect as Evidence for Shared and Specific False Memories Across People

Prasad

Bainbridge

2022

Psychol Sci

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“…This experiment employed MouseView.js (Anwyl-Irvine, Armstrong, & Dalmaijer, 2021), which allowed us to record the incremental reading of sentences in an online experiment.…”

Section: Methodsmentioning

confidence: 99%

“…In Experiment 2, we investigated whether this folk etymology effect (the association of words that overlap in form and meaning) also influences sentence comprehension. Participants made semantic relatedness decisions about pairs of sentences containing those cue and target words (e.g., The kids dodged something followed by She tried to evade/elude the officer), and we measured fixation duration on the target words (using MouseView.js; Anwyl-Irvine, Armstrong & Dalmaijer, 2021). If people make use of similar-sounding attractor words to facilitate meaning access at the sentence level, then participants should read the target word faster (as measured in first-pass fixation) when the second sentence contains a non-arbitrary target compared to an arbitrary target.…”

Section: The Present Studymentioning

confidence: 99%

Similar-sounding words flesh out fuzzy meanings

Haslett¹,

Cai²

2022

Preprint

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The distributional hypothesis (that the meaning of a word corresponds to the contexts where it occurs) struggles to explain how people represent low-frequency words. When distributional information is lacking, people utilize phonological cues, but those cues indicate broad categories, not word meanings per se. We conducted two preregistered experiments to test the hypothesis that people recruit similar-sounding words to represent and access the meanings of low-frequency words. In Experiment 1, native English speakers made semantic relatedness decisions about a cue word (e.g., dodge) followed by a non-arbitrary target (evade) that overlaps in form and meaning with an attractor word (avoid, which is semantically related to dodge) or by an arbitrary control (elude) that is matched with the non-arbitrary target on formal and distributional similarity to the cue word. As we predicted, participants decided faster and more often that non-arbitrary targets, compared to controls, were semantically related to cues. In Experiment 2, participants made semantic relatedness decisions about sentences containing the same cue and target words (e.g., The kids dodged something and She tried to evade/elude the officer). We used MouseView.js to blur the sentences and create a fovea-like aperture directed by the participant’s cursor, allowing us to measure fixation duration. While we did not observe the predicted difference between non-arbitrary and arbitrary targets themselves, we found a lag effect, with shorter fixations on words following non-arbitrary targets, indicating an advantage in accessing the meanings of non-arbitrary words. These experiments provide evidence that similar-sounding words bolster mental representations of low-frequency words.

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“…While artificial attention collected in this way cannot be considered equivalent to eye-tracking metrics, this cursor-controlled spotlight method of capturing spatial attention in online experiments has been explored in other work. In particular, a validation study was performed by the authors of MouseView.js, a JavaScript library supporting experiments of this kind, and finding that patterns of dwell time were similar to those collected with the same stimuli in an eye-tracking experiment(Anwyl-Irvine et al, 2021). Note that this study uses its own implementation of the cursor spotlight method since MouseView.js was released publicly after completion of data collection.Downloaded from http://direct.mit.edu/isal/proceedings-pdf/isal/33/85/1930020/isal_a_00419.pdf by guest on 13 December 2021…”

mentioning

confidence: 98%

Active Dynamical Prospection: Modeling Mental Simulation as Particle Filtering for Sensorimotor Control during Pathfinding

Gordon¹,

Chuang²

2021

The 2021 Conference on Artificial Life

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What do humans do when confronted with a common challenge: we know where we want to go but we are not yet sure the best way to get there, or even if we can. This is the problem posed to agents during spatial navigation and pathfinding, and its solution may give us insights into the more abstract domain of planning in general. In this work, we model pathfinding behavior in a continuous, explicitly exploratory paradigm. In our task, participants (and agents) must coordinate both visual exploration and navigation within a partially observable environment. In this work, we analyze behavioral data from 81 human participants in a novel pathfinding paradigm conducted as an online experiment. We then propose a model of prospective mental simulation as particle filtering, coupled with an attention mechanism inspired by active inference. Lastly, we share an instantiation of this proposal in a computational agent. Our model, Active Dynamical Prospection, demonstrates similar patterns of map solution rate, path selection, and trial duration, as well as attentional behavior (at both aggregate and individual levels) when compared with data from human participants. We also find that both distal attention and delay prior to first move (both potential correlates of prospective simulation) are predictive of task performance.

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MouseView.js: Reliable and valid attention tracking in web-based experiments using a cursor-directed aperture

Cited by 6 publications

References 35 publications

The Visual Mandela Effect as Evidence for Shared and Specific False Memories Across People

The Visual Mandela Effect as Evidence for Shared and Specific False Memories Across People

Similar-sounding words flesh out fuzzy meanings

Active Dynamical Prospection: Modeling Mental Simulation as Particle Filtering for Sensorimotor Control during Pathfinding

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