Evidence map›Paper›PMID 33828752›Full record

ArticleJournal of eye movement research2019

Microsaccades Distinguish Looking From Seeing.

Eva Krueger, Andrea Schneider, Ben D Sawyer, Alain Chavaillaz, Andreas Sonderegger, Rudolf Groner, P A Hancock

Abstract read
In one paragraph

Article in Journal of eye movement research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Eva Krueger
Andrea Schneider
Ben D SawyerMassachusetts Institute of Technology, USA.
Alain ChavaillazUniversity of Fribourg, Switzerland.
Andreas SondereggerÉcole Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
Rudolf GronerUniversity of Bern, Switzerland.
P A HancockUniversity of Central Florida, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding our visual world requires both looking and seeing. Dissociation of these processes can result in the phenomenon of inattentional blindness or 'looking without seeing'. Concomitant errors in applied settings can be serious, and even deadly. Current visual data analysis cannot differentiate between just 'looking' and actual processing of visual information, i.e., 'seeing'. Differentiation may be possible through the examination of microsaccades; the involuntary, smallmagnitude saccadic eye movements that occur during processed visual fixation. Recent work has suggested that microsaccades are post-attentional biosignals, potentially modulated by task. Specifically, microsaccade rates decrease with increased mental task demand, and increase with growing visual task difficulty. Such findings imply that there are fundamental differences in microsaccadic activity between visual and nonvisual tasks. To evaluate this proposition, we used a high-speed eye tracker to record participants in looking for differences between two images or, doing mental arithmetic, or both tasks in combination. Results showed that microsaccade rate was significantly increased in conditions that require high visual attention, and decreased in conditions that require less visual attention. The results support microsaccadic rate reflecting visual attention, and level of visual information processing. A measure that reflects to what extent and how an operator is processing visual information represents a critical step for the application of sophisticated visual assessment to real world tasks.

Indexed as

eye trackingFixational eye movementsmicrosaccadesvisual attentionvisual load

Identifiers

PMID33828752
PMCPMC7962679

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.