Evidence map›Paper›PMID 33751199›Full record

ArticlePsychological research2022

Pictorial low-level features in mental images: evidence from eye fixations.

Corinna S Martarelli, Fred W Mast

Abstract read
PubMed Publisher
In one paragraph

Article in Psychological research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 54% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

2 authors at 2 institutions in 1 country.

Corinna S MartarelliFaculty of Psychology, Swiss Distance University Institute, Brig, Switzerland. corinna.martarelli@fernuni.ch.ORCID http://orcid.org/0000-0001-9160-793X
Fred W MastDepartment of Psychology, University of Bern, Bern, Switzerland.
Swiss Distance University of Applied Sciences · CHUniversity of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is known that eye movements during object imagery reflect areas visited during encoding. But will eye movements also reflect pictorial low-level features of imagined stimuli? In this paper, three experiments are reported in which we investigate whether low-level properties of mental images elicit specific eye movements. Based on the conceptualization of mental images as depictive representations, we expected low-level visual features to influence eye fixations during mental imagery, in the absence of a visual input. In a first experiment, twenty-five participants performed a visual imagery task with high vs. low spatial frequency and high vs. low contrast gratings. We found that both during visual perception and during mental imagery, first fixations were more often allocated to the low spatial frequency-high contrast grating, thus showing that eye fixations were influenced not only by physical properties of visual stimuli but also by its imagined counterpart. In a second experiment, twenty-two participants imagined high contrast and low contrast stimuli that they had not encoded before. Again, participants allocated more fixations to the high contrast mental images than to the low contrast mental images. In a third experiment, we ruled out task difficulty as confounding variable. Our results reveal that low-level visual features are represented in the mind's eye and thus, they contribute to the characterization of mental images in terms of how much perceptual information is re-instantiated during mental imagery.

Indexed as

Fixation, OcularImaginationEye MovementsHumansVisual Perception

Identifiers

PMID33751199
OpenAlexW3137686169

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.