Evidence map›Paper›PMID 31401660›Full record

ArticleExperimental brain research2019

Material surface properties modulate vection strength.

Yuki Morimoto, Hirotaro Sato, Chihiro Hiramatsu, Takeharu Seno

Abstract read
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In one paragraph

Article in Experimental brain research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

4 authors.

Yuki MorimotoFaculty of Design, Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka, 815-8540, Japan.
Hirotaro SatoFaculty of Design, Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka, 815-8540, Japan.
Chihiro HiramatsuFaculty of Design, Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka, 815-8540, Japan.
Takeharu SenoFaculty of Design, Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka, 815-8540, Japan. seno@design.kyushu-u.ac.jp.

Funding

MEXT KAKENHI Grant number JP26700016, JP17K12869MEXT KAKENHI JP18H01100
6 · The paper itself

Abstract

Realistic appearance and complexity in the visual field are known to affect the strength of vection (visually induced self-motion perception). Although surface properties of materials are, therefore, expected to be visual features that influence vection, to date, the results have been mixed. Here, we used computer graphics to simulate self-motion through rendered 3D tunnels constructed from nine different materials (bark, ceramic, fabric, fur, glass, leather, metal, stone, and wood). There are three ways in which the new stimuli are changed from those found in previous studies: (1) as they move, their appearances interactively change with the 3D structures of the simulated world, as do all the lighting effects and 3D geometric appearances, (2) they are colored, (3) and their components covered a large portion of the visual field. The entire inner surface of each tunnel was composed from one of the nine materials, and optic flow was evoked when an observer virtually moved through the tunnel. Bark, fabric, leather, stone, and wood effectively induced strong vection, whereas, ceramic, glass, fur, and metal did not. Regression analyses suggested that low-level image features such as the lighting and amplitude of spatial frequency were the main factors that modulated vection strength. Additionally, subjective impressions of the nine surface materials showed that the perceived depth, smoothness, and rigidity were related to the perceived vection strength. Overall, our results indicate that surface properties of materials do indeed modulate vection strength.

Indexed as

MotionAdultDepth PerceptionFemaleHumansMaleMotion PerceptionOptic FlowSurface PropertiesVisual FieldsComputer graphicsMaterialSimulationSpatial frequencySurface propertiesVection

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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.