Data · dataset · 2023
High familiar faces have both eyes recognition and holistic processing advantages
Listed in ScienceDB
People recognize familiar faces better than unfamiliar faces (Burton & Jenkins, 2012).
Description
However, it remains elusive whether this familiarity advantage is supported by part-based and/or holistic processing. Wang and colleagues (2015, 2019) found both enhanced part-based and holistic processing in eye relative to mouth regions (i.e., in a region-selective manner) for own-race and own-species faces, i.e., faces with more experience.
In this study, we examined the roles of eyes (part-based, region-selective) and holistic processing in the face familiarity effect. Face familiarity was tested at three levels: high-familiar (faces of students from the same department and the same grade who almost always attended all courses together), low-familiar (faces of students from the same department but different grades who attended some courses together), and unfamiliar (faces of schoolmates from different departments who seldom attended the same courses).
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Using an old/new task in Experiment 1, we found that participants recognized eyes from high-familiar faces better than low-familiar and unfamiliar ones, but not for mouths, indicating a region-selective, eyes familiarity effect. Using the “Perceptual field” Paradigm (Van Belle et al., 2015) in Experiment 2, we observed a strong inversion effect for high-familiar faces, a weaker inversion effect for low-familiar faces, but non-significant inversion effect for unfamiliar faces, indicating that holistic processing plays a role in face familiarity effect.
Taken together, our results demonstrated that familiarity, like other experience-based variables (e.g., race and species), can improve both eyes processing and holistic processing, suggesting eyes processing play a role in face holistic processing.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.07944 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.07944 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |