Evidence map›Paper›PMID 29445098›Full record

ArticleScientific reports2018

Representational similarity analysis reveals task-dependent semantic influence of the visual word form area.

Xiaosha Wang, Yangwen Xu, Yuwei Wang, Yi Zeng, Jiacai Zhang, Zhenhua Ling, Yanchao Bi

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

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  17. The Brain Connectome for Chinese Reading.Neuroscience bulletin · 2022
    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.

Xiaosha WangCollege of Information Science and Technology, Beijing Normal University, Beijing, 100875, China.
Yangwen XuNational Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
Yuwei WangResearch Center for Brain-inspired Intelligence & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
Yi ZengResearch Center for Brain-inspired Intelligence & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
Jiacai ZhangCollege of Information Science and Technology, Beijing Normal University, Beijing, 100875, China. jiacai.zhang@bnu.edu.cn.
Zhenhua LingNational Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, 230027, China. zhling@ustc.edu.cn.
Yanchao BiNational Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Access to semantic information of visual word forms is a key component of reading comprehension. In this study, we examined the involvement of the visual word form area (VWFA) in this process by investigating whether and how the activity patterns of the VWFA are influenced by semantic information during semantic tasks. We asked participants to perform two semantic tasks - taxonomic or thematic categorization - on visual words while obtaining the blood-oxygen-level-dependent (BOLD) fMRI responses to each word. Representational similarity analysis with four types of semantic relations (taxonomic, thematic, subjective semantic rating and word2vec) revealed that neural activity patterns of the VWFA were associated with taxonomic information only in the taxonomic task, with thematic information only in the thematic task and with the composite semantic information measured by word2vec in both semantic tasks. Furthermore, the semantic information in the VWFA cannot be explained by confounding factors including orthographic, low-level visual and phonological information. These findings provide positive evidence for the presence of both orthographic and task-relevant semantic information in the VWFA and have significant implications for the neurobiological basis of reading.

Indexed as

ReadingAdolescentAdultBrain MappingFemaleHumansLanguageLinguisticsMagnetic Resonance ImagingMaleOccipital LobeSemanticsTemporal LobeVisual PerceptionYoung Adult

Identifiers

PMID29445098
PMCPMC5813029

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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.