Evidence map›Paper›PMID 36046210›Full record

ArticleFrontiers in human neuroscience2022

Detection of deviance in Japanese kanji compound words.

Yuka Egashira, Yoshimi Kaga, Atsuko Gunji, Yosuke Kita, Motohiro Kimura, Naruhito Hironaga, Hiroshige Takeichi, Sayuri Hayashi, Yuu Kaneko, Hidetoshi Takahashi and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in human neuroscience, 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
0.6field-weighted citation impact, top 32% 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, 2 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

13 authors at 7 institutions in 2 countries.

Yuka EgashiraDepartment of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Yoshimi KagaDepartment of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Atsuko GunjiDepartment of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Yosuke KitaCognitive Brain Research Unit (CBRU), Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Motohiro KimuraDepartment of Information Technology and Human Factors, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
Naruhito HironagaBrain Center, Faculty of Medicine, Kyushu University, Fukuoka, Japan.
Hiroshige TakeichiDepartment of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Sayuri HayashiDepartment of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Yuu KanekoDepartment of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Hidetoshi TakahashiIntegrative Brain Imaging Center, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Takashi HanakawaIntegrative Brain Imaging Center, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Takashi OkadaDepartment of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
Masumi InagakiDepartment of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.
National Center of Neurology and Psychiatry · JPNational Institute of Mental Health · JPKōchi University · JPKyushu University · JPNational Institute of Advanced Industrial Science and Technology · JPUniversity of Helsinki · FIYokohama National University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reading fluency is based on the automatic visual recognition of words. As a manifestation of the automatic processing of words, an automatic deviance detection of visual word stimuli can be observed in the early stages of visual recognition. To clarify whether this phenomenon occurs with Japanese kanji compounds-since their lexicality is related to semantic association-we investigated the brain response by utilizing three types of deviants: differences in font type, lexically correct or incorrect Japanese kanji compound words and pseudo-kanji characters modified from correct and incorrect compounds. We employed magnetoencephalography (MEG) to evaluate the spatiotemporal profiles of the related brain regions. The study included 22 adult native Japanese speakers (16 females). The abovementioned three kinds of stimuli containing 20% deviants were presented during the MEG measurement. Activity in the occipital pole region of the brain was observed upon the detection of font-type deviance within 250 ms of stimulus onset. Although no significant activity upon detecting lexically correct/incorrect kanji compounds or pseudo-kanji character deviations was observed, the activity in the posterior transverse region of the collateral sulcus (pCoS)-which is a fusiform neighboring area-was larger when detecting lexically correct kanji compounds than when detecting pseudo-kanji characters. Taken together, these results support the notion that the automatic detection of deviance in kanji compounds may be limited to a low-level feature, such as the stimulus stroke thickness.

Indexed as

automatic processingkanji compoundslexical processingMEGparafoveal visionreading abilityvisual word processing

Identifiers

PMID36046210
PMCPMC9421146
OpenAlexW4291465436

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.