Evidence map›Paper›PMID 39738346›Full record

ArticleScientific reports2024

Differences in spatiotemporal dynamics for processing specific semantic categories: An EEG study.

Trang Thi Le, Do Anh Quan Luong, Hyosung Joo, Dongseok Kim, Jihwan Woo

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Trang Thi LeDepartment of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
Do Anh Quan LuongDepartment of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
Hyosung JooDepartment of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
Dongseok KimDepartment of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
Jihwan WooDepartment of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea. jhwoo@ulsan.ac.kr.

Funding

National Research Foundation of Korea NRF-2020R1A2C2003319
6 · The paper itself

Abstract

Semantic processing is an essential mechanism in human language comprehension and has profound implications for speech brain-computer interface technologies. Despite recent advances in brain imaging techniques and data analysis algorithms, the mechanisms underlying human brain semantic representations remain a topic of debate, specifically whether this occurs through the activation of selectively separated cortical regions or via a network of distributed and overlapping regions. This study investigates spatiotemporal neural representation during the perception of semantic words related to faces, numbers, and animals using electroencephalography. Source-level analysis focuses on contrasting neural responses to different semantic categories. Critical intervals used in the source contrast analysis are defined using the peak duration of global field power. Effective connectivity, determined through a causality analysis of brain regions activated for semantic processing, is explored. The findings reveal the necessity of a distributed network of regions for processing specific semantic categories and provide evidence suggesting the existence of a neural substrate for semantic representations.

Indexed as

Brain MappingElectroencephalographySemanticsAdultBrainComprehensionFemaleHumansMaleYoung Adultbrain‐computer interfaceeffective connectivityelectroencephalographylexical-semantic processingspatiotemporal dynamics

Identifiers

PMID39738346
PMCPMC11685728

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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.