Evidence map›Paper›PMID 27833159›Full record

ArticleScientific reports2016

Exploring time- and frequency- dependent functional connectivity and brain networks during deception with single-trial event-related potentials.

Jun-Feng Gao, Yong Yang, Wen-Tao Huang, Pan Lin, Sheng Ge, Hong-Mei Zheng, Ling-Yun Gu, Hui Zhou, Chen-Hong Li, Ni-Ni Rao

Abstract read
In one paragraph

Article in Scientific reports, 2016. 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

10 authors.

Jun-Feng GaoKey Laboratory of Cognitive Science of State Ethnic Affairs Commission and Laboratory of Membrane Ion Channels and Medicine, College of Biomedical Engineering, South-Central University for Nationalities, Wuhan, China.
Yong YangSchool of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China.
Wen-Tao HuangKey Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Pan LinKey Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, China.
Sheng GeKey Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, China.
Hong-Mei ZhengHubei Key Laboatory of Medical Information Analysis &Tumor Diagnosis and Treatment, Wuhan, China.
Ling-Yun GuKey Laboratory of Cognitive Science of State Ethnic Affairs Commission and Laboratory of Membrane Ion Channels and Medicine, College of Biomedical Engineering, South-Central University for Nationalities, Wuhan, China.
Hui ZhouKey Laboratory of Cognitive Science of State Ethnic Affairs Commission and Laboratory of Membrane Ion Channels and Medicine, College of Biomedical Engineering, South-Central University for Nationalities, Wuhan, China.
Chen-Hong LiKey Laboratory of Cognitive Science of State Ethnic Affairs Commission and Laboratory of Membrane Ion Channels and Medicine, College of Biomedical Engineering, South-Central University for Nationalities, Wuhan, China.
Ni-Ni RaoKey Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To better characterize the cognitive processes and mechanisms that are associated with deception, wavelet coherence was employed to evaluate functional connectivity between different brain regions. Two groups of subjects were evaluated for this purpose: 32 participants were required to either tell the truth or to lie when facing certain stimuli, and their electroencephalogram signals on 12 electrodes were recorded. The experimental results revealed that deceptive responses elicited greater connectivity strength than truthful responses, particularly in the θ band on specific electrode pairs primarily involving connections between the prefrontal/frontal and central regions and between the prefrontal/frontal and left parietal regions. These results indicate that these brain regions play an important role in executing lying responses. Additionally, three time- and frequency-dependent functional connectivity networks were proposed to thoroughly reflect the functional coupling of brain regions that occurs during lying. Furthermore, the wavelet coherence values for the connections shown in the networks were extracted as features for support vector machine training. High classification accuracy suggested that the proposed network effectively characterized differences in functional connectivity between the two groups of subjects over a specific time-frequency area and hence could be a sensitive measurement for identifying deception.

Indexed as

DeceptionEvoked PotentialsLie DetectionAdultBrainBrain WavesElectroencephalographyFemaleHumansMaleNeural PathwaysWavelet AnalysisYoung Adult

Identifiers

PMID27833159
PMCPMC5105133

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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.