Evidence map›Paper›PMID 28729935›Full record

ArticleBrain and behavior2017

Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.

Qian Guo, Tiantong Zhou, Wenjie Li, Li Dong, Suhong Wang, Ling Zou

Abstract read
In one paragraph

Article in Brain and behavior, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Trial
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  5. Article
  6. [Study of denoising of simultaneous electroencephalogram-functional magnetic resonance imaging signal based on real-time constrained independent components analysis].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2019
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Qian GuoSchool of Information Science and Engineering Changzhou University Changzhou Jiangsu China.
Tiantong ZhouSchool of Information Science and Engineering Changzhou University Changzhou Jiangsu China.
Wenjie LiSchool of Information Science and Engineering Changzhou University Changzhou Jiangsu China.
Li DongSchool of Life Science and Technology University of Electronic Science and Technology of China Chengdu Sichuan China.
Suhong WangChangzhou NO.1 People's Hospital affiliated with Suzhou University Changzhou Jiangsu China.
Ling ZouSchool of Information Science and Engineering Changzhou University Changzhou Jiangsu China.ORCID 0000-0001-5547-2871

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExecutive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years.

objectiveGambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli.

methodsIn this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors.

resultsThe results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results.

conclusionsThe EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.

Indexed as

ElectroencephalographyAdultBrainBrain MappingDecision MakingEmotionsEvoked PotentialsExecutive FunctionFemaleHumansMagnetic Resonance ImagingMalePrefrontal CortexRewardYoung Adultgeneral linear modelhot executive functionK‐means clustering methodregressorsimultaneous EEG‐fMRI

Identifiers

PMID28729935
PMCPMC5516603

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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.