Evidence map›Paper›PMID 36979295›Full record

ArticleBrain sciences2023

Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG-fMRI Investigation.

Yuchao Liu, Yin Zhang, Zhongyi Jiang, Wanzeng Kong, Ling Zou

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Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Yuchao LiuSchool of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, China.
Yin ZhangSchool of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China.
Zhongyi JiangSchool of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, China.
Wanzeng KongCollege of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-0113-6968
Ling ZouSchool of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, China.ORCID 0000-0001-5547-2871

Funding

Ling Zou 2020E10010-04Ling Zou BE2021012-2Ling Zou BE2021012-5Ling Zou CE20225034Yuchao Liu KYCX22_3075
6 · The paper itself

Abstract

backgroundIt is crucial to understand the neural feedback mechanisms and the cognitive decision-making of the brain during the processing of rewards. Here, we report the first attempt for a simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) study in a gambling task by utilizing tensor decomposition.

methodsFirst, the single-subject EEG data are represented as a third-order spectrogram tensor to extract frequency features. Next, the EEG and fMRI data are jointly decomposed into a superposition of multiple sources characterized by space-time-frequency profiles using coupled matrix tensor factorization (CMTF). Finally, graph-structured clustering is used to select the most appropriate model according to four quantitative indices.

resultsThe results clearly show that not only are the regions of interest (ROIs) found in other literature activated, but also the olfactory cortex and fusiform gyrus which are usually ignored. It is found that regions including the orbitofrontal cortex and insula are activated for both winning and losing stimuli. Meanwhile, regions such as the superior orbital frontal gyrus and anterior cingulate cortex are activated upon winning stimuli, whereas the inferior frontal gyrus, cingulate cortex, and medial superior frontal gyrus are activated upon losing stimuli.

conclusionThis work sheds light on the reward-processing progress, provides a deeper understanding of brain function, and opens a new avenue in the investigation of neurovascular coupling via CMTF.

Indexed as

blind source separationdata fusionreward processingsimultaneous EEG–fMRItensor factorization

Identifiers

PMID36979295
PMCPMC10046863

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