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

Background: It 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 t...

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Autores principales: Liu, Yuchao, Zhang, Yin, Jiang, Zhongyi, Kong, Wanzeng, Zou, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046863/
https://www.ncbi.nlm.nih.gov/pubmed/36979295
http://dx.doi.org/10.3390/brainsci13030485
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author Liu, Yuchao
Zhang, Yin
Jiang, Zhongyi
Kong, Wanzeng
Zou, Ling
author_facet Liu, Yuchao
Zhang, Yin
Jiang, Zhongyi
Kong, Wanzeng
Zou, Ling
author_sort Liu, Yuchao
collection PubMed
description Background: It 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. Methods: First, 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. Results: The 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. Conclusion: This 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.
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spelling pubmed-100468632023-03-29 Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation Liu, Yuchao Zhang, Yin Jiang, Zhongyi Kong, Wanzeng Zou, Ling Brain Sci Article Background: It 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. Methods: First, 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. Results: The 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. Conclusion: This 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. MDPI 2023-03-13 /pmc/articles/PMC10046863/ /pubmed/36979295 http://dx.doi.org/10.3390/brainsci13030485 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Yuchao
Zhang, Yin
Jiang, Zhongyi
Kong, Wanzeng
Zou, Ling
Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation
title Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation
title_full Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation
title_fullStr Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation
title_full_unstemmed Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation
title_short Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation
title_sort exploring neural mechanisms of reward processing using coupled matrix tensor factorization: a simultaneous eeg–fmri investigation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046863/
https://www.ncbi.nlm.nih.gov/pubmed/36979295
http://dx.doi.org/10.3390/brainsci13030485
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