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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | Brain Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3425/13/3/485 |
| _version_ | 1827750889827336192 |
|---|---|
| author | Yuchao Liu Yin Zhang Zhongyi Jiang Wanzeng Kong Ling Zou |
| author_facet | Yuchao Liu Yin Zhang Zhongyi Jiang Wanzeng Kong Ling Zou |
| author_sort | Yuchao Liu |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-11T06:50:47Z |
| format | Article |
| id | doaj.art-9a374ccf88d74b439af101191a92a891 |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-03-11T06:50:47Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj.art-9a374ccf88d74b439af101191a92a8912023-11-17T10:00:30ZengMDPI AGBrain Sciences2076-34252023-03-0113348510.3390/brainsci13030485Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI InvestigationYuchao Liu0Yin Zhang1Zhongyi Jiang2Wanzeng Kong3Ling Zou4School of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, ChinaSchool of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, ChinaSchool of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, ChinaCollege of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, ChinaSchool of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, ChinaBackground: 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.https://www.mdpi.com/2076-3425/13/3/485simultaneous EEG–fMRIreward processingtensor factorizationdata fusionblind source separation |
| spellingShingle | Yuchao Liu Yin Zhang Zhongyi Jiang Wanzeng Kong Ling Zou Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation Brain Sciences simultaneous EEG–fMRI reward processing tensor factorization data fusion blind source separation |
| 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 | simultaneous EEG–fMRI reward processing tensor factorization data fusion blind source separation |
| url | https://www.mdpi.com/2076-3425/13/3/485 |
| work_keys_str_mv | AT yuchaoliu exploringneuralmechanismsofrewardprocessingusingcoupledmatrixtensorfactorizationasimultaneouseegfmriinvestigation AT yinzhang exploringneuralmechanismsofrewardprocessingusingcoupledmatrixtensorfactorizationasimultaneouseegfmriinvestigation AT zhongyijiang exploringneuralmechanismsofrewardprocessingusingcoupledmatrixtensorfactorizationasimultaneouseegfmriinvestigation AT wanzengkong exploringneuralmechanismsofrewardprocessingusingcoupledmatrixtensorfactorizationasimultaneouseegfmriinvestigation AT lingzou exploringneuralmechanismsofrewardprocessingusingcoupledmatrixtensorfactorizationasimultaneouseegfmriinvestigation |