Using independent component analysis to extract a cross-modality and individual-specific brain baseline pattern
The ongoing brain activity serves as a baseline that supports both internal and external cognitive processes. However, its precise nature remains unclear. Considering that people display various patterns of brain activity even when engaging in the same task, it is reasonable to believe that individu...
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Elsevier
2024-12-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811924004221 |
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| author | Wei Liu Xuemin Zhang |
| author_facet | Wei Liu Xuemin Zhang |
| author_sort | Wei Liu |
| collection | DOAJ |
| description | The ongoing brain activity serves as a baseline that supports both internal and external cognitive processes. However, its precise nature remains unclear. Considering that people display various patterns of brain activity even when engaging in the same task, it is reasonable to believe that individuals possess their unique brain baseline pattern. Using spatial independent component analysis on a large sample of fMRI data from the Human Connectome Project (HCP), we found an individual-specific component which can be consistently extracted from either resting-state or different task states and is reliable over months. Compared to functional connectome fingerprinting, it is much more stable across different fMRI modalities. Its stability is closely related to high explained variance and is minimally influenced by factors such as noise, scan duration, and scan interval. We propose that this component underlying the ongoing activity represents an individual-specific baseline pattern of brain activity. |
| format | Article |
| id | doaj-art-cdae1e7d00694c28a7e1f3bd0314d732 |
| institution | Kabale University |
| issn | 1095-9572 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj-art-cdae1e7d00694c28a7e1f3bd0314d7322024-11-29T06:23:00ZengElsevierNeuroImage1095-95722024-12-01303120925Using independent component analysis to extract a cross-modality and individual-specific brain baseline patternWei Liu0Xuemin Zhang1Beijing Key Laboratory of Applied Experimental Psychology. National Demonstration Center for Experimental Psychology Education (Beijing Normal University). Faculty of Psychology, Beijing Normal University, Beijing, People's Republic of China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of ChinaBeijing Key Laboratory of Applied Experimental Psychology. National Demonstration Center for Experimental Psychology Education (Beijing Normal University). Faculty of Psychology, Beijing Normal University, Beijing, People's Republic of China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People's Republic of China; Corresponding author.The ongoing brain activity serves as a baseline that supports both internal and external cognitive processes. However, its precise nature remains unclear. Considering that people display various patterns of brain activity even when engaging in the same task, it is reasonable to believe that individuals possess their unique brain baseline pattern. Using spatial independent component analysis on a large sample of fMRI data from the Human Connectome Project (HCP), we found an individual-specific component which can be consistently extracted from either resting-state or different task states and is reliable over months. Compared to functional connectome fingerprinting, it is much more stable across different fMRI modalities. Its stability is closely related to high explained variance and is minimally influenced by factors such as noise, scan duration, and scan interval. We propose that this component underlying the ongoing activity represents an individual-specific baseline pattern of brain activity.http://www.sciencedirect.com/science/article/pii/S1053811924004221Brain baselineIndependent component analysisFunctional connectome fingerprintingExplained varianceFunctional magnetic resonance imaging |
| spellingShingle | Wei Liu Xuemin Zhang Using independent component analysis to extract a cross-modality and individual-specific brain baseline pattern NeuroImage Brain baseline Independent component analysis Functional connectome fingerprinting Explained variance Functional magnetic resonance imaging |
| title | Using independent component analysis to extract a cross-modality and individual-specific brain baseline pattern |
| title_full | Using independent component analysis to extract a cross-modality and individual-specific brain baseline pattern |
| title_fullStr | Using independent component analysis to extract a cross-modality and individual-specific brain baseline pattern |
| title_full_unstemmed | Using independent component analysis to extract a cross-modality and individual-specific brain baseline pattern |
| title_short | Using independent component analysis to extract a cross-modality and individual-specific brain baseline pattern |
| title_sort | using independent component analysis to extract a cross modality and individual specific brain baseline pattern |
| topic | Brain baseline Independent component analysis Functional connectome fingerprinting Explained variance Functional magnetic resonance imaging |
| url | http://www.sciencedirect.com/science/article/pii/S1053811924004221 |
| work_keys_str_mv | AT weiliu usingindependentcomponentanalysistoextractacrossmodalityandindividualspecificbrainbaselinepattern AT xueminzhang usingindependentcomponentanalysistoextractacrossmodalityandindividualspecificbrainbaselinepattern |