Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task
Abstract Emotion processing engages multiple large-scale brain networks. However, prior investigations relying on a priori, contrast-based models of brain activity obscure networks’ distinct temporal dynamics and roles in task performance. Here, we performed tensor independent component analysis to...
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| Format: | Article |
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Nature Portfolio
2025-08-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-025-08543-5 |
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| author | Cole Korponay Julia E. Cohen-Gilbert You Cheng Poornima Kumar Nathaniel G. Harnett Adrian A. Medina Brent P. Forester Kerry J. Ressler Jure Demsar Blaise B. Frederick Christian F. Beckmann David G. Harper Lisa D. Nickerson |
| author_facet | Cole Korponay Julia E. Cohen-Gilbert You Cheng Poornima Kumar Nathaniel G. Harnett Adrian A. Medina Brent P. Forester Kerry J. Ressler Jure Demsar Blaise B. Frederick Christian F. Beckmann David G. Harper Lisa D. Nickerson |
| author_sort | Cole Korponay |
| collection | DOAJ |
| description | Abstract Emotion processing engages multiple large-scale brain networks. However, prior investigations relying on a priori, contrast-based models of brain activity obscure networks’ distinct temporal dynamics and roles in task performance. Here, we performed tensor independent component analysis to identify and track concurrent brain processes, including those with non-canonical dynamics, during the emotional face matching task (EFMT) in healthy young adults (n = 413; n = 416 replication). Ten EFMT-recruited large-scale brain networks were identified, reflecting flexible recoupling of visual association cortex to diverse non-visual networks. These networks collectively engaged 74% of cortex and more strongly explained variability in cognition and a performance-based index of emotion interference than contrast-based amygdala activation/connectivity. Variability in EFMT-recruited network activity was more strongly linked to variability in cognition than affect. Findings reveal a rich landscape of brain activity under the surface of contrast-based fMRI analyses and deepen insights into the distinct brain processes underlying subcomponents of emotional face processing. |
| format | Article |
| id | doaj-art-187ccdd7a58544268f7be9363eeccf1e |
| institution | DOAJ |
| issn | 2399-3642 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj-art-187ccdd7a58544268f7be9363eeccf1e2025-08-20T03:05:56ZengNature PortfolioCommunications Biology2399-36422025-08-018111110.1038/s42003-025-08543-5Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching taskCole Korponay0Julia E. Cohen-Gilbert1You Cheng2Poornima Kumar3Nathaniel G. Harnett4Adrian A. Medina5Brent P. Forester6Kerry J. Ressler7Jure Demsar8Blaise B. Frederick9Christian F. Beckmann10David G. Harper11Lisa D. Nickerson12McLean Imaging Center, McLean HospitalMcLean Imaging Center, McLean HospitalMcLean Imaging Center, McLean HospitalDepartment of Psychiatry, Harvard Medical SchoolDepartment of Psychiatry, Harvard Medical SchoolMcLean Imaging Center, McLean HospitalDepartment of Psychiatry, Tufts University School of MedicineDepartment of Psychiatry, Harvard Medical SchoolFaculty of Computer and Information Science, University of LjubljanaMcLean Imaging Center, McLean HospitalDonders Institute of Brain, Cognition and Behaviour, Radboud UniversityDepartment of Psychiatry, Harvard Medical SchoolMcLean Imaging Center, McLean HospitalAbstract Emotion processing engages multiple large-scale brain networks. However, prior investigations relying on a priori, contrast-based models of brain activity obscure networks’ distinct temporal dynamics and roles in task performance. Here, we performed tensor independent component analysis to identify and track concurrent brain processes, including those with non-canonical dynamics, during the emotional face matching task (EFMT) in healthy young adults (n = 413; n = 416 replication). Ten EFMT-recruited large-scale brain networks were identified, reflecting flexible recoupling of visual association cortex to diverse non-visual networks. These networks collectively engaged 74% of cortex and more strongly explained variability in cognition and a performance-based index of emotion interference than contrast-based amygdala activation/connectivity. Variability in EFMT-recruited network activity was more strongly linked to variability in cognition than affect. Findings reveal a rich landscape of brain activity under the surface of contrast-based fMRI analyses and deepen insights into the distinct brain processes underlying subcomponents of emotional face processing.https://doi.org/10.1038/s42003-025-08543-5 |
| spellingShingle | Cole Korponay Julia E. Cohen-Gilbert You Cheng Poornima Kumar Nathaniel G. Harnett Adrian A. Medina Brent P. Forester Kerry J. Ressler Jure Demsar Blaise B. Frederick Christian F. Beckmann David G. Harper Lisa D. Nickerson Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task Communications Biology |
| title | Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task |
| title_full | Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task |
| title_fullStr | Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task |
| title_full_unstemmed | Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task |
| title_short | Disentangling large-scale brain dynamics and their links to behavior during the emotional face matching task |
| title_sort | disentangling large scale brain dynamics and their links to behavior during the emotional face matching task |
| url | https://doi.org/10.1038/s42003-025-08543-5 |
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