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Abstract
Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.
Original language | English |
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Article number | 1019572 |
Pages (from-to) | 1-16 |
Number of pages | 16 |
Journal | Frontiers in Neuroscience |
Volume | 16 |
DOIs | |
Publication status | Published - 3 Nov 2022 |
Keywords
- clustering
- correlation patterns
- data fusion
- fMRI
- MEG
- multimodal data
- picture naming
Research Beacons, Institutes and Platforms
- Sustainable Futures
- Institute for Data Science and AI
- Digital Futures
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Turing AI Fellowship: Human-AI Research Teams - Steering AI in Experimental Design and Decision-Making
Kaski, S. (PI), Bristow, R. (CoI), Cai, P. (CoI), Jay, C. (CoI) & Peek, N. (CoI)
1/10/21 → 30/09/26
Project: Research