Modular coupling of structure-function reveals network integration (rather than segregation) as the key mechanism for cognitive task discrimination
Fernandez Iriondo, I.; Jimenez Marin, A.; Aginako, N.; Zamora Lopez, G.; Erramuzpe, A.; Bonifazi, P.; Cortes, J.
Show abstract
Understanding how structural and functional brain networks interact to support cognitive processes remains a central challenge in systems neuroscience. In this study, we investigate the dynamics of structure-function coupling (SFC) at the modular level across different cognitive tasks using multimodal neuroimaging data, including anatomical, diffusion, functional at rest and functional at different tasks. By constructing high-resolution structural and functional connectivity matrices, we assessed intra-modular (SFC-INT) and inter-modular (SFC-EXT) coupling to examine their roles in task-specific reorganization. Our results reveal that variations in SFC during cognitive tasks are primarily driven by changes in inter-modular coupling, emphasizing network integration over segregation. Specifically, tasks demanding higher cognitive flexibility, such as the gender stroop task, exhibited increased SFC-EXT, indicating enhanced integration between modules. In contrast, tasks focused on memory processing showed a tendency toward segregation, with lower SFC-EXT values. These findings highlight the significance of inter-modular integration as a flexible and dynamic mechanism underlying cognitive task discrimination. Our study advances the understanding of modular brain network dynamics, suggesting that the brains ability to integrate information across modules plays a pivotal role in cognitive flexibility and task performance.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Distance-dependent distribution thresholding in probabilistic tractography 97%
- Validating Dynamicity in Resting State fMRI with Activation-Informed Temporal Segmentation 97%
- Connectome spectrum electromagnetic tomography: a method to reconstruct electrical brain source-networks at high-spatial resolution 96%
Similar papers in this journal
- The neurocognitive gains of diagnostic reasoning training using simulated interactive veterinary cases. 95%
- Determining the Hierarchical Architecture of the Human Brain Using Subject-Level Clustering of Functional Networks 95%
- Macroscale coupling between structural and effective connectivity in the mouse brain 95%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.