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Updated: Feb 22, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
Default Mode Network Resting State Connectivity Derived From Task-Based fMRI: A Validation Study in People With
Lea Wemheuer1, Anna Doll2,3, Martin Wegrzyn3
1Medical School OWL, Clinical Neuropsychology and Epilepsy Research, Bielefeld University, Bielefeld, Germany.
Background And Purpose:
Resting state functional connectivity can be measured using resting state functional MRI (fMRI), but also task-dependent fMRI in blocked designs. The latter has been demonstrated in healthy participants but not yet validated in clinical cohorts. Since functional connectivity of resting state networks (e.g., default mode network [DMN] and somatomotor network [SMN]) is altered in people with epilepsy, and the impact of the disease on the quality of the intermittent resting state data is unclear, we aimed to validate the method using a clinical fMRI in people with epilepsy.
Methods:
We compared functional connectivity derived from a standard resting state with rest periods of a clinical language fMRI (intermittent resting state) of 92 people with focal epilepsy. Both methods were analyzed across different aspects of functional connectivity: topography, within-network connectivity, and group-level comparisons. Therefore, we conducted independent component analyses (ICAs), similarity-, regions of interest (ROI)-to-ROI-, and second-level seed-based analyses.
Results:
Results indicated similar ICA-derived topography of DMN and SMN from both methods. Within-network connectivity also yielded comparable results. Seed-based analyses of left and right hippocampal connectivity in people with left and right temporal lobe epilepsy also revealed analogous results, with minor restrictions in right hippocampal connectivity.
Conclusion:
The intermittent resting state method produces highly similar results to a standard resting state method in people with epilepsy across different aspects of functional connectivity. It is, therefore, an efficient approach to gain insights into functional connectivity networks in a clinical cohort without performing an additional resting state fMRI.
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