Functional network interactions at rest underlie individual differences in memory ability

Mariët Van Buuren*, Isabella C. Wagner, Guillén Fernández

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


Intrinsic network interactions may underlie individual differences in the ability to remember. The default mode network (DMN) comprises subnetworks implicated in memory, and interactions between the DMN and frontoparietal network (FPN) were shown to support mnemonic processing. However, it is unclear if such interactions during resting-state predict episodic memory ability. We investigated whether intrinsic network interactions within and between the DMN and FPN are related to individual differences in memory performance. Resting-state activity was measured using functional MRI in healthy young adults followed by a memory test for object-location associations that were studied 3 d earlier. We identified two subnetworks within the DMN, the main-DMN and the medial temporal lobe, retrosplenial cortex (MTL_RSC)-DMN. Further, we found regions forming the FPN. Memory performance was associated with lower connectivity within the MTL_RSC-DMN, and stronger connectivity between the main-DMN and FPN. Exploratory whole-brain analysis revealed stronger MTL connectivity with the left posterior parietal cortex that was related to better memory performance. Furthermore, we found increased task-evoked activation during successful retrieval within the main-DMN and FPN, but not within the MTL_RSC-DMN. In sum, lower intrinsic connectivity within the MTL_RSC-DMN, combined with stronger connectivity between the main-DMN and FPN, explain individual differences in memory ability.

Original languageEnglish
Pages (from-to)9-19
Number of pages11
JournalLearning and Memory
Early online date17 Dec 2018
Publication statusPublished - Jan 2019


The authors thank Leonore Bovy for her assistance with data acquisition. This work was supported by the European Research Council (ERC R0001075 to G.F.).

FundersFunder number
H2020 European Research Council
European Research CouncilR0001075


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