Task-related and resting-state fMRI identify distinct networks that preferentially support remembering the past and imagining the future

Adrian W. Gilmore, Steven M. Nelson, Hung Yu Chen, Kathleen B. McDermott

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


The relation between episodic memory and episodic future thought (EFT) remains an active target of research. A growing literature suggests that similar cognitive processes and neural substrates tend to support these acts. However, direct comparisons of whole-brain activity reveal clear differences, with numerous regions more active when engaging in EFT than when remembering, and a smaller collection of regions displaying the opposite pattern of activity. Although various network labels have been applied to prior neuroimaging results, to date no formal resting-state functional connectivity analysis has been conducted. In the current experiment, 48 subjects remembered events from their past and engaged in EFT. Resting-state data were collected from all subjects. Task results replicated recent findings, with more activity during EFT in regions across frontal and parietal cortex, and with more activity during remembering in a smaller number of predominantly parahippocampal and retrosplenial regions. Resting-state connectivity analysis, based on seed locations defined using the fMRI task data, indicated that regions preferentially activated during EFT fell primarily within the default mode network, while those more active during remembering fell primarily within the contextual association network. These results suggest that despite their general similarity, the functional network membership of regions showing task differences is dissociable. We discuss our results in light of several hypotheses that attempt to relate remembering and EFT, and suggest that the data speak to differences in the relative contributions of episodic and semantic memory, as well as controlled and automatic processing, during the acts of remembering or engaging in EFT.

Original languageEnglish (US)
Pages (from-to)180-189
Number of pages10
StatePublished - Feb 2018
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by a grant from the McDonnell Center for Systems Neuroscience at Washington University in St. Louis to K.B.M. and the National Science Foundation Graduate Research Fellowship Program ( DGE-1143954 ) awarded to A.W.G. We thank Jessica Church, Ian Dobbins, Steve Petersen, Todd Braver, Maital Neta, Gagan Wig, Deanna Barch, Tim Laumann, and Karl Szpunar for helpful discussions throughout this work. Thanks also to Christopher Zerr for assistance with manuscript preparation and comments on an earlier draft of this work. We thank Jonathan Power and Evan Gordon for providing MATLAB scripts for functional connectivity analysis and Connectome Workbench, respectively. Thanks to Andrew Fishell, Neil Savalia, and Rohan Mathur for their assistance with data collection, and David Gilmore for contributing photographs for use in Fig. 5 .

Publisher Copyright:
© 2017


  • Contextual association network
  • Default mode network
  • Episodic future thought
  • Episodic memory
  • Resting-state functional connectivity


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