Abstract
The manner by which the human brain learns and recognizes stimuli is a matter of ongoing investigation. Through examination of meta-analyses of task-based functional MRI and resting state functional connectivity MRI, we identified a novel network strongly related to learning and memory. Activity within this network at encoding predicts subsequent item memory, and at retrieval differs for recognized and unrecognized items. The direction of activity flips as a function of recent history: from deactivation for novel stimuli to activation for stimuli that are familiar due to recent exposure. We term this network the 'parietal memory network' (PMN) to reflect its broad involvement in human memory processing. We provide a preliminary framework for understanding the key functional properties of the network.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 534-543 |
| Number of pages | 10 |
| Journal | Trends in Cognitive Sciences |
| Volume | 19 |
| Issue number | 9 |
| DOIs | |
| State | Published - 2015 |
| Externally published | Yes |
Bibliographical note
Funding Information:This work was supported by the National Science Foundation Graduate Research Fellowship under Grant DGE-1143954, Dart NeuroScience LLC, and the McDonnell Center for Systems Neuroscience at Washington University in St Louis. The authors thank Nico Dosenbach, Steve Petersen, Ian Dobbins, Tim Laumann, Hank Chen, and Roddy Roediger for thoughtful discussions related to this work. We also thank Hongkeun Kim for providing several of the statistical map files used to create Figure 1 , Evan Gordon for providing Connectome Workbench scripts, and Jeffrey Berg for assistance in manuscript preparation.
Publisher Copyright:
© 2015 Elsevier Ltd.
Keywords
- Encoding
- Familiarity
- Functional networks
- Memory
- Parietal cortex
- Retrieval