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ISSN : 1226-9654
Memory Encoding and Consolidation in the Default Mode Networks
(New York University)
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Abstract
The current study analyzed the neural signals from the default mode networks (DMN) using the subsequent memory paradigm and a resting-state functional connectivity (rsFC) analysis. Participants learned a number of scenes and faces during functional magnetic resonance imaging (fMRI) and later performed a recognition test. To define the DMN and track the changes in rsFC, resting-state scans were acquired before and after the learning phase. Based on subsequent recognition performance, trials in the learning phase were categorized into either subsequently remembered or subsequently forgotten trials. Here are two main findings: First, DMN subregions showed greater activation for subsequently forgotten than remembered trials. Such subsequent forgetting (SF) effects were most reliable in the right angular gyrus. Second, greater functional connectivity between the hippocampus and the parahippocampal place area (PPA) during the post-learning resting scan predicted better memory for the scenes in the subsequent recognition test. These findings provide information about memory encoding and consolidation functions in the DMN and support the necessity of network-level approaches to understand human memory.
- keywords
- 부호화, 공고화, 디폴트 모드 연결망, 휴지기 기능적 연결성, 후속 기억 패러다임, encoding, consolidation, default mode network, resting-state functional connectivity, subsequent memory paradigm
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