期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2010
卷号：107
期号：16
页码：7550-7555
DOI：10.1073/pnas.0914892107
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：The hippocampus is thought to promote gradual incorporation of novel information into long-term memory by binding, reactivating, and strengthening distributed cortical-cortical connections. Recent studies implicate a key role in this process for hippocampally driven crosstalk with the (ventro)medial prefrontal cortex (vmPFC), which is proposed to become a central node in such representational networks over time. The existence of a relevant prior associative network, or schema, may moreover facilitate this process. Thus, hippocampal-vmPFC crosstalk may support integration of new memories, particularly in the absence of a relevant prior schema. To address this issue, we used functional magnetic resonance imaging (fMRI) and prior schema manipulation to track hippocampal-vmPFC connectivity during encoding and postencoding rest. We manipulated prior schema knowledge by exposing 30 participants to the first part of a movie that was temporally scrambled for 15 participants. The next day, participants underwent fMRI while encoding the movie's final 15 min in original order and, subsequently, while resting. Schema knowledge and item recognition performance show that prior schema was successfully and selectively manipulated. Intersubject synchronization (ISS) and interregional partial correlation analyses furthermore show that stronger prior schema was associated with more vmPFC ISS and less hippocampal-vmPFC interregional connectivity during encoding. Notably, this connectivity pattern persisted during postencoding rest. These findings suggest that additional crosstalk between hippocampus and vmPFC is required to compensate for difficulty integrating novel information during encoding and provide tentative support for the notion that functionally relevant hippocampal-neocortical crosstalk persists during off-line periods after learning.
