Dynamic neural networks supporting memory retrieval.
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How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) medial prefrontal cortex (PFC) network, associated with self-referential processes, 2) medial temporal lobe (MTL) network, associated with memory, 3) frontoparietal network, associated with strategic search, and 4) cingulooperculum network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior.
Image Interpretation, Computer-Assisted
Magnetic Resonance Imaging
Published Version (Please cite this version)10.1016/j.neuroimage.2011.04.039
Publication InfoKragel, Philip A; Rubin, David C; & St Jacques, PL (2011). Dynamic neural networks supporting memory retrieval. Neuroimage, 57(2). pp. 608-616. 10.1016/j.neuroimage.2011.04.039. Retrieved from http://hdl.handle.net/10161/9775.
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Juanita M. Kreps Professor of Psychology and Neuroscience
Please refer to the Rubin Lab website My main research interest has been in long-term memory, especially for complex (or "real-world") stimuli. This work includes the study of autobiographical memory and oral traditions