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Rapid neural reorganization during retrieval practice predicts subsequent long-term retention and false memory

Nature Human Behaviour volume 6, pages 134–145 (2022)Cite this article

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Abstract

Active retrieval can alter the strength and content of a memory, yielding either enhanced or distorted subsequent recall. However, how consolidation influences these retrieval-induced seemingly contradictory outcomes remains unknown. Here we show that rapid neural reorganization over an eight-run retrieval practice predicted subsequent recall. Retrieval practice boosted memory retention following a 24-hour (long-term) but not 30-minute delay, and increased false memory at both delays. Long-term retention gains were predicted by multi-voxel representation distinctiveness in the posterior parietal cortex (PPC) that increased progressively over retrieval practice. False memory was predicted by unstable representation distinctiveness in the medial temporal lobe (MTL). Retrieval practice enhanced the efficiency of memory-related brain networks, through building up PPC and MTL connections with the ventrolateral and dorsolateral prefrontal cortex that predicted long-term retention gains and false memory, respectively. Our findings indicate that retrieval-induced rapid neural reorganization together with consecutive consolidation fosters long-term retention and false memories via distinct pathways.

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Fig. 1: Experimental design and memory differences on RP and NR at two tests.
Fig. 2: Dynamic changes in memory- related multi-voxel patterns over retrieval practice.
Fig. 3: Dynamic changes in intertrial neural pattern distinctiveness in the PPC, MTL and PFC systems and their relation to subsequent memory outcomes.
Fig. 4: Dynamic changes in memory-related neural network configurations over retrieval practice.
Fig. 5: Brain network-based prediction of long-term retention gains after consolidation and network reconfiguration over retrieval practice.
Fig. 6: MTL-based network prediction of general false memory outcome.

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Data availability

All of the necessary behavioural and brain imaging data are available from https://github.com/QinBrainLab/2017_RetrievalPractice. Source data are provided with this paper.

Code availability

All of the necessary behavioural and brain imaging codes are available from https://github.com/QinBrainLab/2017_RetrievalPractice.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (grant nos. 32130045, 31522028, 81571056 and 82021004), the Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning (grant no. CNLZD1503), the Major Project of National Social Science Foundation (grant nos. 19ZDA363 and 20&ZD153) and the Fundamental Research Funds for the Central Universities. J.W. was supported by the International Postdoc Exchange Program in China, and the Special fund (grant no. 2018T110060) from China Postdoctoral Science Foundation Grant. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank Y. Liu and W. Lin for their assistance in conducting the experiment and data collection, and we thank Z. Cui for his advice on data analysis. We also thank F.D. Weber for his valuable comments for the paper.

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Author notes

  1. These authors contributed equally: Liping Zhuang, Jingyi Wang.

Authors and Affiliations

  1. State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China

    Liping Zhuang, Jingyi Wang, Bingsen Xiong, Cheng Bian, Lei Hao & Shaozheng Qin

  2. Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China

    Liping Zhuang, Jingyi Wang, Bingsen Xiong, Cheng Bian, Lei Hao & Shaozheng Qin

  3. College of Teacher Education, Southwest University, Chongqing, China

    Lei Hao

  4. War Related Illness and Injury Study Center, US Department of Veterans Affairs, Palo Alto, CA, USA

    Peter J. Bayley

  5. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA

    Peter J. Bayley

  6. Chinese Institute for Brain Research, Beijing, China

    Shaozheng Qin

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Contributions

S.Q. conceived the experiment. B.X. performed data collection and analysis. L.Z. J.W., C.B. and L.H. performed data analysis. L.Z., J.W., P.J.B. and S.Q. wrote the paper. All authors contributed to data discussion and interpretation.

Corresponding author

Correspondence to Shaozheng Qin.

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Peer review information Nature Human Behaviour thanks Isabella Wagner and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Zhuang, L., Wang, J., Xiong, B. et al. Rapid neural reorganization during retrieval practice predicts subsequent long-term retention and false memory. Nat Hum Behav 6, 134–145 (2022). https://doi.org/10.1038/s41562-021-01188-4

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