Experiences are represented in the brain by patterns of neuronal activity. Ensembles of neurons representing experience undergo activity-dependent plasticity and are important for learning and recall. They are thus considered cellular engrams of memory. Yet, the cellular events that bias neurons to become part of a neuronal representation are largely unknown. In rodents, turnover of structural connectivity has been proposed to underlie the turnover of neuronal representations and also to be a cellular mechanism defining the time duration for which memories are stored in the hippocampus. If these hypotheses are true, structural dynamics of connectivity should be involved in the formation of neuronal representations and concurrently important for learning and recall. To tackle these questions, we used deep-brain 2-photon (2P) time-lapse imaging in transgenic mice in which neurons expressing the Immediate Early Gene (IEG) Arc (activity-regulated cytoskeleton-associated protein) could be permanently labeled during a specific time window. This enabled us to investigate the dynamics of excitatory synaptic connectivity—using dendritic spines as proxies—of hippocampal CA1 (cornu ammonis 1) pyramidal neurons (PNs) becoming part of neuronal representations exploiting Arc as an indicator of being part of neuronal representations. We discovered that neurons that will prospectively express Arc have slower turnover of synaptic connectivity, thus suggesting that synaptic stability prior to experience can bias neurons to become part of representations or possibly engrams. We also found a negative correlation between stability of structural synaptic connectivity and the ability to recall features of a hippocampal-dependent memory, which suggests that faster structural turnover in hippocampal CA1 might be functional for memory.
Bibliographical noteFunding Information:
YL is supported by the Israel Science Foundation (www.isf.org.il; grants # 757/16 and 3213/19), the Deutsche Forschungsgemeinschaft (www.dfg.de; CRC 1080) and the Gatsby Charitable Foundation (www.gatsby.org.uk). AChen is supported by an FP7 Grant from the ERC (erc. europa.eu), the ERANET (www.neuron-eranet.eu) and I-Core programs, the Israeli Ministry of Health (www.health.gov.il), the Bundes Ministerium for Bildung und Forschung (www.bmbf.de), the Nella and Leon Benoziyo Center for Neurological Diseases (www.weizmann.ac.il/pages/nella-andleon-benoziyo-center-neurological-diseases), the Henry Chanoch Krenter Institute for Biomedical Imaging and Genomics, the Israel Science Foundation (www.isf.org.il), the Perlman Family, the Adelis, Marc Besen (besenfoundation.org.au), Pratt (theprattfoundation.org) and Irving I. Moskowitz (www.moskowitzfoundation.org) foundations, and by Roberto and Renata Ruhman and Bruno and Simone Lich. AA is supported by the Max Planck Society (www.mpg.de), the Deutsche Forschungsgemeinschaft (www.dfg.de; grants # AT 205/1-1 and # AT 205/7-1) and the Schram Foundation (www.schram-stiftung.de; grant #T287/29575/2017). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Dr. Ju Lu for writing the first version of the MATLAB graphical user interface (GUI) we used to track dendritic spines, Professor Liqun Luo for early access to the TRAP (targeted recombination in active populations) mice, and the genetically engineered mouse models (GEMM) core facility at the Max Planck Institute for Psychiatry for assistance with maintaining mouse lines. We are also very grateful to Professor Carsten Wotjak, Professor Anton Sirota, and Dr. Nicholas Haynes for their helpful comments.
© 2020 Castello-Waldow et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.