Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
Bence Bagi
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
Eszter Vértes
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
Orsolya Steinbach-Németh
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
Mária R Karlócai
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary
Orsolya I Papp
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary
István Miklós
Alfréd Rényi Institute of Mathematics, Eötvös Loránd Research Network, Budapest, Hungary; Institute for Computer Science and Control, Eötvös Loránd Research Network, Budapest, Hungary
Norbert Hájos
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary
Tamás F Freund
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
Attila I Gulyás
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary
Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
Hippocampal place cells are activated sequentially as an animal explores its environment. These activity sequences are internally recreated (‘replayed’), either in the same or reversed order, during bursts of activity (sharp wave-ripples [SWRs]) that occur in sleep and awake rest. SWR-associated replay is thought to be critical for the creation and maintenance of long-term memory. In order to identify the cellular and network mechanisms of SWRs and replay, we constructed and simulated a data-driven model of area CA3 of the hippocampus. Our results show that the chain-like structure of recurrent excitatory interactions established during learning not only determines the content of replay, but is essential for the generation of the SWRs as well. We find that bidirectional replay requires the interplay of the experimentally confirmed, temporally symmetric plasticity rule, and cellular adaptation. Our model provides a unifying framework for diverse phenomena involving hippocampal plasticity, representations, and dynamics, and suggests that the structured neural codes induced by learning may have greater influence over cortical network states than previously appreciated.