title: A Unified Dynamic Model for Learning, Replay, and Sharp-Wave/Ripples.
abstract: Hippocampal activity is fundamental for episodic memory formation and consolidation. During phases of rest and sleep, it exhibits sharp-wave/ripple (SPW/R) complexes, which are short episodes of increased activity with superimposed high-frequency oscillations. Simultaneously, spike sequences reflecting previous behavior, such as traversed trajectories in space, are replayed. Whereas these phenomena are thought to be crucial for the formation and consolidation of episodic memory, their neurophysiological mechanisms are not well understood. Here we present a unified model showing how experience may be stored and thereafter replayed in association with SPW/Rs. We propose that replay and SPW/Rs are tightly interconnected as they mutually generate and support each other. The underlying mechanism is based on the nonlinear dendritic computation attributable to dendritic sodium spikes that have been prominently found in the hippocampal regions CA1 and CA3, where SPW/Rs and replay are also generated. Besides assigning SPW/Rs a crucial role for replay and thus memory processing, the proposed mechanism also explains their characteristic features, such as the oscillation frequency and the overall wave form. The results shed a new light on the dynamical aspects of hippocampal circuit learning.
  
  
  CONCLUSIONS
  During phases of rest and sleep, the hippocampus, the "memory center" of the brain, generates intermittent patterns of strongly increased overall activity with high-frequency oscillations, the so-called sharp-wave/ripples. We investigate their role in learning and memory processing. They occur together with replay of activity sequences reflecting previous behavior. Developing a unifying computational model, we propose that both phenomena are tightly linked, by mutually generating and supporting each other. The underlying mechanism depends on nonlinear amplification of synchronous inputs that has been prominently found in the hippocampus. Besides assigning sharp-wave/ripples a crucial role for replay generation and thus memory processing, the proposed mechanism also explains their characteristic features, such as the oscillation frequency and the overall wave form.
authors.affiliation: Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany, Bernstein Center for Computational Neuroscience, 37077 Göttingen, Germany, Institute for Nonlinear Dynamics, Georg August University, 37077 Göttingen, Germany.
authors.forename: Sven
authors.initials: S
authors.lastname: Jahnke
authors.affiliation: Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany, Bernstein Center for Computational Neuroscience, 37077 Göttingen, Germany, Institute for Nonlinear Dynamics, Georg August University, 37077 Göttingen, Germany.
authors.forename: Marc
authors.initials: M
authors.lastname: Timme
authors.affiliation: Center for Theoretical Neuroscience, Columbia University, New York, New York 10032-2695, and Donders Institute for Brain, Cognition, and Behavior, Radboud University, 6500 Nijmegen, The Netherlands rm3354@cumc.columbia.edu.
authors.forename: Raoul-Martin
authors.initials: RM
authors.lastname: Memmesheimer
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D003712:Dendrites / Q000502:physiology; D006624:Hippocampus / Q000166:cytology; D007858:Learning / Q000502:physiology*; D008568:Memory / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000503:physiopathology; D009473:Neuronal Plasticity / Q000502:physiology; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D017711:Nonlinear Dynamics
keywords: dendritic spikes; learning; memory; network; replay; sharp-wave/ripples