Reactivation predicts the consolidation of unbiased long-term cognitive maps

Spatial memories that can last a lifetime are thought to be encoded during 'online' periods of exploration and subsequently consolidated into stable cognitive maps through their 'offline' reactivation. However, the mechanisms and computational principles by which offline reactivation stabilize long-lasting spatial representations remain poorly understood. Here, we employed simultaneous fast calcium imaging and electrophysiology to track hippocampal place cells over 2 weeks of online spatial reward learning behavior and offline resting. We describe that recruitment to persistent network-level offline reactivation of spatial experiences in mice predicts the future representational stability of place cells days in advance of their online reinstatement. Moreover, while representations of reward-adjacent locations are generally more stable across days, offline-reactivation-related stability is, conversely, most prominent for reward-distal locations. Thus, while occurring on the tens of milliseconds timescale, offline reactivation is uniquely associated with the stability of multiday representations that counterbalance the overall reward-adjacency bias, thereby predicting the stabilization of cognitive maps that comprehensively reflect entire underlying spatial contexts. These findings suggest that post-learning offline-related memory consolidation plays a complimentary and computationally distinct role in learning compared to online encoding.