A model of hippocampal replay is proposed that gives a biologically plausible account of how the hippocampus could prioritize replay and produce a variety of different replay statistics, and is efficient in driving spatial learning.

Replay of recently experienced trajectories during a decision task is coupled with more effective adaptation to change, whereas replay during rest is associated with limited decision making flexibility.

What will happen where and when could be predicted by the sequential reactivation of place cells that occurs while an animal pauses, suggesting that the replay is linked to mental time travel.

Hippocampal place cells modulate their firing rate during replay events to reflect the increases, or decreases, in firing rate experienced between contexts during behavior.

fMRI evidence for off-task replay predicts subsequent replanning behavior in humans, suggesting that learning from simulated experience during replay helps update past policies in reinforcement learning.

A new state space decoder revealed that most hippocampal sharp-wave ripples contain coherent spatial content, and that this 'replay' typically progresses at speeds similar to those seen during actual experiences.

The combination of short-term and long-term plasticity enables hippocampus to learn goal-directed paths through replay in a reversed order.

Macaque monkeys temporally compress past experiences and use a forward-replay mechanism during judgment of temporal-order between episodes.

In anticipation of a reward, hippocampal place cells simulate desired journeys through areas that have been seen, but not explored.

An experimentally supported model of grid cells naturally enables them to participate in firing sequences that encode rapid trajectories in space.