The learning rate for novel spatial environments in model networks of place cells is determined by the product of the window for plasticity and the auto-correlation of place-cell activity.

Imaging of neurons within the hippocampus, a memory region of the brain, reveals how the brain updates memories during different learning conditions compared to when learning is blocked by amnestic drugs.

Computational modeling of the brain’s navigation system reveals that place cells can drive the formation of hexagonal patterns experimentally observed in grid cells activity.

Place cells in the rat hippocampus encode positions along well-learned routes as opposed to intended destinations.

A very large number of place-field maps can be robustly learned by association of external cues with the grid-driven response, however plasticity in the grid-cell inputs renders the place-cell responses volatile.

A large variety of spatial representations implied in rodent navigation could arise robustly and rapidly from inputs with a weak spatial structure, by an interaction of excitatory and inhibitory synaptic plasticity.

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

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.

A nonspecific cation current mediated by TRPM4 channels is a major contributor to the increase in excitability induced by cholinergic modulation in hippocampal CA1 pyramidal neurons, which are thought to play an important role in episodic memory.

Place cells associated with track-running are activated in rats staying in a nearby box while another rat running on the track, suggesting that social observation facilitates spatial memory representations.