Animals and humans are able to exploit structural knowledge about their environments in order to navigate directly to remembered goal-locations – a process known as vector-based navigation. Notably, vector-based navigation allows for short-cuts utilising previously unvisited routes to be taken and strongly indicates the existence of a cognitive spatial metric. Theoretical considerations, including those derived from AI-based models, suggest that entorhinal grid cells play a central role in this process. Specifically, non-local reactivations, which have been shown to engage grid cells, are thought to provide a means by which such computations are performed but this remains to be demonstrated experimentally.
Bush, D., Barry, C., Manson, D., & Burgess, N. (2015). Using grid cells for navigation. Neuron, 87(3), 507-520.
Banino, A., Barry, C., Uria, B., Blundell, C., Lillicrap, T., Mirowski, P., … & Wayne, G. (2018). Vector-based navigation using grid-like representations in artificial agents. Nature, 557(7705), 429.
Ólafsdóttir, H. F., Carpenter, F., & Barry, C. (2016). Coordinated grid and place cell replay during rest. Nature neuroscience, 19(6), 792.
Pfeiffer, B. E., & Foster, D. J. (2013). Hippocampal place-cell sequences depict future paths to remembered goals. Nature, 497(7447), 74.
Jadhav, S. P., Kemere, C., German, P. W., & Frank, L. M. (2012). Awake hippocampal sharp-wave ripples support spatial memory. Science, 336(6087), 1454-1458.