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.
Mathematical modeling suggests that grid cells in the rodent brain use fundamental principles of number theory to maximize the efficiency of spatial mapping, enabling animals to accurately encode their location with as few neurons as possible.
Grid-cell maps can be aligned to both local and remote reference frames, suggesting that they provide a metric for space beyond the navigationally accessible boundaries of the local environment.
A novel experimental method and analysis is conceived, based on perturbation and sparse recording, to elucidate the circuit structure and mechanisms underlying the responses of grid cells.
Functional magnetic resonance imaging performed while people imagined directions from stationary viewpoints supports theories suggesting that spatially tuned cells such as grid cells underlie mental simulation for future thinking.
When a familiar environment is reshaped, the grid cell spatial code is dynamically anchored to recently encountered boundaries and changes throughout exploration with the specific movement history of the navigator.
A computational model for the formation of neural networks of grid cells in virtual bats suggests that the highly ordered networks presumed to support spatial navigation in two dimensions cannot be routinely established in three-dimensional space.
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.
Mathematical analysis confirms that hexagonal patterns of neuronal activity are the most efficient means for the brain to represent 2D space, and predicts that activity patterns resembling densely packed lattices are optimal for representing 3D space.
