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J Physiol. 2016 Nov 15;594(22):6535-6546. doi: 10.1113/JP270666. Epub 2016 Jan 6.

How environment and self-motion combine in neural representations of space.

Evans T1,2,3,4, Bicanski A2,3, Bush D2,3, Burgess N2,3.

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UCL Centre for Mathematics and Physics in the Life Sciences and Experimental Biology, Gower Street, London, WC1E 6BT, UK.
UCL Institute of Cognitive Neuroscience, 17 Queen Square, London, WC1N 3AZ, UK.
UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
UCL Department of Neuroscience, Physiology and Pharmacology, Gower Street, London, WC1E 6BT, UK.


Estimates of location or orientation can be constructed solely from sensory information representing environmental cues. In unfamiliar or sensory-poor environments, these estimates can also be maintained and updated by integrating self-motion information. However, the accumulation of error dictates that updated representations of heading direction and location become progressively less reliable over time, and must be corrected by environmental sensory inputs when available. Anatomical, electrophysiological and behavioural evidence indicates that angular and translational path integration contributes to the firing of head direction cells and grid cells. We discuss how sensory inputs may be combined with self-motion information in the firing patterns of these cells. For head direction cells, direct projections from egocentric sensory representations of distal cues can help to correct cumulative errors. Grid cells may benefit from sensory inputs via boundary vector cells and place cells. However, the allocentric code of boundary vector cells and place cells requires consistent head-direction information in order to translate the sensory signal of egocentric boundary distance into allocentric boundary vector cell firing, suggesting that the different spatial representations found in and around the hippocampal formation are interdependent. We conclude that, rather than representing pure path integration, the firing of head-direction cells and grid cells reflects the interface between self-motion and environmental sensory information. Together with place cells and boundary vector cells they can support a coherent unitary representation of space based on both environmental sensory inputs and path integration signals.

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