Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Neuronal vector coding in spatial cognition

Nature Reviews Neuroscience volume 21, pages 453–470 (2020)Cite this article

Subjects

Abstract

Several types of neurons involved in spatial navigation and memory encode the distance and direction (that is, the vector) between an agent and items in its environment. Such vectorial information provides a powerful basis for spatial cognition by representing the geometric relationships between the self and the external world. Here, we review the explicit encoding of vectorial information by neurons in and around the hippocampal formation, far from the sensory periphery. The parahippocampal, retrosplenial and parietal cortices, as well as the hippocampal formation and striatum, provide a plethora of examples of vector coding at the single neuron level. We provide a functional taxonomy of cells with vectorial receptive fields as reported in experiments and proposed in theoretical work. The responses of these neurons may provide the fundamental neural basis for the (bottom-up) representation of environmental layout and (top-down) memory-guided generation of visuospatial imagery and navigational planning.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: General properties of vectorial receptive fields.
Fig. 2: Allocentric vector coding neurons.
Fig. 3: Egocentric vector coding cells.
Fig. 4: Reference frame transformation.
Fig. 5: Trace cells and models of spatial cognition.

Similar content being viewed by others

References

  1. O’Keefe, J. & Dostrovsky, J. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res. 34, 171–175 (1971).

    PubMed  Google Scholar 

  2. Hafting, T., Fyhn, M., Molden, S., Moser, M. B. & Moser, E. I. Microstructure of a spatial map in the entorhinal cortex. Nature 436, 801–806 (2005).

    CAS  PubMed  Google Scholar 

  3. Taube, J. S., Muller, R. U. & Ranck, J. B. Head-direction cells recorded from the postsubiculum in freely moving rats. I. Description and quantitative analysis. J. Neurosci. 10, 420–435 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Taube, J. S., Muller, R. U. & Ranck, J. B. Head-direction cells recorded from the postsubiculum in freely moving rats. II. Effects of environmental manipulations. J. Neurosci. 10, 436–447 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Barry, C. et al. The boundary vector cell model of place cell firing and spatial memory. Rev. Neurosci. 17, 71–97 (2006).

    PubMed  PubMed Central  Google Scholar 

  6. Lever, C., Burton, S., Jeewajee, A., O’Keefe, J. & Burgess, N. Boundary vector cells in the subiculum of the hippocampal formation. J. Neurosci. 29, 9771–9777 (2009). This paper presents an experimental confirmation and systematic examination of boundary vector cells in the rat subiculum, confirming previous theoretical predictions.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Solstad, T., Boccara, C. N., Kropff, E., Moser, M. B. & Moser, E. I. Representation of geometric borders in the entorhinal cortex. Science 322, 1865–1868 (2008).

    CAS  PubMed  Google Scholar 

  8. Savelli, F., Yoganarasimha, D. & Knierim, J. J. Influence of boundary removal on the spatial representations of the medial entorhinal cortex. Hippocampus 18, 1270–1282 (2008). Together with Solstad et al. (2008), this paper is the first report of border cells — which code for proximal boundaries in a fixed allocentric direction — in the medial entorhinal cortex.

    PubMed  PubMed Central  Google Scholar 

  9. Deshmukh, S. S. & Knierim, J. J. Influence of local objects on hippocampal representations: landmark vectors and memory. Hippocampus 23, 253–267 (2013). This study reports landmark vector cells, with receptive fields at a fixed allocentric direction and distance from a subset of objects placed within a larger enclosure, in the hippocampus of rodents.

    PubMed  Google Scholar 

  10. Høydal, Ø. A., Skytøen, E. R., Andersson, S. O., Moser, M. B. & Moser, E. I. Object-vector coding in the medial entorhinal cortex. Nature 568, 400–404 (2019). This paper is the first experimental report of object vector cells in the rodent medial entorhinal cortex.

    PubMed  Google Scholar 

  11. Taube, J. S. The head direction signal: origins and sensory-motor integration. Annu. Rev. Neurosci. 30, 181–207 (2007).

    CAS  PubMed  Google Scholar 

  12. Wang, C. et al. Egocentric coding of external items in the lateral entorhinal cortex. Science 362, 945–949 (2018). This article reports the neural correlates of egocentric bearing (and distance in a subset of cells) to nearby boundaries and objects in the lateral entorhinal cortex of rats, a structure not traditionally associated with spatial firing correlates.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Hinman, J. R., Chapman, G. W. & Hasselmo, M. E. Neuronal representation of environmental boundaries in egocentric coordinates. Nat. Commun. 10, 2772 (2019). This study reports egocentric boundary cells in the striatum of rodents.

    PubMed  PubMed Central  Google Scholar 

  14. Alexander, A. S. et al. Egocentric boundary vector tuning of the retrosplenial cortex. Sci. Adv. 6, eaaz2322 (2020). This article reports egocentric boundary cells in the retrosplenial cortex of rodents.

    PubMed  PubMed Central  Google Scholar 

  15. Wijngaarden, J. B. G., van, Babl, S. S. & Ito, H. T. Representation of distance and direction of nearby boundaries in retrosplenial cortex. Preprint at bioRxiv https://doi.org/10.1101/807453 (2019).

    Article  Google Scholar 

  16. Peyrache, A., Schieferstein, N. & Buzsáki, G. Transformation of the head-direction signal into a spatial code. Nat. Commun. 8, 1752 (2017).

    PubMed  PubMed Central  Google Scholar 

  17. Gofman, X. et al. Dissociation between postrhinal cortex and downstream parahippocampal regions in the representation of egocentric boundaries. Curr. Biol. 29, 2751–2757 (2019). Together with Peyrache et al. (2017), this study presents experimental evidence for long-predicted neurons with boundary vector coding modulated by head direction.

    CAS  PubMed  Google Scholar 

  18. Nakazawa, K. et al. Requirement for hippocampal CA3 NMDA receptors in associative memory recall. Science 297, 211–218 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. O’Keefe, J. & Nadel, L. The Hippocampus as a Cognitive Map (Oxford Univ. Press, 1978).

  20. Byrne, P., Becker, S. & Burgess, N. Remembering the past and imagining the future: a neural model of spatial memory and imagery. Psychol. Rev. 114, 340–375 (2007). This article, based on the original model by Becker and Burgess (2001), presents the so-called BBB model of spatial memory for extended environmental features, including a head direction-modulated gain-field circuit.

    PubMed  PubMed Central  Google Scholar 

  21. Bicanski, A. & Burgess, N. A neural-level model of spatial memory and imagery. eLife 7, 1–3 (2018). Building on the work of Byrne et al. (2007), this article presents a comprehensive systems-level model of spatial memory, which predicts the existence of egocentric, allocentric and head direction-modulated object vector cells, accounts for trace responses and shows how grid cells can support mental navigation in imagery of familiar and novel spatial experiences.

    Google Scholar 

  22. Sarel, A., Finkelstein, A., Las, L. & Ulanovsky, N. Vectorial representation of spatial goals in the hippocampus of bats. Science 355, 176–180 (2017).

    CAS  PubMed  Google Scholar 

  23. O’ Keefe, J. & Burgess, N. Geometric determinants of the place fields of hippocampal neurons. Nature 381, 425–428 (1996).

    Google Scholar 

  24. Hartley, T., Burgess, N., Lever, C., Cacucci, F. & O’Keefe, J. Modeling place fields in terms of the cortical inputs to the hippocampus. Hippocampus 10, 369–379 (2000). This model predicts the existence of boundary vector cells as inputs to place cells and constitutes a model of self-localization ultimately based on sensory inputs (boundary distance and direction) as a necessary complement to path integration inputs to place cells.

    CAS  PubMed  Google Scholar 

  25. Burgess, N., Jackson, A., Hartley, T. & O’Keefe, J. Predictions derived from modelling the hippocampal role in navigation. Biol. Cybern. 83, 301–312 (2000).

    CAS  PubMed  Google Scholar 

  26. McNaughton, B., Knierim, J. & Wilson, M. in The Cognitive Neurosciences (ed. Gazzaniga, M. S.) 585–595 (MIT Press, 1994).

  27. Stewart, S., Jeewajee, A., Wills, T. J., Burgess, N. & Lever, C. Boundary coding in the rat subiculum. Philos. Trans. R. Soc. B Biol. Sci. 369, 20120514 (2014).

    Google Scholar 

  28. Lever, C., Burgess, N., Cacucci, F., Hartley, T. & O’Keefe, J. What can the hippocampal representation of environmental geometry tell us about Hebbian learning? Biol. Cybern. 87, 356–372 (2002).

    PubMed  Google Scholar 

  29. Grieves, R. M., Duvelle, É. & Dudchenko, P. A. A boundary vector cell model of place field repetition. Spat. Cogn. Comput. 18, 217–256 (2018).

    Google Scholar 

  30. Lever, C., Wills, T., Cacucci, F., Burgess, N. & O’Keefe, J. Long-term plasticity in hippocampal place-cell representation of environmental geometry. Nature 416, 90–94 (2002).

    CAS  PubMed  Google Scholar 

  31. Bienenstock, E. L., Cooper, L. N. & Munro, P. W. Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. J. Neurosci. 2, 32–48 (1982).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Edvardsen, V., Bicanski, A. & Burgess, N. Navigating with grid and place cells in cluttered environments. Hippocampus 30, 220–232 (2019).

    PubMed  Google Scholar 

  33. Hardcastle, K., Ganguli, S. & Giocomo, L. M. Environmental boundaries as an error correction mechanism for grid cells. Neuron 86, 827–839 (2015).

    CAS  PubMed  Google Scholar 

  34. Keinath, A. T., Epstein, R. A. & Balasubramanian, V. Environmental deformations dynamically shift the grid cell spatial metric. eLife 7, e38169 (2018).

    PubMed  PubMed Central  Google Scholar 

  35. Becker, S. & Burgess, N. Modelling spatial recall, mental imagery and neglect. in Advances in Neural Information Processing Systems 96–102 (eds Jordan, M. I., LeCun, Y. & Solla, S. A.) (MIT Press, 2001).

  36. Burgess, N., Becker, S., King, J. A. & O’Keefe, J. Memory for events and their spatial context: models and experiments. Philos. Trans. R. Soc. B: Biol. Sci. 356, 1493–1503 (2001).

    CAS  Google Scholar 

  37. Evans, T., Bicanski, A., Bush, D. & Burgess, N. How environment and self-motion combine in neural representations of space. J. Physiol. 594, 6535–6546 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. McNaughton, B. L., Battaglia, F. P., Jensen, O., Moser, E. I. & Moser, M. B. Path integration and the neural basis of the ‘cognitive map’. Nat. Rev. Neurosci. 7, 663–678 (2006).

    CAS  PubMed  Google Scholar 

  39. O’Keefe, J. & Burgess, N. Dual phase and rate coding in hippocampal place cells: theoretical significance and relationship to entorhinal grid cells. Hippocampus 15, 853–866 (2005).

    PubMed  PubMed Central  Google Scholar 

  40. Koenig, J., Linder, A. N., Leutgeb, J. K. & Leutgeb, S. The spatial periodicity of grid cells is not sustained during reduced theta oscillations. Science 332, 592–595 (2011).

    CAS  PubMed  Google Scholar 

  41. Berger, T. W., Swanson, G. W., Milner, T. A., Lynch, G. S. & Thompson, R. F. Reciprocal anatomical connections between hippocampus and subiculum in the rabbit: evidence for subicular innervation of regio superior. Brain Res. 183, 265–276 (1980).

    CAS  PubMed  Google Scholar 

  42. Köhler, C. Intrinsic projections of the retrohippocampal region in the rat brain. I. The subicular complex. J. Comp. Neurol. 236, 504–522 (1985).

    PubMed  Google Scholar 

  43. Commins, S., Aggleton, J. P. & O’Mara, S. M. Physiological evidence for a possible projection from dorsal subiculum to hippocampal area CA1. Exp. Brain Res. 146, 155–160 (2002).

    PubMed  Google Scholar 

  44. Shao, L. R. & Dudek, F. E. Electrophysiological evidence using focal flash photolysis of caged glutamate that CA1 pyramidal cells receive excitatory synaptic input from the subiculum. J. Neurophysiol. 93, 3007–3011 (2005).

    PubMed  Google Scholar 

  45. Jackson, J. et al. Reversal of theta rhythm flow through intact hippocampal circuits. Nat. Neurosci. 17, 1362–1370 (2014).

    CAS  PubMed  Google Scholar 

  46. Sun, Y. et al. Cell-type-specific circuit connectivity of hippocampal CA1 revealed through Cre-dependent rabies tracing. Cell Rep. 7, 269–280 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Xu, X., Sun, Y., Holmes, T. C. & López, A. J. Noncanonical connections between the subiculum and hippocampal CA1. J. Comp. Neurol. 524, 3666–3673 (2016).

    PubMed  PubMed Central  Google Scholar 

  48. Sun, Y., Nitz, D. A., Holmes, T. C. & Xu, X. Opposing and complementary topographic connectivity gradients revealed by quantitative analysis of canonical and noncanonical hippocampal CA1 inputs. eNeuro 5, ENEURO.0322-17.2018 (2018).

  49. Sun, Y. et al. CA1-projecting subiculum neurons facilitate object–place learning. Nat. Neurosci. 22, 1857–1870 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Poulter, S., Hartley, T. & Lever, C. The neurobiology of mammalian navigation. Curr. Biol. 28, R1023–R1042 (2018).

    CAS  PubMed  Google Scholar 

  51. Langston, R. F. et al. Development of the spatial representation system in the rat. Science 328, 1576–1580 (2010).

    CAS  PubMed  Google Scholar 

  52. Wills, T. J., Cacucci, F., Burgess, N. & O’Keefe, J. Development of the hippocampal cognitive map in preweanling rats. Science 328, 1573–1576 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Chen, G., Lu, Y., King, J. A., Cacucci, F. & Burgess, N. Differential influences of environment and self-motion on place and grid cell firing. Nat. Commun. 10, 630 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Doeller, C. F. & Burgess, N. Distinct error-correcting and incidental learning of location relative to landmarks and boundaries. Proc. Natl Acad. Sci. USA 105, 5909–5914 (2008).

    CAS  PubMed  Google Scholar 

  55. Knierim, J. J., Lee, I. & Hargreaves, E. L. Hippocampal place cells: parallel input streams, subregional processing, and implications for episodic memory. Hippocampus 16, 755–764 (2006).

    PubMed  Google Scholar 

  56. Chersi, F. & Burgess, N. The cognitive architecture of spatial navigation: hippocampal and striatal contributions. Neuron 88, 64–77 (2015).

    CAS  PubMed  Google Scholar 

  57. Packard, M. G. & McGaugh, J. L. Inactivation of hippocampus or caudate nucleus with lidocaine differentially affects expression of place and response learning. Neurobiol. Learn. Mem. 65, 65–72 (1996).

    CAS  PubMed  Google Scholar 

  58. Knierim, J. J., Neunuebel, J. P. & Deshmukh, S. S. Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local–global reference frames. Philos. Trans. R. Soc. B: Biol. Sci. 369, 20130369 (2014).

    Google Scholar 

  59. LaChance, P. A., Todd, T. P. & Taube, J. S. A sense of space in postrhinal cortex. Science 365, eaax4192 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Kunz, L. et al. A neural code for egocentric spatial maps in the human medial temporal lobe. Preprint at bioRxiv https://doi.org/10.1101/2020.03.03.973131 (2020).

  61. Jercog, P. E. et al. Heading direction with respect to a reference point modulates place-cell activity. Nat. Commun. 10, 2333 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Sharp, P. E. Computer simulation of hippocampal place cells. Psychobiology 19, 103–115 (1991).

    Google Scholar 

  63. Pouget, A. & Sejnowski, T. J. Spatial transformations in the parietal cortex using basis functions. J. Cogn. Neurosci. 9, 222–237 (1997). This influential modelling study suggests that parietal cortex gain-field neurons form a basis set from which different sensory-motor/coordinate transformations can be composed and provides inspiration for the notion that gain-field neurons implement a coordinate transform between egocentric and allocentric vectorial responses (see Becker and Burgess (2001) and Byrne et al. (2007)).

    CAS  PubMed  Google Scholar 

  64. Galletti, C., Battaglini, P. P. & Fattori, P. Eye position influence on the parieto-occipital area PO (V6) of the macaque monkey. Eur. J. Neurosci. 7, 2486–2501 (1995).

    CAS  PubMed  Google Scholar 

  65. Snyder, L. H., Grieve, K. L., Brotchie, P. & Andersen, R. A. Separate body- and world-referenced representations of visual space in parietal cortex. Nature 394, 887–891 (1998).

    CAS  PubMed  Google Scholar 

  66. Salinas, E. & Abbott, L. F. Transfer of coded information from sensory to motor networks. J. Neurosci. 15, 6461–6474 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Pouget, A., Deneve, S. & Duhamel, J. R. A computational perspective on the neural basis of multisensory spatial representations. Nat. Rev. Neurosci. 3, 741–747 (2002).

    CAS  PubMed  Google Scholar 

  68. Burgess, N., Maguire, E. A., Spiers, H. J. & O’Keefe, J. A temporoparietal and prefrontal network for retrieving the spatial context of lifelike events. Neuroimage 14, 439–453 (2001).

    CAS  PubMed  Google Scholar 

  69. Zipser, D. A computational model of hippocampal place fields. Behav. Neurosci. 99, 1006–1018 (1985).

    CAS  PubMed  Google Scholar 

  70. Touretzky, D. S. & Redish, A. D. Theory of rodent navigation based on interacting representations of space. Hippocampus 6, 247–270 (1996).

    CAS  PubMed  Google Scholar 

  71. Recce, M. & Harris, K. D. Memory for places: a navigational model in support of Marr’s theory of hippocampal function. Hippocampus 6, 735–748 (1996).

    CAS  PubMed  Google Scholar 

  72. Lambrey, S. et al. Distinct visual perspective-taking strategies involve the left and right medial temporal lobe structures differently. Brain 131, 523–534 (2008).

    CAS  PubMed  Google Scholar 

  73. Chrastil, E. R., Sherrill, K. R., Hasselmo, M. E. & Stern, C. E. There and back again: hippocampus and retrosplenial cortex track homing distance during human path integration. J. Neurosci. 35, 15442–15452 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Epstein, R. A., Parker, W. E. & Feiler, A. M. Where am I now? Distinct roles for parahippocampal and retrosplenial cortices in place recognition. J. Neurosci. 27, 6141–6149 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Wang, C., Chen, X. & Knierim, J. J. Egocentric and allocentric representations of space in the rodent brain. Curr. Opin. Neurobiol. 60, 12–20 (2020).

    CAS  PubMed  Google Scholar 

  76. Eichenbaum, H. & Cohen, N. J. Can we reconcile the declarative memory and spatial navigation views on hippocampal function? Neuron 83, 764–770 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Tsao, A., Moser, M. B. & Moser, E. I. Traces of experience in the lateral entorhinal cortex. Curr. Biol. 23, 399–405 (2013).

    CAS  PubMed  Google Scholar 

  78. Weible, A. P., Rowland, D. C., Pang, R. & Kentros, C. Neural correlates of novel object and novel location recognition behavior in the mouse anterior cingulate cortex. J. Neurophysiol. 102, 2055–2068 (2009).

    PubMed  Google Scholar 

  79. Weible, A. P., Rowland, D. C., Monaghan, C. K., Wolfgang, N. T. & Kentros, C. G. Neural correlates of long-term object memory in the mouse anterior cingulate cortex. J. Neurosci. 32, 5598–5608 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Deshmukh, S. S. & Knierim, J. J. Representation of non-spatial and spatial information in the lateral entorhinal cortex. Front. Behav. Neurosci. 5, 69 (2011).

    PubMed  PubMed Central  Google Scholar 

  81. O’Keefe, J. Place units in the hippocampus of the freely moving rat. Exp. Neurol. 51, 78–109 (1976).

    PubMed  Google Scholar 

  82. Poulter, S., Lee, S. A., Dachtler, J., Wills, T. J. & Lever, C. Vector trace cells in the subiculum of the hippocampal formation. Preprint at bioRxiv https://doi.org/10.1101/805242 (2019). This study reports evidence for trace vector cells (distinct from boundary vector cells) in the distal (relative to CA1) subiculum, which can reflect a previously encountered — now absent — boundary in their firing.

  83. Ji, D. & Wilson, M. A. Coordinated memory replay in the visual cortex and hippocampus during sleep. Nat. Neurosci. 10, 100–107 (2007).

    CAS  PubMed  Google Scholar 

  84. Rothschild, G., Eban, E. & Frank, L. M. A cortical–hippocampal–cortical loop of information processing during memory consolidation. Nat. Neurosci. 20, 251–259 (2017).

    CAS  PubMed  Google Scholar 

  85. Nitzan, N. et al. Propagation of hippocampal ripples to the neocortex by way of a subiculum–retrosplenial pathway. Nat. Commun. 11, 1947 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Andersen, R. A. Multimodal integration for the representation of space in the posterior parietal cortex. Philos. Trans. R. Soc. B: Biol. Sci. 352, 1421–1428 (1997).

    CAS  Google Scholar 

  87. Clark, B. J., Simmons, C. M., Berkowitz, L. E. & Wilber, A. A. The retrosplenial–parietal network and reference frame coordination for spatial navigation. Behav. Neurosci. 132, 416–429 (2018).

    PubMed  PubMed Central  Google Scholar 

  88. Burwell, R. & Agster, K. in Learning and Memory: A Comprehensive Reference (ed. Byrne, J. H.) 47–66 (Academic, 2008).

  89. Burwell, R. D., Witter, M. P. & Amaral, D. G. Perirhinal and postrhinal cortices of the rat: a review of the neuroanatomical literature and comparison with findings from the monkey brain. Hippocampus 5, 390–408 (1995).

    CAS  PubMed  Google Scholar 

  90. Nitz, D. A. Tracking route progression in the posterior parietal cortex. Neuron 49, 747–756 (2006).

    CAS  PubMed  Google Scholar 

  91. Alexander, A. S. & Nitz, D. A. Retrosplenial cortex maps the conjunction of internal and external spaces. Nat. Neurosci. 18, 1143–1151 (2015).

    CAS  PubMed  Google Scholar 

  92. Wilber, A. A., Clark, B. J., Forster, T. C., Tatsuno, M. & McNaughton, B. L. Interaction of egocentric and world-centered reference frames in the rat posterior parietal cortex. J. Neurosci. 34, 5431–5446 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. Julian, J. B., Ryan, J., Hamilton, R. H. & Epstein, R. A. The occipital place area is causally involved in representing environmental boundaries during navigation. Curr. Biol. 26, 1104–1109 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Shine, J. P., Valdés-Herrera, J. P., Tempelmann, C. & Wolbers, T. Evidence for allocentric boundary and goal direction information in the human entorhinal cortex and subiculum. Nat. Commun. 10, 4004 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Crowne, D. P., Richardson, C. M. & Dawson, K. A. Parietal and frontal eye field neglect in the rat. Behav. Brain Res. 22, 227–231 (1986).

    CAS  PubMed  Google Scholar 

  96. Margulies, D. S. et al. Precuneus shares intrinsic functional architecture in humans and monkeys. Proc. Natl. Acad. Sci. USA 106, 20069–20074 (2009).

    CAS  PubMed  Google Scholar 

  97. Rolls, E. T., Robertson, R. G. & Georges-François, P. Spatial view cells in the primate hippocampus. Eur. J. Neurosci. 9, 1789–1794 (1997).

    CAS  PubMed  Google Scholar 

  98. Courellis, H. S. et al. Spatial encoding in primate hippocampus during free navigation. PLoS Biol. 17, e3000546 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Rolls, E. T. Spatial coordinate transforms linking the allocentric hippocampal and egocentric parietal primate brain systems for memory, action in space, and navigation. Hippocampus 30, 332–353 (2019).

    PubMed  Google Scholar 

  100. Burwell, R. D. & Amaral, D. G. Cortical afferents of the perirhinal, postrhinal, and entorhinal cortices of the rat. J. Comp. Neurol. 398, 179–205 (1998).

    CAS  PubMed  Google Scholar 

  101. Cavada, C. & Goldman-Rakic, P. S. Multiple visual areas in the posterior parietal cortex of primates. Prog. Brain Res. 95, 123–137 (1993).

    CAS  PubMed  Google Scholar 

  102. Horner, A. J., Bisby, J. A., Zotow, E., Bush, D. & Burgess, N. Grid-like processing of imagined navigation. Curr. Biol. 26, 842–847 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Bellmund, J. L., Deuker, L., Navarro Schröder, T. & Doeller, C. F. Grid-cell representations in mental simulation. eLife 5, e17089 (2016).

    PubMed  PubMed Central  Google Scholar 

  104. Erdem, U. M. & Hasselmo, M. A goal-directed spatial navigation model using forward trajectory planning based on grid cells. Eur. J. Neurosci. 35, 916–931 (2012).

    PubMed  PubMed Central  Google Scholar 

  105. Erdem, U. M. & Hasselmo, M. E. A biologically inspired hierarchical goal directed navigation model. J. Physiol. Paris. 108, 28–37 (2014).

    PubMed  Google Scholar 

  106. Kubie, J. L. & Fenton, A. A. Linear look-ahead in conjunctive cells: an entorhinal mechanism for vector-based navigation. Front. Neural Circuits 6, 20 (2012).

    PubMed  PubMed Central  Google Scholar 

  107. Bush, D. & Burgess, N. A hybrid oscillatory interference/continuous attractor network model of grid cell firing. J. Neurosci. 34, 5065–5079 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Marr, D. C. & Poggio, T. in Neuronal Mechanisms in Visual Perception Vol. 15 (eds Poppel, E., Held, R., Dowling, J. E.) 470–488 (Neurosciences Research Program Bulletin, 1977).

  109. Eichenbaum, H. What versus where: non-spatial aspects of memory representation by the hippocampus. Curr. Top. Behav. Neurosci. 37, 101–117 (2018).

    PubMed  Google Scholar 

  110. Constantinescu, A. O., OReilly, J. X. & Behrens, T. E. J. Organizing conceptual knowledge in humans with a gridlike code. Science 352, 1464–1468 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  111. Whittington, J. C. et al. The Tolman–Eichenbaum machine: unifying space and relational memory through generalisation in the hippocampal formation. Preprint at bioRxiv https://doi.org/10.1101/770495 (2019).

  112. Aronov, D., Nevers, R. & Tank, D. W. Mapping of a non-spatial dimension by the hippocampal–entorhinal circuit. Nature 543, 719–722 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. Bicanski, A. & Burgess, N. A computational model of visual recognition memory via grid cells. Curr. Biol. 37, 101–117 (2019).

    Google Scholar 

  114. Fyhn, M., Hafting, T., Treves, A., Moser, M.-B. & Moser, E. I. Hippocampal remapping and grid alignment in entorhinal cortex. Nature 446, 190–194 (2007).

    CAS  PubMed  Google Scholar 

  115. Buxbaum, L. J. et al. Hemispatial neglect: subtypes, neuroanatomy, and disability. Neurology 62, 749–756 (2004).

    CAS  PubMed  Google Scholar 

  116. Bisiach, E. & Luzzatti, C. Unilateral neglect of representational space. Cortex 14, 129–133 (1978).

    CAS  PubMed  Google Scholar 

  117. Coslett, H. B. Neglect in vision and visual imagery: a double dissociation. Brain 120, 1163–1171 (1997).

    PubMed  Google Scholar 

  118. Ortigue, S. et al. Pure representational neglect after right thalamic lesion. Ann. Neurol. 50, 401–404 (2001).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

A.B. and N.B. acknowledge funding by the European Research Council (ERC) Advanced grant NEUROMEM and a Wellcome Principal Research Fellowship to N.B. They thank D. Bush for useful discussion feedback on the manuscript.

Author information

Authors and Affiliations

  1. Institute of Cognitive Neuroscience, University College London, London, UK

    Andrej Bicanski & Neil Burgess

Authors
  1. Andrej Bicanski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neil Burgess
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The authors contributed equally to all aspects of the article.

Corresponding authors

Correspondence to Andrej Bicanski or Neil Burgess.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Glossary

Receptive field

A limited area of ‘stimulus space’ that drives a neuron to fire when occupied by a stimulus. Stimulus space can be sensory (for example, the skin surface) or abstract (for example, locations in an environment).

Grid cells

Cells in the entorhinal cortex with spatial receptive fields arranged in repeating hexagonal patterns across the environment, thought to underlie path integration and vector navigation, and possibly relational computations beyond space.

Head direction cells

Cells that fire when an animal’s head is at a specific orientation relative to external landmarks, found in an extended network of cortical and subcortical brain areas.

Spatial cognition

The capacity of human and non-human animals for mental representation and manipulation of spatial information.

Firing rate maps

Histograms of time-averaged neural activity binned according to the location of the animal in an experimental arena.

Path integration

Tracking changes in self-location by integrating self-motion information, such as linear and angular velocity.

Firing fields

Patches of elevated firing in the firing rate map of a neuron. One receptive field can generate multiple firing fields as the agent moves and brings different stimuli into the receptive field of the neuron.

Reference frame

A common coordinate system in which to relate multiple observations.

Theta oscillations

Prominent oscillations of 5–10 Hz in the local field potential, ubiquitous in rodents during locomotion and, in shorter bursts, associated with memory in humans.

Competitive learning

A learning algorithm that assumes winner-takes-all dynamics in the postsynaptic population (for example, via lateral inhibition), such that only one postsynaptic neuron is active enough to strengthen its connections from active presynaptic neurons.

Gain-field neurons

Neurons whose firing rate in response to the presence of a stimulus in their receptive field is gain-modulated by a second signal. For example, eye position can up-modulate or down-modulate the response to a stimulus in a retinal receptive field.

Hebbian learning

A learning theory originated by Donald Hebb in 1949 stating that a neuron that partakes in making another neuron fire will strengthen its synapse to that neuron (regardless of individual spike timings).

Replay events

The reactivation of neurons in sequence, compressed in time. Replay events were originally observed in hippocampal place cells during ‘sharp wave’-modulated high-frequency ripples in the local field potential while the animal is resting.

Spatial view cells

Cells in the primate hippocampus that fire whenever a given location in an environment is observed, regardless of the animal’s location and pose in that environment.

Pattern completion

The reactivation of all neurons comprising a pre-existing pattern of neural activity caused by activity in a subset of those neurons.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bicanski, A., Burgess, N. Neuronal vector coding in spatial cognition. Nat Rev Neurosci 21, 453–470 (2020). https://doi.org/10.1038/s41583-020-0336-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41583-020-0336-9

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing