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Spatial cognition in bats and rats: from sensory acquisition to multiscale maps and navigation

An Erratum to this article was published on 20 February 2015

Key Points

  • Real-life navigation takes place in large natural environments that are complex and multiscaled. There is a fundamental gap between large-scale navigation and typical laboratory studies of the neurobiology of navigation, in which animals navigate in small boxes. This is a gap in spatial scales, in the richness of sensory information available, and in the techniques used and models proposed for describing small-scale versus large-scale navigation.

  • Spatial cells in the mammalian hippocampal formation include place cells, grid cells, head-direction cells and border (boundary) cells. It is unknown whether and how these neurons contribute to natural navigation on scales beyond a few meters.

  • Bats are excellent animal models for studying spatial cognition, because they are superb navigators, and possess multiple excellent sensory systems, including vision, olfaction and echolocation (biosonar). Bat echolocation is an active-sensing system with high accuracy and dynamic flexibility, which bears surprising similarities to rat whisking and sniffing, with the benefit that bat biosonar can be analysed quantitatively by using the mathematical theory of sonar.

  • Large-scale navigation is likely to be dominated by incoming sensory information rather than by self-motion cues (path integration). Two prominent sensory-based models of place fields, the boundary vector cell (BVC) model and the view-based model, both predict that sensory resolution determines the spatial resolution of place cells.

  • The multiscale character of natural habitats, from small rat burrows and bat caves to large kilometre-scale trajectories, suggests that neural spatial representation by place cells should adapt to this multiscale structure. Three phenomena described in the literature could serve as mechanisms for such multiscale representation: these include the dorsoventral gradient of place-field size in the hippocampus and dorsoventral gradient of grid-spacing in the medial entorhinal cortex, the dynamic adjustment of place-field size to environmental dimensions, and the enhanced precision of spatial representation using population coding.

  • Theoretical models suggested several ways to bridge the gap between spatial representations for 1-m boxes used in laboratory experiments, versus kilometre-scale natural environments. Models of place cells proposed that place fields could rescale according to environmental size, or that place cells can exhibit dozens or hundreds of place fields per neuron; whereas for grid cells, models proposed a combinatorial grid code that could represent simultaneously both small-scale and large geographical environments.

  • Future directions include the need to understand which of these theoretical models best captures the actual neural basis of large-scale navigation, as well as the need to elucidate the neural mechanisms of route planning, re-orienting after losing one's path, and how different maps are stitched together. To answer these questions would require electrophysiological recordings from the hippocampal formation of animals navigating in large-scale, complex naturalistic environments.

Abstract

Spatial orientation and navigation rely on the acquisition of several types of sensory information. This information is then transformed into a neural code for space in the hippocampal formation through the activity of place cells, grid cells and head-direction cells. These spatial representations, in turn, are thought to guide long-range navigation. But how the representations encoded by these different cell types are integrated in the brain to form a neural 'map and compass' is largely unknown. Here, we discuss this problem in the context of spatial navigation by bats and rats. We review the experimental findings and theoretical models that provide insight into the mechanisms that link sensory systems to spatial representations and to large-scale natural navigation.

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Figure 1: Sensory modalities of bats.
Figure 2: Effects of sensory input on spatial representation.
Figure 3: Spatial representations on multiple scales.
Figure 4: Models of large-scale spatial codes.

References

  1. Cochran, W. W., Mouritsen, H. & Wikelski, M. Migrating songbirds recalibrate their magnetic compass daily from twilight cues. Science 304, 405–408 (2004).

    Article  CAS  PubMed  Google Scholar 

  2. Wallraff, H. G. Avian Navigation: Pigeon Homing as a Paradigm (Springer, 2005).

    Google Scholar 

  3. Thorup, K. et al. Evidence for a navigational map stretching across the continental U.S. in a migratory songbird. Proc. Natl Acad. Sci. USA 104, 18115–18119 (2007).

    Article  PubMed  Google Scholar 

  4. Boles, L. C. & Lohmann, K. J. True navigation and magnetic maps in spiny lobsters. Nature 421, 60–63 (2003).

    Article  CAS  PubMed  Google Scholar 

  5. Muller, M. & Wehner, R. Path integration in desert ants, Cataglyphis fortis. Proc. Natl Acad. Sci. USA 85, 5287–5290 (1988).

    Article  CAS  PubMed  Google Scholar 

  6. Wittlinger, M., Wehner, R. & Wolf, H. The ant odometer: stepping on stilts and stumps. Science 312, 1965–1967 (2006).

    Article  CAS  PubMed  Google Scholar 

  7. Cheng, K., Narendra, A., Sommer, S. & Wehner, R. Traveling in clutter: navigation in the Central Australian desert ant Melophorus bagoti. Behav. Process. 80, 261–268 (2009).

    Article  Google Scholar 

  8. Menzel, R. et al. Honey bees navigate according to a map-like spatial memory. Proc. Natl Acad. Sci. USA 102, 3040–3045 (2005).

    Article  CAS  PubMed  Google Scholar 

  9. Lohmann, K. J., Lohmann, C. M., Ehrhart, L. M., Bagley, D. A. & Swing, T. Animal behaviour: geomagnetic map used in sea-turtle navigation. Nature 428, 909–910 (2004).

    Article  CAS  PubMed  Google Scholar 

  10. Wu, L. Q. & Dickman, J. D. Neural correlates of a magnetic sense. Science 336, 1054–1057 (2012).

    Article  CAS  PubMed  Google Scholar 

  11. Zapka, M. et al. Visual but not trigeminal mediation of magnetic compass information in a migratory bird. Nature 461, 1274–1277 (2009).

    Article  CAS  PubMed  Google Scholar 

  12. Gagliardo, A., Ioale, P., Savini, M., Dell'Omo, G. & Bingman, V. P. Hippocampal-dependent familiar area map supports corrective re-orientation following navigational error during pigeon homing: a GPS-tracking study. Eur. J. Neurosci. 29, 2389–2400 (2009).

    Article  PubMed  Google Scholar 

  13. Kramer, G. Die sonnenorientierung der vögel. Verh. Dtsch. Zool. Ges. 1, 77–84 (1953).

    Google Scholar 

  14. O'Keefe, J. & Nadel, L. The Hippocampus as a Cognitive Map (Oxford Univ. Press, 1978). This is a seminal book that described the first discovery of place-selective neurons in the hippocampus, and proposed that these cells are the neural basis of a 'cognitive map' representing the animal's location within the environment.

    Google Scholar 

  15. Wilson, M. A. & McNaughton, B. L. Dynamics of the hippocampal ensemble code for space. Science 261, 1055–1058 (1993).

    Article  CAS  PubMed  Google Scholar 

  16. O'Keefe, J. & Burgess, N. Geometric determinants of the place fields of hippocampal neurons. Nature 381, 425–428 (1996). This paper demonstrated the important influence of environmental boundaries on hippocampal place cells, and introduced the boundary vector cell (BVC) model of place cells.

    Article  CAS  PubMed  Google Scholar 

  17. Hollup, S. A., Molden, S., Donnett, J. G., Moser, M.-B. & Moser, E. I. Accumulation of hippocampal place fields at the goal location in an annular watermaze task. J. Neurosci. 21, 1635–1644 (2001).

    Article  CAS  PubMed  Google Scholar 

  18. Lee, I., Yoganarasimha, D., Rao, G. & Knierim, J. J. Comparison of population coherence of place cells in hippocampal subfields CA1 and CA3. Nature 430, 456–459 (2004).

    Article  CAS  PubMed  Google Scholar 

  19. Kjelstrup, K. B. et al. Finite scale of spatial representation in the hippocampus. Science 321, 140–143 (2008). This is the first paper that went beyond the spatial scales of small experimental boxes, to an 18-m track. This study showed a dramatic scaling of place-field size with the size of the environment, as well as a dorsoventral gradient of place-field sizes in the hippocampus.

    Article  CAS  PubMed  Google Scholar 

  20. Harvey, C. D., Collman, F., Dombeck, D. A. & Tank, D. W. Intracellular dynamics of hippocampal place cells during virtual navigation. Nature 461, 941–946 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Royer, S., Sirota, A., Patel, J. & Buzsáki, G. Distinct representations and theta dynamics in dorsal and ventral hippocampus. J. Neurosci. 30, 1777–1787 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Epsztein, J., Lee, A. K., Chorev, E. & Brecht, M. Impact of spikelets on hippocampal CA1 pyramidal cell activity during spatial exploration. Science 327, 474–477 (2010).

    Article  CAS  PubMed  Google Scholar 

  23. Ulanovsky, N. & Moss, C. F. Hippocampal cellular and network activity in freely moving echolocating bats. Nature Neurosci. 10, 224–233 (2007).

    Article  CAS  PubMed  Google Scholar 

  24. 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).

    Article  CAS  PubMed  Google Scholar 

  25. Sargolini, F. et al. Conjunctive representation of position, direction, and velocity in entorhinal cortex. Science 312, 758–762 (2006).

    Article  CAS  PubMed  Google Scholar 

  26. Barry, C., Hayman, R., Burgess, N. & Jeffery, K. J. Experience-dependent rescaling of entorhinal grids. Nature Neurosci. 10, 682–684 (2007).

    Article  CAS  PubMed  Google Scholar 

  27. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Boccara, C. N. et al. Grid cells in pre- and parasubiculum. Nature Neurosci. 13, 987–994 (2010).

    Article  CAS  PubMed  Google Scholar 

  29. Brandon, M. P. et al. Reduction of theta rhythm dissociates grid cell spatial periodicity from directional tuning. Science 332, 595–599 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Yartsev, M. M., Witter, M. P. & Ulanovsky, N. Grid cells without theta oscillations in the entorhinal cortex of bats. Nature 479, 103–107 (2011).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  32. Zugaro, M. B., Tabuchi, E., Fouquier, C., Berthoz, A. & Wiener, S. I. Active locomotion increases peak firing rates of anterodorsal thalamic head direction cells. J. Neurophysiol. 86, 692–702 (2001).

    Article  CAS  PubMed  Google Scholar 

  33. Yoganarasimha, D., Yu, X. & Knierim, J. J. Head direction cell representations maintain internal coherence during conflicting proximal and distal cue rotations: comparison with hippocampal place cells. J. Neurosci. 26, 622–631 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  35. Ulanovsky, N. & Moss, C. F. What the bat's voice tells the bat's brain. Proc. Natl Acad. Sci. USA 105, 8491–8498 (2008).

    Article  PubMed  Google Scholar 

  36. Villa, B. R. & Cockrum, E. L. Migration in the guano bat Tadarida brasiliensis mexicana (Saussure). J. Mammal. 43, 43–64 (1962).

    Article  Google Scholar 

  37. Glass, B. P. Seasonal movements of Mexican freetail bats Tadarida brasiliensis mexicana banded in the Great Plains. Southwest. Nat. 27, 127–133 (1982).

    Article  Google Scholar 

  38. Hutterer, R., Ivanova, T., Meyer-Cords, C. & Rodrigues, L. Bat Migrations in Europe: a Review of Banding Data and Literature (German Agency for Nature Conservation, 2005).

    Google Scholar 

  39. Richter, H. V. & Cumming, G. S. First application of satellite telemetry to track African straw-coloured fruit bat migration. J. Zool. 275, 172–176 (2008).

    Article  Google Scholar 

  40. Winter, Y. & Stich, K. P. Foraging in a complex naturalistic environment: capacity of spatial working memory in flower bats. J. Exp. Biol. 208, 539–548 (2005).

    Article  PubMed  Google Scholar 

  41. Neuweiler, G. & Möhres, F. P. Die rolle des ortsgedachtnisses bei der orientierung der Grossblatt-Fledermaus, Megaderma Lyra. Zeit. Ver. Physiol. 57, 147–171 (1967).

    Article  Google Scholar 

  42. Fiete, I. R., Burak, Y. & Brookings, T. What grid cells convey about rat location. J. Neurosci. 28, 6858–6871 (2008). The first theoretical study to suggest the notion of a combinatorial grid code for representing very large environments using moderate-sized grids. The grid code relies on combining grids of different scales, which allows representation of both small and large environments.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Sreenivasan, S. & Fiete, I. Grid cells generate an analog error-correcting code for singularly precise neural computation. Nature Neurosci. 14, 1330–1337 (2011).

    Article  CAS  PubMed  Google Scholar 

  44. Mathis, A., Herz, A. V. & Stemmler, M. B. Resolution of nested neuronal representations can be exponential in the number of neurons. Phys. Rev. Lett. 109, 018103 (2012).

    Article  CAS  PubMed  Google Scholar 

  45. Mathis, A., Herz, A. V. & Stemmler, M. Optimal population codes for space: grid cells outperform place cells. Neural Comput. 24, 2280–2317 (2012).

    Article  PubMed  Google Scholar 

  46. Hedrick, K. R. & Zhang, K. Megamap: continuous attractor model for place cells representing large environments (Poster). Program No. 578.01, Soc. Neurosci. Annual Meeting. San Diego (2013).

  47. Ahissar, E. & Arieli, A. Figuring space by time. Neuron 32, 185–201 (2001).

    Article  CAS  PubMed  Google Scholar 

  48. Kepecs, A., Uchida, N. & Mainen, Z. F. The sniff as a unit of olfactory processing. Chem. Senses 31, 167–179 (2006).

    Article  PubMed  Google Scholar 

  49. Smear, M., Shusterman, R., O'Connor, R., Bozza, T. & Rinberg, D. Perception of sniff phase in mouse olfaction. Nature 479, 397–400 (2011).

    Article  CAS  PubMed  Google Scholar 

  50. Porter, J. et al. Mechanisms of scent-tracking in humans. Nature Neurosci. 10, 27–29 (2007).

    Article  CAS  PubMed  Google Scholar 

  51. Diamond, M. E., von Heimendahl, M., Knutsen, P. M., Kleinfeld, D. & Ahissar, E. 'Where' and 'what' in the whisker sensorimotor system. Nature Rev. Neurosci. 9, 601–612 (2008).

    Article  CAS  Google Scholar 

  52. Griffin, D. R. Listening in the Dark (Yale Univ. Press, 1958). A seminal book in the field of animal behaviour, which described the discovery of bat echolocation and launched the field of animal biosonar.

    Google Scholar 

  53. Schnitzler, H.-U., Moss, C. F. & Denzinger, A. From spatial orientation to food acquisition in echolocating bats. Trends Ecol. Evolut. 18, 386–394 (2003).

    Article  Google Scholar 

  54. Masters, W. M., Moffat, A. J. & Simmons, J. A. Sonar tracking of horizontally moving targets by the big brown bat Eptesicus fuscus. Science 228, 1331–1333 (1985).

    Article  CAS  PubMed  Google Scholar 

  55. Ghose, K. & Moss, C. F. Steering by hearing: a bat's acoustic gaze is linked to its flight motor output by a delayed, adaptive linear law. J. Neurosci. 26, 1704–1710 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Yovel, Y., Falk, B., Moss, C. F. & Ulanovsky, N. Optimal localization by pointing off axis. Science 327, 701–704 (2010).

    Article  CAS  PubMed  Google Scholar 

  57. Simmons, J. A. The resolution of target range by echolocating bats. J. Acoust. Soc. Am. 54, 157–173 (1973).

    Article  CAS  PubMed  Google Scholar 

  58. Simmons, J. A. Perception of echo phase information in bat sonar. Science 204, 1336–1338 (1979).

    Article  CAS  PubMed  Google Scholar 

  59. Riquimaroux, H., Gaioni, S. J. & Suga, N. Cortical computational maps control auditory perception. Science 251, 565–568 (1991).

    Article  CAS  PubMed  Google Scholar 

  60. Bell, G. P. & Fenton, M. B. The use of Doppler-shifted echoes as a flutter detection and clutter rejection system - the echolocation and feeding-behavior of Hipposideros ruber (Chiroptera, Hipposideridae). Behav. Ecol. Sociobiol. 15, 109–114 (1984).

    Article  Google Scholar 

  61. Schnitzler, H.-U. & Denzinger, A. Auditory fovea and Doppler shift compensation: adaptations for flutter detection in echolocating bats using CF-FM signals. J. Comp. Physiol. A 197, 541–559 (2011).

    Article  Google Scholar 

  62. Simmons, J. A. et al. Target structure and echo spectral discrimination by echolocating bats. Science 186, 1130–1132 (1974).

    Article  CAS  PubMed  Google Scholar 

  63. Grunwald, J. E., Schörnich, S. & Wiegrebe, L. Classification of natural textures in echolocation. Proc. Natl Acad. Sci. USA 101, 5670–5674 (2004).

    Article  CAS  PubMed  Google Scholar 

  64. Simon, R., Holderied, M. W., Koch, C. U. & von Helversen, O. Floral acoustics: conspicuous echoes of a dish-shaped leaf attract bat pollinators. Science 333, 631–633 (2011).

    Article  CAS  PubMed  Google Scholar 

  65. Falk, B., Williams, T., Aytekin, M. & Moss, C. F. Adaptive behavior for texture discrimination by the free-flying big brown bat, Eptesicus fuscus. J. Comp. Physiol. A 197, 491–503 (2011).

    Article  Google Scholar 

  66. Genzel, D. & Wiegrebe, L. Size does not matter: size-invariant echo-acoustic object classification. J. Comp. Physiol. A 199, 159–168 (2013).

    Article  Google Scholar 

  67. Simmons, J. A., Fenton, M. B. & O'Farrell, M. J. Echolocation and pursuit of prey by bats. Science 203, 16–21 (1979).

    Article  CAS  PubMed  Google Scholar 

  68. Melcón, M. L., Denzinger, A. & Schnitzler, H.-U. Aerial hawking and landing: approach behaviour in Natterer's bats, Myotis nattereri (Kuhl 1818). J. Exp. Biol. 210, 4457–4464 (2007).

    Article  PubMed  Google Scholar 

  69. Skolnik, M. I. Introduction to Radar Systems (McGraw-Hill, 2001).

    Google Scholar 

  70. Berg, R. W. & Kleinfeld, D. Rhythmic whisking by rat: retraction as well as protraction of the vibrissae is under active muscular control. J. Neurophysiol. 89, 104–117 (2003).

    Article  PubMed  Google Scholar 

  71. Mitchinson, B., Martin, C. J., Grant, R. A. & Prescott, T. J. Feedback control in active sensing: rat exploratory whisking is modulated by environmental contact. Proc. Biol. Sci. 274, 1035–1041 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Grant, R. A., Mitchinson, B., Fox, C. W. & Prescott, T. J. Active touch sensing in the rat: anticipatory and regulatory control of whisker movements during surface exploration. J. Neurophysiol. 101, 862–874 (2009).

    Article  PubMed  Google Scholar 

  73. Deutsch, D., Pietr, M., Knutsen, P. M., Ahissar, E. & Schneidman, E. Fast feedback in active sensing: touch-induced changes to whisker-object interaction. PLoS ONE 7, e44272 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. McCamy, M. B., Otero-Millan, J., Di Stasi, L. L., Macknik, S. L. & Martinez-Conde, S. Highly informative natural scene regions increase microsaccade production during visual scanning. J. Neurosci. 34, 2956–2966 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Jakobsen, L. & Surlykke, A. Vespertilionid bats control the width of their biosonar sound beam dynamically during prey pursuit. Proc. Natl Acad. Sci. USA 107, 13930–13935 (2010).

    Article  CAS  PubMed  Google Scholar 

  76. Yovel, Y., Falk, B., Moss, C. F. & Ulanovsky, N. Active control of acoustic field-of-view in a biosonar system. PLoS Biol. 9, e1001150 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Lawrence, B. D. & Simmons, J. A. Measurements of atmospheric attenuation at ultrasonic frequencies and the significance for echolocation by bats. J. Acoust. Soc. Am. 71, 585–590 (1982).

    Article  CAS  PubMed  Google Scholar 

  78. Holderied, M. W. & von Helversen, O. Echolocation range and wingbeat period match in aerial-hawking bats. Proc. Biol. Sci. 270, 2293–2299 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Boonman, A., Bar-On, Y., Cvikel, N. & Yovel, Y. It's not black or white - on the range of vision and echolocation in echolocating bats. Front. Physiol. 4, 248 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Stilz, W. P. & Schnitzler, H.-U. Estimation of the acoustic range of bat echolocation for extended targets. J. Acoust. Soc. Am. 132, 1765–1775 (2012).

    Article  PubMed  Google Scholar 

  81. Williams, T. C., Williams, J. M. & Griffin, D. R. The homing ability of the neotropical bat Phyllostomus hastatus, with evidence for visual orientation. Anim. Behav. 14, 468–473 (1966).

    Article  CAS  PubMed  Google Scholar 

  82. Tsoar, A. et al. Large-scale navigational map in a mammal. Proc. Natl Acad. Sci. USA 108, E718–724 (2011). This study examined the navigation of Egyptian fruit bats in the wild, using global positioning system (GPS) data loggers, and provided the first behavioural evidence for a 100-km cognitive map in a mammal.

    Article  PubMed  Google Scholar 

  83. Neuweiler, G. The Biology of Bats (Oxford Univ. Press, 2000).

    Google Scholar 

  84. Heffner, R. S., Koay, G. & Heffner, H. E. Sound localization in an Old-World fruit bat (Rousettus aegyptiacus): acuity, use of binaural cues, and relationship to vision. J. Comp. Psychol. 113, 297–306 (1999).

    Article  CAS  PubMed  Google Scholar 

  85. Childs, S. B. & Buchler, E. R. Perception of simulated stars by Eptesicus fuscus (Vespertilionidae): A potential navigational mechanism. Anim. Behav. 29, 1028–1035 (1981).

    Article  Google Scholar 

  86. Jacobs, L. F. From chemotaxis to the cognitive map: the function of olfaction. Proc. Natl Acad. Sci. USA 109, 10693–10700 (2012).

    Article  PubMed  Google Scholar 

  87. Sterbing-D'Angelo, S. et al. Bat wing sensors support flight control. Proc. Natl Acad. Sci. USA 108, 11291–11296 (2011).

    Article  PubMed  Google Scholar 

  88. Horowitz, S. S., Cheney, C. A. & Simmons, J. A. Interaction of vestibular, echolocation, and visual modalities guiding flight by the big brown bat, Eptesicus fuscus. J. Vestib. Res. 14, 17–32 (2004).

    PubMed  Google Scholar 

  89. Holland, R. A., Thorup, K., Vonhof, M. J., Cochran, W. W. & Wikelski, M. Navigation: bat orientation using Earth's magnetic field. Nature 444, 702 (2006).

    Article  CAS  PubMed  Google Scholar 

  90. Wang, Y., Pan, Y., Parsons, S., Walker, M. & Zhang, S. Bats respond to polarity of a magnetic field. Proc. Biol. Sci. 274, 2901–2905 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Holland, R. A., Borissov, I. & Siemers, B. M. A nocturnal mammal, the greater mouse-eared bat, calibrates a magnetic compass by the sun. Proc. Natl Acad. Sci. USA 107, 6941–6945 (2010).

    Article  PubMed  Google Scholar 

  92. Laska, M. Olfactory Sensitivity to food odor components in the short-tailed fruit bat, Carollia perspicillata (Phyllostomatidae, Chiroptera). J. Comp. Physiol. A 166, 395–399 (1990).

    Article  Google Scholar 

  93. Stackman, R. W. & Taube, J. S. Firing properties of head direction cells in the rat anterior thalamic nucleus: dependence on vestibular input. J. Neurosci. 17, 4349–4358 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. O'Keefe, J. in The Hippocampus Book (eds Andersen, P., Morris, R. G., Amaral, D. G., Bliss, T. V. & O'Keefe, J.) 475–549 (Oxford Univ. Press, 2007).

    Google Scholar 

  95. Moser, E. I., Kropff, E. & Moser, M.-B. Place cells, grid cells, and the brain's spatial representation system. Annu. Rev. Neurosci. 31, 69–89 (2008).

    Article  CAS  PubMed  Google Scholar 

  96. 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).

    Article  CAS  PubMed  Google Scholar 

  97. Pfeiffer, B. E. & Foster, D. J. Hippocampal place-cell sequences depict future paths to remembered goals. Nature 497, 74–79 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. O'Keefe, J. & Conway, D. H. Hippocampal place units in the freely moving rat: why they fire where they fire. Exp. Brain Res. 31, 573–590 (1978).

    Article  CAS  PubMed  Google Scholar 

  99. Muller, R. U. & Kubie, J. L. The effects of changes in the environment on the spatial firing of hippocampal complex-spike cells. J. Neurosci. 7, 1951–1968 (1987).

    Article  CAS  PubMed  Google Scholar 

  100. Derdikman, D. & Moser, E. I. A manifold of spatial maps in the brain. Trends Cogn. Sci. 14, 561–569 (2010).

    Article  PubMed  Google Scholar 

  101. Solstad, T., Moser, E. I. & Einevoll, G. T. From grid cells to place cells: a mathematical model. Hippocampus 16, 1026–1031 (2006).

    Article  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  103. 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).

    Article  CAS  PubMed  Google Scholar 

  104. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Taube, J. S. Head direction cells recorded in the anterior thalamic nuclei of freely moving rats. J. Neurosci. 15, 70–86 (1995).

    Article  CAS  PubMed  Google Scholar 

  106. Knierim, J. J., Kudrimoti, H. S. & McNaughton, B. L. Place cells, head direction cells, and the learning of landmark stability. J. Neurosci. 15, 1648–1659 (1995).

    Article  CAS  PubMed  Google Scholar 

  107. Rubin, A., Yartsev, M. M. & Ulanovsky, N. Encoding of head direction by hippocampal place cells in bats. J. Neurosci. 34, 1067–1080 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Tolman, E. C. Cognitive maps in rats and men. Psychol. Rev. 55, 189–208 (1948).

    Article  CAS  PubMed  Google Scholar 

  109. McHugh, T. J., Blum, K. I., Tsien, J. Z., Tonegawa, S. & Wilson, M. A. Impaired hippocampal representation of space in CA1-specific NMDAR1 knockout mice. Cell 87, 1339–1349 (1996).

    Article  CAS  PubMed  Google Scholar 

  110. Ono, T., Nakamura, K., Nishijo, H. & Eifuku, S. Monkey hippocampal neurons related to spatial and nonspatial functions. J. Neurophysiol. 70, 1516–1529 (1993).

    Article  CAS  PubMed  Google Scholar 

  111. Ekstrom, A. D. et al. Cellular networks underlying human spatial navigation. Nature 425, 184–188 (2003).

    Article  CAS  PubMed  Google Scholar 

  112. Killian, N. J., Jutras, M. J. & Buffalo, E. A. A map of visual space in the primate entorhinal cortex. Nature 491, 761–764 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Jacobs, J. et al. Direct recordings of grid-like neuronal activity in human spatial navigation. Nature Neurosci. 16, 1188–1190 (2013).

    Article  CAS  PubMed  Google Scholar 

  114. Las, L. & Ulanovsky, N. in Space, Time and Memory in the Hippocampal Formation (eds Derdikman, D. & Knierim, J. J.) 431–465 (Springer, 2014).

    Book  Google Scholar 

  115. Etienne, A. S. & Jeffery, K. J. Path integration in mammals. Hippocampus 14, 180–192 (2004).

    Article  PubMed  Google Scholar 

  116. Etienne, A. S. et al. Navigation through vector addition. Nature 396, 161–164 (1998).

    Article  CAS  PubMed  Google Scholar 

  117. Cheung, A., Zhang, S., Stricker, C. & Srinivasan, M. V. Animal navigation: the difficulty of moving in a straight line. Biol. Cybern. 97, 47–61 (2007).

    Article  PubMed  Google Scholar 

  118. Cheung, A. Animal path integration: a model of positional uncertainty along tortuous paths. J. Theor. Biol. 341, 17–33 (2014).

    Article  PubMed  Google Scholar 

  119. 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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  121. Taylor, K. D. Range of movement and activity of common rats (Rattus norvegicus) on agricultural land. J. Appl. Ecol. 15, 663–677 (1978).

    Article  Google Scholar 

  122. Strosslin, T., Sheynikhovich, D., Chavarriaga, R. & Gerstner, W. Robust self-localisation and navigation based on hippocampal place cells. Neural Netw. 18, 1125–1140 (2005).

    Article  PubMed  Google Scholar 

  123. Sheynikhovich, D., Chavarriaga, R., Strosslin, T., Arleo, A. & Gerstner, W. Is there a geometric module for spatial orientation? Insights from a rodent navigation model. Psychol. Rev. 116, 540–566 (2009).

    Article  PubMed  Google Scholar 

  124. Zeil, J. Visual homing: an insect perspective. Curr. Opin. Neurobiol. 22, 285–293 (2012). This paper highlighted the richness of sensory information available for navigation outdoors, which is not captured by typical laboratory experiments conducted in empty boxes. The paper also described the idea of view-based navigation in insects.

    Article  CAS  PubMed  Google Scholar 

  125. Dupret, D., O'Neill, J., Pleydell-Bouverie, B. & Csicsvari, J. The reorganization and reactivation of hippocampal maps predict spatial memory performance. Nature Neurosci. 13, 995–1002 (2010).

    Article  CAS  PubMed  Google Scholar 

  126. Jensen, M. E., Moss, C. F. & Surlykke, A. Echolocating bats can use acoustic landmarks for spatial orientation. J. Exp. Biol. 208, 4399–4410 (2005).

    Article  PubMed  Google Scholar 

  127. Zadicario, P., Avni, R., Zadicario, E. & Eilam, D. 'Looping' - an exploration mechanism in a dark open field. Behav. Brain Res. 159, 27–36 (2005).

    Article  PubMed  Google Scholar 

  128. Avni, R., Zadicario, P. & Eilam, D. Exploration in a dark open field: a shift from directional to positional progression and a proposed model of acquiring spatial information. Behav. Brain Res. 171, 313–323 (2006).

    Article  PubMed  Google Scholar 

  129. Mendelssohn, H. & Yom-Tov, Y. Fauna Palaestina: Mammalia of Israel (The Israel Academy of Sciences and Humanities, 1999).

    Google Scholar 

  130. Cnotka, J., Möhle, M. & Rehkämper, G. Navigational experience affects hippocampus size in homing pigeons. Brain Behav. Evol. 72, 233–238 (2008).

    Article  PubMed  Google Scholar 

  131. Jacobs, L. F., Gaulin, S. J., Sherry, D. F. & Hoffman, G. E. Evolution of spatial cognition: sex-specific patterns of spatial behavior predict hippocampal size. Proc. Natl Acad. Sci. USA 87, 6349–6352 (1990).

    Article  CAS  PubMed  Google Scholar 

  132. Safi, K. & Dechmann, D. K. Adaptation of brain regions to habitat complexity: a comparative analysis in bats (Chiroptera). Proc. Biol. Sci. 272, 179–186 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  133. Maguire, E. A. et al. Navigation-related structural change in the hippocampi of taxi drivers. Proc. Natl Acad. Sci. USA 97, 4398–4403 (2000). This paper suggested involvement of the human hippocampus in long-distance navigation. The study showed that the volume of posterior hippocampus is larger in London taxi drivers, who are navigational experts, compared to control subjects; and hippocampal volume also correlated with years of experience as a taxi driver.

    Article  CAS  PubMed  Google Scholar 

  134. Yartsev, M. M. & Ulanovsky, N. Representation of three-dimensional space in the hippocampus of flying bats. Science 340, 367–372 (2013). This study reported the first neural recordings in freely flying bats, and demonstrated three-dimensional spherical place fields during flight, as well as scaling of place-field size with three-dimensional environmental size.

    Article  CAS  PubMed  Google Scholar 

  135. Amaral, D. & Lavenex, P. in The Hippocampus Book (eds Andersen, P., Morris, R. G., Amaral, D. G., Bliss, T. V. & O'Keefe, J.) 37–115 (Oxford Univ. Press, 2007).

    Google Scholar 

  136. Fenton, A. A. et al. Unmasking the CA1 ensemble place code by exposures to small and large environments: more place cells and multiple, irregularly arranged, and expanded place fields in the larger space. J. Neurosci. 28, 11250–11262 (2008). This paper showed that when a standard experimental box was doubled in size, hippocampal place cells exhibited an increased number of place fields per neuron.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Park, E., Dvorak, D. & Fenton, A. A. Ensemble place codes in hippocampus: CA1, CA3, and dentate gyrus place cells have multiple place fields in large environments. PLoS ONE 6, e22349 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Jung, M. W., Wiener, S. I. & McNaughton, B. L. Comparison of spatial firing characteristics of units in dorsal and ventral hippocampus of the rat. J. Neurosci. 14, 7347–7356 (1994). This paper provided the first report of the dorsoventral scaling of place-field size in hippocampal place cells.

    Article  CAS  PubMed  Google Scholar 

  139. Maurer, A. P., VanRhoads, S. R., Sutherland, G. R., Lipa, P. & McNaughton, B. L. Self-motion and the origin of differential spatial scaling along the septo-temporal axis of the hippocampus. Hippocampus 15, 841–852 (2005).

    Article  PubMed  Google Scholar 

  140. Poucet, B., Thinus-Blanc, C. & Muller, R. U. Place cells in the ventral hippocampus of rats. Neuroreport 5, 2045–2048 (1994).

    Article  CAS  PubMed  Google Scholar 

  141. Brun, V. H. et al. Progressive increase in grid scale from dorsal to ventral medial entorhinal cortex. Hippocampus 18, 1200–1212 (2008).

    Article  PubMed  Google Scholar 

  142. Stensola, H. et al. The entorhinal grid map is discretized. Nature 492, 72–78 (2012). This study showed a modular organization of grid cells, with an increase in grid scale along the dorsoventral axis of the medial entorhinal cortex.

    Article  CAS  PubMed  Google Scholar 

  143. Barry, C., Ginzberg, L. L., O'Keefe, J. & Burgess, N. Grid cell firing patterns signal environmental novelty by expansion. Proc. Natl Acad. Sci. USA 109, 17687–17692 (2012).

    Article  PubMed  Google Scholar 

  144. Worden, R. Navigation by fragment fitting: a theory of hippocampal function. Hippocampus 2, 165–187 (1992).

    Article  CAS  PubMed  Google Scholar 

  145. Wolbers, T. & Wiener, J. M. Challenges for identifying the neural mechanisms that support spatial navigation: the impact of spatial scale. Front. Hum. Neurosci. 8, 571 (2014). This paper focused on the complexities of human navigation and the effects of spatial scale. The paper highlighted why small-scale navigation in boxes does not fully capture real-life navigation, and offered a number of suggestions as to how to approach the problem of large-scale human navigation.

    Article  PubMed  PubMed Central  Google Scholar 

  146. Montello, D. R. in Spatial Information Theory: a Theoretical Basis for GIS, European Conference COSIT 1993, Lecture Notes in Computer Science 716 (eds Hirtle, S. C. & Frank, A. U.) 312–321 (Springer, 1993).

    Google Scholar 

  147. Meilinger, T. in Spatial Cognition VI: Learning, Reasoning, and Talking About Space, International Conference Spatial Cognition (eds Freksa, C., Newcombe, N.S., Gärdenfors, P. & Wölfl, S.) 344–360 (Springer, 2008).

    Book  Google Scholar 

  148. Rich, P. D., Liaw, H. P. & Lee, A. K. Large environments reveal the statistical structure governing hippocampal representations. Science 345, 814–817 (2014).

    Article  CAS  PubMed  Google Scholar 

  149. Derdikman, D. et al. Fragmentation of grid cell maps in a multicompartment environment. Nature Neurosci. 12, 1325–1332 (2009). This paper showed that both place coding and grid coding break down in compartmentalized environments. This highlighted the need to study neural codes for space in more complex habitats.

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  151. Whitlock, J. R., Pfuhl, G., Dagslott, N., Moser, M.-B. & Moser, E. I. Functional split between parietal and entorhinal cortices in the rat. Neuron 73, 789–802 (2012).

    Article  CAS  PubMed  Google Scholar 

  152. Harvey, C. D., Coen, P. & Tank, D. W. Choice-specific sequences in parietal cortex during a virtual-navigation decision task. Nature 484, 62–68 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Wood, E. R., Dudchenko, P. A., Robitsek, R. J. & Eichenbaum, H. Hippocampal neurons encode information about different types of memory episodes occurring in the same location. Neuron 27, 623–633 (2000).

    Article  CAS  PubMed  Google Scholar 

  155. Johnson, A. & Redish, A. D. Neural ensembles in CA3 transiently encode paths forward of the animal at a decision point. J. Neurosci. 27, 12176–12189 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Whitlock, J. R., Sutherland, R. J., Witter, M. P., Moser, M. -B. & Moser, E. I. Navigating from hippocampus to parietal cortex. Proc. Natl Acad. Sci. USA 105, 14755–14762 (2008).

    Article  PubMed  Google Scholar 

  157. Foster, D. J. & Knierim, J. J. Sequence learning and the role of the hippocampus in rodent navigation. Curr. Opin. Neurobiol. 22, 294–300 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Smirnakis, S. M., Berry, M. J., Warland, D. K., Bialek, W. & Meister, M. Adaptation of retinal processing to image contrast and spatial scale. Nature 386, 69–73 (1997).

    Article  CAS  PubMed  Google Scholar 

  159. Fairhall, A. L., Lewen, G. D., Bialek, W. & de Ruyter Van Steveninck, R. R. Efficiency and ambiguity in an adaptive neural code. Nature 412, 787–792 (2001).

    Article  CAS  PubMed  Google Scholar 

  160. Ulanovsky, N., Las, L. & Nelken, I. Processing of low-probability sounds by cortical neurons. Nature Neurosci. 6, 391–398 (2003).

    Article  CAS  PubMed  Google Scholar 

  161. Ulanovsky, N., Las, L., Farkas, D. & Nelken, I. Multiple time scales of adaptation in auditory cortex neurons. J. Neurosci. 24, 10440–10453 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Antunes, F. M., Nelken, I., Covey, E. & Malmierca, M. S. Stimulus-specific adaptation in the auditory thalamus of the anesthetized rat. PLoS ONE 5, e14071 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Burak, Y. & Fiete, I. R. Accurate path integration in continuous attractor network models of grid cells. PLoS Comput. Biol. 5, e1000291 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Finkelstein, A. et al. Three-dimensional head-direction coding in the bat brain. Nature 517, 159–164 (2015). This paper reported on three-dimensional tuning of head-direction cells in bats; the first three-dimensional neural compass described in any mammal. These cells could support navigation in three-dimensional space.

    Article  CAS  PubMed  Google Scholar 

  165. Jones, G. & Holderied, M. W. Bat echolocation calls: adaptation and convergent evolution. Proc. Biol. Sci. 274, 905–912 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  166. Gillam, E. H., Ulanovsky, N. & McCracken, G. F. Rapid jamming avoidance in biosonar. Proc. Biol. Sci. 274, 651–660 (2007).

    Article  PubMed  Google Scholar 

  167. Holderied, M. W., Jones, G. & von Helversen, O. Flight and echolocation behaviour of whiskered bats commuting along a hedgerow: range-dependent sonar signal design, Doppler tolerance and evidence for 'acoustic focussing'. J. Exp. Biol. 209, 1816–1826 (2006).

    Article  PubMed  Google Scholar 

  168. Jutras, M. J., Fries, P. & Buffalo, E. A. Oscillatory activity in the monkey hippocampus during visual exploration and memory formation. Proc. Natl Acad. Sci. USA 110, 13144–13149 (2013).

    Article  PubMed  Google Scholar 

  169. Peebles, P. Z. Radar Principles (Wiley, 1998).

    Google Scholar 

  170. Jones, G. Echolocation. Curr. Biol. 15, R484–R488 (2005).

    Article  CAS  PubMed  Google Scholar 

  171. Aikath, D., Weible, A. P., Rowland, D. C. & Kentros, C. G. Role of self-generated odor cues in contextual representation. Hippocampus (2014).

  172. Zhang, S., Schönfeld, F., Wiskott, L. & Manahan-Vaughan, D. Spatial representations of place cells in darkness are supported by path integration and border information. Front. Behav. Neurosci. 8, 222 (2014).

    PubMed  PubMed Central  Google Scholar 

  173. Battaglia, F. P., Sutherland, G. R. & McNaughton, B. L. Local sensory cues and place cell directionality: additional evidence of prospective coding in the hippocampus. J. Neurosci. 24, 4541–4550 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  174. Olypher, A. V., Lansky, P., Muller, R. U. & Fenton, A. A. Quantifying location-specific information in the discharge of rat hippocampal place cells. J. Neurosci. Methods 127, 123–135 (2003).

    Article  CAS  PubMed  Google Scholar 

  175. Ulanovsky, N. & Moss, C. F. Dynamics of hippocampal spatial representation in echolocating bats. Hippocampus 21, 150–161 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  176. Yovel, Y., Geva-Sagiv, M. & Ulanovsky, N. Click-based echolocation in bats: not so primitive after all. J. Comp. Physiol. A 197, 515–530 (2011).

    Article  Google Scholar 

  177. Gallistel, C. R. The Organization of Learning (MIT Press, 1990).

    Google Scholar 

  178. Buchler, E. R. & Childs, S. B. Orientation to distant sounds by foraging big brown bats (Eptesicus fuscus). Anim. Behav. 29, 428–432 (1981).

    Article  Google Scholar 

  179. Blatcheley, W. S. in Indiana Caves and their Fauna. Indiana Department of Geology and Natural Resources, 21st Annual Report 121–212 (1896).

    Book  Google Scholar 

  180. Mittelstaedt, M. L. & Mittelstaedt, H. in Avian Navigation (eds Papi, F. & Wallraff, H. G.) 290–297 (Springer, 1982).

    Book  Google Scholar 

  181. Wolf, H. Odometry and insect navigation. J. Exp. Biol. 214, 1629–1641 (2011).

    Article  PubMed  Google Scholar 

  182. Wehner, R. & Wehner, S. Path Integration in desert ants — approaching a long-standing puzzle in insect navigation. Monit. Zool. Ital. 20, 309–331 (1986).

    Google Scholar 

  183. Maaswinkel, H. & Whishaw, I. Q. Homing with locale, taxon, and dead reckoning strategies by foraging rats: sensory hierarchy in spatial navigation. Behav. Brain Res. 99, 143–152 (1999).

    Article  CAS  PubMed  Google Scholar 

  184. Höller, P. & Schmidt, U. The orientation behaviour of the lesser spearnosed bat, Phyllostomus discolor (Chiroptera) in a model roost. J. Comp. Physiol. A 179, 245–254 (1996).

    Article  PubMed  Google Scholar 

  185. Höller, P. Orientation by the bat Phyllostomus discolor (Phyllostomidae) on the return flight to its roosting place. Ethology 100, 72–83 (1995).

    Article  Google Scholar 

  186. Bennett, A. T. Do animals have cognitive maps? J. Exp. Biol. 199, 219–224 (1996).

    CAS  PubMed  Google Scholar 

  187. Wiltschko, R. & Wiltschko, W. Magnetoreception. Adv. Exp. Med. Biol. 739, 126–141 (2012).

    Article  CAS  PubMed  Google Scholar 

  188. Riggs, L. A. in Vision and Visual Perception (ed. Graham, C. H.) 321–349 (Wiley, 1965).

    Google Scholar 

  189. Suthers, R. A. in Biology of Bats (ed. Wimsatt, W. A.) 265–309 (Academic Press, 1970).

    Google Scholar 

  190. Moulton, D. G. & Eayrs, J. T. Studies in olfactory acuity: II. Relative detectability of n-aliphatic alcohols by the rat. Q. J. Exp. Psychol. 12, 99–109 (1960).

    Article  Google Scholar 

  191. Moulton, D. G. Studies in olfactory acuity: III. relative detectability of n-aliphatic acetates by the rat. Q. J. Exp. Psychol. 12, 203–213 (1960).

    Article  Google Scholar 

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Acknowledgements

We thank D. Derdikman, S. Romani, A. Finkelstein, A. Rubin, T. Eliav, G. Ginosar, A. Wallach and R. Paz for helpful comments on the manuscript; D. Sheynikhovich for simulations of the view-based model of place cells; and G. Brodsky for graphics. This work was supported by research grants to N.U. from the European Research Council (ERC–NEUROBAT), the Human Frontiers Science Program (HFSP RGP0062/2009-C), and the Israel Science Foundation (ISF 1017/08 and ISF 1319/13).

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Glossary

Place cells

Hippocampal neurons that become active whenever the animal traverses a specific location in the environment, called the 'place field'. The dimensions of the place field govern the spatial resolution of a single place cell; and together, multiple place cells are thought to represent a mental map of absolute (allocentric) space.

Grid cells

Neurons in the medial entorhinal cortex (and some adjacent regions) that become active whenever the animal traverses one of the vertices of a periodic hexagonal or triangular lattice that tiles the environment.

Head-direction cells

Neurons found in multiple brain areas, which become active whenever the animal's head points to a specific absolute (allocentric) direction, thus providing a compass signal.

Doppler effect

The change in wave frequency for an observer that is moving relative to the wave source. For example, when an ambulance with a siren approaches an observer, a high-pitched sound (high frequency) is heard, but the perceived frequency drops when the ambulance passes and drives away. Bats know their own emitted frequency, and thus can use the perceived shifted frequency of the echo (Doppler shift) to compute the relative velocity of the target.

Magnetosensation

The ability to detect the Earth's magnetic field and use it to compute direction or spatial position. Utilizing magnetosensation for navigation purposes has been described in many animals, including some rodents and bats.

Egocentric coordinates

Coordinates that are given relative to the body axis; for example, '1 km to your left'.

Allocentric coordinates

Coordinates that are independent of the observer's orientation; for example, '1 km North of Tel Aviv'. Also known as absolute-space coordinates.

Border cells

(Also known as boundary cells.) Neurons that become active when the animal is close to a salient border of the environment, thus signalling the environmental geometry.

Distal senses

Senses that provide long-range information to the animal. For rats, vision is the primary distal sense. Bats have two distal senses, echolocation and vision, when considering a small environment like a cave or a room. However, echolocation range is limited to < 100 m, so on a scale of kilometres, echolocation may be classified as proximal, while vision remains a truly distal sense. In both species, olfaction is a proximal sense in enclosed spaces (cave, burrow), but may serve as a distal sense outdoors where winds can carry odours from afar.

Proximal senses

Senses that are restricted to a short range. For rats, somatosensation (whisking) and olfaction are the primary proximal senses.

Dorsoventral axis of the hippocampus

The hippocampus of rats and bats is an elongated, banana-shaped structure, and its long axis is referred to as the dorsoventral axis (or septotemporal axis). Place fields increase in size approximately 10-fold along this axis.

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Geva-Sagiv, M., Las, L., Yovel, Y. et al. Spatial cognition in bats and rats: from sensory acquisition to multiscale maps and navigation. Nat Rev Neurosci 16, 94–108 (2015). https://doi.org/10.1038/nrn3888

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