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Interactions between rodent visual and spatial systems during navigation

Abstract

Many behaviours that are critical for animals to survive and thrive rely on spatial navigation. Spatial navigation, in turn, relies on internal representations about one’s spatial location, one’s orientation or heading direction and the distance to objects in the environment. Although the importance of vision in guiding such internal representations has long been recognized, emerging evidence suggests that spatial signals can also modulate neural responses in the central visual pathway. Here, we review the bidirectional influences between visual and navigational signals in the rodent brain. Specifically, we discuss reciprocal interactions between vision and the internal representations of spatial position, explore the effects of vision on representations of an animal’s heading direction and vice versa, and examine how the visual and navigational systems work together to assess the relative distances of objects and other features. Throughout, we consider how technological advances and novel ethological paradigms that probe rodent visuo-spatial behaviours allow us to advance our understanding of how brain areas of the central visual pathway and the spatial systems interact and enable complex behaviours.

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Fig. 1: Brain areas that represent information related to space, vision and head direction.
Fig. 2: Visual control of spatial representations and spatial signals in visual areas.
Fig. 3: Influence of vision on head-direction cells and influences of head orientation on visual cortex activity.
Fig. 4: The influence of visual depth signals on visuo-spatial processing.

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References

  1. Parker, P. R. L. et al. Distance estimation from monocular cues in an ethological visuomotor task. eLife 11, e74708 (2022). Through the development of a visual distance estimation task for freely moving mice, this study reveals that mice can effectively exploit monocular cues, in particular motion parallax cues from headbobs, to estimate visual depth.

    PubMed  PubMed Central  Google Scholar 

  2. Boone, H. C. et al. Natural binocular depth discrimination behavior in mice explained by visual cortical activity. Curr. Biol. 31, 2191–2198.e3 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Shamash, P. et al. Mice learn multi-step routes by memorizing subgoal locations. Nat. Neurosci. 24, 1270–1279 (2021).

    CAS  PubMed  Google Scholar 

  4. Hoy, J. L., Yavorska, I., Wehr, M. & Niell, C. M. Vision drives accurate approach behavior during prey capture in laboratory mice. Curr. Biol. 26, 3046–3052 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Johnson, K. P. et al. Cell-type-specific binocular vision guides predation in mice. Neuron 109, 1527–1539.e4 (2021). This study identifies the RGC types responsible for ipsilateral projections (ipsi-RGCs) and demonstrates that selective ablation of these specific cells (<2% of RGCs) in adult mice significantly impairs their hunting success.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Michaiel, A. M., Abe, E. T. & Niell, C. M. Dynamics of gaze control during prey capture in freely moving mice. eLife 9, e57458 (2020). In this work, recordings of eye and head position during mouse prey capture reveal that eye movements in mice, even during dynamic and interactive behaviours, serve the dual role of maintaining gaze stability during head movements and facilitating gaze relocation during directed head turns with remarkable accuracy.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Yilmaz, M. & Meister, M. Rapid innate defensive responses of mice to looming visual stimuli. Curr. Biol. 23, 2011–2015 (2013).

    CAS  PubMed  Google Scholar 

  8. De Franceschi, G., Vivattanasarn, T., Saleem, A. B. & Solomon, S. G. Vision guides selection of freeze or flight defense strategies in mice. Curr. Biol. 26, 2150–2154 (2016).

    PubMed  Google Scholar 

  9. La Chioma, A., Bonhoeffer, T. & Hübener, M. Area-specific mapping of binocular disparity across mouse visual cortex. Curr. Biol. 29, 2954–2960.e5 (2019).

    PubMed  Google Scholar 

  10. Morris, R. G. M., Garrud, P., Rawlins, J. N. P. & O’Keefe, J. Place navigation impaired in rats with hippocampal lesions. Nature 297, 681–683 (1982).

    CAS  PubMed  Google Scholar 

  11. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 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 

  13. 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 

  14. 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). As the present Review briefly touches upon descriptions of the various spatial cell types, we refer readers to this review for an extensive discussion of the various cell types in the spatial system.

    CAS  PubMed  Google Scholar 

  15. 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 

  16. 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 

  17. Wiener, S. I. and Taube, J. S. Head Direction Cells and the Neural Mechanisms of Spatial Orientation (MIT Press, 2005).

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

    CAS  PubMed  Google Scholar 

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

  20. Yoder, R. M., Clark, B. J. & Taube, J. S. Origins of landmark encoding in the brain. Trends Neurosci. 34, 561–571 (2011). This review summarizes evidence on how visual information could be processed along several cortical processing streams and is transformed into spatial signals within the limbic system, highlighting the role of the dorsal presubiculum.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Saleem, A. B. Two stream hypothesis of visual processing for navigation in mouse. Curr. Opin. Neurobiol. 64, 70–78 (2020).

    CAS  PubMed  Google Scholar 

  22. Saleem, A. B., Diamanti, E. M., Fournier, J., Harris, K. D. & Carandini, M. Coherent encoding of subjective spatial position in visual cortex and hippocampus. Nature 562, 124–127 (2018). This study reveals spatial modulations of mouse V1 neurons by showing that V1 neurons respond differently to the same visual landmark in different spatial positions along a VR corridor, and that the modulations align with hippocampal representations.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Fiser, A. et al. Experience-dependent spatial expectations in mouse visual cortex. Nat. Neurosci. 19, 1658–1664 (2016).

    CAS  PubMed  Google Scholar 

  24. Diamanti, E. M. et al. Spatial modulation of visual responses arises in cortex with active navigation. eLife 10, e63705 (2021). This study suggests that spatial modulation in the central visual pathway emerges in V1, persists through HVAs, and is enhanced by active exploration.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Vélez-Fort, M. et al. A circuit for integration of head- and visual-motion signals in layer 6 of mouse primary visual cortex. Neuron 98, 179–191.e6 (2018). This study shows the existence of signals related to the direction and angular velocity of horizontal rotation of the head in neurons in layer 6 of mouse V1, suggesting that visual-motion processing in V1 L6 is multisensory and contextually dependent on the motion status of the animal’s head.

    PubMed  PubMed Central  Google Scholar 

  26. Miura, S. K. & Scanziani, M. Distinguishing externally from saccade-induced motion in visual cortex. Nature 610, 135–142 (2022). This study demonstrates that during saccadic eye movements, by integrating a non-visual input received from the pulvinar with the visual input from the retina, V1 shows differential responses to external and self-generated motion.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Meyer, A. F., Poort, J., O’Keefe, J., Sahani, M. & Linden, J. F. A head-mounted camera system integrates detailed behavioral monitoring with multichannel electrophysiology in freely moving mice. Neuron 100, 46–60.e7 (2018). This work is an open-source toolkit for a lightweight, head-mounted head and eye-tracking system for mice, which provides a crucial methodological foundation for studying vision in mice during unrestricted movement.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Song, E. Y., Kim, Y. B., Kim, Y. H. & Jung, M. W. Role of active movement in place-specific firing of hippocampal neurons. Hippocampus 15, 8–17 (2005).

    PubMed  Google Scholar 

  29. Chen, G., King, J. A., Burgess, N. & O’Keefe, J. How vision and movement combine in the hippocampal place code. Proc. Natl Acad. Sci. USA 110, 378–383 (2013).

    CAS  PubMed  Google Scholar 

  30. Terrazas, A. et al. Self-motion and the hippocampal spatial metric. J. Neurosci. 25, 8085–8096 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 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 

  32. Wallace, D. J. et al. Rats maintain an overhead binocular field at the expense of constant fusion. Nature 498, 65–69 (2013).

    CAS  PubMed  Google Scholar 

  33. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Grieves, R. M. & Jeffery, K. J. The representation of space in the brain. Behav. Process. 135, 113–131 (2017). This review provides an overview of the literature on place cells, HD cells and grid cells, highlighting their role in the formation of a cognitive map, and discusses additional spatially modulated neurons that may contribute to this map.

    Google Scholar 

  35. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Muller, R. U., Bostock, E., Taube, J. S. & Kubie, J. L. On the directional firing properties of hippocampal place cells. J. Neurosci. 14, 7235–7251 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed  Google Scholar 

  38. Jeffery, K. J., Wilson, J. J., Casali, G. & Hayman, R. M. Neural encoding of large-scale three-dimensional space — properties and constraints. Front. Psychol. 6, 927 (2015).

    PubMed  PubMed Central  Google Scholar 

  39. O’Keefe, J. & Speakman, A. Single unit activity in the rat hippocampus during a spatial memory task. Exp. Brain Res. 68, 1–27 (1987).

    PubMed  Google Scholar 

  40. Lenck-Santini, P. P., Save, E. & Poucet, B. Evidence for a relationship between place-cell spatial firing and spatial memory performance. Hippocampus 11, 377–390 (2001).

    CAS  PubMed  Google Scholar 

  41. Fournier, J. et al. Mouse visual cortex is modulated by distance traveled and by theta oscillations. Curr. Biol. 30, 3811–3817.e6 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Keinath, A. T., Julian, J. B., Epstein, R. A. & Muzzio, I. A. Environmental geometry aligns the hippocampal map during spatial reorientation. Curr. Biol. 27, 309–317 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Lenck-Santini, P.-P., Muller, R. U., Save, E. & Poucet, B. Relationships between place cell firing fields and navigational decisions by rats. J. Neurosci. 22, 9035–9047 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 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 

  45. Jeffery, K. J. Spatial cognition: entorhinal cortex and the hippocampal place-cell map. Curr. Biol. 25, R1181–R1183 (2015).

    CAS  PubMed  Google Scholar 

  46. Radvansky, B. A., Oh, J. Y., Climer, J. R. & Dombeck, D. A. Behavior determines the hippocampal spatial mapping of a multisensory environment. Cell Rep. 36, 109444 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Save, E., Nerad, L. & Poucet, B. Contribution of multiple sensory information to place field stability in hippocampal place cells. Hippocampus 10, 64–76 (2000).

    CAS  PubMed  Google Scholar 

  48. Jeffery, K. J. Integration of the sensory inputs to place cells: what, where, why, and how? Hippocampus 17, 775–785 (2007).

    PubMed  Google Scholar 

  49. Morris, R. G. M. Spatial localization does not require the presence of local cues. Learn. Motiv. 12, 239–260 (1981).

    Google Scholar 

  50. Fenton, A. A., Arolfo, M. P., Nerad, L. & Bures, J. Place navigation in the Morris water maze under minimum and redundant extra-maze cue conditions. Behav. Neural Biol. 62, 178–189 (1994).

    CAS  PubMed  Google Scholar 

  51. Liu, Z., Francis Turner, L. & Bures, J. Impairment of place navigation of rats in the Morris water maze by intermittent light is inversely related to the duration of the flash. Neurosci. Lett. 180, 59–62 (1994).

    CAS  PubMed  Google Scholar 

  52. Arolfo, M. P., Nerad, L., Schenk, F. & Bures, J. Absence of snapshot memory of the target view interferes with place navigation learning by rats in the water maze. Behav. Neurosci. 108, 308–316 (1994).

    CAS  PubMed  Google Scholar 

  53. Prusky, G. T., West, P. W. R. & Douglas, R. M. Reduced visual acuity impairs place but not cued learning in the Morris water task. Behavioural Brain Res. 116, 135–140 (2000).

    CAS  Google Scholar 

  54. Chapillon, P. Very brief exposure to visual distal cues is sufficient for young mice to navigate in the Morris water maze. Behav. Process. 46, 15–24 (1999).

    CAS  Google Scholar 

  55. Jeffery, K. J. & O’Keefe, J. M. Learned interaction of visual and idiothetic cues in the control of place field orientation. Exp. Brain Res. 127, 151–161 (1999).

    CAS  PubMed  Google Scholar 

  56. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Scaplen, K. M., Gulati, A. A., Heimer-McGinn, V. L. & Burwell, R. D. Objects and landmarks: hippocampal place cells respond differently to manipulations of visual cues depending on size, perspective, and experience. Hippocampus 24, 1287–1299 (2014).

    PubMed  PubMed Central  Google Scholar 

  58. Fenton, A. A., Csizmadia, G. & Muller, R. U. Conjoint control of hippocampal place cell firing by two visual stimuli. I. The effects of moving the stimuli on firing field positions. J. Gen. Physiol. 116, 191–209 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Spiers, H. J., Hayman, R. M. A., Jovalekic, A., Marozzi, E. & Jeffery, K. J. Place field repetition and purely local remapping in a multicompartment environment. Cereb. Cortex 25, 10–25 (2015).

    PubMed  Google Scholar 

  60. Harland, B. et al. Lesions of the head direction cell system increase hippocampal place field repetition. Curr. Biol. 27, 2706–2712.e2 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Chen, G., Manson, D., Cacucci, F. & Wills, T. J. Absence of visual input results in the disruption of grid cell firing in the mouse. Curr. Biol. 26, 2335–2342 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Quirk, G. J., Muller, R. U. & Kubie, J. L. The firing of hippocampal place cells in the dark depends on the rat’s recent experience. J. Neurosci. 10, 2008–2017 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Cheng, K. & Newcombe, N. S. Is there a geometric module for spatial orientation? Squaring theory and evidence. Psychon. Bull. Rev. 12, 1–23 (2005).

    PubMed  Google Scholar 

  64. Knight, R., Hayman, R., Lin Ginzberg, L. & Jeffery, K. Geometric cues influence head direction cells only weakly in nondisoriented rats. J. Neurosci. 31, 15681–15692 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Clark, B. J., Harris, M. J. & Taube, J. S. Control of anterodorsal thalamic head direction cells by environmental boundaries: comparison with conflicting distal landmarks. Hippocampus 22, 172–187 (2012).

    PubMed  Google Scholar 

  66. Dombeck, D. A., Khabbaz, A. N., Collman, F., Adelman, T. L. & Tank, D. W. Imaging large-scale neural activity with cellular resolution in awake, mobile mice. Neuron 56, 43–57 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Dombeck, D. A., Harvey, C. D., Tian, L., Looger, L. L. & Tank, D. W. Functional imaging of hippocampal place cells at cellular resolution during virtual navigation. Nat. Neurosci. 13, 1433–1440 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Thurley, K. & Ayaz, A. Virtual reality systems for rodents. Curr. Zool. 63, 109–119 (2017).

    PubMed  Google Scholar 

  69. Minderer, M., Harvey, C. D., Donato, F. & Moser, E. I. Neuroscience: virtual reality explored. Nature 533, 324–325 (2016).

    CAS  PubMed  Google Scholar 

  70. Cushman, J. D. et al. Multisensory control of multimodal behavior: do the legs know what the tongue is doing? PLoS ONE 8, e80465 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Ravassard, P. et al. Multisensory control of hippocampal spatiotemporal selectivity. Science 340, 1342–1346 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Campbell, M. G. et al. Principles governing the integration of landmark and self-motion cues in entorhinal cortical codes for navigation. Nat. Neurosci. 21, 1096–1106 (2018). This study reports that the integration of landmarks and self-motion cues by entorhinal grid cells, border cells and speed cells is context dependent, where the degree and direction of VR gain manipulations determine the context.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Kinkhabwala, A. A., Gu, Y., Aronov, D. & Tank, D. W. Visual cue-related activity of cells in the medial entorhinal cortex during navigation in virtual reality. eLife 9, e43140 (2020). This study discovers ‘cue cells’ in the MEC, which have firing fields close to visual landmarks in the environment, and thus are suggested to have an important role in correcting errors accumulated during path integration.

    PubMed  PubMed Central  Google Scholar 

  74. Casali, G., Shipley, S., Dowell, C., Hayman, R. & Barry, C. Entorhinal neurons exhibit cue locking in rodent VR. Front. Cell. Neurosci. 12, 512 (2018).

    PubMed  Google Scholar 

  75. Purandare, C. S. et al. Moving bar of light evokes vectorial spatial selectivity in the immobile rat hippocampus. Nature 602, 461–467 (2022). Using a visual display around a body-fixed rat on a spherical treadmill, this study finds that a significant portion of dorsal CA1 neurons in the hippocampus show stable tuning for the angular position of a moving bar of light, independent of behaviour and rewards, thus enabling the generation of a spatial representation based on a purely visual input.

    CAS  PubMed  Google Scholar 

  76. Ji, D. & Wilson, M. A. Coordinated memory replay in the visual cortex and hippocampus during sleep. Nat. Neurosci. 10, 100–107 (2007). This study finds that during slow-wave sleep, rat V1 has periods of high activity, during which multi-cell firing sequences replay awake experiences coincident with memory replay events in the hippocampus.

    CAS  PubMed  Google Scholar 

  77. Haggerty, D. C. & Ji, D. Activities of visual cortical and hippocampal neurons co-fluctuate in freely moving rats during spatial behavior. eLife 4, e08902 (2015).

    PubMed  PubMed Central  Google Scholar 

  78. Morimoto, M. M., Uchishiba, E. & Saleem, A. B. Organization of feedback projections to mouse primary visual cortex. iScience 24, 102450 (2021).

    PubMed  PubMed Central  Google Scholar 

  79. Wang, Q., Gao, E. & Burkhalter, A. Gateways of ventral and dorsal streams in mouse visual cortex. J. Neurosci. 31, 1905–1918 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Taube, J. S., Goodridge, J. P., Golob, E. J., Dudchenko, P. A. & Stackman, R. W. Processing the head direction cell signal: a review and commentary. Brain Res. Bull. 40, 477–484 (1996).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  82. Dudchenko, P. A., Wood, E. R. & Smith, A. A new perspective on the head direction cell system and spatial behavior. Neurosci. Biobehav. Rev. 105, 24–33 (2019).

    PubMed  Google Scholar 

  83. Mizumori, S. J. & Williams, J. D. Directionally selective mnemonic properties of neurons in the lateral dorsal nucleus of the thalamus of rats. J. Neurosci. 13, 4015–4028 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Blair, H. T. & Sharp, P. E. Anticipatory head direction signals in anterior thalamus: evidence for a thalamocortical circuit that integrates angular head motion to compute head direction. J. Neurosci. 15, 6260–6270 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Tsanov, M. et al. Theta-modulated head direction cells in the rat anterior thalamus. J. Neurosci. 31, 9489–9502 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Giocomo, L. M. et al. Topography of head direction cells in medial entorhinal cortex. Curr. Biol. 24, 252–262 (2014).

    CAS  PubMed  Google Scholar 

  88. Cho, J. & Sharp, P. E. Head direction, place, and movement correlates for cells in the rat retrosplenial cortex. Behav. Neurosci. 115, 3–25 (2001).

    CAS  PubMed  Google Scholar 

  89. Chen, L. L., Lin, L. H., Green, E. J., Barnes, C. A. & McNaughton, B. L. Head-direction cells in the rat posterior cortex. I. Anatomical distribution and behavioral modulation. Exp. Brain Res. 101, 8–23 (1994).

    CAS  PubMed  Google Scholar 

  90. Lozano, Y. R. et al. Retrosplenial and postsubicular head direction cells compared during visual landmark discrimination. Brain Neurosci. Adv. 1, 2398212817721859 (2017).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  92. Redish, A. D., David Redish, A., Elga, A. N. & Touretzky, D. S. A coupled attractor model of the rodent head direction system. Netw.: Comput. Neural Syst. 7, 671–685 (1996).

    Google Scholar 

  93. Zhang, K. Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: a theory. J. Neurosci. 16, 2112–2126 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Angelaki, D. E. et al. A gravity-based three-dimensional compass in the mouse brain. Nat. Commun. 11, 1855 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Knierim, J. J., Kudrimoti, H. S. & McNaughton, B. L. Interactions between idiothetic cues and external landmarks in the control of place cells and head direction cells. J. Neurophysiol. 80, 425–446 (1998).

    CAS  PubMed  Google Scholar 

  96. Muller, R. U., Ranck, J. B. Jr & Taube, J. S. Head direction cells: properties and functional significance. Curr. Opin. Neurobiol. 6, 196–206 (1996).

    CAS  PubMed  Google Scholar 

  97. Zugaro, M. B., Tabuchi, E. & Wiener, S. I. Influence of conflicting visual, inertial and substratal cues on head direction cell activity. Exp. Brain Res. 133, 198–208 (2000).

    CAS  PubMed  Google Scholar 

  98. Taube, J. S. & Burton, H. L. Head direction cell activity monitored in a novel environment and during a cue conflict situation. J. Neurophysiol. 74, 1953–1971 (1995).

    CAS  PubMed  Google Scholar 

  99. Jacob, P.-Y. et al. An independent, landmark-dominated head-direction signal in dysgranular retrosplenial cortex. Nat. Neurosci. 20, 173–175 (2017).

    CAS  PubMed  Google Scholar 

  100. Zhang, N., Grieves, R. M. & Jeffery, K. J. Environment symmetry drives a multidirectional code in rat retrosplenial cortex. J. Neurosci. 42, 9227–9241 (2022). Using recordings of directionally tuned cells in the RSP, this study discovers that rotational symmetry in an environment reveals multi-directional HD cells, which could have onefold, twofold or fourfold rotational symmetry reflecting the symmetry in the environment.

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Sattler, N. J. & Wehr, M. A head-mounted multi-camera system for electrophysiology and behavior in freely-moving mice. Front. Neurosci. 14, 592417 (2020).

    PubMed  Google Scholar 

  102. Meyer, A. F., O’Keefe, J. & Poort, J. Two distinct types of eye-head coupling in freely moving mice. Curr. Biol. 30, 2116–2130.e6 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Holmgren, C. D. et al. Visual pursuit behavior in mice maintains the pursued prey on the retinal region with least optic flow. eLife 10, e70838 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  104. Cullen, K. E. & Chacron, M. J. Neural substrates of perception in the vestibular thalamus during natural self-motion: a review. Curr. Res. Neurobiol. 4, 100073 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Busse, L. et al. Sensation during active behaviors. J. Neurosci. 37, 10826–10834 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. Parker, P. R. L., Brown, M. A., Smear, M. C. & Niell, C. M. Movement-related signals in sensory areas: roles in natural behavior. Trends Neurosci. 43, 581–595 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  107. Flossmann, T. & Rochefort, N. L. Spatial navigation signals in rodent visual cortex. Curr. Opin. Neurobiol. 67, 163–173 (2021).

    CAS  PubMed  Google Scholar 

  108. Guitchounts, G., Lotter, W., Dapello, J. & Cox, D. Stable 3D head direction signals in the primary visual cortex. Preprint at biorxiv https://doi.org/10.1101/2020.09.04.283762v2 (2020).

    Article  Google Scholar 

  109. Guitchounts, G., Masís, J., Wolff, S. B. E. & Cox, D. Encoding of 3D head orienting movements in the primary visual cortex. Neuron 108, 512–525.e4 (2020).

    CAS  PubMed  Google Scholar 

  110. Parker, P. R. L., Abe, E. T. T., Leonard, E. S. P., Martins, D. M. & Niell, C. M. Joint coding of visual input and eye/head position in V1 of freely moving mice. Neuron 110, 3897–3906 (2022).

    CAS  PubMed  Google Scholar 

  111. Bouvier, G., Senzai, Y. & Scanziani, M. Head movements control the activity of primary visual cortex in a luminance-dependent manner. Neuron 108, 500–511.e5 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. Orlowska-Feuer, P. et al. Look-up and look-down neurons in the mouse visual thalamus during freely moving exploration. Curr. Biol. 32, 3987–3999.e4 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. Mimica, B. et al. Behavioral decomposition reveals rich encoding structure employed across neocortex. Preprint at biorxiv https://doi.org/10.1101/2022.02.08.479515v2 (2022).

    Article  Google Scholar 

  114. Dale, A. & Cullen, K. E. The ventral posterior lateral thalamus preferentially encodes externally applied versus active movement: implications for self-motion perception. Cereb. Cortex 29, 305–318 (2019).

    PubMed  Google Scholar 

  115. Rancz, E. A. et al. Widespread vestibular activation of the rodent cortex. J. Neurosci. 35, 5926–5934 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. Parker, P. R. L. et al. A dynamic sequence of visual processing initiated by gaze shifts. Preprint at biorxiv https://doi.org/10.1101/2022.08.23.504847v1 (2022).

    Article  Google Scholar 

  117. Andersen, R. A., Snyder, L. H., Li, C. S. & Stricanne, B. Coordinate transformations in the representation of spatial information. Curr. Opin. Neurobiol. 3, 171–176 (1993).

    CAS  PubMed  Google Scholar 

  118. Brecht, M., Preilowski, B. & Merzenich, M. M. Functional architecture of the mystacial vibrissae. Behav. Brain Res. 84, 81–97 (1997).

    CAS  PubMed  Google Scholar 

  119. Knierim, J. J. & Hamilton, D. A. Framing spatial cognition: neural representations of proximal and distal frames of reference and their roles in navigation. Physiol. Rev. 91, 1245–1279 (2011).

    PubMed  Google Scholar 

  120. Shapiro, M. L., Tanila, H. & Eichenbaum, H. Cues that hippocampal place cells encode: dynamic and hierarchical representation of local and distal stimuli. Hippocampus 7, 624–642 (1997).

    CAS  PubMed  Google Scholar 

  121. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. 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).

    CAS  PubMed  Google Scholar 

  123. Knierim, J. J. Dynamic interactions between local surface cues, distal landmarks, and intrinsic circuitry in hippocampal place cells. J. Neurosci. 22, 6254–6264 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  124. Renaudineau, S., Poucet, B. & Save, E. Flexible use of proximal objects and distal cues by hippocampal place cells. Hippocampus 17, 381–395 (2007).

    PubMed  Google Scholar 

  125. 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 

  126. 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 

  127. Deshmukh, S. S. & Knierim, J. J. Influence of local objects on hippocampal representations: landmark vectors and memory. Hippocampus 23, 253–267 (2013).

    PubMed  Google Scholar 

  128. 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).

    PubMed  Google Scholar 

  129. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  130. Zugaro, M. B., Berthoz, A. & Wiener, S. I. Background, but not foreground, spatial cues are taken as references for head direction responses by rat anterodorsal thalamus neurons. J. Neurosci. 21, RC154 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  131. Cressant, A., Muller, R. U. & Poucet, B. Failure of centrally placed objects to control the firing fields of hippocampal place cells. J. Neurosci. 17, 2531–2542 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  132. Bourboulou, R. et al. Dynamic control of hippocampal spatial coding resolution by local visual cues. eLife 8, e44487 (2019).

    PubMed  PubMed Central  Google Scholar 

  133. Andersson, S. O., Moser, E. I. & Moser, M.-B. Visual stimulus features that elicit activity in object-vector cells. Commun. Biol. 4, 1219 (2021). This study identifies the basic visual features that elicit responses in object vector cells of the MEC, demonstrating the ability of object vector cells to encode vectorial distances to various visual stimuli, including two-dimensional objects, transparent stimuli and even simple visual contrast.

    PubMed  PubMed Central  Google Scholar 

  134. Wang, C. et al. Egocentric coding of external items in the lateral entorhinal cortex. Science 362, 945–949 (2018). This study finds neurons in the LEC that were active when animals were at a specific egocentric distance from objects placed within the environment.

    CAS  PubMed  PubMed Central  Google Scholar 

  135. Alexander, A. S. et al. Egocentric boundary vector tuning of the retrosplenial cortex. Sci. Adv. 6, eaaz2322 (2020). This study reports the presence of a large percentage of egocentric boundary vector cells in the RSP, which have increased firing rate when the animal is a specific distance and angle from a boundary.

    PubMed  PubMed Central  Google Scholar 

  136. Gibson, E. J. & Walk, R. D. The ‘Visual Cliff’. Sci. Am. 202, 64–71 (1960).

    CAS  PubMed  Google Scholar 

  137. Scoville, W. B. & Milner, B. Loss of recent memory after bilateral hippocampal lesions. J. Neurol. Neurosurg. Psychiatry 20, 11–21 (1957).

    CAS  PubMed  PubMed Central  Google Scholar 

  138. Milner, B., Squire, L. R. & Kandel, E. R. Cognitive neuroscience and the study of memory. Neuron 20, 445–468 (1998).

    CAS  PubMed  Google Scholar 

  139. Ranganath, C. Time, memory, and the legacy of Howard Eichenbaum. Hippocampus 29, 146–161 (2019).

    PubMed  Google Scholar 

  140. Eichenbaum, H. The Cognitive Neuroscience of Memory: An Introduction (Oxford Univ. Press, 2002).

  141. Constantinescu, A. O., O’Reilly, 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 

  142. Aronov, D., Nevers, R. & Tank, D. W. Mapping of a non-spatial dimension by the hippocampal–entorhinal circuit. Nature 543, 719–722 (2017). Through training rats to manipulate a lever, and thereby control the frequency of an emitted sound, the researchers observe selective firing of neurons in the hippocampus and entorhinal cortices that encode specific sound frequencies, suggesting that the hippocampal–entorhinal system is capable of representing non-spatial variables in addition to spatial information encoded by place cells and grid cells.

    CAS  PubMed  PubMed Central  Google Scholar 

  143. Clark, R. E. & Squire, L. R. Similarity in form and function of the hippocampus in rodents, monkeys, and humans. Proc. Natl Acad. Sci. USA 110, 10365–10370 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  145. Miller, J. F. et al. Neural activity in human hippocampal formation reveals the spatial context of retrieved memories. Science 342, 1111–1114 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  146. Doeller, C. F., Barry, C. & Burgess, N. Evidence for grid cells in a human memory network. Nature 463, 657–661 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  147. Epstein, R. A., Patai, E. Z., Julian, J. B. & Spiers, H. J. The cognitive map in humans: spatial navigation and beyond. Nat. Neurosci. 20, 1504–1513 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  148. Land, M. F. Eye movements of vertebrates and their relation to eye form and function. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 201, 195–214 (2015).

    PubMed  Google Scholar 

  149. Luongo, F. J. et al. Mice and primates use distinct strategies for visual segmentation. eLife 12, e74394 (2023).

    PubMed  PubMed Central  Google Scholar 

  150. Epstein, R. A. & Baker, C. I. Scene perception in the human brain. Annu. Rev. Vis. Sci. 5, 373–397 (2019). This review summarizes functional neuroimaging studies exploring human perception and understanding of complex scenes, in particular findings on three cortical regions that exhibit selectivity for scenes and encode a range of visual and functional properties related to scene perception.

    PubMed  PubMed Central  Google Scholar 

  151. Arcaro, M. J. & Livingstone, M. S. Retinotopic organization of scene areas in macaque inferior temporal cortex. J. Neurosci. 37, 7373–7389 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  152. Kornblith, S., Cheng, X., Ohayon, S. & Tsao, D. Y. A network for scene processing in the macaque temporal lobe. Neuron 79, 766–781 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  153. Nasr, S. et al. Scene-selective cortical regions in human and nonhuman primates. J. Neurosci. 31, 13771–13785 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  154. Liska, J. P. et al. Running modulates primate and rodent visual cortex differently. Preprint at biorxiv https://doi.org/10.1101/2022.06.13.495712v3 (2022).

  155. Talluri, B. C. et al. Activity in primate visual cortex is minimally driven by spontaneous movements. Preprint at biorxiv https://doi.org/10.1101/2022.09.08.507006v1 (2022).

  156. Avitan, L. & Stringer, C. Not so spontaneous: multi-dimensional representations of behaviors and context in sensory areas. Neuron 110, 3064–3075 (2022).

    CAS  PubMed  Google Scholar 

  157. Stringer, C. et al. Spontaneous behaviors drive multidimensional, brainwide activity. Science 364, 255 (2019).

    PubMed  PubMed Central  Google Scholar 

  158. Musall, S., Kaufman, M. T., Juavinett, A. L., Gluf, S. & Churchland, A. K. Single-trial neural dynamics are dominated by richly varied movements. Nat. Neurosci. 22, 1677–1686 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  159. Heeger, D. J. Theory of cortical function. Proc. Natl Acad. Sci. USA 114, 1773–1782 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  160. Nienborg, H. & Cumming, B. G. Decision-related activity in sensory neurons reflects more than a neuron’s causal effect. Nature 459, 89–92 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  161. Straka, H., Simmers, J. & Chagnaud, B. P. A new perspective on predictive motor signaling. Curr. Biol. 28, R232–R243 (2018).

    CAS  PubMed  Google Scholar 

  162. Keller, G. B., Bonhoeffer, T. & Hübener, M. Sensorimotor mismatch signals in primary visual cortex of the behaving mouse. Neuron 74, 809–815 (2012).

    CAS  PubMed  Google Scholar 

  163. Thiele, A., Henning, P., Kubischik, M. & Hoffmann, K.-P. Neural mechanisms of saccadic suppression. Science 295, 2460–2462 (2002).

    CAS  PubMed  Google Scholar 

  164. Salinas, E. & Sejnowski, T. J. Gain modulation in the central nervous system: where behavior, neurophysiology, and computation meet. Neuroscientist 7, 430–440 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  165. Salinas, E. & Abbott, L. F. A model of multiplicative neural responses in parietal cortex. Proc. Natl Acad. Sci. USA 93, 11956–11961 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  166. Rigotti, M. et al. The importance of mixed selectivity in complex cognitive tasks. Nature 497, 585–590 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  167. 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).

    PubMed  PubMed Central  Google Scholar 

  168. Bicanski, A. & Burgess, N. A neural-level model of spatial memory and imagery. eLife 7, e33752 (2018).

    PubMed  PubMed Central  Google Scholar 

  169. Bicanski, A. & Burgess, N. Neuronal vector coding in spatial cognition. Nat. Rev. Neurosci. 21, 453–470 (2020).

    CAS  PubMed  Google Scholar 

  170. Li, T., Arleo, A. & Sheynikhovich, D. Modeling place cells and grid cells in multi-compartment environments: entorhinal–hippocampal loop as a multisensory integration circuit. Neural Netw. 121, 37–51 (2020).

    PubMed  Google Scholar 

  171. Arleo, A. & Gerstner, W. Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity. Biol. Cybern. 83, 287–299 (2000).

    CAS  PubMed  Google Scholar 

  172. Pereira, T. D. et al. SLEAP: a deep learning system for multi-animal pose tracking. Nat. Methods 19, 486–495 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  173. Mathis, A. et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat. Neurosci. 21, 1281–1289 (2018). This work presents deep learning-based software for tracking body parts from videos, which alongside with other tracking software allows detailed behavioural tracking, for instance to disentangle the influence of other behaviours on spatial modulations.

    CAS  PubMed  Google Scholar 

  174. Hoy, J. L., Bishop, H. I. & Niell, C. M. Defined cell types in superior colliculus make distinct contributions to prey capture behavior in the mouse. Curr. Biol. 29, 4130–4138.e5 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  175. Pakan, J. M. P., Currie, S. P., Fischer, L. & Rochefort, N. L. The impact of visual cues, reward, and motor feedback on the representation of behaviorally relevant spatial locations in primary visual cortex. Cell Rep. 24, 2521–2528 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  176. Kui, G. G., Krysiak, M., Banda, K. & Rodman, H. R. Context dependence of head bobs in gerbils and potential neural contributions. Behav. Brain Res. 418, 113622 (2022).

    PubMed  Google Scholar 

  177. Del Grosso, N. A. & Sirota, A. Ratcave: a 3D graphics python package for cognitive psychology experiments. Behav. Res. Methods 51, 2085–2093 (2019).

    PubMed  PubMed Central  Google Scholar 

  178. Lein, E. S. et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007).

    CAS  PubMed  Google Scholar 

  179. Bakker, R., Tiesinga, P. & Kötter, R. The Scalable Brain Atlas: instant web-based access to public brain atlases and related content. Neuroinformatics 13, 353–366 (2015).

    PubMed  PubMed Central  Google Scholar 

  180. Hölscher, C., Schnee, A., Dahmen, H., Setia, L. & Mallot, H. A. Rats are able to navigate in virtual environments. J. Exp. Biol. 208, 561–569 (2005).

    PubMed  Google Scholar 

  181. Aghajan, Z. M. et al. Impaired spatial selectivity and intact phase precession in two-dimensional virtual reality. Nat. Neurosci. 18, 121–128 (2015).

    CAS  PubMed  Google Scholar 

  182. Aronov, D. & Tank, D. W. Engagement of neural circuits underlying 2D spatial navigation in a rodent virtual reality system. Neuron 84, 442–456 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  183. Chen, G., King, J. A., Lu, Y., Cacucci, F. & Burgess, N. Spatial cell firing during virtual navigation of open arenas by head-restrained mice. eLife 7, e34789 (2018).

    PubMed  PubMed Central  Google Scholar 

  184. Madhav, M. S. et al. The Dome: a virtual reality apparatus for freely locomoting rodents. J. Neurosci. Methods 368, 109336 (2022).

    PubMed  Google Scholar 

  185. Stowers, J. R. et al. Virtual reality for freely moving animals. Nat. Methods 14, 995–1002 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  186. Lopes, G. et al. Creating and controlling visual environments using BonVision. eLife 10, e65541 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  187. Štih, V., Petrucco, L., Kist, A. M. & Portugues, R. Stytra: an open-source, integrated system for stimulation, tracking and closed-loop behavioral experiments. PLoS Comput. Biol. 15, e1006699 (2019).

    PubMed  PubMed Central  Google Scholar 

  188. Pereira, T. D. et al. Fast animal pose estimation using deep neural networks. Nat. Methods 16, 117–125 (2019).

    CAS  PubMed  Google Scholar 

  189. Nityananda, V. & Read, J. C. A. Stereopsis in animals: evolution, function and mechanisms. J. Exp. Biol. 220, 2502–2512 (2017).

    PubMed  PubMed Central  Google Scholar 

  190. Julesz, B. Binocular depth perception without familiarity cues. Science 145, 356–362 (1964).

    CAS  PubMed  Google Scholar 

  191. Kim, H. R., Angelaki, D. E. & DeAngelis, G. C. The neural basis of depth perception from motion parallax. Philos. Trans. R. Soc. Lond. B Biol. Sci. 371, 20150256 (2016).

    PubMed  PubMed Central  Google Scholar 

  192. Read, J. C. A. Binocular vision and stereopsis across the animal kingdom. Annu. Rev. Vis. Sci. 7, 389–415 (2021).

    PubMed  Google Scholar 

  193. Koch, S. M. et al. Pathway-specific genetic attenuation of glutamate release alters select features of competition-based visual circuit refinement. Neuron 71, 235–242 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  194. Seabrook, T. A., Burbridge, T. J., Crair, M. C. & Huberman, A. D. Architecture, function, and assembly of the mouse visual system. Annu. Rev. Neurosci. 40, 499–538 (2017).

    CAS  PubMed  Google Scholar 

  195. Dräger, U. C. & Olsen, J. F. Origins of crossed and uncrossed retinal projections in pigmented and albino mice. J. Comp. Neurol. 191, 383–412 (1980).

    PubMed  Google Scholar 

  196. Reese, B. E. ‘Hidden lamination’ in the dorsal lateral geniculate nucleus: the functional organization of this thalamic region in the rat. Brain Res. 472, 119–137 (1988).

    CAS  PubMed  Google Scholar 

  197. Coleman, J. E., Law, K. & Bear, M. F. Anatomical origins of ocular dominance in mouse primary visual cortex. Neuroscience 161, 561–571 (2009).

    CAS  PubMed  Google Scholar 

  198. Bauer, J. et al. Limited functional convergence of eye-specific inputs in the retinogeniculate pathway of the mouse. Neuron 109, 2457–2468.e12 (2021).

    CAS  PubMed  Google Scholar 

  199. Dräger, U. C. Receptive fields of single cells and topography in mouse visual cortex. J. Comp. Neurol. 160, 269–290 (1975).

    PubMed  Google Scholar 

  200. Ramachandra, V., Pawlak, V., Wallace, D. J. & Kerr, J. N. D. Impact of visual callosal pathway is dependent upon ipsilateral thalamus. Nat. Commun. 11, 1889 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  201. Zhao, X., Liu, M. & Cang, J. Sublinear binocular integration preserves orientation selectivity in mouse visual cortex. Nat. Commun. 4, 2088 (2013).

    PubMed  Google Scholar 

  202. Scholl, B., Burge, J. & Priebe, N. J. Binocular integration and disparity selectivity in mouse primary visual cortex. J. Neurophysiol. 109, 3013–3024 (2013).

    PubMed  PubMed Central  Google Scholar 

  203. Oommen, B. S. & Stahl, J. S. Eye orientation during static tilts and its relationship to spontaneous head pitch in the laboratory mouse. Brain Res. 1193, 57–66 (2008).

    CAS  PubMed  Google Scholar 

  204. Stabio, M. E. et al. A novel map of the mouse eye for orienting retinal topography in anatomical space. J. Comp. Neurol. 526, 1749–1759 (2018).

    PubMed  PubMed Central  Google Scholar 

  205. Meister, M. & Cox, D. Rats maintain a binocular field centered on the horizon. F1000Res. 2, 176 (2013).

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors thank K. J. Jeffery and M. Huebener for feedback on an earlier version of the manuscript. This work was supported by Deutsche Forschungsgemeinschaft (DFG) SFB 1233 Robust Vision: Inference Principles and Neural Mechanisms TP 10/13 (project number: 276693517), DFG SFB 870 TP 19 (project number: 118803580), DFG BU 1808/6-2 and 1808/5-2, and a ONE Munich Strategy Forum grant (LMU Munich, TU Munich and the Bavarian Ministry for Science and Art) to L.B. This work was also supported by The Sir Henry Dale Fellowship from the Wellcome Trust and Royal Society (200501) and the Human Frontier in Science Program (RGY0076/2018) to A.B.S.

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Glossary

Active sampling

A cognitive or behavioural strategy, in which an organism seeks out and acquires specific sensory information from its environment in an active process, as opposed to passively receiving sensory input.

Allocentric position

In a world-centric reference frame, defined with respect to external cues or landmarks and independent of the observer’s own position or orientation.

Corollary discharge

Often referred to as a neural signal that is obtained by passing a motor efference copy through a forward model of motor control. As the corollary discharge is then in sensory coordinates, it can be directly compared with sensory signals.

Distal cues

Cues that are large, stationary and so far away from the animal that they have fixed directional positions from anywhere within the environment. Distal cues are typically visual landmarks. Laboratory studies commonly refer to visual cues as distal if they are placed on the walls of the experimental room in which the arena is situated.

Efference copies

Copies of the motor commands sent from the motor areas of the brain to other regions, including sensory areas. This information can be used to predict (or generate an expectation for) the outcomes of the motor command.

Egocentric

In an observer-centric reference frame, defined relative to the observer’s features (for example, body position and orientation or eye position).

Gain fields

In the context of spatial representations, neural representations in which the activity of the neurons encodes both the location of a stimulus in the sensory space and the current state of the animal’s body. The firing rate is multiplicatively modulated by the position of the sensor (such as the eye or arm) or the animal and/or its orientation in space. This spatial tuning facilitates the integration of sensory information with body-centred information.

Gaze

The line of sight (per eye), determined by both the position of the eye in orbit (eye position) and the position of the head in space.

Grid cells

A type of neurons that display spatial selectivity, characterized by multiple firing fields arranged in a hexagonal grid pattern across the environment. These cells increase the firing rate when the animal moves through any of their fields and are thought to have a role in coding distances as the animal navigates its surroundings.

Head direction

The direction towards which the head of an animal is pointing.

Head-direction cells

(HD cells). Cells that exhibit their highest level of activity when the animal’s head is oriented towards a specific direction, remaining inactive in other directions. Different HD cells can be active in different directions, and when considered as a population, these cells collectively represent all possible directions.

Heading direction

The direction towards which the whole body of an animal is moving.

Landmarks

Distinctive features or objects in the environment that are stably related to specific locations or bearings on the map, and thus can be used as reference points for navigation.

Motion parallax

The perceptual phenomenon in which objects located at different distances from an observer appear to move at different speeds or directions when the observer moves. This serves as a monocular depth cue providing information about the relative distances between objects in the visual scene.

Object/boundary vector cells

A type of neurons that become active when an animal is located at a specific vectorial distance relative to an object or boundary in the environment.

Path integration

A navigational strategy used by animals to maintain an estimate of their current position in space. It consists of the accumulation of self-motion-related interoceptive information over time from an egocentric reference point.

Place cells

A type of neurons that exhibit heightened activity when an animal occupies a specific location in its environment (or a few positions in large environments), irrespective of the animal’s head direction.

Proximal cues

Cues that are small and often located within the animal’s immediate environment or very close to it, so that they can change their relative directional position as the animal moves around.

Reafferent visual input

The sensory information that is received by the visual system as a result of the interaction between an organism’s own movements and the external environment; that is, sensory signals generated by the movement of the eyes, head or body.

Saccadic suppression

A phenomenon in visual perception in which visual information is suppressed or reduced during saccadic movements. This is thought to prevent motion blur from reaching awareness and to support our uninterrupted visual experience.

Stereopsis

The perception of visual depth that arises from binocular disparity; that is, the slight difference in the visual input received by each eye due to their slightly different positions on the head.

Virtual reality

(VR). An artificial, simulated environment that updates in a manner that is contingent on one’s action. Human VR systems often use computer peripherals to capture a subject’s actions. Rodent VR systems instead typically use optical sensors or rotary encoders to capture a subject’s actions on a treadmill.

Visual depth

The distance or three-dimensional spatial relationships between objects (or other environmental features) estimated based on visual features in the scene.

VR gain

This is the relationship between the physical distance travelled by a subject on a treadmill (or other sensor) and the virtual distance travelled in a given virtual reality (VR) environment. Increasing gain refers to making larger movements in VR (and decreasing gain to smaller movements in VR) for the same physical distance travelled.

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Saleem, A.B., Busse, L. Interactions between rodent visual and spatial systems during navigation. Nat. Rev. Neurosci. 24, 487–501 (2023). https://doi.org/10.1038/s41583-023-00716-7

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