Grid Cells and Neural Coding in High-End Cortices
2013; Cell Press; Volume: 80; Issue: 3 Linguagem: Inglês
10.1016/j.neuron.2013.09.043
ISSN1097-4199
AutoresEdvard I Moser, May‐Britt Moser,
Tópico(s)Memory and Neural Mechanisms
ResumoAn ultimate goal of neuroscience is to understand the mechanisms of mammalian intellectual functions, many of which are thought to depend extensively on the cerebral cortex. While this may have been considered a remote objective when Neuron was launched in 1988, neuroscience has now evolved to a stage where it is possible to decipher neural-circuit mechanisms in the deepest parts of the cortex, far away from sensory receptors and motoneurons. In this review, we show how studies of place cells in the hippocampus and grid cells in the entorhinal cortex may provide some of the first glimpses into these mechanisms. We shall review the events that led up to the discovery of grid cells and a functional circuit in the entorhinal cortex and highlight what we currently see as the big questions in this field—questions that, if resolved, will add to our understanding of cortical computation in a general sense. An ultimate goal of neuroscience is to understand the mechanisms of mammalian intellectual functions, many of which are thought to depend extensively on the cerebral cortex. While this may have been considered a remote objective when Neuron was launched in 1988, neuroscience has now evolved to a stage where it is possible to decipher neural-circuit mechanisms in the deepest parts of the cortex, far away from sensory receptors and motoneurons. In this review, we show how studies of place cells in the hippocampus and grid cells in the entorhinal cortex may provide some of the first glimpses into these mechanisms. We shall review the events that led up to the discovery of grid cells and a functional circuit in the entorhinal cortex and highlight what we currently see as the big questions in this field—questions that, if resolved, will add to our understanding of cortical computation in a general sense. The cerebral cortex is the multilayered sheet of neural tissue that covers the cerebral hemispheres. The size of the cerebral cortex has increased tremendously during mammalian evolution, and it is the growth of this brain structure that is thought to give rise to the widely expanded repertoire of intellectual abilities in primates. Complex cognitive processes such as memory, imagination, reasoning, planning, and decision making are examples of functions that depend on activity across widespread cortical networks. How these functions emerge as a product of activity in distributed neuronal assemblies is poorly understood, but with the current progress in neuroscience, we may be able to figure out parts of the mechanistic fundament of some of these functions in the not too distant future. Much of what we know about cortical computation can be traced back to Hubel and Wiesel's early work in the visual cortex. More than half a century ago, Hubel and Wiesel, 1959Hubel D.H. Wiesel T.N. Receptive fields of single neurones in the cat's striate cortex.J. Physiol. 1959; 148: 574-591Crossref PubMed Scopus (2706) Google Scholar recorded activity of individual neurons in V1 of the cat visual cortex while patterns of light and dark were presented to the eyes of the animal. One of their key observations was that V1 neurons respond to elementary components of the visual scene. Many of their neurons fired specifically in response to bars or edges of particular orientations—some at discrete locations in the visual field (simple cells), others across a wider spatial range (complex cells) (Hubel and Wiesel, 1962Hubel D.H. Wiesel T.N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.J. Physiol. 1962; 160: 106-154Crossref PubMed Scopus (8580) Google Scholar). The discovery of these cells was accompanied by the first conceptual model for the formation of receptive fields in the visual cortex, in which a spatial summation mechanism accounted for the transformations from center-surround receptive fields in the thalamus to simple cells in the cortex and from simple cells to complex cells at subsequent stages (Hubel and Wiesel, 1962Hubel D.H. Wiesel T.N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.J. Physiol. 1962; 160: 106-154Crossref PubMed Scopus (8580) Google Scholar). These ideas created a fundament not only for visual neuroscience, but also for computational studies of the cortex. Hubel and Wiesel's early studies were also important because they defined a functional architecture for visually responsive neurons in V1. The studies showed that in cats and monkeys, V1 neurons are organized in layer-spanning left-eye and right-eye ocular dominance bands as well as superimposed columns of cells that respond to similar features of the visual input, such as the orientation of the stimulus (Hubel and Wiesel, 1962Hubel D.H. Wiesel T.N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.J. Physiol. 1962; 160: 106-154Crossref PubMed Scopus (8580) Google Scholar, Hubel and Wiesel, 1974Hubel D.H. Wiesel T.N. Sequence regularity and geometry of orientation columns in the monkey striate cortex.J. Comp. Neurol. 1974; 158: 267-293Crossref PubMed Scopus (695) Google Scholar, Hubel and Wiesel, 1977Hubel D.H. Wiesel T.N. Ferrier lecture. Functional architecture of macaque monkey visual cortex.Proc. R. Soc. Lond. B Biol. Sci. 1977; 198: 1-59Crossref PubMed Google Scholar). Subsequent work showed that orientation columns are arranged gradually around pinwheel centers (Bonhoeffer and Grinvald, 1991Bonhoeffer T. Grinvald A. Iso-orientation domains in cat visual cortex are arranged in pinwheel-like patterns.Nature. 1991; 353: 429-431Crossref PubMed Scopus (647) Google Scholar) and that, within orientation columns, cells are further organized according to direction preferences (Payne et al., 1981Payne B.R. Berman N. Murphy E.H. Organization of direction preferences in cat visual cortex.Brain Res. 1981; 211: 445-450Crossref PubMed Scopus (43) Google Scholar, Tolhurst et al., 1981Tolhurst D.J. Dean A.F. Thompson I.D. Preferred direction of movement as an element in the organization of cat visual cortex.Exp. Brain Res. 1981; 44: 340-342Crossref PubMed Scopus (38) Google Scholar, Weliky et al., 1996Weliky M. Bosking W.H. Fitzpatrick D. A systematic map of direction preference in primary visual cortex.Nature. 1996; 379: 725-728Crossref PubMed Scopus (196) Google Scholar). The early studies in V1 were followed by descriptions of receptive fields at higher levels of the visual system (e.g., Gross et al., 1972Gross C.G. Rocha-Miranda C.E. Bender D.B. Visual properties of neurons in inferotemporal cortex of the Macaque.J. Neurophysiol. 1972; 35: 96-111PubMed Google Scholar, Desimone et al., 1984Desimone R. Albright T.D. Gross C.G. Bruce C. Stimulus-selective properties of inferior temporal neurons in the macaque.J. Neurosci. 1984; 4: 2051-2062PubMed Google Scholar). In general, as the number of synaptic relays increased, visual receptive fields became larger and more selective, and the mechanisms that could generate those patterns became harder to access. At the top of the cortical hierarchy, where information is combined across sensory systems, it was often no longer possible to match the firing patterns to any experimentally defined stimulus patterns. The fundament that the progress in visual systems neuroscience has laid for understanding cortical computation remains unequalled. The description of the neural elements of visual representations and their organization into functional circuits has been followed by advances in other cortical sensory systems, but in all of these systems, the biggest insights are, in general, still limited to the earliest stages of cortical processing. Less is known about the higher-order association cortices, where inputs cannot be traced back to particular sensory origins. One reason why the computational operations of most high-end association cortices remain terra incognita is that, for each synaptic relay that is added, neural activity becomes increasingly decoupled from the specific features of the sensory environment. With a lacking understanding of both afferent and efferent brain regions, and the ways that information is integrated across hierarchical levels, it may get difficult to find stimulus patterns that possess any predictable relationship to the firing pattern of the recorded cells. Yet, it is the high-end cortices that we need to target if we want to understand the most complex cognitive functions. The hippocampus and entorhinal cortex have often been depicted as the apex of the cortical hierarchy (Felleman and Van Essen, 1991Felleman D.J. Van Essen D.C. Distributed hierarchical processing in the primate cerebral cortex.Cereb. Cortex. 1991; 1: 1-47Crossref PubMed Scopus (5448) Google Scholar, Van Essen et al., 1992Van Essen D.C. Anderson C.H. Felleman D.J. Information processing in the primate visual system: an integrated systems perspective.Science. 1992; 255: 419-423Crossref PubMed Scopus (836) Google Scholar, Squire and Zola-Morgan, 1991Squire L.R. Zola-Morgan S. The medial temporal lobe memory system.Science. 1991; 253: 1380-1386Crossref PubMed Scopus (2337) Google Scholar, Lavenex and Amaral, 2000Lavenex P. Amaral D.G. Hippocampal-neocortical interaction: a hierarchy of associativity.Hippocampus. 2000; 10: 420-430Crossref PubMed Scopus (627) Google Scholar; Figure 1). On this background, it may come as a surprise that these systems contain a set of representations that perfectly match an attribute of the external world: the animal's location in space. In the hippocampus, place cells fire specifically at one or a few locations in the animal's environment (O'Keefe and Dostrovsky, 1971O'Keefe J. Dostrovsky J. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat.Brain Res. 1971; 34: 171-175Crossref PubMed Scopus (3810) Google Scholar). In the medial part of the entorhinal cortex, grid cells fire at multiple locations that, for each cell, define a hexagonal array across the entire available space (Hafting et al., 2005Hafting T. Fyhn M. Molden S. Moser M.-B. Moser E.I. Microstructure of a spatial map in the entorhinal cortex.Nature. 2005; 436: 801-806Crossref PubMed Scopus (2432) Google Scholar, Moser et al., 2008Moser E.I. Kropff E. Moser M.-B. Place cells, grid cells, and the brain's spatial representation system.Annu. Rev. Neurosci. 2008; 31: 69-89Crossref PubMed Scopus (1141) Google Scholar; Figure 2). Grid cells intermingle with head direction cells, which fire specifically when the animal faces certain directions, and border cells, which fire specifically when animals move along borders of the local environment (Sargolini et al., 2006Sargolini F. Fyhn M. Hafting T. McNaughton B.L. Witter M.P. Moser M.-B. Moser E.I. Conjunctive representation of position, direction, and velocity in entorhinal cortex.Science. 2006; 312: 758-762Crossref PubMed Scopus (928) Google Scholar, Savelli et al., 2008Savelli F. Yoganarasimha D. Knierim J.J. Influence of boundary removal on the spatial representations of the medial entorhinal cortex.Hippocampus. 2008; 18: 1270-1282Crossref PubMed Scopus (215) Google Scholar, Solstad et al., 2008Solstad T. Boccara C.N. Kropff E. Moser M.-B. Moser E.I. Representation of geometric borders in the entorhinal cortex.Science. 2008; 322: 1865-1868Crossref PubMed Scopus (693) Google Scholar). Collectively, these cell types form the elements of what we will refer to as the entorhinal-hippocampal space circuit.Figure 2A Grid Cell from the Medial Entorhinal Cortex of the Rat BrainShow full captionThe gray trace is the trajectory of a rat that is foraging in a 2.2 m wide enclosure. Spike locations of the grid cell are superimposed on the track. Each black dot corresponds to one spike. Data were recorded by Kristian Frøland.View Large Image Figure ViewerDownload Hi-res image Download (PPT) The gray trace is the trajectory of a rat that is foraging in a 2.2 m wide enclosure. Spike locations of the grid cell are superimposed on the track. Each black dot corresponds to one spike. Data were recorded by Kristian Frøland. In this review, we shall take a historical perspective and describe the unfolding of a system of elementary correlates for representation of space in the hippocampus and the entorhinal cortex. We shall discuss mechanisms that might generate this representation, many synapses away from the specific receptive fields of the sensory cortices, and we shall elaborate on how the evolution of a functional architecture within this system might benefit not only mapping of space, but also the formation of high-capacity memory. The study of spatial representation and spatial navigation started long before neuroscientists approached the cortex. The notion of an internal spatial map can be traced back to Edward C. Tolman, who in his cognitive theory of learning suggested that behavior was guided by a map-like representation of stimulus relationships in the environment, rather than by chains of stimulus-response sequences of the type envisaged by Thorndike and Hull (Tolman, 1948Tolman E.C. Cognitive maps in rats and men.Psychol. Rev. 1948; 55: 189-208Crossref PubMed Scopus (3663) Google Scholar). The internal map was thought to enable animals to navigate flexibly in the environment, taking shortcuts and making detours when previously traveled routes were less effective. Tolman's ideas remained controversial for decades, partly because scientists did not have tools to determine if the cognitive entities proposed by Tolman actually existed. Tolman's ideas were revitalized many years after his death, after the development of microelectrodes for extracellular recording from single neurons in behaving animals. This development led Ranck, 1973Ranck Jr., J.B. Studies on single neurons in dorsal hippocampal formation and septum in unrestrained rats. I. Behavioral correlates and firing repertoires.Exp. Neurol. 1973; 41: 461-531Crossref PubMed Scopus (946) Google Scholar and O'Keefe and Dostrovsky, 1971O'Keefe J. Dostrovsky J. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat.Brain Res. 1971; 34: 171-175Crossref PubMed Scopus (3810) Google Scholar to monitor activity from single neurons in the hippocampus of freely moving rats. Both laboratories found reliable links between neural firing and the animal's behavior, but it was O'Keefe and Dostrovsky who found that the firing depended on the animal's location in the environment. Cells with location-dependent firing were termed place cells, and their specific firing locations were referred to as place fields. Different cells were found to have different place fields (O'Keefe, 1976O'Keefe J. Place units in the hippocampus of the freely moving rat.Exp. Neurol. 1976; 51: 78-109Crossref PubMed Scopus (1159) Google Scholar). The place representation was shown to be nontopographic in the sense that place fields of neighboring cells appeared no more similar than place fields of more widely spaced neurons. The fact that each location in the environment was associated with a unique combination of active place cells pointed to the place cells of the hippocampus as a physical manifestation of Tolman's cognitive map (O'Keefe and Nadel, 1978O'Keefe J. Nadel L. The Hippocampus as a Cognitive Map. Clarendon Press, Oxford1978Google Scholar). This idea was later reinforced when new technology made it possible to record simultaneously from many dozens of place cells and the trajectory of the animal could be reconstructed from the cumulative firing of these cells (Wilson and McNaughton, 1993Wilson M.A. McNaughton B.L. Dynamics of the hippocampal ensemble code for space.Science. 1993; 261: 1055-1058Crossref PubMed Scopus (1582) Google Scholar). The discovery of place cells was followed by three decades of studies focusing, among other questions, on the properties of the environment that determined the localized firing of the place cells (Muller, 1996Muller R. A quarter of a century of place cells.Neuron. 1996; 17: 813-822Abstract Full Text Full Text PDF PubMed Scopus (278) Google Scholar). The neural origin of the signal remained deeply enigmatic, however. Much of the challenge was related to the relative isolation of the hippocampus in the functional brain map. The hippocampus was encircled by areas that were poorly characterized structurally as well as functionally. The major cortical input and output of the hippocampus, the entorhinal cortex, was no exception. It is only now that the entorhinal cortex is beginning to peek out from the dark. At the turn of the millennium, entorhinal activity from freely moving animals had been reported in only a handful of studies. Of particular interest is the report by Quirk et al., 1992Quirk G.J. Muller R.U. Kubie J.L. Ranck Jr., J.B. The positional firing properties of medial entorhinal neurons: description and comparison with hippocampal place cells.J. Neurosci. 1992; 12: 1945-1963PubMed Google Scholar in which the authors recorded activity of individual neurons in medial entorhinal cortex while rats were foraging in a cylindrical environment identical to the ones used by the same authors for place-cell recording in the hippocampus. The neurons had spatial firing preferences, but the firing fields appeared larger and noisier than in hippocampal neurons, and the coactivity patterns did not, like place cells, respond to geometric transformations of the environment. Together with two studies that showed similarly dispersed firing fields in linearized environments (Barnes et al., 1990Barnes C.A. McNaughton B.L. Mizumori S.J. Leonard B.W. Lin L.H. Comparison of spatial and temporal characteristics of neuronal activity in sequential stages of hippocampal processing.Prog. Brain Res. 1990; 83: 287-300Crossref PubMed Scopus (266) Google Scholar, Frank et al., 2000Frank L.M. Brown E.N. Wilson M. Trajectory encoding in the hippocampus and entorhinal cortex.Neuron. 2000; 27: 169-178Abstract Full Text Full Text PDF PubMed Scopus (496) Google Scholar), the observations of Quirk et al., 1992Quirk G.J. Muller R.U. Kubie J.L. Ranck Jr., J.B. The positional firing properties of medial entorhinal neurons: description and comparison with hippocampal place cells.J. Neurosci. 1992; 12: 1945-1963PubMed Google Scholar suggested that some location-specific firing exists prior to the hippocampus. However, the confined nature of the firing was thought to originate within the hippocampus itself. The idea that place fields evolved within the hippocampal circuit led us to monitor activity in place cells from CA1, the output stage of the hippocampus, after all input from other hippocampal subfields was disconnected (Brun et al., 2002Brun V.H. Otnass M.K. Molden S. Steffenach H.A. Witter M.P. Moser M.-B. Moser E.I. Place cells and place recognition maintained by direct entorhinal-hippocampal circuitry.Science. 2002; 296: 2243-2246Crossref PubMed Scopus (485) Google Scholar). Somewhat to our surprise, small, well-defined place fields were still present in CA1, suggesting either that place fields were generated within the local network of CA1 or they were derived, primarily, from spatially responsive cells in upstream cortical regions with direct inputs to the CA1. We decided to explore the latter alternative. A key event in the search for cortical origins of the place-cell signal was the recognition that the hippocampal-entorhinal system is functionally organized along its dorsoventral axis. Our own awareness to this issue was raised by the observation that spatial learning in a water maze navigation task is impaired significantly more by lesions in the dorsal part of the hippocampus than by equally large lesions in the ventral part (Moser et al., 1993Moser E.I. Moser M.-B. Andersen P. Spatial learning impairment parallels the magnitude of dorsal hippocampal lesions, but is hardly present following ventral lesions.J. Neurosci. 1993; 13: 3916-3925PubMed Google Scholar, Moser et al., 1995Moser M.-B. Moser E.I. Forrest E. Andersen P. Morris R.G.M. Spatial learning with a minislab in the dorsal hippocampus.Proc. Natl. Acad. Sci. USA. 1995; 92: 9697-9701Crossref PubMed Scopus (665) Google Scholar). This observation directed us to studies of Menno Witter, who in the 1980s provided evidence for rigid topographical organization along the hippocampal-entorhinal dorsoventral axis. Witter and colleagues showed that dorsal parts of the hippocampus connect to dorsal parts of the entorhinal cortex and ventral parts of the hippocampus to ventral parts of the entorhinal cortex (Witter and Groenewegen, 1984Witter M.P. Groenewegen H.J. Laminar origin and septotemporal distribution of entorhinal and perirhinal projections to the hippocampus in the cat.J. Comp. Neurol. 1984; 224: 371-385Crossref PubMed Scopus (152) Google Scholar, Witter et al., 1989Witter M.P. Groenewegen H.J. Lopes da Silva F.H. Lohman A.H.M. Functional organization of the extrinsic and intrinsic circuitry of the parahippocampal region.Prog. Neurobiol. 1989; 33: 161-253Crossref PubMed Scopus (759) Google Scholar). Dorsal and ventral entorhinal regions were in turn linked to different parts of the rest of the brain (Witter et al., 1989Witter M.P. Groenewegen H.J. Lopes da Silva F.H. Lohman A.H.M. Functional organization of the extrinsic and intrinsic circuitry of the parahippocampal region.Prog. Neurobiol. 1989; 33: 161-253Crossref PubMed Scopus (759) Google Scholar, Burwell and Amaral, 1998Burwell R.D. Amaral D.G. Cortical afferents of the perirhinal, postrhinal, and entorhinal cortices of the rat.J. Comp. Neurol. 1998; 398: 179-205Crossref PubMed Scopus (570) Google Scholar). The discovery of entorhinal-hippocampal projection topography raised the possibility that previous recordings in the entorhinal cortex had not targeted those regions that had the strongest connections to the dorsal quarter of the hippocampus, where nearly all place-cell activity had been recorded at that time. With this mismatch in mind, we decided, together with Menno Witter, to approach the dorsalmost parts of the medial entorhinal cortex. The move paid off; recordings from this region showed firing fields that were as sharp and confined as in the hippocampus (Fyhn et al., 2004Fyhn M. Molden S. Witter M.P. Moser E.I. Moser M.B. Spatial representation in the entorhinal cortex.Science. 2004; 305: 1258-1264Crossref PubMed Scopus (899) Google Scholar). The difference was that each cell had multiple firing fields that were scattered around in the entire recording arena. In order to visualize the spatial organization of the firing fields of each cell, we next decided to test the animals in larger environments, where a larger number of fields could be displayed (Hafting et al., 2005Hafting T. Fyhn M. Molden S. Moser M.-B. Moser E.I. Microstructure of a spatial map in the entorhinal cortex.Nature. 2005; 436: 801-806Crossref PubMed Scopus (2432) Google Scholar). It could now be seen that the fields formed a hexagonal array, with equilateral triangles as a unit, like the arrangement of marble holes on a Chinese checkerboard (Figure 2). We termed the cells grid cells. The grid pattern was similar for all cells, but the spacing of the fields, the orientation of the grid axes, and the x-y location of the grid fields (their grid phase) might vary from cell to cell. The pattern persisted when the room lights were turned off and was not abolished by variations in the speed and the direction of the animal, pointing to self-motion signals as a major component of the mechanism that determined the firing locations. The continuous adjustment for changes in speed and direction suggested that grid cells had access to path-integration information (Hafting et al., 2005Hafting T. Fyhn M. Molden S. Moser M.-B. Moser E.I. Microstructure of a spatial map in the entorhinal cortex.Nature. 2005; 436: 801-806Crossref PubMed Scopus (2432) Google Scholar, McNaughton et al., 2006McNaughton B.L. Battaglia F.P. Jensen O. Moser E.I. Moser M.B. Path integration and the neural basis of the 'cognitive map'.Nat. Rev. Neurosci. 2006; 7: 663-678Crossref PubMed Scopus (1285) Google Scholar). However, at the same time, grid fields appeared in the same locations on successive trials, and the fields rotated in correspondence with rotated landmarks, suggesting that firing positions are also responsive to the configuration of landmarks in each environment. More extensive recordings soon showed that grid cells intermingle with other cell types. While grid cells predominated in layer II of the medial entorhinal cortex, intermediate and deep layers also contained a large fraction of head direction cells (Sargolini et al., 2006Sargolini F. Fyhn M. Hafting T. McNaughton B.L. Witter M.P. Moser M.-B. Moser E.I. Conjunctive representation of position, direction, and velocity in entorhinal cortex.Science. 2006; 312: 758-762Crossref PubMed Scopus (928) Google Scholar). Head direction cells, originally described in the dorsal presubiculum (Ranck, 1985Ranck J.B. Head direction cells in the deep cell layer of dorsal presubiculum in freely moving rats.in: Buzsáki G. Vanderwolf C.H. Electrical Activity of the Archicortex. Akademiai Kiado, Budapest1985: 217-220Google Scholar), are cells that fire specifically when animals face a certain direction, regardless of the animal's position (Taube et al., 1990aTaube J.S. Muller R.U. Ranck Jr., J.B. Head-direction cells recorded from the postsubiculum in freely moving rats. I. Description and quantitative analysis.J. Neurosci. 1990; 10: 420-435PubMed Google Scholar, Taube et al., 1990bTaube J.S. Muller R.U. Ranck Jr., J.B. Head-direction cells recorded from the postsubiculum in freely moving rats. II. Effects of environmental manipulations.J. Neurosci. 1990; 10: 436-447PubMed Google Scholar). In the medial entorhinal cortex, many head direction cells were also grid cells, firing only when the animal passed through the grid vertices with its head in a certain direction (Sargolini et al., 2006Sargolini F. Fyhn M. Hafting T. McNaughton B.L. Witter M.P. Moser M.-B. Moser E.I. Conjunctive representation of position, direction, and velocity in entorhinal cortex.Science. 2006; 312: 758-762Crossref PubMed Scopus (928) Google Scholar). Two years later, grid cells and head direction cells were found to colocalize with a third type of cell: border cells (Savelli et al., 2008Savelli F. Yoganarasimha D. Knierim J.J. Influence of boundary removal on the spatial representations of the medial entorhinal cortex.Hippocampus. 2008; 18: 1270-1282Crossref PubMed Scopus (215) Google Scholar, Solstad et al., 2008Solstad T. Boccara C.N. Kropff E. Moser M.-B. Moser E.I. Representation of geometric borders in the entorhinal cortex.Science. 2008; 322: 1865-1868Crossref PubMed Scopus (693) Google Scholar). These cells fired specifically when the animal was near one or several borders of the local environment, such as a wall or an edge. The firing fields followed the walls when the walls were moved, and when a new wall was inserted, a new firing field often emerged along the insert. Grid cells, head direction cells, and border cells were found to coexist not only in the medial entorhinal cortex, but also in the adjacent presubiculum and parasubiculum (Boccara et al., 2010Boccara C.N. Sargolini F. Thoresen V.H. Solstad T. Witter M.P. Moser E.I. Moser M.-B. Grid cells in pre- and parasubiculum.Nat. Neurosci. 2010; 13: 987-994Crossref PubMed Scopus (349) Google Scholar). Collectively, these observations pointed to a second internal map of space, different from the place-cell map described in the hippocampus. Grid cells, head direction cells, and border cells may be key elements of this map. The clearest difference between these cell types and the place cells in the hippocampus is perhaps the invariance of the activity patterns in the entorhinal cortex. Entorhinal cells appear to fire in all environments, and many cells maintain their phase and orientation relationships from one environment to the next. For example, two grid cells with similar vertex locations in one environment may fire at similar positions also in other environments (Fyhn et al., 2007Fyhn M. Hafting T. Treves A. Moser M.-B. Moser E.I. Hippocampal remapping and grid realignment in entorhinal cortex.Nature. 2007; 446: 190-194Crossref PubMed Scopus (470) Google Scholar). The persistence of coactivity patterns also applies to head direction cells (Taube et al., 1990bTaube J.S. Muller R.U. Ranck Jr., J.B. Head-direction cells recorded from the postsubiculum in freely moving rats. II. Effects of environmental manipulations.J. Neurosci. 1990; 10: 436-447PubMed Google Scholar, Taube and Burton, 1995Taube J.S. Burton H.L. Head direction cell activity monitored in a novel environment and during a cue conflict situation.J. 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