45 Drawing the Map
How Movement, Landmarks, and Experience Become Neural Structure
45.1 Begin with the animal
Chapter 44 identified an ancient hippocampal or medial-pallial system across bony vertebrates. The present chapter asks what that system does while an animal moves through the world.
The evolutionary starting point is not a person recalling a birthday or imagining next year. It is a mobile vertebrate leaving a refuge. The animal travels through changing sensory conditions, turns around obstacles, searches for food or shelter, and eventually must return. The goal may be hidden. The outward route may not be available in reverse. No single smell, landmark, or motor response will always provide the answer.
An animal facing that problem gains a major advantage from keeping track of its own movement and relating it to stable features of the environment. It needs to know which way it is facing, how far it has traveled, where boundaries lie, which routes connect one place to another, and where a useful destination should be even when that destination cannot be sensed directly. Flexible navigation reduces wasted movement and increases the chance of reaching food, water, shelter, mates, or escape routes before energy and time run out.
Living teleost fishes are not unchanged ancestors. They have followed their own evolutionary paths for hundreds of millions of years. They nevertheless constrain the explanation because they possess hippocampal-like pallium without a mammalian neocortex or the language-supported autobiographical system of humans. Goldfish with lesions of the lateral pallium can still approach a visible cue but lose the ability to find a place defined by relations among surrounding cues. Teleost pallial populations also carry information about the animal’s location during active sensing and navigation [@rodriguez2002conservation; @fotowat2019navigation; @yang2024zebrafishplace]. A function that depends on human narrative, semantic knowledge, or multilevel frontal control cannot explain why this system was already useful in those brains.
The evolutionary starting point is therefore concrete. The ancient system improved control of movement through an environment when the answer was not supplied by the stimulus currently in front of the animal. It allowed past movement and learned environmental structure to guide the next action.
This starting point does not reduce the hippocampus to a navigation-only box. A place is already relational. It is defined by the arrangement of boundaries, landmarks, directions, routes, and goals. The same machinery that distinguishes one place from another can later be elaborated to distinguish episodes, task contexts, and other structured situations. Evolution supplies the order of explanation: begin with vertebrate lineages that possess hippocampal pallium without mammalian cortical elaborations, then ask what later circuits added.
The hippocampal–entorhinal system allows a mobile animal to keep track of where it is, how it arrived there, and which routes lead toward places that are not currently visible. It combines self-motion, direction, boundaries, landmarks, and experience in a recurrent population code. Mammalian and human systems place richer contexts, goals, and event content under control of that ancient map; they do not explain its origin.
45.2 A place enters the physiology
Edward Tolman inferred a cognitive map from behavior. His rats did not merely repeat reinforced turns. They approached goals from new starting points, changed routes when familiar paths were blocked, and sometimes took shortcuts they had never been trained to perform. Their behavior depended on relations among places rather than on one fixed chain of responses [@tolman1948cognitive].
John O’Keefe and Jonathan Dostrovsky supplied the first direct physiological evidence. In 1971 they recorded single neurons from the hippocampus while rats moved freely through an enclosure. Some neurons fired little through most of the environment but became active when the rat occupied a restricted region. O’Keefe called these neurons place cells, and the region associated with elevated firing became the cell’s place field [@okeefe1971spatial].
A place field is not a tiny picture or a mark printed on an internal chart. Investigators construct a firing-rate map by dividing the enclosure into spatial bins, measuring how long the animal occupied each bin, and calculating the cell’s firing rate there. The resulting colored patch shows a statistical relation between neural activity and the animal’s position. It is a view of the data, not an image found inside the rat.
The physiological result is still remarkable. At any moment, a population of hippocampal neurons carries enough location-related information to distinguish one part of a familiar environment from another. A decoder supplied with the activity of many cells can estimate where the animal is. The map is therefore a relation among population activity, the moving body, and the environment.
Place cells also make a claim about what the hippocampus does not require. A location does not have one defining stimulus. The animal can occupy the same place while facing different directions, receiving different retinal images, or sampling different odors. Place-related activity can persist in darkness for a time and can remain recognizable as particular cues change. The system integrates multiple sources of evidence rather than waiting for one sensory feature to announce the answer.
The simplest description is useful: place cells tell the system where the animal is. It becomes misleading only when treated as complete. A cell can have more than one field, fields are not distributed as a uniform set of pixels, and the active population can change when the behavioral meaning of an environment changes. The hippocampus represents a place as part of a situation, not as an isolated coordinate.
45.3 The same location can be a different situation
Consider a rat running along the central stem of a T-maze. On one trial it has come from the left and is heading toward the right. On another it has come from the right and is heading toward the left. Its paws can occupy the same floorboards while the journey is different. Hippocampal and entorhinal neurons can distinguish those traversals. Some fire on one route but not the other, or at different rates depending on where the animal came from and where it is going [@frank2000trajectory].
This result changes the interpretation of a place field. Physical position remains important, but position is not the whole represented state. Route, direction, recent history, expected destination, and task demands can alter the population active at that position. A useful navigational system must make those distinctions. The same junction can require a left turn when returning to shelter and a right turn when approaching food.
The population can also reorganize when the larger context changes. In rate remapping, many cells retain fields in roughly the same locations but change how strongly they fire. In global remapping, a different ensemble becomes active or fields move to different locations. Entorhinal grid patterns can realign along with the hippocampal change [@fyhn2007remapping]. The new pattern separates environments or situations that should not control behavior in the same way.
Remapping is sometimes described as instability in a spatial code. That interpretation misses its functional value. An animal needs enough stability to recognize a place across ordinary changes in viewpoint, illumination, and sensory noise. It also needs enough flexibility to distinguish two situations that share the same geometry but predict different outcomes. A stable map that ignored context would repeatedly send the animal toward the wrong goal.
The map is therefore not a photograph of the surroundings. It is an organized estimate of the animal’s relation to a world in which particular actions lead to particular consequences. Spatial location supplies the scaffold. Route, context, and goal determine what that location means for the next action.
45.4 A circuit, not a row of instruments
Place cells are only the most famous signals in a larger system. The hippocampal formation receives extensive input from entorhinal and adjoining parahippocampal cortices. Activity passes through dentate gyrus, CA fields, subiculum, and several direct and indirect pathways, then returns to entorhinal cortex and other cortical and subcortical regions. The circuit is recurrent. It does not begin with a finished entorhinal coordinate and end with a passive hippocampal label.
The discovery of grid cells made that temptation especially strong. When a rat forages across an open floor, many neurons in medial entorhinal cortex fire in several locations. Plot those locations and they often approximate a triangular lattice, producing sixfold or hexagonal symmetry [@hafting2005microstructure]. Different cells have different spatial phases, and groups of cells form modules with related spacing and orientation. Grid spacing tends to increase from dorsal toward more ventral entorhinal levels [@stensola2012modules].
This pattern is well suited to representing displacement. As the animal moves, the population changes in a regular way. Multiple modules operating at different spatial scales can jointly distinguish positions over a range much larger than the spacing of any single module. Grid activity has therefore become central to models of path integration, continuous attractor dynamics, and multiscale position coding.
The grid is not an invariant sheet of graph paper laid over every environment. Change the enclosure geometry and the pattern can distort, reorient, or become less regular. Environmental geometry shapes grid symmetry [@krupic2015geometry]. During a path-integration task in which mice searched for a lever and then returned in darkness, grid populations tracked movement even though a stable open-field lattice was not continuously expressed. The representation shifted between room-centered and lever-centered reference frames while preserving important relations within the population [@peng2025referenceframes].
Grid activity should therefore be described as an internally organized, movement-sensitive population code that contributes to estimating position. It is not a complete Cartesian coordinate system independent of landmarks, task, and hippocampal feedback.
That last point matters anatomically. Medial entorhinal lesions reduce the precision and long-term stability of hippocampal place fields, but they do not erase every place field. Influence also runs in the other direction. Inactivating the hippocampus disrupts the periodic organization of entorhinal grid firing [@hales2014mec; @bonnevie2013grid]. Grid and place populations constrain one another inside a loop.
Other recurring signals contribute to that loop.
Head-direction cells fire according to the direction the animal faces in the horizontal plane. A cell may prefer northeast and remain quiet when the animal faces southwest, regardless of where the animal stands. Populations of these cells provide an allocentric directional signal, often described as a neural compass [@taube1990head].
Border cells fire strongly when the animal is near one or more environmental boundaries [@solstad2008borders]. Boundary-vector cells are defined more specifically by a boundary at a preferred direction and distance from the animal [@lever2009boundary]. The two terms should not be treated as synonyms, although both identify ways in which environmental edges organize activity.
Speed and velocity signals change with linear or angular movement. Some medial entorhinal neurons increase their firing rate with running speed, while other populations carry combinations of position, direction, speed, and theta-related information [@kropff2015speed; @hardcastle2017multiplexed]. These variables are not housed in perfectly separate boxes. Many neurons show mixed selectivity, and the strength of their tuning changes with behavior.
The named cell classes remain useful because each made one relation conspicuous. Head-direction cells exposed direction. Grid cells exposed periodic spatial organization. Border cells exposed environmental edges. Speed cells exposed movement rate. But the animal is not navigated by a row of independent gauges. The map arises from interacting populations that combine body movement with external structure.
The firing fields of many grid cells approximate sixfold symmetry because neighboring fields are arranged at roughly 60-degree intervals. That geometry is an empirical finding. Why the network produces it remains an active mechanistic question.
Several classes of model can generate periodic activity. Continuous-attractor models organize a population so that an activity pattern moves smoothly as the animal moves. Oscillatory models derive spatial periodicity from interference among movement-sensitive rhythms. Efficient-coding and self-organization accounts ask what representations emerge when a network learns from natural trajectories. These models make different assumptions, and no single mechanism has closed the question.
Grid modules add a second observation. Cells within a module share similar spacing and orientation but differ in phase. Modules with different scales can be compared to gears with different numbers of teeth: the joint configuration can distinguish many more positions than any one gear alone. This gives the population enormous coding capacity. It does not prove that downstream neurons read the code as an odometer, nor that grid activity alone determines every place field.
The conclusion is clear. Grid populations provide a highly structured signal about movement and position. Their modular organization offers a plausible basis for multiscale spatial estimation, while their distortions reveal continuing dependence on environmental geometry and task.
45.5 The ancient computation: keeping track while moving
The most fundamental problem is not recognizing a familiar landmark. It is keeping track of position when the landmark is behind the animal, hidden by an obstacle, or temporarily absent.
Many mobile animals solve part of this problem through path integration. The animal begins from a known location and continually updates an estimate of its position from its own movement. Turning changes heading. Forward motion changes distance from the starting point. Integrating those changes can produce a direct homeward vector even after a winding outward path.
Desert ants offer a striking behavioral example. An ant leaves its nest and follows a long, irregular search path. After finding food, it often turns toward the nest and takes a relatively direct route home. The ant does not need to retrace every outbound turn. It has accumulated information about direction and distance while moving [@muellerwehner1988path]. Ants do not possess a vertebrate hippocampus; they isolate the computational advantage of path integration without identifying the vertebrate circuit that performs it.
A vertebrate brain has several sources for the same general calculation. The vestibular system reports rotations and linear acceleration. Proprioception and touch report movement of the limbs and body. Optic flow provides visual evidence of self-motion. Motor-related signals indicate actions that have just been issued. Head-direction and speed-related populations supply variables needed to update the estimate.
Path integration is powerful because it continues to operate when external evidence is poor. It is also inevitably imperfect. Small errors in estimating each turn or segment accumulate. A system using self-motion alone will drift farther from the true position as time and distance increase.
This limitation reveals why the external world remains part of the computation. Boundaries and landmarks provide correction. In rodents, error in grid firing grows with time and distance since the last boundary encounter, and contact with an informative boundary reduces the error in the direction constrained by that boundary [@hardcastle2015boundaries]. Landmarks can rotate or reanchor head-direction and place representations. Familiar geometry prevents an internally updated estimate from wandering indefinitely.
The relation is reciprocal. Self-motion keeps the map moving when landmarks are unavailable. Landmarks and boundaries correct the drift produced by self-motion. Neither source is sufficient by itself across the conditions a freely moving animal encounters.
This interaction also explains why the grid pattern changes with the environment. If the code were an isolated metric, environmental distortion would count only as failure. In a control system, calibration to the world is part of successful operation. A local object can become the relevant reference for homing. A barrier can divide one open surface into routes that are no longer interchangeable. A wall can supply the positional evidence needed to reset accumulated error.
Teleost physiology keeps the interpretation grounded. A weakly electric fish actively moves its electric sensing field across nearby objects while pallial activity tracks aspects of location and movement [@fotowat2019navigation]. The system operates inside a sensorimotor loop. The animal moves to acquire evidence, uses that evidence to update its relation to the environment, and changes movement again. The map is not contemplated from outside the behavior. It is constructed while controlling the body.
Path integration carries the estimate forward when sensory evidence is sparse. Boundaries and landmarks keep the estimate from drifting away from the world.
45.6 Development assembles and anchors the system
Development reveals how internal organization and environmental calibration are joined.
Before rat pups open their eyes, head-direction cells already show coherent relations within the population. When one cell’s preferred direction shifts, the others tend to shift with it. The network therefore has an internal directional organization before stable visual landmarks are available. But its preferred directions drift relative to the outside world and can change between recording periods. After eye opening, visual cues rapidly anchor the population to stable external directions [@bjerknes2015coherence].
Vision does not create the directional network from nothing. It stabilizes a network already organized by developing circuitry, vestibular signals, movement, and early nonvisual experience. The correct contrast is not innate versus learned. The system is partly preconfigured and then calibrated through use.
When young rats first begin to explore, head-direction activity is comparatively mature. Place-related activity is already present but gains spatial precision and stability over subsequent days. Stable adult-like grid periodicity appears later [@langston2010development; @wills2010development]. The sequence provides a plausible developmental scaffold: direction and self-motion signals are available early, place populations organize rapidly, and periodic entorhinal structure continues to mature with exploration.
Developmental order should not be confused with evolutionary order. A rat builds one modern mammalian system during a few postnatal weeks. It does not replay the history by which medial-pallial circuits changed across vertebrate lineages. Development shows how signals interact in the construction of a rat’s map. Comparative evidence is required to infer what the ancestral system contributed.
The two sources of evidence nevertheless converge on one principle. The map is neither copied from the visual scene nor fully specified before experience. Internal movement-related organization meets external environmental structure. The animal’s own action brings those sources into register.
45.7 From location to route
A coordinate answers one question: where is the animal? Successful navigation requires another: what can be reached from here?
A wall makes the distinction obvious. Two locations can be physically close but separated by a barrier. A distant doorway may be the only available transition between them. Straight-line distance therefore does not determine the next useful action. The animal must learn how places are connected.
The term state can sound more abstract than the biology requires. In this chapter, a state means the information needed to distinguish the animal’s current navigational situation. It can include position, heading, route, nearby boundaries, recent movement, and the current destination. Two visits to the same coordinate can be different states when they make different transitions possible.
A transition is movement from one such state to another. Repeated travel teaches which transitions are available, which are blocked, which are fast, and which lead toward a goal. A route is an ordered series of transitions. A shortcut becomes possible when the animal can use the learned relations without simply replaying one trained motor sequence.
This is the point at which a spatial map becomes predictive. Current population activity does not need to contain a picture of the future. It needs to be shaped by the states that tend to follow the present state and by the routes through which they are reached.
The successor representation gives one formal account of that idea. A state is represented partly through the future states expected to follow it under the animal’s usual policy, with nearer and more probable successors weighted more strongly. This predicts that neural similarity should reflect not only physical distance but learned transition structure. Insert a barrier, change the allowed route, or train a new policy, and the predictive relation among states should change [@stachenfeld2017predictive].
The successor representation is not a synonym for hippocampus. It is one model that makes the transition idea precise enough to test. Animals can plan beyond a familiar policy, and hippocampal populations carry sensory, contextual, temporal, and goal-related information not exhausted by one formalism. The model matters because it explains why a map built for action cannot be reduced to Euclidean geometry.
This remains an evolutionary argument, not a retreat into abstraction. A fish returning to shelter already confronts transition structure. A rock wall, vegetation, current, or predator can make the nearest route unusable. The animal benefits from representing how one place leads to another and from selecting a different route when conditions change. Later cortical systems can supply remote goals, explicit rules, verbal instructions, and social constraints. They elaborate control over the map. They do not create the basic problem of reachability.
45.8 The map moves ahead of the animal
So far the map has been described through firing rates accumulated across seconds or minutes of movement. Neural activity also has temporal structure within each traversal.
During active exploration in rats, hippocampal population activity is organized by a prominent theta rhythm, commonly in the range of approximately 6 to 12 hertz. As a rat crosses a place field, the corresponding place cell often fires at progressively earlier phases of the theta cycle. O’Keefe and Michael Recce called this phase precession [@okeeferecce1993phase].
The timing difference allows successive locations to be compressed. Imagine overlapping place fields arranged along a route. Early in one theta cycle, cells associated with recently occupied locations may fire. Later phases represent the current location and positions farther ahead. Across the population, an ordered spatial segment can therefore unfold within a fraction of a second.
These theta sequences are not simply firing-rate maps replayed faster. They are population patterns constructed from precise relations among spike timing, theta phase, the animal’s movement, and the active route. Nor does every place cell show identical phase precession on every pass, and not every theta cycle contains a clean forward sequence.
Phase precession and population sequences are also distinguishable. They often coexist, but one is not the automatic consequence of the other. Across CA1 populations, strong sequence organization can occur under conditions in which individual cells show weak phase precession. Experimental suppression of direct entorhinal layer III input to CA1 can weaken phase precession while strengthening population theta sequences [@guardamagna2023heterogeneity; @guardamagna2025entorhinal].
The firm conclusion does not require one universal theta mechanism.
During movement, hippocampal populations can represent a short route extending beyond the body’s instantaneous position.
That temporal organization gives the map a prospective edge. The represented location can advance ahead of the animal on the scale at which one movement is selected over another.
45.9 At a choice point
Tolman noticed that rats often paused at a junction and turned toward one route, then another, before committing. He called the behavior vicarious trial and error. Decades later, Adam Johnson and David Redish recorded ensembles in hippocampal area CA3 during similar pauses. Decoded population activity did not remain fixed at the rat’s body. It swept ahead along one possible arm of the maze and then another [@johnsonredish2007paths].
The recording supplied a physiological basis for evaluating routes without first moving through them. The animal remained at the choice point while the represented location traveled down alternatives.
Later experiments have separated the represented goal from the animal’s current heading and movement. In the Honeycomb maze, a rat waits on one platform while two neighboring platforms are raised. Reaching a remembered goal requires a sequence of local choices, and the rat’s head, next movement, and ultimate goal do not always point in the same direction. Hippocampal theta sweeps were biased toward the remembered goal independently of current heading and movement. Stronger goal alignment preceded correct choices, and the effect increased with experience [@yu2026thetasweeps].
The result is more specific than saying that the hippocampus imagines the future. The recordings reveal coordinated population activity directed toward a remembered destination. They do not reveal the rat’s subjective experience. What they establish is the control-relevant fact: the map can be oriented by a goal the animal is not currently facing.
Goal-directed sweeps also show why the hippocampus should not be described as an autonomous navigator. The destination must matter to the animal. Value, bodily need, task rules, and action selection depend on interactions with hypothalamic, amygdala, striatal, frontal, and sensorimotor systems. Those systems can bias which route is relevant. The hippocampal population supplies structured alternatives through the learned environment.
45.10 When the body stops
A different sequence state appears during quiet wakefulness and non-REM sleep. Large groups of hippocampal neurons discharge during brief sharp-wave ripples, events that are physiologically distinct from movement-related theta. Their ordered activity is compressed into tens to hundreds of milliseconds.
Some ripple sequences recapitulate a recently traveled route. They can proceed in the same order as behavior or in reverse order [@fosterwilson2006reverse]. Other sequences represent a path toward a remembered goal or a route the animal has not just traveled [@pfeifferfoster2013future]. The general term replay is convenient, but it should not imply that every ripple is an exact recording played back from storage.
The content depends on recent experience, current goals, behavioral state, and the wider circuits coordinated with the hippocampus. A reverse sequence after reward may help relate an outcome to the path that preceded it. A forward sequence before movement may make a route available for selection. A sleep sequence may contribute to longer-term reorganization across hippocampal and cortical networks. These possibilities overlap, but they are not interchangeable descriptions of one event.
Causal interventions show that ripples matter. Selectively suppressing sharp-wave ripples impairs learning or later performance in spatial-memory tasks [@girardeau2009ripples; @jadhav2012ripples]. The appropriate conclusion is not that every ripple consolidates one memory. It is that ripple-associated population events make a necessary contribution under conditions in which recently acquired spatial structure must influence later behavior.
Theta sequences and ripple sequences therefore reveal complementary operations. During active engagement, theta-scale activity relates the present movement to nearby route structure and goals. During pauses, quiet wakefulness, and sleep, ripple-associated activity can express recent, reverse, alternative, or goal-directed trajectories at a faster timescale.
45.11 What evolution added without replacing the core
The physiology now permits a clearer evolutionary statement.
The basal advantage was flexible navigation. An animal could leave a useful place, update its location while moving, use boundaries and landmarks to correct error, and select a route toward a goal that was not currently visible. This capacity did not require language, explicit reasoning, or a narrated self. It required a body in motion, a world with stable relations, and a circuit able to preserve those relations long enough to guide action.
Even this basal system was more than a compass. A compass supplies direction but not location. Path integration supplies displacement but drifts. A landmark identifies one feature but may disappear from view. A response chain works only while the familiar sequence remains available. The hippocampal system combined these partial sources into a flexible estimate. It could distinguish routes, reorganize when the environment changed, and express trajectories beyond the body’s current position.
That is already a relational achievement, but it is not an abstract faculty floating free of biology. The relations concern concrete ecological variables: this boundary lies beside that refuge; this turn follows that corridor; this route reaches the feeding site; this landmark predicts the entrance when the entrance itself is hidden. The ancient map was a structure for controlling movement.
Vertebrate evolution did not stop there. Mammalian hippocampal and entorhinal circuits became embedded in a greatly expanded pallium. Sensory association cortices could provide richer information about objects, scenes, and contexts. Amygdala and orbitofrontal systems could supply more differentiated outcomes and affective significance. Striatal systems could compare routes with learned action values. Frontal systems could maintain remote goals, rules, and alternatives that were not dictated by the immediately strongest cue.
Human cortical systems add further levels of control. Language can specify a destination never personally visited. Semantic knowledge can identify the kind of place being sought. Social instruction can prohibit the shortest route. Narrative can organize events around people, causes, and long intervals. Cultural artifacts place maps, schedules, and records outside the nervous system and feed their structure back into it.
Those additions matter enormously for human memory and planning. They should not be mistaken for the original function of the hippocampal system. An organ already present in teleosts did not evolve to support verbal recollection or a culturally extended personal history. Later systems gained access to an older way of organizing places, transitions, and possible routes.
Nor does this produce a ladder with fish at the bottom and humans at the top. Living lineages solve different ecological problems and elaborate different circuits. Goldfish can perform flexible navigation, temporal association, and relational inference [@rodriguez2002conservation; @gomez2022trace; @soteloparrilla2025transitive]. Other vertebrate lineages have elaborated the same ancient system under different ecological demands. The evolutionary claim concerns explanatory priority, not a ranking of species.
To understand the system, begin with the animal that must leave and return. Then ask what becomes possible when additional cortical systems can control which cues enter the map, which goals orient it, which sequences are generated, and how its output is combined with language, value, and social knowledge.
Evolution preserved a map for controlling movement through a world not fully visible from the present location. Later brains did not replace that map. They learned to ask more of it.
45.12 Coda: from places to other spaces
This chapter began with a mobile animal and ended with population activity that can move ahead of the body. Place cells identify locations within context. Grid, direction, boundary, speed, and sensory signals help update and anchor the representation. Remapping distinguishes situations that share physical coordinates. Learned transitions turn locations into routes. Theta and ripple-associated sequences express paths that are not being traversed at that moment.
Physical navigation remains the clearest case because the relevant variables can be measured directly. Position, movement, boundaries, routes, and goals can be plotted against neural activity. The evolutionary advantage is equally concrete: the map helps an animal reach what it needs when the goal is absent from current sensation.
The next chapter, Navigating Things That Are Not Places, asks how far the organizing principles extend. Can a circuit shaped by movement through physical space also order tones, concepts, sequences, and other relations? That question should be approached from the evolutionary base established here. The evolutionary hypothesis developed in this chapter is that those later uses elaborate a system whose basal adaptive value is most visible when an animal finds its way.
Established findings. Hippocampal and entorhinal populations carry information about location, route, direction, boundaries, movement, context, and goals. Self-motion signals update spatial activity when landmarks are sparse, while boundaries and landmarks anchor and recalibrate that activity. Place and grid representations change with route, environmental geometry, and task. During theta states and sharp-wave ripples, population activity can express ordered trajectories extending beyond the animal’s current position.
The chapter’s organizing interpretation. The basal adaptive advantage of the system was flexible navigation: keeping track of the body’s relation to places and routes when the goal was not immediately visible. Because a place is defined by relations among self-motion, landmarks, boundaries, and possible transitions, the ancient spatial map was relational from the beginning. Mammalian and human systems elaborate that map with richer goals, contexts, and event content rather than creating its basic organizing principle.
Open questions. The field has not established a single mechanism that generates grid periodicity, a single readout by which grid populations determine hippocampal place fields, or one universal function for theta and ripple-associated sequences. Comparative evidence also cannot recover the exact behavioral repertoire of the first vertebrate hippocampal system or prove that every later nonspatial use arose through one simple exaptation. Those uncertainties limit the historical detail without weakening the central conclusion that navigation provides the clearest evolutionary foundation for hippocampal function.