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Place cell

A place cell is a type of neuron found primarily in the hippocampus of the mammalian brain that selectively fires action potentials when an animal is located within a specific region of its environment, known as the place field, thereby contributing to the formation of an internal cognitive map for spatial navigation and memory encoding. These cells were first identified in 1971 by John O'Keefe and Jonathan Dostrovsky through single-unit recordings in the CA1 region of the hippocampus in freely moving rats, where they observed that certain neurons discharged robustly only when the animal occupied particular positions in a test environment. Place cells exhibit stable but flexible firing patterns, with place fields typically spanning 30-60 cm in rodents and varying in size and shape depending on the environmental context, such as the size of the arena or the presence of landmarks. The activity of place cells is modulated by both external sensory cues, like visual or olfactory landmarks, and internal signals, including the animal's and , allowing the neural representation to update dynamically as the animal explores. In larger environments, individual place cells can develop multiple place fields, but collectively, populations of place cells provide a comprehensive, allocentric map of that is independent of the animal's egocentric . When the environment changes—such as altering the shape of a testing arena or switching between distinct rooms—place cell firing remaps rapidly, either partially or completely, reflecting the brain's ability to form distinct representations for different contexts. Beyond spatial coding, place cells play a crucial role in by replaying sequences of experiences during rest or sleep through sharp-wave ripples, a high-frequency oscillation in the that consolidates learned spatial trajectories and supports storage. They integrate inputs from other specialized cells in the hippocampal formation, such as grid cells in the —which provide a metric lattice for distance and direction—and border cells, which signal environmental boundaries, to generate a unified . Disruptions to place cell function, as seen in hippocampal lesions, impair spatial learning and , underscoring their importance in behaviors from to goal-directed across species, including humans as evidenced by studies.

Discovery and Background

Historical Discovery

Place cells were first identified in 1971 by John O'Keefe and Jonathan Dostrovsky through extracellular recordings from the of freely moving rats, revealing that certain pyramidal neurons fired selectively when the animal was in specific locations within its environment. This discovery occurred serendipitously during studies of hippocampal responses to somatosensory stimuli, where the location-specific firing patterns emerged as a prominent feature independent of sensory inputs. In their seminal short communication published in Brain Research, O'Keefe and Dostrovsky described these "place-specific" units, proposing that they contributed to a spatial mapping function in the . Building on this initial evidence, O'Keefe and Lynn Nadel elaborated the theoretical implications in their 1978 book The Hippocampus as a , positing that place cells formed the neural basis for an allocentric representation of space, akin to Edward Tolman's earlier concept of a . The book integrated the place cell findings with broader hippocampal lesion studies, arguing that the constructs and maintains internal spatial models essential for and . However, the discovery faced initial skepticism within the community, dominated by behaviorist paradigms that emphasized stimulus-response associations over cognitive representations, delaying widespread acceptance. Replication efforts were hampered by technological limitations in the , as chronic single-unit recordings in freely behaving animals required precise implantation and behavioral tracking, which were rudimentary without advanced . It was not until the early , with improvements in technology and the introduction of video-based head-tracking systems, that more robust replications confirmed the stability and specificity of place cell activity, as demonstrated in studies using radial arm mazes. These advancements, including quantitative analyses by McNaughton and colleagues, solidified the role of place cells in . The foundational contributions of place cell research were recognized with the 2014 in or , awarded to O'Keefe (shared with and Edvard I. Moser for their discovery of grid cells, a complementary spatial representation in the ).

Relationship to Grid Cells and Other Spatial Neurons

Place cells in the integrate spatial information from various neurons to form a of the environment. A primary input comes from grid cells in the medial (MEC), which were discovered in and exhibit periodic firing patterns arranged in a across the navigated space. These grid cells provide a scalable, metric representation of location, with firing fields repeating at regular intervals that vary systematically across modules defined by . The convergence of inputs from multiple grid cell modules onto individual place cells is believed to underlie the localized firing fields of place cells, enabling precise spatial coding. Head-direction cells, first identified in the postsubiculum, encode an animal's instantaneous directional heading independent of location and project to both the MEC and . These cells maintain a consistent preferred firing direction, updated via path integration and stabilized by visual landmarks, and their activity modulates the directional selectivity observed in some hippocampal place cells, particularly in novel or asymmetric environments. In the , head-direction signals interact with firing to generate anisotropic patterns, further refining the directional components of place cell representations. Additional entorhinal inputs include cells, which fire selectively near environmental boundaries such as walls or edges, comprising about 10% of MEC neurons and influencing the positioning and shape of place field peripheries. Object-vector cells in the MEC, which encode the allocentric distance and direction to nearby objects, provide place cells with object-centered spatial references, allowing to salient landmarks without relying solely on global geometry. These inputs collectively contribute to the robustness of place cell activity against environmental changes. Theoretical models, such as continuous networks, propose that inputs to the generate place fields through interference mechanisms, where the superposition of periodic patterns from different modules produces localized peaks resembling place cell firing. In these -based s, recurrent connectivity within the hippocampal network stabilizes the resulting representations, while entorhinal inputs drive the initial computation via excitatory projections. Such models explain how the combinatorial activity of , head-direction, , and object-vector cells forms a unified spatial for place cells.

Core Properties

Place Fields

Place fields represent the core spatial tuning characteristic of place cells, defined as discrete regions within an where a place cell exhibits significantly elevated firing rates compared to surrounding areas. In , these fields typically span 30-60 cm in diameter, with peak firing rates reaching 20-50 Hz that decline sharply outside the field boundaries. This selective activation allows place cells to encode specific locations, forming a sparse neural representation of . The firing pattern of place cells demonstrates sparsity, with only 10-20% of cells active at any given , ensuring efficient coverage of the without redundant overlap. Firing rate versus position typically follows Gaussian-like tuning curves, where the rate increases smoothly to a peak within the field and falls off symmetrically, providing a probabilistic of spatial . In small arenas, place cells generally exhibit a single place field, but the number of fields per cell varies in larger environments, often increasing to multiple irregular fields that collectively tile space. A 2025 study revealed universal statistical properties governing field sizes, shapes, and arrangements across species and dimensionalities, explaining this variability through underlying Gaussian input statistics. Recent findings further indicate that, in familiar environments, all active pyramidal cells in the dorsal CA1 region function as place cells, challenging prior notions of a subset of specialized neurons. Place field properties are influenced by inputs from entorhinal grid cells, which provide a periodic that helps shape the spatial selectivity of hippocampal place cells.

Stability, Remapping, and Multiple Fields

Place cells exhibit remarkable in their firing patterns when the environment remains consistent. In familiar, fixed environments, the spatial firing fields of place cells show high between repeated recording sessions, with maximum spatial correlations often exceeding 0.8, indicating reliable of over short timescales such as within or across brief exposures. This persists even with minor manipulations that preserve overall environmental cues, such as rotating a prominent or removing it temporarily, where fields rotate predictably or maintain their core properties without significant disruption. However, place cells demonstrate adaptability through remapping when environmental contexts change, a process that allows the hippocampal map to update in response to novelty. Subtle alterations, such as introducing barriers that bisect firing fields or modifying local cues without altering the overall shape, often induce partial remapping characterized by changes in firing rates within existing fields—termed rate remapping—while preserving field locations. In contrast, major changes like reshaping the (e.g., from a to a ) trigger global remapping, where the majority of place cells exhibit entirely new firing patterns uncorrelated with prior sessions, effectively generating a distinct spatial code. Seminal studies from the , building on earlier work, highlighted how contextual novelty drives this remapping, with the degree of change scaling with the salience of environmental modifications. In larger or open environments that exceed the scale of typical arenas, individual place cells frequently develop multiple firing fields rather than a single one, enabling coverage of expansive spaces. Recent analyses across , including and bats, reveal that these multiple fields vary heterogeneously in shape, size, and spacing, following universal statistical patterns such as Rayleigh-distributed field widths in one-dimensional tracks and gaps between fields in two- or three-dimensional settings. This multiplicity emerges as environments scale up, contrasting with the singular fields observed in confined spaces, and supports a more flexible, multi-scale representation of navigationally relevant areas. The underlying mechanisms of remapping and stability involve in the , particularly (LTP) and long-term depression (), which adjust connectivity to adapt place field properties without necessarily requiring immediate behavioral changes unless linked to learning. For instance, novelty-induced in CA1 synapses facilitates the initial formation and long-term maintenance of stable fields, as blocking impairs cross-day correlations and accelerates but destabilizes field establishment. Bidirectional plasticity, encompassing both and , further enables rapid modifications to existing fields during contextual shifts, ensuring the place cell ensemble can reconfigure efficiently. These plastic processes tie remapping to experience-dependent updates, preserving stability in familiar contexts while allowing adaptive recoding in novel ones.

Phase Precession

Phase precession refers to the systematic forward shift in the timing of action potentials from hippocampal place cells relative to the ongoing (8–12 Hz), such that spikes occur at progressively earlier s of the cycle as the animal traverses a place field, typically advancing by approximately 180 degrees from the field's entry to exit. This temporal coding mechanism allows individual place cells to fire multiple times within a single cycle, with the of each encoding the animal's within the field more reliably than timing alone. The phenomenon was first identified in the early 1990s through extracellular recordings from rat CA1 pyramidal cells during spatial navigation tasks on linear tracks. John O'Keefe and Michael Recce observed that place cell bursts consistently began near the trough of the (around 180–270 degrees) upon entering the place field but precessed forward, often completing a full cycle or more by the field's end, with the degree of ranging from 100 to 355 degrees across cells. Subsequent analyses revealed that this compresses sequential activation of place cells representing successive locations into brief theta-cycle "sweeps," effectively representing future positions ahead of the animal's actual trajectory by 100–200 ms. Mathematically, phase precession is often modeled as a linear advancement of the spike φ relative to the animal's or time, approximated by φ = φ₀ - (v / λ) ⋅ θ, where φ₀ is the entry , v is the animal's , λ is the wavelength (distance covered per theta cycle, typically 10–20 cm at running speeds), and θ tracks the cycle progression; this form derives from the mismatch between the place cell's elevated intrafield firing rate (slightly faster than frequency) and the oscillation, producing a phase shift proportional to movement through the field. In network models, this emerges from asymmetric recurrent excitation in CA3–CA1 circuits, where activity propagates ahead of the sensory input representing the animal's . Beyond basic traversal, phase facilitates by temporally organizing place cell ensembles to encode experienced paths in compressed form, supporting of spatial trajectories. The rate—the slope of phase advance per unit distance—varies systematically with behavioral factors: it increases with running speed, as higher velocities traverse fields more quickly relative to cycles, and adjusts with environmental novelty, where initial exposures yield shallower slopes that steepen and stabilize over repeated visits as spatial representations mature.

Directionality and Asymmetry

Place cells in generally exhibit bidirectional firing patterns, activating when the animal passes through a specific regardless of traversal . However, approximately 25% of these cells demonstrate significant or unidirectional selectivity, often modulated by the animal's head . This asymmetry arises from interactions with head-direction cells, which provide directional input to refine spatial tuning in the . Such directionality becomes particularly prominent in goal-oriented navigation tasks, where place fields adapt to encode intended paths or decisions. For instance, in T-maze alternation paradigms, place cells shift from symmetric to direction-specific firing, with increased selectivity along trajectories toward rewarded arms, supporting route-based memory formation. This task-dependent emergence highlights how behavioral demands can reshape place cell responses beyond pure location coding.

Sensory and Behavioral Influences

Visuospatial and Olfactory Inputs

Place cells in the are strongly influenced by visuospatial cues, particularly distant landmarks, which serve to and orient their firing fields. Seminal experiments demonstrated that rotating extramaze visual cues, such as a single on the wall of a cylindrical arena, results in a corresponding of place fields by approximately the same , indicating that these cues exert precise control over spatial representations. This highlights the reliance of place cells on stable visual landmarks to maintain consistent spatial mapping during navigation. Olfactory inputs contribute to place cell stability through projections from the to the and lateral , which then relay information to the . These inputs are particularly crucial in cue-poor or dark environments, where they help sustain place field coherence when visual cues are absent. For instance, in complete darkness, place cell firing patterns initially persist based on recent experience but gradually degrade unless supported by olfactory and tactile cues, demonstrating the compensatory role of olfaction. Studies from the early further showed that spatial olfactory cues can stabilize place fields even in visually deprived conditions, with field stability increasing when odors are consistently associated with specific locations. The integration of visuospatial and olfactory cues in place cell activity reveals a hierarchical processing, where visual inputs typically dominate in well-lit environments. In lighted arenas, manipulations of visual landmarks reliably remap place fields, while olfactory cues exert secondary influence unless visual information is removed. However, in , olfactory cues compensate by maintaining field stability, suggesting a flexibility that adapts to sensory availability. This dominance of visual cues in lit conditions, with olfactory support in low-light scenarios, underscores the hippocampus's ability to prioritize reliable exteroceptive signals for spatial coding.

Vestibular and Movement Inputs

Place cells receive critical self-motion signals from the , which detects head tilts and linear accelerations via the , helping to maintain the stability of place fields during changes in or . In experiments comparing head-fixed and freely moving , place cell firing remains robust in head-fixed setups on real-world platforms, though vestibular inputs are partially compromised, underscoring their role in supporting spatial representations without full head movement freedom. These inputs interact with visuospatial cues to anchor place fields to the environment, ensuring coherent mapping. Path integration, or , further integrates vestibular and motor efference copies—internal signals of self-movement—with optic flow to update place cell activity, allowing brief persistence of firing even in cue-deprived conditions like . This mechanism enables animals to estimate position from integrated velocity and direction signals, with hippocampal lesions disrupting such behaviors. Place cells thus rely on these idiothetic cues to sustain spatial tuning temporarily until external landmarks recalibrate the map. Movement speed profoundly modulates place cell firing rates, with neurons exhibiting higher rates during faster locomotion, as evidenced by velocity tuning curves from early recordings in freely moving rats. This speed-dependent increase in firing helps encode dynamic navigational states, independent of positional specificity. Recent two-photon calcium imaging studies reveal diverse calcium dynamics in place field formation, where behavioral time scale synaptic plasticity events—marked by large somatic calcium transients—show a positive correlation between running speed on formation laps and subsequent place field width, highlighting speed's role in shaping spatial selectivity. In contrast, non-plasticity-like fields emerge with smaller transients uncorrelated to speed, indicating multiple pathways for field establishment influenced by movement vigor.

Role in Memory Formation

Pattern Completion and Separation

Place cell ensembles in the hippocampus contribute to memory formation by performing pattern completion and pattern separation, two complementary computations that enable the storage and retrieval of spatial representations. Pattern completion allows the retrieval of a complete spatial memory from partial or degraded cues, a process facilitated by the recurrent connections within the CA3 region of the . In this mechanism, partial activation of place cells triggers the autoassociative network in CA3 to reconstruct the full pattern of activity corresponding to the original environment, drawing from Tolman-inspired theories of cognitive mapping and formalized in 1990s computational models of hippocampal function. In contrast, pattern separation orthogonalizes similar input patterns to minimize interference between memories, primarily occurring in the through sparse, non-overlapping activations of cells that project to CA3. This process ensures that distinct engrams form for similar but non-identical environments, preventing during encoding. Computational models emphasize the role of the in expanding and decorrelating entorhinal inputs via mechanisms like sparse coding and , which enhance the uniqueness of place cell representations. Experimental evidence for these processes comes from studies using the Morris water maze, where removal of distal cues after training leads to preserved spatial performance in control animals, indicating CA3-mediated pattern completion, but impairs performance in mice with CA3-specific knockouts. Conversely, tasks with overlapping contexts, such as morphed environments, demonstrate pattern separation as place cell firing patterns remap orthogonally in the and CA3 to distinguish subtle differences. The sparsity of place cell activity, with only a small fraction of cells active at any , underpins these computations by enabling high-capacity storage of approximately $10^4 to $10^5 bits per in the hippocampal . This sparse maximizes the number of distinguishable spatial maps while supporting efficient separation and .

Reactivation, Replay, and Preplay

Place cells demonstrate reactivation during offline states such as and , where ensembles of neurons fire in coordinated sequences that reconstruct prior spatial experiences. This phenomenon was first observed in rats navigating familiar environments, with place cell activity patterns re-emerging in a temporally compressed manner during these quiescent periods. Reactivation is prominently linked to sharp-wave ripples (SWRs), transient bursts of high-frequency oscillations in the ranging from 140 to 200 Hz, which facilitate the synchronous firing of place cell assemblies. A key aspect of reactivation involves the replay of place cell sequences, which can occur in both forward and reverse directions to support and behavioral adaptation. Forward replay, where sequences mirror the temporal order experienced during exploration, often follows rewarding events and contributes to by reinforcing trajectories leading to goals, such as post-reward paths in spatial tasks. In contrast, reverse replay—sequences played backward from reward locations—has been shown in studies from the to aid in evaluating potential actions and updating value estimates, with its occurrence uniquely modulated by changes in reward magnitude. Preplay refers to the predictive activation of place cell sequences representing novel, unexperienced spatial paths prior to their occurrence, suggesting a role in prospective and formation. In rats exposed to new environments, these preconfigured sequences emerge during before behavioral , enabling rapid of future trajectories. Recent work has further elucidated how experience-dependent mechanisms, such as synaptic adjustments in hippocampal area CA1, amplify the referencing of relevant place cell replays to maintain flexible cognitive maps.

Integration with Episodic and Time Coding

Place cells in the contribute to by integrating spatial information with non-spatial elements, such as objects and events, to encode the "what-where-when" structure of experiences. This binding occurs through conjunctive representations, where place cells form coordinated activity patterns with object-selective neurons in the medial and other regions, allowing the to associate specific locations with particular items or contexts. For instance, during object exploration tasks in , place cell firing remaps in response to object novelty or , reflecting the incorporation of "what" and "where" details into spatial codes. A key mechanism for incorporating the "when" component involves time cells, which are hippocampal neurons that fire sequentially during temporally structured delays in the absence of movement. In CA1 and CA3 subfields, these time cells generate ordered sequences that parallel place cell trajectories, effectively bridging spatial and temporal information to represent spatiotemporal contexts. Pastalkova et al. (2008) identified this phenomenon in rats performing a waiting task on a , where distinct populations of hippocampal cells activated in a time-locked manner, independent of spatial cues but predictive of subsequent paths. This integration enables the to construct coherent episodic traces that sequence events across both and time. Recent studies have further elucidated the dynamic interplay between spatial and temporal coding in place cell networks. In a 2024 Neuron investigation, researchers recorded from hippocampal in navigating virtual environments and found of between and time representations, where increasing temporal demands reduced spatial specificity in individual cells, yet overall ensembles maintained integrated space-time codes essential for task performance. Such mechanisms support flexible by balancing immediate spatial mapping with broader temporal context. Place cell ensembles also facilitate prospective coding, anticipating future events by flexibly adapting population activity to encode potential sequences. A 2025 study demonstrated that novel environmental information triggers enhanced prospective representations in hippocampal place cells, allowing to predict and select among multiple goal-directed paths during tasks. This adaptive coding underscores the role of place cells in forward-looking episodic , where spatial frameworks extend to temporal of event outcomes.

Place Cells Across Species

Rodents and Bats

Place cells were first identified in , specifically rats, through extracellular recordings in the dorsal , where individual CA1 pyramidal neurons exhibit spatially selective firing patterns known as place fields, typically consisting of one or a few discrete regions of elevated activity during exploration of small enclosed like boxes. These canonical place fields in are often stable across repeated exposures to the same familiar , with peak firing rates occurring when the animal is within the field, and they demonstrate robust phase precession, where spikes advance progressively earlier in the hippocampal rhythm as the animal traverses the field. In tasks such as the Morris water maze, place cell representations undergo remapping, with fields reorganizing to reflect changes in task demands or environmental modifications, supporting spatial learning and formation. Recent large-scale recordings in mice have confirmed that, in familiar setups, virtually all active CA1 pyramidal cells function as place cells, challenging earlier notions of a sparse coding subset and highlighting the ubiquity of spatial selectivity in this region under stable conditions.00750-3) In bats, place cells have been extensively studied in echolocating species like the Egyptian fruit bat, revealing hippocampal neurons that encode location in during free flight, with place fields adapting dynamically to volumetric environments and flight trajectories. These bat place cells, recorded from the dorsal CA1, show expanded fields in larger, open arenas compared to the compact setups typical in studies, and they integrate echolocation-based sensory cues with self-motion signals to maintain spatial representations during rapid, aerial . Unlike the more rigid, landmark-driven fields in , bat place cells exhibit greater flexibility in cue-poor or dynamic settings, such as in unstructured outdoor spaces, where self-motion integration via path integration plays a prominent role in stabilizing firing patterns. Comparatively, place cells display higher dependence on distal visual cues for stability in controlled lab environments, leading to partial or global remapping when cues are altered, whereas place cells demonstrate enhanced resilience through , including vestibular and proprioceptive inputs during flight, which supports in vast, feature-sparse natural habitats.31229-7) Experimental techniques have been pivotal: in , multi-tetrode arrays implanted in the enable chronic, high-density extracellular recordings from hundreds of neurons during unrestrained behavior in mazes or open fields, allowing detailed analysis of ensemble dynamics. In bats, wireless telemetry systems facilitate recordings from freely flying animals in three-dimensional arenas or tunnels, capturing place cell activity without tethering constraints and revealing adaptations to echolocation-guided exploration.

Primates and Humans

In , particularly rhesus monkeys, hippocampal neurons predominantly exhibit properties of spatial view cells rather than pure place cells. These cells respond to allocentric views of specific locations in the when the animal gazes toward them, independent of the monkey's own position or head direction. This visual dominance reflects adaptations for foveal vision and scene processing, contrasting with the path integration-based firing of rodent place cells. Due to the expanded hippocampus, these spatial fields are broader, less sparse, and associated with lower peak firing rates (averaging ~1 Hz) compared to the compact, high-rate fields in . In humans, intracranial recordings from patients during the 2010s identified place-like cells in the that demonstrate spatial selectivity during navigation tasks. These neurons fire in relation to specific locations within virtual environments, supporting allocentric spatial coding akin to rodent place cells, though often with broader due to methodological constraints in human recordings. Functional MRI studies from 2023 onward have further revealed hippocampal spatial during VR navigation, with oscillations modulating position-specific activity near learned locations and boundaries. A of place cell detection algorithms applied to and intracranial datasets confirmed similar overall sparsity in firing patterns across , with only a small fraction of neurons (~10%) active at any given location. However, place-like cells exhibited more abstract and diffuse coding, clustering at lower tuning strengths, which may facilitate generalization beyond pure spatial metrics. These cells also contribute to , encoding imagined or verbally described spaces through consistent theta dynamics in the anterior , enabling the reconstruction of non-experienced trajectories.

Non-Mammalian Animals

Research on place cells has extended beyond mammals to non-mammalian vertebrates and , revealing evolutionary conservation of spatial coding mechanisms alongside notable differences in stability, neural substrates, and oscillatory patterns. In these species, place-like neurons often exhibit sparse firing and responses to novel environments, but they typically lack the prominent rhythms characteristic of mammalian hippocampal activity. These findings suggest that core elements of spatial representation emerged early in vertebrate evolution, adapted to diverse navigational demands such as or flying. In , a fish, place s have been identified in the dorsal pallium, considered the homolog of the mammalian . A using brain-wide in freely swimming larval demonstrated that pallial neurons form stable spatial representations during virtual tasks, with place fields guiding swimming trajectories in a population code. These fields emerged dynamically, encoding location through coordinated activity across ∼10% of active pallial s, and showed specificity to visual landmarks, highlighting the role of the dorsal pallium in spatial mapping. Unlike mammalian place s, representations rely more on population-level decoding rather than individual , yet they share remapping in response to environmental novelty. Among birds, place-like cells appear in the hippocampal formation and adjacent hyperpallium, adapted for aerial navigation and caching behaviors. In homing pigeons, electrophysiological recordings revealed location cells tuned to specific positions in open arenas, path cells selective for trajectories toward goals, and pattern cells responding to clustered environmental features around reward sites. These cells, recorded in 2017, exhibit spatial selectivity but are less stable across sessions compared to mammalian counterparts, with multiple firing fields and weaker confinement to single locations. In food-caching corvids like black-capped chickadees, a 2021 study identified more stable place cells in the hippocampus, mapping multiple cache sites over weeks and modulating with task context, challenging prior views of inherent instability in avian spatial coding. Bird place cells demonstrate sparsity similar to mammals, firing in only a small fraction of environments, and show enhanced responses to novel spatial configurations during caching tasks. However, avian systems lack theta oscillations, relying instead on other rhythms for coordinating spatial sequences. Evidence for place-like activity in remains limited, with no true spatial map-forming cells identified. In , mushroom body neurons display place-like tuning during navigation in olfactory-defined arenas, where activity correlates with position in odor gradients rather than visual space. These neurons process combinatorial olfactory cues sparsely, enabling associative spatial learning, but fail to form stable, environment-specific fields akin to vertebrate place cells. Such tuning supports goal-directed behavior in feature-poor environments but represents context-dependent modulation rather than a dedicated spatial map. Across non-mammalian species, place-like cells exhibit conserved features such as sparse activation and sensitivity to novelty, facilitating efficient encoding of salient locations despite divergent brain architectures. For instance, both zebrafish pallial and avian hippocampal neurons remap rapidly to novel cues, mirroring mammalian pattern separation. However, non-mammalian representations often show greater instability over time and sessions, as evidenced by multi-field responses and context-dependent shifts, potentially due to the absence of theta-modulated synchronization. This comparative instability underscores adaptations to ephemeral environments like water or air, while shared sparsity optimizes coding efficiency across phyla.

Pathological and Experimental Disruptions

Substance Effects and Acute Disruptions

Acute administration of ethanol in rodents induces dose-dependent destabilization of hippocampal place fields without causing global silencing of place cell activity. At moderate doses such as 1.0 g/kg intraperitoneally, ethanol reduces the spatial selectivity of place cells by increasing out-of-field firing and decreasing in-field rates, leading to impaired navigational accuracy during intoxication. Higher doses, around 1.5 g/kg, result in approximately 35% of place fields disappearing, 38% showing reduced firing rates, and about 7-16% exhibiting remapping or novel field emergence, while overall spatial information content remains unchanged. These effects are reversible upon ethanol clearance and occur alongside partial locomotor slowing, highlighting a selective disruption of spatial encoding rather than broad neural suppression. NMDA receptor antagonists, such as , acutely disrupt key temporal dynamics of place cells. At doses of 7.5-50 mg/kg, ketamine preserves the basic mechanism of theta phase but reduces its range across the theta cycle by roughly 35% (from ~290° to ~190°), alongside shallower slopes and decreased infield firing rates correlated with slowed . At 8 mg/kg, ketamine halves the density of sharp-wave ripples (SWRs) and diminishes their associated replay content, impairing the offline reactivation of spatial sequences essential for . Opioid agonists targeting μ-opioid receptors () also alter SWR-associated place cell activity in the . Application of MOR agonists (1 nM-10 μM) enhances sharp wave amplitude and increases the incidence of SWR sequences but reduces ripple oscillation duration at higher concentrations (≥100 nM), potentially disrupting coordinated population bursts during rest. Acute manipulations like optogenetic silencing of medial (MEC) inputs to the cause rapid partial remapping of place fields. Brief inactivation via ArchT or hM4D pharmacogenetics in mice instantly lowers spatial correlations between pre- and post-inactivation maps (e.g., from to r ≈ 0.41), shifting the active CA1 population without altering individual field sizes or spatial tuning. These substance-induced and acute disruptions correlate with behavioral deficits in spatial tasks, particularly path integration reliant on hippocampal self-motion cues. Low-dose (0.5 g/kg) fragments the coordinated hippocampal-striatal activity patterns that support vector-based path integration, leading to errors in estimating and during in .

Neurodegenerative and Aging Effects

In Alzheimer's disease (AD), amyloid-β accumulation disrupts place cell function, leading to instability in place fields and reduced replay of neural sequences essential for memory consolidation. Studies in Tg2576 mouse models from the 2000s demonstrated that aged transgenic mice exhibit degraded place cell stability, with firing patterns correlating directly with amyloid plaque burden and associated memory deficits. More recent work in APPNL-G-F knock-in mice has shown that amyloid-β pathology impairs both rate and temporal coding of spatial information in CA1 place cells, manifesting as fragmented firing fields and diminished precision in representing locations. These disruptions extend to reduced reactivation of place cell ensembles during sharp-wave ripples, a process critical for offline memory processing, as observed in awake AD mouse models where inhibitory synaptic changes shorten ripple events and weaken sequence replay. Tau pathology, originating in the and spreading to hippocampal regions, further exacerbates place cell dysfunction by altering connectivity between upstream and downstream circuits. In tauopathy models like rTg4510 mice, entorhinal tau accumulation leads to reduced grid cell periodicity, which propagates to impair hippocampal place coding and correlates with spatial memory loss. This spread induces functional disconnection between CA3 and CA1 subfields, with CA3 place fields shrinking and losing pattern completion capabilities, while CA1 cells show decreased and spatial , directly linking these neural changes to AD-related memory impairments. Human intracranial EEG studies in 2023 have identified similar place cell-like activity in the medial , suggesting that early AD pathology may fragment these representations, though direct causal links remain under investigation in patient cohorts. Normal aging also progressively degrades place cell properties, independent of overt neurodegeneration, contributing to age-related decline. In aged rats, hippocampal place fields broaden significantly—typically by 20-50% compared to young adults—resulting in reduced spatial specificity and less reliable location coding, as documented in electrophysiological recordings. This field expansion is accompanied by weakened oscillations, with decreased power impairing phase precession, the mechanism by which place cells advance their firing phase relative to the to sequence spatial experiences. Consequently, aged rodents show poorer pattern separation, a process reliant on precise place cell activity for distinguishing similar environments. Place cell fragmentation has been proposed as an early of , integrating findings from and models, with disrupted place field stability and replay deficits linked to entorhinal tau propagation; hippocampal serves as a sensitive indicator of cognitive vulnerability before widespread plaque or tangle accumulation.

Developmental and Genetic Disorders

Place cells exhibit significant abnormalities in neurodevelopmental disorders, particularly those involving genetic mutations that disrupt hippocampal and dynamics. In (FXS), the most common inherited form of and a leading genetic cause of autism spectrum disorder, knockout rat models demonstrate impaired coordination of CA1 place cell sequences during both active exploration and subsequent rest periods, leading to deficits in spatial sequence representation that may underlie cognitive impairments. This disruption is linked to the absence of fragile X mental retardation protein (FMRP), which normally regulates mRNA translation at synapses, resulting in overexpression of (mGluR5) and excessive mGluR-dependent long-term depression that compromises sequence stability. Phase precession, a key mechanism for temporal coding in place cell firing relative to oscillations, is also altered in FXS models, with Fmr1-null mice showing shifted phases and weakened correlations, further impairing the ordered of place cell ensembles. In models, such as mice with 22q11.2 deletion syndrome—a genetic risk factor for the disorder—place cell remapping is disrupted due to dysregulation, leading to unstable spatial representations and impaired goal-directed plasticity in the . signaling from the modulates CA1 place cell reorientation during rule learning, and hyperdopaminergic states in these models promote excitation-inhibition imbalances that prevent adaptive remapping, contributing to cognitive inflexibility observed in . Similarly, autism-linked mutations, such as those in the chromatin regulator KDM5A, alter hippocampal cell identity and synaptic gene expression. Genetic knockouts targeting subunits, like NR2B (encoded by Grin2b), disrupt place field formation during juvenile development by impairing activity-dependent synaptic strengthening in the . NR2B-containing s predominate in early postnatal stages and are essential for at Schaffer collateral-CA1 synapses, with conditional reductions leading to immature place field properties and poor spatial discrimination in young rodents. Therapeutic interventions in FXS models, including optogenetic reactivation of hippocampal engrams—sparse ensembles of place cells encoding specific experiences—have shown promise in rescuing memory deficits by restoring defective reactivation during , highlighting potential circuit-level treatments for sequence impairments.

Computational and Theoretical Models

Biophysical Mechanisms of Place Field Formation

Behavioral timescale synaptic plasticity (BTSP) plays a central role in the formation of place fields through synaptic potentiation at synapses between CA3 and CA1 pyramidal neurons. and studies have shown that presynaptic activity from CA3 place or cells, paired with postsynaptic in CA1 on behavioral timescales, induces BTSP specifically at these synapses, strengthening connections that align with spatial locations traversed by the animal. This synaptic strengthening is thought to consolidate weak initial inputs into stable place field representations. Intrinsic excitability properties of CA1 pyramidal neurons further contribute to place field emergence via calcium dynamics in their dendrites. A 2025 study using in vivo two-photon in head-restrained mice demonstrated that and dendritic calcium transients vary across cells during novel environment exposure, with some place fields forming through gradual increases in dendritic excitability and others via abrupt bursts, highlighting heterogeneous biophysical mechanisms that shape field onset and specificity. These allow individual neurons to tune their response thresholds to sensory-driven inputs, enabling the selective that defines place fields. Dendritic spikes in CA1 pyramidal cells facilitate nonlinear of synaptic inputs, transforming diffuse weak signals into focused, Gaussian-shaped place fields. has shown that local dendritic calcium spikes, often preceding somatic firing, amplify coincident excitatory inputs from entorhinal and CA3 sources while suppressing non-coincident ones, thereby generating the bell-shaped firing rate profiles characteristic of place cells. This nonlinear processing ensures that only spatially tuned input clusters effectively drive output spikes, enhancing the precision of spatial coding. Computational modeling supports these cellular processes by illustrating how recurrent excitation and inhibition balance in CA1 networks underlies place field formation. Sensory inputs from the entorhinal cortex serve as the primary drivers, initiating these biophysical cascades during spatial exploration, with BTSP integrating grid cell metric signals for tuned representations.

Population Coding and Universal Statistics

Place cell ensembles in the hippocampus collectively encode an animal's position through coordinated firing patterns, enabling the reconstruction of spatial trajectories from population activity. Population vector decoding, an early method that weights the preferred locations of individual place cells by their firing rates, has been extended in the 2010s using Bayesian probabilistic models to achieve higher precision. These Bayesian approaches integrate prior knowledge of movement continuity and firing rate maps to infer position, yielding trajectory reconstruction accuracies of approximately 5-10 cm in controlled environments like linear tracks or open arenas. For instance, in foraging tasks, median decoding errors as low as 8 cm were reported using ensembles of 30-50 place cells, with further refinements in real-time applications maintaining errors around 10-15 cm even with smaller populations of 5-10 neurons. Recent theoretical advances have revealed universal statistical properties in place cell firing distributions, invariant across species, environmental scales, and even dimensionalities. These scale-invariant patterns unify the heterogeneity observed in small, sharply tuned fields typical of in familiar arenas with the broader, more irregular fields seen in large or novel spaces, such as those navigated by bats in 3D environments. A 2025 model posits that place fields emerge from a Gaussian random modulated by firing thresholds across neurons, explaining empirical distributions of field sizes, overlaps, and shapes without invoking environment-specific . This framework demonstrates that field statistics follow power-law-like , where larger environments exhibit proportionally more cells with extended or multiple fields, preserving representational across contexts. In large environments, place cells often exhibit multiple fields, allowing coverage of expansive spaces while maintaining decoding fidelity. Attractor dynamics provide a foundational for how place cell populations maintain stable representations and enable continuous remapping between environments via recurrent in CA3. In the continuous model, place fields form a smooth manifold where excitatory collaterals in CA3 autoassociative networks stabilize activity bumps corresponding to current position, while path integration updates the state during movement. This architecture accounts for partial remapping—where some cells shift firing locations gradually—facilitating the transition between distinct spatial maps without full reconfiguration. Seminal simulations showed that such dynamics support error correction in self-localization and explain observed field stability over short timescales alongside adaptive remapping in response to contextual changes. Contemporary computational analyses challenge traditional engram-based interpretations of hippocampal population coding, suggesting that many place cell phenomena arise from effective computations in sparse, random rather than structured memory traces. A 2025 study demonstrates that a randomly connected with sparsifying inhibition—termed DivSparse—replicates key features like sparsity, stability, and remapping without requiring pre-wired attractors or dedicated engram circuits. This implies that ensemble-level coding may emerge generically from sparsity and input statistics, questioning the necessity of experience-dependent synaptic specificity for spatial representations and highlighting the role of inhibitory tuning in universal place cell statistics.

References

  1. [1]
    [PDF] Spatial Cells in the Hippocampal Formation - Nobel Prize
    The phase of place cell firing is highly correlated with the position of the animal (C). After. O'Keefe and Recce (1993). had been removed (O'Keefe and Speakman ...
  2. [2]
    Place Cells, Grid Cells, and Memory - PMC - PubMed Central - NIH
    The most striking relationship was noted by O'Keefe and Dostrovsky, who found that hippocampal cells responded specifically to the current location of the ...<|control11|><|separator|>
  3. [3]
    [PDF] The Brain's Navigational Place and Grid Cell System - Nobel Prize
    The discoveries of place and grid cells by. John O'Keefe, May-Britt Moser and Edvard I. Moser present a paradigm shift in our understanding of how ensembles ...
  4. [4]
    The hippocampus as a spatial map. Preliminary evidence ... - PubMed
    The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res. 1971 Nov;34(1):171-5. doi: ...
  5. [5]
    The hippocampus as a spatial map. Preliminary evidence from unit ...
    The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Author links open overlay panelJ. O'Keefe, J. Dostrovsky.
  6. [6]
    [PDF] The Hippocampus as a Cognitive Map - Faculty
    John O'Keefe & Lynn Nadel (1978) The Hippocampus as a Cognitive Map ,. Oxford University Press. You may redistribute the file electronically providing you do ...
  7. [7]
    The 2014 Nobel Prize in Physiology or Medicine - Advanced ...
    John O'Keefe discovered place cells in the hippocampus that signal position and provide the brain with spatial memory capacity. May-Britt Moser and Edvard I ...Missing: challenges replication
  8. [8]
    [PDF] Placing hippocampal single-unit studies in a historical context
    However, the primary impetus for the theory was a finding reported by O'Keefe and Dostrovsky in 1971. The authors reported that the firing rates of a number of ...
  9. [9]
    The Nobel Prize in Physiology or Medicine 2014 - Press release
    Oct 6, 2014 · Other nerve cells were activated when the rat was at other places. O'Keefe concluded that these “place cells” formed a map of the room. More ...
  10. [10]
    Microstructure of a spatial map in the entorhinal cortex - Nature
    Jun 19, 2005 · Here we show that the dorsocaudal medial entorhinal cortex (dMEC) contains a directionally oriented, topographically organized neural map of the spatial ...
  11. [11]
    Spatial Firing of Hippocampal Place Cells in Blind Rats
    Mar 1, 1998 · The firing rate of place cells in blind rats was lower according to ... cell firing in the place field to the previous behavior of the rat.
  12. [12]
    The Hippocampal Rate Code: Anatomy, Physiology and Theory - PMC
    In contrast, MEC has very few silent cells and the active cells have a six-fold higher mean firing rate: around 2.5 Hz [32] (Figure 2G). The firing of all ...
  13. [13]
    Universal statistics of hippocampal place fields across species and ...
    Apr 2, 2025 · We present a model that explains irregular CA1 responses in large environments. The theory explains statistics of field sizes, arrangement, and shape ...Results · Parameter Variation Across... · Star Methods
  14. [14]
    What do grid cells contribute to place cell firing? - PMC - NIH
    It is commonly assumed that grid cell inputs generate hippocampal place fields, but recent empirical evidence brings this assumption into doubt.
  15. [15]
    None
    ### Summary of Place Cell Stability and Remapping
  16. [16]
  17. [17]
    LTD is involved in the formation and maintenance of rat ... - Nature
    Jan 4, 2021 · Therefore, the specific role of LTP and LTD in regulating place cell encoding dynamics and the subsequent consolidation of their stable place ...
  18. [18]
    Bidirectional synaptic plasticity rapidly modifies hippocampal ... - eLife
    Dec 9, 2021 · We found that this behavioral timescale synaptic plasticity (BTSP) can also reshape existing place fields via bidirectional synaptic weight changes.
  19. [19]
    Theta phase precession of grid and place cell firing in open ...
    Effects of firing and running speed on phase precession, in cells that show significant phase precession versus pdcd (place cells above and grid cells below).
  20. [20]
    Place cells on a maze encode routes rather than destinations - eLife
    Jun 10, 2016 · One way of answering this question is to study the brains of rats, because the basic plan of a rodent's brain is similar to that of other ...
  21. [21]
    Experience-dependent firing rate remapping generates directional ...
    (Rat 1 ran on the circular track twice a day, so the afternoon session of day 1 was considered session 2 and analyzed with the other rats' day 2, and the ...
  22. [22]
    Spatial View Cells in the Primate Hippocampus - Rolls - 1997
    In a sample of 352 cells recorded in the hippocampus and parahippocampal cortex, a population of 'spatial view' cells was found to respond when the monkey ...Missing: 1990s | Show results with:1990s
  23. [23]
  24. [24]
    Contribution of multiple sensory information to place field stability in ...
    In the present study, we assessed the effects of removing visual and/or olfactory cues on place field stability.Missing: stabilizing | Show results with:stabilizing
  25. [25]
  26. [26]
  27. [27]
    Hippocampal Spatial Representations Require Vestibular Input - PMC
    These results indicate that vestibular signals provide an important influence over the expression of hippocampal spatial representations.
  28. [28]
    Place Cells in Head-Fixed Mice Navigating a Floating Real-World ...
    Place cells have been readily recorded using electrophysiological techniques in freely moving mice and rats. However, additional insight into system function ...Missing: bidirectional unidirectional
  29. [29]
    Interactions Between Idiothetic Cues and External Landmarks in the ...
    The firing properties of place cells and head direction cells are controlled by an interaction between landmarks and idiothetic cues, just as an animal's ...
  30. [30]
    Dead reckoning (path integration) requires the hippocampal formation
    We present a series of studies that suggests that dead reckoning is an important component of spontaneous exploratory behavior and the learned spatial behavior ...
  31. [31]
    Dead reckoning (path integration) requires the hippocampal formation
    When dead reckoning (deduced reckoning or path integration), they integrate self-movement cues over time to locate a present position or to return to a starting ...
  32. [32]
    Spatial representations of place cells in darkness are supported by ...
    Contribution of multiple sensory information to place field stability in hippocampal place cells. ... Spatial olfactory learning contributes to place field ...
  33. [33]
    The contributions of position, direction, and velocity to single unit ...
    The place/direction specificity of CS cells was significantly higher in CA1 than in CA3 and CA3 CS cells exhibited a striking preference for the inward radial ...Missing: rate | Show results with:rate
  34. [34]
    Diverse calcium dynamics underlie place field formation in ... - eLife
    Sep 30, 2025 · In a novel environment, many CA1PCs are active already during the first traversal of their PFs, but a fraction of cells become place cells after ...
  35. [35]
    The mechanisms for pattern completion and pattern separation in ...
    The aim of this paper is to describe some of the different types of pattern separation and pattern completion in the hippocampal system, and the mechanisms ...
  36. [36]
    Pattern separation in the hippocampus - PMC - NIH
    Separation and completion are not synonymous with remapping and stability. Place cell remapping is typically defined as place cells having distinct firing ...
  37. [37]
    Place cells, spatial maps and the population code for memory
    In this review, we show how hippocampal place cells have been recently used as a model system to advance our understanding of how location and memory are ...
  38. [38]
    Mechanisms of experience-dependent place-cell referencing in ...
    Apr 1, 2025 · Together, these results suggest that experience-dependent adjustment of synaptic input shapes PC referencing to support a flexible cognitive map ...
  39. [39]
    Episodic memory: Neuronal codes for what, where, and when
    Jul 23, 2019 · For instance, sequences of place cells are compressed within theta cycles so that place cells coding passed or upcoming locations are active ...
  40. [40]
    Object-translocation induces event coding in the rat hippocampus
    May 24, 2025 · In this study, we aimed to distinguish the “where” and “what” components of local object memory by analyzing place cell activity across the ...
  41. [41]
    Internally generated cell assembly sequences in the rat hippocampus
    We found that reliably and continually changing cell assemblies in the rat hippocampus appeared not only during spatial navigation but also in the absence of ...
  42. [42]
    Integration and competition between space and time in ... - PubMed
    Nov 6, 2024 · The results strongly suggest a competitive and integrated representation of space-time by single hippocampal neurons, which may provide the ...
  43. [43]
    New information triggers prospective codes to adapt for flexible ...
    May 24, 2025 · Here we show that new information triggered increased hippocampal prospective representations of both possible goals.
  44. [44]
    Theta phase precession in hippocampal neuronal populations and ...
    Theta phase precession is when cell spike activity advances to earlier theta cycle phases. Temporal sequences of place fields are compressed within theta ...
  45. [45]
    Hippocampal place cell remapping occurs with memory storage of ...
    Jul 19, 2023 · We conclude that place cell remapping occurs in response to events that are remembered rather than merely perceived and forgotten.
  46. [46]
    Hippocampal cellular and network activity in freely moving ... - PubMed
    Here we report the first hippocampal recordings from echolocating bats, mammals phylogenetically distant from rodents, which showed place cells very similar to ...
  47. [47]
    [PDF] Spatial cognition in bats and rats: from sensory acquisition to ...
    Two recent studies showed that rat place fields were significantly smaller when visual landmarks were present than when they were absent171,172. In a different ...
  48. [48]
    Comparing Mouse and Rat Hippocampal Place Cell Activities and ...
    Sep 20, 2018 · We provide a quantitative comparison in place field properties, as well as theta sequences and replays, between rats and mice as they ran on the same novel ...Missing: diameter | Show results with:diameter
  49. [49]
    3D Hippocampal Place Field Dynamics in Free-Flying Echolocating ...
    Aug 22, 2018 · We present data from the free-flying laryngeal echolocating big brown bat, which shows 3-D place cells without continuous theta.Abstract · Introduction · Materials and Methods · Discussion
  50. [50]
    Neural Correlates of Spatial Navigation in Primate Hippocampus
    Nov 2, 2022 · Last, monkey “place fields” are often dispersed and not as sparse, and the peak firing rate is much lower than that in rodents. Therefore, place ...Neural Correlates Of Spatial... · Theta Phase Coding In... · Eye Movement Coding And Head...
  51. [51]
    Dynamic neural representations of memory and space during ...
    Oct 20, 2023 · These results demonstrate how human MTL oscillations can represent both memory and space in a temporally flexible manner during freely moving navigation.
  52. [52]
    Evaluating Place Cell Detection Methods in Rats and Humans
    Sep 3, 2025 · Each paper was reviewed for key methodological features including recording site, behavioral task, spatial tuning analysis, and classification ...
  53. [53]
    Human neural dynamics of real-world and imagined navigation
    Mar 10, 2025 · In navigational tasks featuring repetitive segments, such as ours, place cells and grid cells tend to form repetitive firing sequences that ...
  54. [54]
    Neural representations of space in the hippocampus of a food ...
    Jul 16, 2021 · Unlike place cells observed in mammals, hippocampal activity reported in non-mammals is neither confined in space nor stable over time (14–18).Missing: instability | Show results with:instability<|control11|><|separator|>
  55. [55]
    A population code for spatial representation in the zebrafish ... - Nature
    Aug 28, 2024 · In this study, using tracking microscopy to record brain-wide calcium activity in freely swimming larval zebrafish, we compute the spatial ...
  56. [56]
    Coupling of Sharp Wave Events between Zebrafish Hippocampal ...
    Apr 24, 2024 · Single-cell calcium imaging coupled to local field potential recordings revealed that ∼10% of active cells in the dorsal telencephalon ...
  57. [57]
    Are There Place Cells in the Avian Hippocampus? - PubMed
    Sep 4, 2017 · Research with homing pigeons has discovered hippocampal cells, including location cells, path cells, and pattern cells, that share some but not all properties ...Missing: hyperpallium | Show results with:hyperpallium
  58. [58]
    Visual Place Learning in Drosophila melanogaster - PubMed Central
    Place cells, grid cells, and the brain's spatial representation system. Annu ... Drosophila mushroom bodies are dispensable for visual, tactile, and motor ...
  59. [59]
    Spatial learning in feature-impoverished environments in Drosophila
    Dec 2, 2024 · Our findings demonstrate that Drosophila can dynamically adapt to environmental complexities when solving spatial learning tasks by creating and ...<|control11|><|separator|>
  60. [60]
    Finding a place and leaving a mark in memory formation - PMC
    Place memory formation in Drosophila​​ While, such cells within specific regions have not yet been identified in invertebrates, circuit analysis of spatial ...
  61. [61]
    Ethanol alters spatial processing of hippocampal place cells - PubMed
    This study describes a new mechanism by which ethanol alters brain function and may impair performance on tasks requiring spatial navigation.
  62. [62]
    Acute Effects of Ethanol on Hippocampal Spatial Representation ...
    Nov 5, 2020 · Acute alcohol exposure impairs hippocampus-dependent spatial memory. However, there is little evidence for the effects of ethanol on the spike ...
  63. [63]
    Hippocampal phase precession is preserved under ketamine, but ...
    Ketamine did not affect the ability of CA1 place cells to precess despite changes to place cell firing rates, local field potential properties and locomotor ...
  64. [64]
    NMDA receptors promote hippocampal sharp-wave ripples and the ...
    NMDA receptor antagonists ketamine and PCP have direct effects on the dopamine D(2) and serotonin 5-HT(2) receptors-implications for models of schizophrenia.Missing: precession | Show results with:precession
  65. [65]
    Effects of μ-opioid receptor modulation on the hippocampal network ...
    Key results: All three MOR agonists (1 nM-10 μM) significantly increased the amplitude of sharp waves and the occurrence of SWR sequences, but reduced the ...
  66. [66]
    Hippocampal Remapping after Partial Inactivation of the Medial ...
    Nov 4, 2015 · Partial inactivation of medial entorhinal cortex causes remapping in the hippocampus. Inactivation-induced remapping is instantaneous.
  67. [67]
    Acute Low Alcohol Disrupts Hippocampus-Striatum Neural Correlate ...
    In the other behavioral or Western blot tests, each rat was only received one treatment. Behavioral Apparatus and Pre-training. Rats were trained according to ...
  68. [68]
    Place cell firing correlates with memory deficits and amyloid plaque ...
    We have recorded place cells in the Tg2576 mouse model of AD, and we report that aged (16 mo) but not young (3 mo) transgenic mice show degraded neuronal ...
  69. [69]
    Hippocampal place cells exhibit impairments in spatial information ...
    Jun 16, 2023 · APPNL-G-F CA1 place cells exhibited deficits in both rate coding and temporal coding of spatial information indicating that amyloid β pathology, ...
  70. [70]
    Impaired speed encoding & grid cell periodicity in mouse tauopathy
    Nov 26, 2020 · Dementia-related tau pathology reduces speed encoding in the medial entorhinal cortex and is associated with reduced grid cell function, ...
  71. [71]
    Spatial memory deficits in Alzheimer's disease and their connection ...
    Place cell abnormalities have been reported in different mouse models of AD. rTg4510 mice (7–8 months) with advanced tau pathology and progressive ...
  72. [72]
    Brain Aging: Changes in the Nature of Information Coding by the ...
    Jul 1, 1997 · Advanced age in rats is associated with a decline in spatial memory capacities dependent on hippocampal processing.
  73. [73]
    The Effect of Aging on Experience-Dependent Plasticity of ...
    As the place fields expanded, the rate of change of firing with phase slowed accordingly, so that the net phase change remained constant. Thus changes in field ...
  74. [74]
    Entorhinal‐based path integration selectively predicts midlife risk of ...
    Feb 29, 2024 · Entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimer's disease (AD), associated with EC grid cell ...
  75. [75]
    Hippocampal Place Cell Sequences Are Impaired in a Rat Model of ...
    Apr 9, 2025 · To be included for further analysis, the peak firing rate in a place field had to be at least 1 Hz, and the minimum length of a place field had ...
  76. [76]
    Defective memory engram reactivation underlies impaired fear ...
    Nov 20, 2020 · Activity-dependent genetic labeling during behavioral learning shows Fragile-X syndrome model mice exhibit impaired hippocampal engram ...
  77. [77]
    Hippocampal Place Cell Firing Patterns Can Induce Long-Term ...
    Overlapping place cell pairs are required for the induction of synaptic plasticity. A corollary of the model by which LTP allows synapses between place cells to ...Missing: remapping | Show results with:remapping
  78. [78]
    Bidirectional Hebbian Plasticity at Hippocampal Mossy Fiber ...
    Dec 24, 2008 · We propose that MF LTP in LM interneurons preserves the sparsity of pyramidal cell activation, thus allowing CA3 to maintain its role in pattern separation.
  79. [79]
    A realistic computational model for the formation of a Place Cell
    Dec 8, 2023 · We used a morphologically and biophysically detailed computational model of a CA1 pyramidal neuron to show how, and under which conditions, it can turn into a ...
  80. [80]
    A Statistical Paradigm for Neural Spike Train Decoding Applied to ...
    Sep 15, 1998 · For animal 1 (2) the median decoding error based on 34 (33) place cells recorded during 10 min of foraging was 8.0 (7.7) cm.Missing: centimeters | Show results with:centimeters
  81. [81]
    Real-Time Position Reconstruction with Hippocampal Place Cells
    Real-time decoding: the position reconstruction algorithm uses the on-line sorted spikes and the firing rate vector as inputs to predict the position of the ...
  82. [82]
    Efficient neural decoding of self-location with a deep recurrent network
    Based on observation of place cell activity it is possible to accurately decode an animal's location. The precision of this decoding sets a lower bound for the ...<|control11|><|separator|>
  83. [83]
    Path Integration and Cognitive Mapping in a Continuous Attractor ...
    Aug 1, 1997 · A minimal synaptic architecture is proposed for how the brain might perform path integration by computing the next internal representation of self-location.