Choice of method of place cell classification determines the population of cells identified.

Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Here we tested four methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method); the stability of cells' activity over repeated traversals of an environment (Stability method); a combination of these parameters with the size of the place field (Combination method); and the spatial information held by the cells (Information method). The methods performed differently from each other on both model and real data. In real datasets, vastly different numbers of place cells were identified using the four methods, with little overlap between the populations identified as place cells. Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. Ultimately, we recommend the Peak method be used in future studies to identify place cell populations, as this method is robust to moderate variations in place field within a session, and makes no inherent assumptions about the spatial information in place fields, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties.

Hippocampal place cells encode global location but not connectivity in a complex space.

Flexible navigation relies on a cognitive map of space, thought to be implemented by hippocampal place cells: neurons that exhibit location-specific firing. In connected environments, optimal navigation requires keeping track of one's location and of the available connections between subspaces. We examined whether the dorsal CA1 place cells of rats encode environmental connectivity in four geometrically identical boxes arranged in a square. Rats moved between boxes by pushing saloon-type doors that could be locked in one or both directions. Although rats demonstrated knowledge of environmental connectivity, their place cells did not respond to connectivity changes, nor did they represent doorways differently from other locations. Place cells coded location in a global reference frame, with a different map for each box and minimal repetitive fields despite the repetitive geometry. These results suggest that CA1 place cells provide a spatial map that does not explicitly include connectivity.

The Tolman-Eichenbaum Machine: Unifying Space and Relational Memory through Generalization in the Hippocampal Formation.

The hippocampal-entorhinal system is important for spatial and relational memory tasks. We formally link these domains, provide a mechanistic understanding of the hippocampal role in generalization, and offer unifying principles underlying many entorhinal and hippocampal cell types. We propose medial entorhinal cells form a basis describing structural knowledge, and hippocampal cells link this basis with sensory representations. Adopting these principles, we introduce the Tolman-Eichenbaum machine (TEM). After learning, TEM entorhinal cells display diverse properties resembling apparently bespoke spatial responses, such as grid, band, border, and object-vector cells. TEM hippocampal cells include place and landmark cells that remap between environments. Crucially, TEM also aligns with empirically recorded representations in complex non-spatial tasks. TEM also generates predictions that hippocampal remapping is not random as previously believed; rather, structural knowledge is preserved across environments. We confirm this structural transfer over remapping in simultaneously recorded place and grid cells.

Targeted Activation of Hippocampal Place Cells Drives Memory-Guided Spatial Behavior.

The hippocampus is crucial for spatial navigation and episodic memory formation. Hippocampal place cells exhibit spatially selective activity within an environment and have been proposed to form the neural basis of a cognitive map of space that supports these mnemonic functions. However, the direct influence of place cell activity on spatial navigation behavior has not yet been demonstrated. Using an 'all-optical' combination of simultaneous two-photon calcium imaging and two-photon optogenetics, we identified and selectively activated place cells that encoded behaviorally relevant locations in a virtual reality environment. Targeted stimulation of a small number of place cells was sufficient to bias the behavior of animals during a spatial memory task, providing causal evidence that hippocampal place cells actively support spatial navigation and memory.

Robust emergence of sharply tuned place-cell responses in hippocampal neurons with structural and biophysical heterogeneities.

Hippocampal pyramidal neurons sustain propagation of fast electrical signals and are electrotonically non-compact structures exhibiting cell-to-cell variability in their complex dendritic arborization. In this study, we demonstrate that sharp place-field tuning and several somatodendritic functional maps concomitantly emerge despite the presence of geometrical heterogeneities in these neurons. We establish this employing an unbiased stochastic search strategy involving thousands of models that spanned several morphologies and distinct profiles of dispersed synaptic localization and channel expression. Mechanistically, employing virtual knockout models (VKMs), we explored the impact of bidirectional modulation in dendritic spike prevalence on place-field tuning sharpness. Consistent with the prior literature, we found that across all morphologies, virtual knockout of either dendritic fast sodium channels or N-methyl-D-aspartate receptors led to a reduction in dendritic spike prevalence, whereas A-type potassium channel knockouts resulted in a non-specific increase in dendritic spike prevalence. However, place-field tuning sharpness was critically impaired in all three sets of VKMs, demonstrating that sharpness in feature tuning is maintained by an intricate balance between mechanisms that promote and those that prevent dendritic spike initiation. From the functional standpoint of the emergence of sharp feature tuning and intrinsic functional maps, within this framework, geometric variability was compensated by a combination of synaptic democracy, the ability of randomly dispersed synapses to yield sharp tuning through dendritic spike initiation, and ion-channel degeneracy. Our results suggest electrotonically non-compact neurons to be endowed with several degrees of freedom, encompassing channel expression, synaptic localization and morphological microstructure, in achieving sharp feature encoding and excitability homeostasis.

Neural Dynamics Indicate Parallel Integration of Environmental and Self-Motion Information by Place and Grid Cells.

Place cells and grid cells in the hippocampal formation are thought to integrate sensory and self-motion information into a representation of estimated spatial location, but the precise mechanism is unknown. We simulated a parallel attractor system in which place cells form an attractor network driven by environmental inputs and grid cells form an attractor network performing path integration driven by self-motion, with inter-connections between them allowing both types of input to influence firing in both ensembles. We show that such a system is needed to explain the spatial patterns and temporal dynamics of place cell firing when rats run on a linear track in which the familiar correspondence between environmental and self-motion inputs is changed. In contrast, the alternative architecture of a single recurrent network of place cells (performing path integration and receiving environmental inputs) cannot reproduce the place cell firing dynamics. These results support the hypothesis that grid and place cells provide two different but complementary attractor representations (based on self-motion and environmental sensory inputs, respectively). Our results also indicate the specific neural mechanism and main predictors of hippocampal map realignment and make predictions for future studies.

Hippocampal functional organization: A microstructure of the place cell network encoding space.

A clue to hippocampal function has been the discovery of place cells, leading to the 'spatial map' theory. Although the firing attributes of place cells are well documented, little is known about the organization of the spatial map. Unit recording studies, thus far, have reported a low coherence between neighboring cells and geometric space, leading to the prevalent view that the spatial map is not topographically organized. However, the number of simultaneously recorded units is severely limited, rendering construction of the spatial map nearly impossible. To visualize the functional organization of place cells, we used the activity-dependent immediate-early gene Zif268 in combination with behavioral, pharmacological and electrophysiological methods, in mice and rats exploring an environment. Here, we show that in animals confined to a small part of a maze, principal cells in the CA1/CA3 subfields of the dorsal hippocampus immunoreactive (IR) for Zif268 adhere to a 'cluster-type' organization. Unit recordings confirmed that the Zif268 IR clusters correspond to active place cells, while blockade of NMDAR (which alters place fields) disrupted the Zif268 IR clusters. Contrary to the prevalent view that the spatial map consists of a non-topographic neural network, our results provide evidence for a 'cluster-type' functional organization of hippocampal neurons encoding for space.

Differential influences of environment and self-motion on place and grid cell firing.

Place and grid cells in the hippocampal formation provide foundational representations of environmental location, and potentially of locations within conceptual spaces. Some accounts predict that environmental sensory information and self-motion are encoded in complementary representations, while other models suggest that both features combine to produce a single coherent representation. Here, we use virtual reality to dissociate visual environmental from physical motion inputs, while recording place and grid cells in mice navigating virtual open arenas. Place cell firing patterns predominantly reflect visual inputs, while grid cell activity reflects a greater influence of physical motion. Thus, even when recorded simultaneously, place and grid cell firing patterns differentially reflect environmental information (or 'states') and physical self-motion (or 'transitions'), and need not be mutually coherent.

Recalibration of path integration in hippocampal place cells.

Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain1. To detect the animal's location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks2,3 and measuring the distance and direction that the animal has travelled from previously occupied locations4-7. The latter mechanism-known as path integration-requires a finely tuned gain factor that relates the animal's self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates8,9. Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant9-14, but behavioural evidence in humans suggests that the gain is modifiable15. Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system4,8,16-19, but also rapidly fine-tune the integration computation itself.

Spatial cell firing during virtual navigation of open arenas by head-restrained mice.

We present a mouse virtual reality (VR) system which restrains head-movements to horizontal rotations, compatible with multi-photon imaging. This system allows expression of the spatial navigation and neuronal firing patterns characteristic of real open arenas (R). Comparing VR to R: place and grid, but not head-direction, cell firing had broader spatial tuning; place, but not grid, cell firing was more directional; theta frequency increased less with running speed, whereas increases in firing rates with running speed and place and grid cells' theta phase precession were similar. These results suggest that the omni-directional place cell firing in R may require local-cues unavailable in VR, and that the scale of grid and place cell firing patterns, and theta frequency, reflect translational motion inferred from both virtual (visual and proprioceptive) and real (vestibular translation and extra-maze) cues. By contrast, firing rates and theta phase precession appear to reflect visual and proprioceptive cues alone.

Implantation of Chronic Silicon Probes and Recording of Hippocampal Place Cells in an Enriched Treadmill Apparatus.

An important requisite for understanding brain function is the identification of behavior and cell activity correlates. Silicon probes are advanced electrodes for large-scale electrophysiological recording of neuronal activity, but the procedures for their chronic implantation are still underdeveloped. The activity of hippocampal place cells is known to correlate with an animal's position in the environment, but the underlying mechanisms are still unclear. To investigate place cells, here we describe a set of techniques which range from the fabrication of devices for chronic silicon probe implants to the monitoring of place field activity in a cue-enriched treadmill apparatus. A micro-drive and a hat are built by fitting and fastening together 3D-printed plastic parts. A silicon probe is mounted on the micro-drive, cleaned, and coated with dye. A first surgery is performed to fix the hat on the skull of a mouse. Small landmarks are fabricated and attached to the belt of a treadmill. The mouse is trained to run head-fixed on the treadmill. A second surgery is performed to implant the silicon probe in the hippocampus, following which broadband electrophysiological signals are recorded. Finally, the silicon probe is recovered and cleaned for reuse. The analysis of place cell activity in the treadmill reveals a diversity of place field mechanisms, outlining the benefit of the approach.

Exposure to complex environments results in more sparse representations of space in the hippocampus.

The neural circuitry mediating sensory and motor representations is adaptively tuned by an animal's interaction with its environment. Similarly, higher order representations such as spatial memories can be modified by exposure to a complex environment (CE), but in this case the changes in brain circuitry that mediate the effect are less well understood. Here, we show that prolonged CE exposure was associated with increased selectivity of CA1 "place cells" to a particular recording arena compared to a social control (SC) group. Furthermore, fewer CA1 and DG neurons in the CE group expressed high levels of Arc protein, a marker of recent activation, following brief exposure to a completely novel environment. The reduced Arc expression was not attributable to overall changes in cell density or number. These data indicate that one effect of CE exposure is to modify high-level spatial representations in the brain by increasing the sparsity of population coding within networks of neurons. Greater sparsity could result in a more efficient and compact coding system that might alter behavioural performance on spatial tasks. The results from a behavioural experiment were consistent with this hypothesis, as CE-treated animals habituated more rapidly to a novel environment despite showing equivalent initial responding.

Hippocampal Place Cells Couple to Three Different Gamma Oscillations during Place Field Traversal.

Three distinct gamma oscillations, generated in different CA1 layers, occur at different phases of concurrent theta oscillation. In parallel, firing of place cells displays phase advancement over successive cycles of theta oscillations while an animal passes through the place field. Is the theta-phase-precessing output of place cells shaped by distinct gamma oscillations along different theta phases during place field traversal? We simultaneously recorded firing of place cells and three layer-specific gamma oscillations using current-source-density analysis of multi-site field potential measurements in mice. We show that spike timing of place cells can tune to all three gamma oscillations, but phase coupling to the mid-frequency gamma oscillation conveyed from the entorhinal cortex was restricted to leaving a place field. A subset of place cells coupled to two different gamma oscillations even during single-place field traversals. Thus, an individual CA1 place cell can combine and relay information from multiple gamma networks while the animal crosses the place field.

[From Grid Cells to Place Cells:A Gauss Distribution Activation Function Model].

It has been found that in biological studies,the simple linear superposition mathematical model cannot be used to express the feature mapping relationship from multiple activated grid cells' grid fields to a single place cell's place field output in the hippocampus of the cerebral cortex of rodents.To solve this problem,people introduced the Gauss distribution activation function into the area.We in this paper use the localization properties of the function to deal with the linear superposition output of grid cells' input and the connection weights between grid cells and place cells,which filters out the low activation rate place fields.We then obtained a single place cell field which is consistent with biological studies.Compared to the existing competitive learning algorithm place cell model,independent component analysis method place cell model,Bayesian positon reconstruction method place cell model,our experimental results showed that the model on the neurophysiological basis can not only express the feature mapping relationship between multiple activated grid cells grid fields and a single place cell's place field output in the hippocampus of the cerebral cortex of rodents,but also make the algorithm simpler,the required grid cells input less and the accuracy rate of the output of a single place field higher.