The input-output transformation of the hippocampal granule cells: from grid cells to place fields

Low excitatory innervation balances high intrinsic excitability of immature dentate neurons

Persistent neurogenesis in the dentate gyrus produces immature neurons with high intrinsic excitability and low levels of inhibition that are predicted to be more broadly responsive to afferent activity than mature neurons. Mounting evidence suggests that these immature neurons are necessary for generating distinct neural representations of similar contexts, but it is unclear how broadly responsive neurons help distinguish between similar patterns of afferent activity. Here we show that stimulation of the entorhinal cortex in mouse brain slices paradoxically generates spiking of mature neurons in the absence of immature neuron spiking. Immature neurons with high intrinsic excitability fail to spike due to insufficient excitatory drive that results from low innervation rather than silent synapses or low release probability. Our results suggest that low synaptic connectivity prevents immature neurons from responding broadly to cortical activity, potentially enabling excitable immature neurons to contribute to sparse and orthogonal dentate representations.

Immature dentate gyrus neurons are highly excitable and are thought to be more responsive to afferent activity than mature neurons. Here, the authors find stimulation of the entorhinal cortex paradoxically generates spiking in mature rather than immature neurons due to low synaptic connectivity of immature cells.

Computational Modeling of Adult Neurogenesis

The restriction of adult neurogenesis to only a handful of regions of the brain is suggestive of some shared requirement for this dramatic form of structural plasticity. However, a common driver across neurogenic regions has not yet been identified. Computational studies have been invaluable in providing insight into the functional role of new neurons; however, researchers have typically focused on specific scales ranging from abstract neural networks to specific neural systems, most commonly the dentate gyrus area of the hippocampus. These studies have yielded a number of diverse potential functions for new neurons, ranging from an impact on pattern separation to the incorporation of time into episodic memories to enabling the forgetting of old information. This review will summarize these past computational efforts and discuss whether these proposed theoretical functions can be unified into a common rationale for why neurogenesis is required in these unique neural circuits.

Ten Years of Grid Cells

The medial entorhinal cortex (MEC) creates a neural representation of space through a set of functionally dedicated cell types: grid cells, border cells, head direction cells, and speed cells. Grid cells, the most abundant functional cell type in the MEC, have hexagonally arranged firing fields that tile the surface of the environment. These cells were discovered only in 2005, but after 10 years of investigation, we are beginning to understand how they are organized in the MEC network, how their periodic firing fields might be generated, how they are shaped by properties of the environment, and how they interact with the rest of the MEC network. The aim of this review is to summarize what we know about grid cells and point out where our knowledge is still incomplete.

Neuromorphic VLSI realization of the hippocampal formation

The medial entorhinal cortex grid cells, aided by the subicular head direction cells, are thought to provide a matrix which is utilized by the hippocampal place cells for calculation of position of an animal during spatial navigation. The place cells are thought to function as an internal GPS for the brain and provide a spatiotemporal stamp on episodic memories. Several computational neuroscience models have been proposed to explain the place specific firing patterns of the cells of the hippocampal formation - including the GRIDSmap model for grid cells and Bayesian integration for place cells. In this work, we present design and measurement results from a first ever system of silicon circuits which successfully realize the function of the hippocampal formation of brain based on these models.

Target-selectivity of parvalbumin-positive interneurons in layer II of medial entorhinal cortex in normal and epileptic animals

The medial entorhinal cortex layer II (MEClayerII ) is a brain region critical for spatial navigation and memory, and it also demonstrates a number of changes in patients with, and animal models of, temporal lobe epilepsy (TLE). Prior studies of GABAergic microcircuitry in MEClayerII revealed that cholecystokinin-containing basket cells (CCKBCs) select their targets on the basis of the long-range projection pattern of the postsynaptic principal cell. Specifically, CCKBCs largely avoid reelin-containing principal cells that form the perforant path to the ipsilateral dentate gyrus and preferentially innervate non-perforant path forming calbindin-containing principal cells. We investigated whether parvalbumin containing basket cells (PVBCs), the other major perisomatic targeting GABAergic cell population, demonstrate similar postsynaptic target selectivity as well. In addition, we tested the hypothesis that the functional or anatomic arrangement of circuit selectivity is disrupted in MEClayerII in chronic TLE, using the repeated low-dose kainate model in rats. In control animals, we found that PVBCs innervated both principal cell populations, but also had significant selectivity for calbindin-containing principal cells in MEClayerII . However, the magnitude of this preference was smaller than for CCKBCs. In addition, axonal tracing and paired recordings showed that individual PVBCs were capable of contacting both calbindin and reelin-containing principal cells. In chronically epileptic animals, we found that the intrinsic properties of the two principal cell populations, the GABAergic perisomatic bouton numbers, and selectivity of the CCKBCs and PVBCs remained remarkably constant in MEClayerII . However, miniature IPSC frequency was decreased in epilepsy, and paired recordings revealed the presence of direct excitatory connections between principal cells in the MEClayerII in epilepsy, which is unusual in normal adult MEClayerII . Taken together, these findings advance our knowledge about the organization of perisomatic inhibition both in control and in epileptic animals. © 2015 Wiley Periodicals, Inc.

Grid Cells and Place Cells: An Integrated View of their Navigational and Memory Function

Much has been learned about the hippocampal/entorhinal system, but an overview of how its parts work in an integrated way is lacking. One question regards the function of entorhinal grid cells. We propose here that their fundamental function is to provide a coordinate system for producing mind-travel in the hippocampus, a process that accesses associations with upcoming positions. We further propose that mind-travel occurs during the second half of each theta cycle. By contrast, the first half of each theta cycle is devoted to computing current position using sensory information from the lateral entorhinal cortex (LEC) and path integration information from the medial entorhinal cortex (MEC). This model explains why MEC lesions can abolish hippocampal phase precession but not place fields.

An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X

Animals successfully forage within new environments by learning, simulating and adapting to their surroundings. The functions behind such goal-oriented behavior can be decomposed into 5 top-level objectives: 'how', 'why', 'what', 'where', 'when' (H4W). The paradigms of classical and operant conditioning describe some of the behavioral aspects found in foraging. However, it remains unclear how the organization of their underlying neural principles account for these complex behaviors. We address this problem from the perspective of the Distributed Adaptive Control theory of mind and brain (DAC) that interprets these two paradigms as expressing properties of core functional subsystems of a layered architecture. In particular, we propose DAC-X, a novel cognitive architecture that unifies the theoretical principles of DAC with biologically constrained computational models of several areas of the mammalian brain. DAC-X supports complex foraging strategies through the progressive acquisition, retention and expression of task-dependent information and associated shaping of action, from exploration to goal-oriented deliberation. We benchmark DAC-X using a robot-based hoarding task including the main perceptual and cognitive aspects of animal foraging. We show that efficient goal-oriented behavior results from the interaction of parallel learning mechanisms accounting for motor adaptation, spatial encoding and decision-making. Together, our results suggest that the H4W problem can be solved by DAC-X building on the insights from the study of classical and operant conditioning. Finally, we discuss the advantages and limitations of the proposed biologically constrained and embodied approach towards the study of cognition and the relation of DAC-X to other cognitive architectures.

A principle of economy predicts the functional architecture of grid cells

Grid cells in the brain respond when an animal occupies a periodic lattice of ‘grid fields’ during navigation. Grids are organized in modules with different periodicity. We propose that the grid system implements a hierarchical code for space that economizes the number of neurons required to encode location with a given resolution across a range equal to the largest period. This theory predicts that (i) grid fields should lie on a triangular lattice, (ii) grid scales should follow a geometric progression, (iii) the ratio between adjacent grid scales should be √e for idealized neurons, and lie between 1.4 and 1.7 for realistic neurons, (iv) the scale ratio should vary modestly within and between animals. These results explain the measured grid structure in rodents. We also predict optimal organization in one and three dimensions, the number of modules, and, with added assumptions, the ratio between grid periods and field widths.

DOI:http://dx.doi.org/10.7554/eLife.08362.001

In the 1930s, neuroscientists studying how rodents find their way through a maze proposed that the animals could construct an internal map of the maze inside their heads. The map was thought to enable the animals to navigate between familiar locations and also to identify shortcuts and alternative routes whenever familiar ones were blocked.

In the 1960s, recordings of electrical activity in the rat brain provided the first clues as to which nerve cells form this spatial map. In a region of the brain called the hippocampus, nerve cells called ‘place cells’ are active whenever the rat finds itself in a specific location. However, place cells alone are not able to support all types of navigation. Some spatial tasks also require cells in a region of the brain called the medial entorhinal cortex (MEC), which supplies most of the information that the hippocampus receives.

Cells in the MEC called ‘grid cells’ represent two-dimensional space as a repeating grid of triangles. A given grid cell is activated if the animal is located at a particular distance and angle away from the center of any of these triangles. The size of the triangles in these grids varies systematically throughout the MEC. Individual grid cells at one end of the structure encode space in finer detail than grid cells at the opposite end.

Wei et al. have now used mathematical modeling to explore how grid cells are organized. The model assumes that the brain seeks to encode space at whatever resolution an animal requires using as few nerve cells as possible. The model successfully reproduces several known features of grid cells, including the triangular shape of the grid, and the fact that the size of the triangles increases in steps of a specific size across the MEC.

In addition to providing a mathematical basis for the way that grid cells are organized in the brain, the model makes a number of testable predictions. These include predictions of the number of grid cells in the rat brain, as well as the pattern that grid cells adopt in three-dimensions: a question that is currently being studied in bats. Wei et al.'s findings suggest that the code used by the grid to represent space is an analog of a decimal number system—except that space is not subdivided by factors of 10 to form decimal ‘digits’, but by a quantity related to a famous constant in the field of mathematics called Euler's number.

DOI:http://dx.doi.org/10.7554/eLife.08362.002

In vivo evaluation of the dentate gate theory in epilepsy

The dentate gyrus is a region subject to intense study in epilepsy because of its posited role as a 'gate', acting to inhibit overexcitation in the hippocampal circuitry through its unique synaptic, cellular and network properties that result in relatively low excitability. Numerous changes predicted to produce dentate hyperexcitability are seen in epileptic patients and animal models. However, recent findings question whether changes are causative or reactive, as well as the pathophysiological relevance of the dentate in epilepsy. Critically, direct in vivo modulation of dentate 'gate' function during spontaneous seizure activity has not been explored. Therefore, using a mouse model of temporal lobe epilepsy with hippocampal sclerosis, a closed-loop system and selective optogenetic manipulation of granule cells during seizures, we directly tested the dentate 'gate' hypothesis in vivo. Consistent with the dentate gate theory, optogenetic gate restoration through granule cell hyperpolarization efficiently stopped spontaneous seizures. By contrast, optogenetic activation of granule cells exacerbated spontaneous seizures. Furthermore, activating granule cells in non-epileptic animals evoked acute seizures of increasing severity. These data indicate that the dentate gyrus is a critical node in the temporal lobe seizure network, and provide the first in vivo support for the dentate 'gate' hypothesis.

Memory storage fidelity in the hippocampal circuit: the role of subregions and input statistics

In the last decades a standard model regarding the function of the hippocampus in memory formation has been established and tested computationally. It has been argued that the CA3 region works as an auto-associative memory and that its recurrent fibers are the actual storing place of the memories. Furthermore, to work properly CA3 requires memory patterns that are mutually uncorrelated. It has been suggested that the dentate gyrus orthogonalizes the patterns before storage, a process known as pattern separation. In this study we review the model when random input patterns are presented for storage and investigate whether it is capable of storing patterns of more realistic entorhinal grid cell input. Surprisingly, we find that an auto-associative CA3 net is redundant for random inputs up to moderate noise levels and is only beneficial at high noise levels. When grid cell input is presented, auto-association is even harmful for memory performance at all levels. Furthermore, we find that Hebbian learning in the dentate gyrus does not support its function as a pattern separator. These findings challenge the standard framework and support an alternative view where the simpler EC-CA1-EC network is sufficient for memory storage.

Place cells, grid cells, and memory

The hippocampal system is critical for storage and retrieval of declarative memories, including memories for locations and events that take place at those locations. Spatial memories place high demands on capacity. Memories must be distinct to be recalled without interference and encoding must be fast. Recent studies have indicated that hippocampal networks allow for fast storage of large quantities of uncorrelated spatial information. The aim of the this article is to review and discuss some of this work, taking as a starting point the discovery of multiple functionally specialized cell types of the hippocampal-entorhinal circuit, such as place, grid, and border cells. We will show that grid cells provide the hippocampus with a metric, as well as a putative mechanism for decorrelation of representations, that the formation of environment-specific place maps depends on mechanisms for long-term plasticity in the hippocampus, and that long-term spatiotemporal memory storage may depend on offline consolidation processes related to sharp-wave ripple activity in the hippocampus. The multitude of representations generated through interactions between a variety of functionally specialized cell types in the entorhinal-hippocampal circuit may be at the heart of the mechanism for declarative memory formation.

Parvalbumin and neuropeptide Y expressing hippocampal GABA-ergic inhibitory interneuron numbers decline in a model of Gulf War illness

Cognitive dysfunction is amongst the most conspicuous symptoms in Gulf War illness (GWI). Combined exposure to the nerve gas antidote pyridostigmine bromide (PB), pesticides and stress during the Persian Gulf War-1 (PGW-1) are presumed to be among the major causes of GWI. Indeed, our recent studies in rat models have shown that exposure to GWI-related (GWIR) chemicals and mild stress for 4 weeks engenders cognitive impairments accompanied with several detrimental changes in the hippocampus. In this study, we tested whether reduced numbers of hippocampal gamma-amino butyric acid (GABA)-ergic interneurons are among the pathological changes induced by GWIR-chemicals and stress. Animals were exposed to low doses of GWIR-chemicals and mild stress for 4 weeks. Three months after this exposure, subpopulations of GABA-ergic interneurons expressing the calcium binding protein parvalbumin (PV), the neuropeptide Y (NPY) and somatostatin (SS) in the hippocampus were stereologically quantified. Animals exposed to GWIR-chemicals and stress for 4 weeks displayed reduced numbers of PV-expressing GABA-ergic interneurons in the dentate gyrus and NPY-expressing interneurons in the CA1 and CA3 subfields. However, no changes in SS+ interneuron population were observed in the hippocampus. Furthermore, GABA-ergic interneuron deficiency in these animals was associated with greatly diminished hippocampus neurogenesis. Because PV+ and NPY+ interneurons play roles in maintaining normal cognitive function and neurogenesis, and controlling the activity of excitatory neurons in the hippocampus, reduced numbers of these interneurons may be one of the major causes of cognitive dysfunction and reduced neurogenesis observed in GWI. Hence, strategies that improve inhibitory neurotransmission in the hippocampus may prove beneficial for reversing cognitive dysfunction in GWI.

Hippocampal remapping is constrained by sparseness rather than capacity

Grid cells in the medial entorhinal cortex encode space with firing fields that are arranged on the nodes of spatial hexagonal lattices. Potential candidates to read out the space information of this grid code and to combine it with other sensory cues are hippocampal place cells. In this paper, we investigate a population of grid cells providing feed-forward input to place cells. The capacity of the underlying synaptic transformation is determined by both spatial acuity and the number of different spatial environments that can be represented. The codes for different environments arise from phase shifts of the periodical entorhinal cortex patterns that induce a global remapping of hippocampal place fields, i.e., a new random assignment of place fields for each environment. If only a single environment is encoded, the grid code can be read out at high acuity with only few place cells. A surplus in place cells can be used to store a space code for more environments via remapping. The number of stored environments can be increased even more efficiently by stronger recurrent inhibition and by partitioning the place cell population such that learning affects only a small fraction of them in each environment. We find that the spatial decoding acuity is much more resilient to multiple remappings than the sparseness of the place code. Since the hippocampal place code is sparse, we thus conclude that the projection from grid cells to the place cells is not using its full capacity to transfer space information. Both populations may encode different aspects of space.

The mammalian brain represents space in the population of hippocampal place cells as well as in the population of medial entorhinal cortex grid cells. Since both populations are active at the same time, space information has to be synchronized between the two. Both brain areas are reciprocally connected, and it is unclear how the two codes influence each other. In this paper, we analyze a theoretical model of how a place code processes inputs from the grid cell population. The model shows that the sparseness of the place code poses a much stronger constraint than maximal information transfer. We thus conclude that the potentially high spatial acuity of the grid code cannot be efficiently conveyed to a sparse place cell population and thus propose that sparseness and spatial acuity are two independent objectives of the neuronal place representation.

Beyond the bolus: transgenic tools for investigating the neurophysiology of learning and memory

Understanding the neural mechanisms underlying learning and memory in the entorhinal-hippocampal circuit is a central challenge of systems neuroscience. For more than 40 years, electrophysiological recordings in awake, behaving animals have been used to relate the receptive fields of neurons in this circuit to learning and memory. However, the vast majority of such studies are purely observational, as electrical, surgical, and pharmacological circuit manipulations are both challenging and relatively coarse, being unable to distinguish between specific classes of neurons. Recent advances in molecular genetic tools can overcome many of these limitations, enabling unprecedented control over neural activity in behaving animals. Expression of pharmaco- or optogenetic transgenes in cell-type-specific "driver" lines provides unparalleled anatomical and cell-type specificity, especially when delivered by viral complementation. Pharmacogenetic transgenes are specially designed neurotransmitter receptors exclusively activated by otherwise inactive synthetic ligands and have kinetics similar to traditional pharmacology. Optogenetic transgenes use light to control the membrane potential, and thereby operate at the millisecond timescale. Thus, activation of pharmacogenetic transgenes in specific neuronal cell types while recording from other parts of the circuit allows investigation of the role of those neurons in the steady state, whereas optogenetic transgenes allow one to determine the immediate network response.

Modeling inheritance of phase precession in the hippocampal formation

Spatial information about the environment is encoded by the activity of place and grid cells in the hippocampal formation. As an animal traverses a cell's firing field, action potentials progressively shift to earlier phases of the theta oscillation (6-10 Hz). This "phase precession" is observed also in the prefrontal cortex and the ventral striatum, but mechanisms for its generation are unknown. However, once phase precession exists in one region, it might also propagate to downstream regions. Using a computational model, we analyze such inheritance of phase precession, for example, from the entorhinal cortex to CA1 and from CA3 to CA1. We find that distinctive subthreshold and suprathreshold features of the membrane potential of CA1 pyramidal cells (Harvey et al., 2009; Mizuseki et al., 2012; Royer et al., 2012) can be explained by inheritance and that excitatory input is essential. The model explains how inhibition modulates the slope and range of phase precession and provides two main testable predictions. First, theta-modulated inhibitory input to a CA1 pyramidal cell is not necessary for phase precession. Second, theta-modulated inhibitory input on its own generates membrane potential peaks that are in phase with peaks of the extracellular field. Furthermore, we suggest that the spatial distribution of field centers of a population of phase-precessing input cells determines, not only the place selectivity, but also the characteristics of phase precession of the targeted output cell. The inheritance model thus can explain why phase precession is observed throughout the hippocampal formation and other areas of the brain.

Interneurons. Fast-spiking, parvalbumin⁺ GABAergic interneurons: from cellular design to microcircuit function

The success story of fast-spiking, parvalbumin-positive (PV(+)) GABAergic interneurons (GABA, γ-aminobutyric acid) in the mammalian central nervous system is noteworthy. In 1995, the properties of these interneurons were completely unknown. Twenty years later, thanks to the massive use of subcellular patch-clamp techniques, simultaneous multiple-cell recording, optogenetics, in vivo measurements, and computational approaches, our knowledge about PV(+) interneurons became more extensive than for several types of pyramidal neurons. These findings have implications beyond the "small world" of basic research on GABAergic cells. For example, the results provide a first proof of principle that neuroscientists might be able to close the gaps between the molecular, cellular, network, and behavioral levels, representing one of the main challenges at the present time. Furthermore, the results may form the basis for PV(+) interneurons as therapeutic targets for brain disease in the future. However, much needs to be learned about the basic function of these interneurons before clinical neuroscientists will be able to use PV(+) interneurons for therapeutic purposes.

Grid cells and cortical representation

One of the grand challenges in neuroscience is to comprehend neural computation in the association cortices, the parts of the cortex that have shown the largest expansion and differentiation during mammalian evolution and that are thought to contribute profoundly to the emergence of advanced cognition in humans. In this Review, we use grid cells in the medial entorhinal cortex as a gateway to understand network computation at a stage of cortical processing in which firing patterns are shaped not primarily by incoming sensory signals but to a large extent by the intrinsic properties of the local circuit.

A signature of attractor dynamics in the CA3 region of the hippocampus

The notion of attractor networks is the leading hypothesis for how associative memories are stored and recalled. A defining anatomical feature of such networks is excitatory recurrent connections. These "attract" the firing pattern of the network to a stored pattern, even when the external input is incomplete (pattern completion). The CA3 region of the hippocampus has been postulated to be such an attractor network; however, the experimental evidence has been ambiguous, leading to the suggestion that CA3 is not an attractor network. In order to resolve this controversy and to better understand how CA3 functions, we simulated CA3 and its input structures. In our simulation, we could reproduce critical experimental results and establish the criteria for identifying attractor properties. Notably, under conditions in which there is continuous input, the output should be "attracted" to a stored pattern. However, contrary to previous expectations, as a pattern is gradually "morphed" from one stored pattern to another, a sharp transition between output patterns is not expected. The observed firing patterns of CA3 meet these criteria and can be quantitatively accounted for by our model. Notably, as morphing proceeds, the activity pattern in the dentate gyrus changes; in contrast, the activity pattern in the downstream CA3 network is attracted to a stored pattern and thus undergoes little change. We furthermore show that other aspects of the observed firing patterns can be explained by learning that occurs during behavioral testing. The CA3 thus displays both the learning and recall signatures of an attractor network. These observations, taken together with existing anatomical and behavioral evidence, make the strong case that CA3 constructs associative memories based on attractor dynamics.

Oscillatory dynamics and place field maps reflect hippocampal ensemble processing of sequence and place memory under NMDA receptor control

Place coding in the hippocampus requires flexible combination of sensory inputs (e.g., environmental and self-motion information) with memory of past events. We show that mouse CA1 hippocampal spatial representations may either be anchored to external landmarks (place memory) or reflect memorized sequences of cell assemblies depending on the behavioral strategy spontaneously selected. These computational modalities correspond to different CA1 dynamical states, as expressed by theta and low- and high-frequency gamma oscillations, when switching from place to sequence memory-based processing. These changes are consistent with a shift from entorhinal to CA3 input dominance on CA1. In mice with a deletion of forebrain NMDA receptors, the ability of place cells to maintain a map based on sequence memory is selectively impaired and oscillatory dynamics are correspondingly altered, suggesting that oscillations contribute to selecting behaviorally appropriate computations in the hippocampus and that NMDA receptors are crucial for this function.

Representation of geometric borders in the developing rat

Local space is represented by a number of functionally specific cell types, including place cells in the hippocampus and grid cells, head direction cells, and border cells in the medial entorhinal cortex (MEC). These cells form a functional map of external space already at the time when rat pups leave the nest for the first time in their life, at the age of 2.5 weeks. However, while place cells have adult-like firing fields from the outset, grid cells have irregular and variable fields until the fourth week, raising doubts about their contribution to place cell firing at young age. Recording in MEC of juvenile rats, we show that, unlike grid cells, border cells express adult-like firing fields from the first days of exposure to an open environment, at postnatal days 16-18. Thus, spatial signals from border cells may be sufficient to maintain spatially localized firing in juvenile hippocampal place cells.

Distinct determinants of sparse activation during granule cell maturation

Adult neurogenesis continually produces a small population of immature granule cells (GCs) within the dentate gyrus. The physiological properties of immature GCs distinguish them from the more numerous mature GCs and potentially enables distinct network functions. To test how the changing properties of developing GCs affect spiking behavior, we examined synaptic responses of mature and immature GCs in hippocampal slices from adult mice. Whereas synaptic inhibition restricted GC spiking at most stages of maturation, the relative influence of inhibition, excitatory synaptic drive, and intrinsic excitability shifted over the course of maturation. Mature GCs received profuse afferent innervation such that spiking was suppressed primarily by inhibition, whereas immature GC spiking was also limited by the strength of excitatory drive. Although the input resistance was a reliable indicator of maturation, it did not determine spiking probability at immature stages. Our results confirm the existence of a transient period during GC maturation when perforant path stimulation can generate a high probability of spiking, but also reveal that immature GC excitability is tempered by functional synaptic inhibition and reduced excitatory innervation, likely maintaining the sparse population activity observed in vivo.

What do grid cells contribute to place cell firing?

The unitary firing fields of hippocampal place cells are commonly assumed to be generated by input from entorhinal grid cell modules with differing spatial scales. Here, we review recent research that brings this assumption into doubt. Instead, we propose that place cell spatial firing patterns are determined by environmental sensory inputs, including those representing the distance and direction to environmental boundaries, while grid cells provide a complementary self-motion related input that contributes to maintaining place cell firing. In this view, grid and place cell firing patterns are not successive stages of a processing hierarchy, but complementary and interacting representations that work in combination to support the reliable coding of large-scale space.

Grid cells and neural coding in high-end cortices

An ultimate goal of neuroscience is to understand the mechanisms of mammalian intellectual functions, many of which are thought to depend extensively on the cerebral cortex. While this may have been considered a remote objective when Neuron was launched in 1988, neuroscience has now evolved to a stage where it is possible to decipher neural-circuit mechanisms in the deepest parts of the cortex, far away from sensory receptors and motoneurons. In this review, we show how studies of place cells in the hippocampus and grid cells in the entorhinal cortex may provide some of the first glimpses into these mechanisms. We shall review the events that led up to the discovery of grid cells and a functional circuit in the entorhinal cortex and highlight what we currently see as the big questions in this field--questions that, if resolved, will add to our understanding of cortical computation in a general sense.

Functional connectivity of the entorhinal-hippocampal space circuit

The mammalian space circuit is known to contain several functionally specialized cell types, such as place cells in the hippocampus and grid cells, head-direction cells and border cells in the medial entorhinal cortex (MEC). The interaction between the entorhinal and hippocampal spatial representations is poorly understood, however. We have developed an optogenetic strategy to identify functionally defined cell types in the MEC that project directly to the hippocampus. By expressing channelrhodopsin-2 (ChR2) selectively in the hippocampus-projecting subset of entorhinal projection neurons, we were able to use light-evoked discharge as an instrument to determine whether specific entorhinal cell groups--such as grid cells, border cells and head-direction cells--have direct hippocampal projections. Photoinduced firing was observed at fixed minimal latencies in all functional cell categories, with grid cells as the most abundant hippocampus-projecting spatial cell type. We discuss how photoexcitation experiments can be used to distinguish the subset of hippocampus-projecting entorhinal neurons from neurons that are activated indirectly through the network. The functional breadth of entorhinal input implied by this analysis opens up the potential for rich dynamic interactions between place cells in the hippocampus and different functional cell types in the entorhinal cortex (EC).

Architecture of spatial circuits in the hippocampal region

The hippocampal region contains several principal neuron types, some of which show distinct spatial firing patterns. The region is also known for its diversity in neural circuits and many have attempted to causally relate network architecture within and between these unique circuits to functional outcome. Still, much is unknown about the mechanisms or network properties by which the functionally specific spatial firing profiles of neurons are generated, let alone how they are integrated into a coherently functioning meta-network. In this review, we explore the architecture of local networks and address how they may interact within the context of an overarching space circuit, aiming to provide directions for future successful explorations.

Theta-gamma-modulated synaptic currents in hippocampal granule cells in vivo define a mechanism for network oscillations

Theta-gamma network oscillations are thought to represent key reference signals for information processing in neuronal ensembles, but the underlying synaptic mechanisms remain unclear. To address this question, we performed whole-cell (WC) patch-clamp recordings from mature hippocampal granule cells (GCs) in vivo in the dentate gyrus of anesthetized and awake rats. GCs in vivo fired action potentials at low frequency, consistent with sparse coding in the dentate gyrus. GCs were exposed to barrages of fast AMPAR-mediated excitatory postsynaptic currents (EPSCs), primarily relayed from the entorhinal cortex, and inhibitory postsynaptic currents (IPSCs), presumably generated by local interneurons. EPSCs exhibited coherence with the field potential predominantly in the theta frequency band, whereas IPSCs showed coherence primarily in the gamma range. Action potentials in GCs were phase locked to network oscillations. Thus, theta-gamma-modulated synaptic currents may provide a framework for sparse temporal coding of information in the dentate gyrus.

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Granule cells in vivo fire action potentials sparsely but often in bursts

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Granule cells are exposed to barrages of fast excitatory postsynaptic currents

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Granule cells receive theta-coherent excitation but gamma-coherent inhibition

Does the entorhinal cortex use the Fourier transform?

Some neurons in the entorhinal cortex (EC) fire bursts when the animal occupies locations organized in a hexagonal grid pattern in their spatial environment. Place cells have also been observed, firing bursts only when the animal occupies a particular region of the environment. Both of these types of cells exhibit theta-cycle modulation, firing bursts in the 4–12 Hz range. Grid cells fire bursts of action potentials that precess with respect to the theta cycle, a phenomenon dubbed “theta precession.” Various models have been proposed to explain these phenomena, and how they relate to navigation. Among the most promising are the oscillator interference models. The bank-of-oscillators model proposed by Welday et al. (2011) exhibits all these features. However, their simulations are based on theoretical oscillators, and not implemented entirely with spiking neurons. We extend their work in a number of ways. First, we place the oscillators in a frequency domain and reformulate the model in terms of Fourier theory. Second, this perspective suggests a division of labor for implementing spatial maps: position vs. map layout. The animal's position is encoded in the phases of the oscillators, while the spatial map shape is encoded implicitly in the weights of the connections between the oscillators and the read-out nodes. Third, it reveals that the oscillator phases all need to conform to a linear relationship across the frequency domain. Fourth, we implement a partial model of the EC using spiking leaky integrate-and-fire (LIF) neurons. Fifth, we devise new coupling mechanisms, enlightened by the global phase constraint, and show they are capable of keeping spiking neural oscillators in consistent formation. Our model demonstrates place cells, grid cells, and phase precession. The Fourier model also gives direction for future investigations, such as integrating sensory feedback to combat drift, or explaining why grid cells exist at all.

Regulation of action potential delays via voltage-gated potassium Kv1.1 channels in dentate granule cells during hippocampal epilepsy

Action potential (AP) responses of dentate gyrus granule (DG) cells have to be tightly regulated to maintain hippocampal function. However, which ion channels control the response delay of DG cells is not known. In some neuron types, spike latency is influenced by a dendrotoxin (DTX)-sensitive delay current (ID) mediated by unidentified combinations of voltage-gated K(+) (Kv) channels of the Kv1 family Kv1.1-6. In DG cells, the ID has not been characterized and its molecular basis is unknown. The response phenotype of mature DG cells is usually considered homogenous but intrinsic plasticity likely occurs in particular in conditions of hyperexcitability, for example during temporal lobe epilepsy (TLE). In this study, we examined response delays of DG cells and underlying ion channel molecules by employing a combination of gramicidin-perforated patch-clamp recordings in acute brain slices and single-cell reverse transcriptase quantitative polymerase chain reaction (SC RT-qPCR) experiments. An in vivo mouse model of TLE consisting of intrahippocampal kainate (KA) injection was used to examine epilepsy-related plasticity. Response delays of DG cells were DTX-sensitive and strongly increased in KA-injected hippocampi; Kv1.1 mRNA was elevated 10-fold, and the response delays correlated with Kv1.1 mRNA abundance on the single cell level. Other Kv1 subunits did not show overt changes in mRNA levels. Kv1.1 immunolabeling was enhanced in KA DG cells. The biophysical properties of ID and a delay heterogeneity within the DG cell population was characterized. Using organotypic hippocampal slice cultures (OHCs), where KA incubation also induced ID upregulation, the homeostatic reversibility and neuroprotective potential for DG cells were tested. In summary, the AP timing of DG cells is effectively controlled via scaling of Kv1.1 subunit transcription. With this antiepileptic mechanism, DG cells delay their responses during hyperexcitation.

Adult neurogenesis in the mammalian hippocampus: why the dentate gyrus?

In the adult mammalian brain, newly generated neurons are continuously incorporated into two networks: interneurons born in the subventricular zone migrate to the olfactory bulb, whereas the dentate gyrus (DG) of the hippocampus integrates locally born principal neurons. That the rest of the mammalian brain loses significant neurogenic capacity after the perinatal period suggests that unique aspects of the structure and function of DG and olfactory bulb circuits allow them to benefit from the adult generation of neurons. In this review, we consider the distinctive features of the DG that may account for it being able to profit from this singular form of neural plasticity. Approaches to the problem of neurogenesis are grouped as "bottom-up," where the phenotype of adult-born granule cells is contrasted to that of mature developmentally born granule cells, and "top-down," where the impact of altering the amount of neurogenesis on behavior is examined. We end by considering the primary implications of these two approaches and future directions.

Conflicts between local and global spatial frameworks dissociate neural representations of the lateral and medial entorhinal cortex

Manipulation of spatial reference frames is a common experimental tool to investigate the nature of hippocampal information coding and to investigate high-order processes, such as cognitive coordination. However, it is unknown how the hippocampus afferents represent the local and global reference frames of an environment. To address these issues, single units were recorded in freely moving rats with multi-tetrode arrays targeting the superficial layers of the lateral entorhinal cortex (LEC) and medial entorhinal cortex (MEC), the two primary cortical inputs to the hippocampus. Rats ran clockwise laps around a circular track partitioned into quadrants covered by different textures (the local reference frame). The track was centered in a circular environment with distinct landmarks on the walls (the global reference frame). Here we demonstrate a novel dissociation between MEC and LEC in that the global frame controlled the MEC representation and the local frame controlled the LEC representation when the reference frames were rotated in equal, but opposite, directions. Consideration of the functional anatomy of the hippocampal circuit and popular models of attractor dynamics in CA3 suggests a mechanistic explanation of previous data showing a dissociation between the CA3 and CA1 regions in their responses to this local-global conflict. Furthermore, these results are consistent with a model of the LEC providing the hippocampus with the external sensory content of an experience and the MEC providing the spatial context, which combine to form conjunctive codes in the hippocampus that form the basis of episodic memory.

Spatial scale and place field stability in a grid-to-place cell model of the dorsoventral axis of the hippocampus

The rodent hippocampus and entorhinal cortex contain spatially modulated cells that serve as the basis for spatial coding. Both medial entorhinal grid cells and hippocampal place cells have been shown to encode spatial information across multiple spatial scales that increase along the dorsoventral axis of these structures. Place cells near the dorsal pole possess small, stable, and spatially selective firing fields, while ventral cells have larger, less stable, and less spatially selective firing fields. One possible explanation for these dorsoventral changes in place field properties is that they arise as a result of similar dorsoventral differences in the properties of the grid cell inputs to place cells. Here, we test the alternative hypothesis that dorsoventral place field differences are due to higher amounts of nonspatial inputs to ventral hippocampal cells. We use a computational model of the entorhinal-hippocampal network to assess the relative contributions of grid scale and nonspatial inputs in determining place field size and stability. In addition, we assess the consequences of grid node firing rate heterogeneity on place field stability. Our results suggest that dorsoventral differences in place cell properties can be better explained by changes in the amount of nonspatial inputs, rather than by changes in the scale of grid cell inputs, and that grid node heterogeneity may have important functional consequences. The observed gradient in field size may reflect a shift from processing primarily spatial information in the dorsal hippocampus to processing more nonspatial, contextual, and emotional information near the ventral hippocampus.

Optogenetic dissection of entorhinal-hippocampal functional connectivity

We used a combined optogenetic-electrophysiological strategy to determine the functional identity of entorhinal cells with output to the place-cell population in the hippocampus. Channelrhodopsin-2 (ChR2) was expressed selectively in the hippocampus-targeting subset of entorhinal projection neurons by infusing retrogradely transportable ChR2-coding recombinant adeno-associated virus in the hippocampus. Virally transduced ChR2-expressing cells were identified in medial entorhinal cortex as cells that fired at fixed minimal latencies in response to local flashes of light. A large number of responsive cells were grid cells, but short-latency firing was also induced in border cells and head-direction cells, as well as cells with irregular or nonspatial firing correlates, which suggests that place fields may be generated by convergence of signals from a broad spectrum of entorhinal functional cell types.

Influence of local objects on hippocampal representations: Landmark vectors and memory

The hippocampus is thought to represent nonspatial information in the context of spatial information. An animal can derive both spatial information as well as nonspatial information from the objects (landmarks) it encounters as it moves around in an environment. In this article, correlates of both object-derived spatial as well as nonspatial information in the hippocampus of rats foraging in the presence of objects are demonstrated. A new form of CA1 place cells, called landmark-vector cells, that encode spatial locations as a vector relationship to local landmarks is described. Such landmark vector relationships can be dynamically encoded. Of the 26 CA1 neurons that developed new fields in the course of a day's recording sessions, in eight cases, the new fields were located at a similar distance and direction from a landmark as the initial field was located relative to a different landmark. In addition, object-location memory in the hippocampus is also described. When objects were removed from an environment or moved to new locations, a small number of neurons in CA1 and CA3 increased firing at the locations where the objects used to be. In some neurons, this increase occurred only in one location, indicating object + place conjunctive memory; in other neurons, the increase in firing was seen at multiple locations where an object used to be. Taken together, these results demonstrate that the spatially restricted firing of hippocampal neurons encode multiple types of information regarding the relationship between an animal's location and the location of objects in its environment.

Functional circuits of new neurons in the dentate gyrus

The hippocampus is crucial for memory formation. New neurons are added throughout life to the hippocampal dentate gyrus (DG), a brain area considered important for differential storage of similar experiences and contexts. To better understand the functional contribution of adult neurogenesis to pattern separation processes, we recently used a novel synapse specific trans-neuronal tracing approach to identify the (sub) cortical inputs to new dentate granule cells (GCs). It was observed that newly born neurons receive sequential innervation from structures important for memory function. Initially, septal-hippocampal cells provide input to new neurons, including transient innervation from mature GCs as well as direct feedback from area CA3 pyramidal neurons. After about 1 month perirhinal (PRH) and lateral entorhinal cortex (LEC), brain areas deemed relevant to integration of novel sensory and environmental information, become substantial input to new GCs. Here, we review the developmental time-course and proposed functional relevance of new neurons, within the context of their unique neural circuitry.

Dynamic functions of GABA signaling during granule cell maturation

The dentate gyrus is one of the few areas of the brain where new neurons are generated throughout life. Neural activity influences multiple stages of neurogenesis, thereby allowing experience to regulate the production of new neurons. It is now well established that GABA_A receptor-mediated signaling plays a pivotal role in mediating activity-dependent regulation of adult neurogenesis. GABA first acts as a trophic signal that depolarizes progenitors and early post mitotic granule cells, enabling network activity to control molecular cascades essential for proliferation, survival and growth. Following the development of glutamatergic synaptic inputs, GABA signaling switches from excitatory to inhibitory. Thereafter robust synaptic inhibition enforces low spiking probability of granule cells in response to cortical excitatory inputs and maintains the sparse activity patterns characteristic of this brain region. Here we review these dynamic functions of GABA across granule cell maturation, focusing on the potential role of specific interneuron circuits at progressive developmental stages. We further highlight questions that remain unanswered about GABA signaling in granule cell development and excitability.

The computational influence of neurogenesis in the processing of spatial information in the dentate gyrus

This study was designed to analyze the effect of hippocampal neurogenesis on the spatial maps of granule cells. Accordingly, we developed and improved an artificial neural network that was originally proposed by Aimone. Many biological processes were included in this revised model to improve the biological relevance of the results. We proposed a novel learning-testing protocol to analyze the activation of encoding place cells across contexts and over time in the dentate gyrus. We observed that, regardless of the presence of neurogenesis, the quantity and morphology of the place fields were represented in the same manner by granule cells. Additionally, we observed that neurogenesis was an effective mechanism for reducing the degree of rate remapping that occurred in the place fields of the granule cells.

The operation of pattern separation and pattern completion processes associated with different attributes or domains of memory

Pattern separation and pattern completion processes are central to how the brain processes information in an efficient manner. Research into these processes is escalating and deficient pattern separation is being implicated in a wide array of genetic disorders as well as in neurocognitive aging. Despite the quantity of research, there remains a controversy as to precisely which behavioral paradigms should be used to best tap into pattern separation and pattern completion processes, as well as to what constitute legitimate outcome measures reflecting impairments in pattern separation and pattern completion. This review will discuss a theory based on multiple memory systems that provides a framework upon which behavioral tasks can be designed and their results interpreted. Furthermore, this review will discuss the nature of pattern separation and pattern completion and extend these processes outside the hippocampus and across all domains of information processing. After these discussions, an optimal strategy for designing behavioral paradigms to evaluate pattern separation and pattern completion processes will be provided.

Hippocampal place fields emerge upon single-cell manipulation of excitability during behavior

The origin of the spatial receptive fields of hippocampal place cells has not been established. A hippocampal CA1 pyramidal cell receives thousands of synaptic inputs, mostly from other spatially tuned neurons; however, how the postsynaptic neuron's cellular properties determine the response to these inputs during behavior is unknown. We discovered that, contrary to expectations from basic models of place cells and neuronal integration, a small, spatially uniform depolarization of the spatially untuned somatic membrane potential of a silent cell leads to the sudden and reversible emergence of a spatially tuned subthreshold response and place-field spiking. Such gating of inputs by postsynaptic neuronal excitability reveals a cellular mechanism for receptive field origin and may be critical for the formation of hippocampal memory representations.

Selective reduction of AMPA currents onto hippocampal interneurons impairs network oscillatory activity

Reduction of excitatory currents onto GABAergic interneurons in the forebrain results in impaired spatial working memory and altered oscillatory network patterns in the hippocampus. Whether this phenotype is caused by an alteration in hippocampal interneurons is not known because most studies employed genetic manipulations affecting several brain regions. Here we performed viral injections in genetically modified mice to ablate the GluA4 subunit of the AMPA receptor in the hippocampus (GluA4^HC−/− mice), thereby selectively reducing AMPA receptor-mediated currents onto a subgroup of hippocampal interneurons expressing GluA4. This regionally selective manipulation led to a strong spatial working memory deficit while leaving reference memory unaffected. Ripples (125–250 Hz) in the CA1 region of GluA4^HC−/− mice had larger amplitude, slower frequency and reduced rate of occurrence. These changes were associated with an increased firing rate of pyramidal cells during ripples. The spatial selectivity of hippocampal pyramidal cells was comparable to that of controls in many respects when assessed during open field exploration and zigzag maze running. However, GluA4 ablation caused altered modulation of firing rate by theta oscillations in both interneurons and pyramidal cells. Moreover, the correlation between the theta firing phase of pyramidal cells and position was weaker in GluA4^HC−/− mice. These results establish the involvement of AMPA receptor-mediated currents onto hippocampal interneurons for ripples and theta oscillations, and highlight potential cellular and network alterations that could account for the altered working memory performance.

From A to Z: a potential role for grid cells in spatial navigation

Since their discovery, the strikingly regular and spatially stable firing of entorhinal grid cells has attracted the attention of experimentalists and theoreticians alike. The bulk of this work has focused either on the assumption that the principal role of grid cells is to support path integration or the extent to which their multiple firing locations can drive the sparse activity of hippocampal place cells. Here, we propose that grid cells are best understood as part of a network that combines self-motion and environmental cues to accurately track an animal’s location in space. Furthermore, that grid cells - more so than place cells - efficiently encode self-location in allocentric coordinates. Finally, that the regular structure of grid firing fields represents information about the relative structure of space and, as such, may be used to guide goal directed navigation.

Spatial firing correlates of physiologically distinct cell types of the rat dentate gyrus

The dentate gyrus (DG) occupies a key position in information flow through the hippocampus. Its principal cell, the granule cell, has spatially selective place fields. However, the behavioral correlates of cells located in the hilus of the rat dentate gyrus are unknown. We report here that cells below the granule layer show spatially selective firing that consists of multiple subfields. Other cells recorded from the DG had single place fields. Compared with cells with multiple fields, cells with single fields fired at lower rates during sleep were less bursty, and were more likely to be recorded simultaneously with large populations of neurons that were active during sleep and silent during behavior. We propose that cells with single fields are likely to be mature granule cells that use sparse encoding to potentially disambiguate input patterns. Furthermore, we hypothesize that cells with multiple fields might be cells of the hilus or newborn granule cells. These data are the first demonstration, based on physiological criteria, that single- and multiple-field cells constitute at least two distinct cell classes in the DG. Because of the heterogeneity of firing correlates and cell types in the DG, understanding which cell types correspond to which firing patterns, and how these correlates change with behavioral state and between different environments, are critical questions for testing long-standing computational theories that the DG performs a pattern separation function using a very sparse coding strategy.

A goal-directed spatial navigation model using forward trajectory planning based on grid cells

A goal-directed navigation model is proposed based on forward linear look-ahead probe of trajectories in a network of head direction cells, grid cells, place cells and prefrontal cortex (PFC) cells. The model allows selection of new goal-directed trajectories. In a novel environment, the virtual rat incrementally creates a map composed of place cells and PFC cells by random exploration. After exploration, the rat retrieves memory of the goal location, picks its next movement direction by forward linear look-ahead probe of trajectories in several candidate directions while stationary in one location, and finds the one activating PFC cells with the highest reward signal. Each probe direction involves activation of a static pattern of head direction cells to drive an interference model of grid cells to update their phases in a specific direction. The updating of grid cell spiking drives place cells along the probed look-ahead trajectory similar to the forward replay during waking seen in place cell recordings. Directions are probed until the look-ahead trajectory activates the reward signal and the corresponding direction is used to guide goal-finding behavior. We report simulation results in several mazes with and without barriers. Navigation with barriers requires a PFC map topology based on the temporal vicinity of visited place cells and a reward signal diffusion process. The interaction of the forward linear look-ahead trajectory probes with the reward diffusion allows discovery of never-before experienced shortcuts towards a goal location.

Framing spatial cognition: neural representations of proximal and distal frames of reference and their roles in navigation

The most common behavioral test of hippocampus-dependent, spatial learning and memory is the Morris water task, and the most commonly studied behavioral correlate of hippocampal neurons is the spatial specificity of place cells. Despite decades of intensive research, it is not completely understood how animals solve the water task and how place cells generate their spatially specific firing fields. Based on early work, it has become the accepted wisdom in the general neuroscience community that distal spatial cues are the primary sources of information used by animals to solve the water task (and similar spatial tasks) and by place cells to generate their spatial specificity. More recent research, along with earlier studies that were overshadowed by the emphasis on distal cues, put this common view into question by demonstrating primary influences of local cues and local boundaries on spatial behavior and place-cell firing. This paper first reviews the historical underpinnings of the "standard" view from a behavioral perspective, and then reviews newer results demonstrating that an animal's behavior in such spatial tasks is more strongly controlled by a local-apparatus frame of reference than by distal landmarks. The paper then reviews similar findings from the literature on the neurophysiological correlates of place cells and other spatially correlated cells from related brain areas. A model is proposed by which distal cues primarily set the orientation of the animal's internal spatial coordinate system, via the head direction cell system, whereas local cues and apparatus boundaries primarily set the translation and scale of that coordinate system.

Place cells, grid cells, attractors, and remapping

Place and grid cells are thought to use a mixture of external sensory information and internal attractor dynamics to organize their activity. Attractor dynamics may explain both why neurons react coherently following sufficiently large changes to the environment (discrete attractors) and how firing patterns move smoothly from one representation to the next as an animal moves through space (continuous attractors). However, some features of place cell behavior, such as the sometimes independent responsiveness of place cells to environmental change (called “remapping”), seem hard to reconcile with attractor dynamics. This paper suggests that the explanation may be found in an anatomical separation of the two attractor systems coupled with a dynamic contextual modulation of the connection matrix between the two systems, with new learning being back-propagated into the matrix. Such a scheme could explain how place cells sometimes behave coherently and sometimes independently.