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Hippocampal CA1 neurons generate single spikes and stereotyped bursts of spikes. However, it is unclear how individual neurons dynamically switch between these output modes and whether these two spiking outputs relay distinct information. We performed extracellular recordings in spatially navigating rats and cellular voltage imaging and optogenetics in awake mice. We found that spike bursts are preferentially linked to cellular and network theta rhythms (3-12 Hz) and encode an animal's position via theta phase precession, particularly as animals are entering a place field. In contrast, single spikes exhibit additional coupling to gamma rhythms (30-100 Hz), particularly as animals leave a place field. Biophysical modeling suggests that intracellular properties alone are sufficient to explain the observed input frequency-dependent spike coding. Thus, hippocampal neurons regulate the generation of bursts and single spikes according to frequency-specific network and intracellular dynamics, suggesting that these spiking modes perform distinct computations to support spatial behavior., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

This paper reviews the recent experimental finding that neurons in behaving rodents show egocentric coding of the environment in a number of structures associated with the hippocampus. Many animals generating behavior on the basis of sensory input must deal with the transformation of coordinates from the egocentric position of sensory input relative to the animal, into an allocentric framework concerning the position of multiple goals and objects relative to each other in the environment. Neurons in retrosplenial cortex show egocentric coding of the position of boundaries in relation to an animal. These neuronal responses are discussed in relation to existing models of the transformation from egocentric to allocentric coordinates using gain fields and a new model proposing transformations of phase coding that differ from current models. The same type of transformations could allow hierarchical representations of complex scenes. The responses in rodents are also discussed in comparison to work on coordinate transformations in humans and non-human primates., (© 2023 Wiley Periodicals LLC.)

Extensive computational modeling has focused on the hippocampal formation and related cortical structures. This introduction describes the topics addressed by individual articles in part two of this special issue of the journal Hippocampus on the topic of computational models of the hippocampus and related structures., (© 2020 Wiley Periodicals LLC.)

Interval timing, which operates on timescales of seconds to minutes, is distributed across multiple brain regions and may use distinct circuit mechanisms as compared to millisecond timing and circadian rhythms. However, its study has proven difficult, as timing on this scale is deeply entangled with other behaviors. Several circuit and cellular mechanisms could generate sequential or ramping activity patterns that carry timing information. Here we propose that a productive approach is to draw parallels between interval timing and spatial navigation, where direct analogies can be made between the variables of interest and the mathematical operations necessitated. Along with designing experiments that isolate or disambiguate timing behavior from other variables, new techniques will facilitate studies that directly address the neural mechanisms that are responsible for interval timing.

We reveal how implementing the homogeneous, multi-scale mapping frameworks observed in the mammalian brain's mapping systems radically improves the performance of a range of current robotic localization techniques. Roboticists have developed a range of predominantly single- or dual-scale heterogeneous mapping approaches (typically locally metric and globally topological) that starkly contrast with neural encoding of space in mammalian brains: a multi-scale map underpinned by spatially responsive cells like the grid cells found in the rodent entorhinal cortex. Yet the full benefits of a homogeneous multi-scale mapping framework remain unknown in both robotics and biology: in robotics because of the focus on single- or two-scale systems and limits in the scalability and open-field nature of current test environments and benchmark datasets; in biology because of technical limitations when recording from rodents during movement over large areas. New global spatial databases with visual information varying over several orders of magnitude in scale enable us to investigate this question for the first time in real-world environments. In particular, we investigate and answer the following questions: why have multi-scale representations, how many scales should there be, what should the size ratio between consecutive scales be and how does the absolute scale size affect performance? We answer these questions by developing and evaluating a homogeneous, multi-scale mapping framework mimicking aspects of the rodent multi-scale map, but using current robotic place recognition techniques at each scale. Results in large-scale real-world environments demonstrate multi-faceted and significant benefits for mapping and localization performance and identify the key factors that determine performance.

To provide a substrate for remembering where in space events have occurred, place cells must reliably encode the same positions across long timescales. However, in many cases, place cells exhibit instability by randomly reorganizing their place fields between experiences, challenging this premise. Recent evidence suggests that, in some cases, instability could also arise from coherent rotations of place fields, as well as from random reorganization. To investigate this possibility, we performed in vivo calcium imaging in dorsal hippocampal region CA1 of freely moving mice while they explored two arenas with different geometry and visual cues across 8 days. The two arenas were rotated randomly between sessions and then connected, allowing us to probe how cue rotations, the integration of new information about the environment, and the passage of time concurrently influenced the spatial coherence of place fields. We found that spatially coherent rotations of place-field maps in the same arena predominated, persisting up to 6 days later, and that they frequently rotated in a manner that did not match that of the arena rotation. Furthermore, place-field maps were flexible, as mice frequently employed a similar, coherent configuration of place fields to represent each arena despite their differing geometry and eventual connection. These results highlight the ability of the hippocampus to retain consistent relationships between cells across long timescales and suggest that, in many cases, apparent instability might result from a coherent rotation of place fields., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The ability to update position and orientation to reach a goal is crucial to spatial navigation and individuals vary considerably in this ability. The current structural MRI study used voxel-based morphometry (VBM) analysis to relate individual differences in human brain morphology to performance in an active navigation task that relied on updating position and orientation in a landmark-free environment. Goal-directed navigation took place from either a first person perspective, similar to a person walking through the landmark-free environment, or Survey perspective, a bird's eye view. Critically, the first person perspective required a transformation of spatial information from an allocentric into an egocentric reference frame for goal-directed navigation. Significant structural volume correlations in the hippocampus, entorhinal cortex, and thalamus were related to first person navigational accuracy. Our results support the theory that hippocampus, entorhinal cortex, and thalamus are key structures for updating position and orientation during ground-level navigation. Furthermore, the results suggest that morphological differences in these regions underlie individual navigational abilities, providing an important link between animal models of navigation and the variability in human navigation., (Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.)

Animals must perform spatial navigation for a range of different behaviors, including selection of trajectories toward goal locations and foraging for food sources. To serve this function, a number of different brain regions play a role in coding different dimensions of sensory input important for spatial behavior, including the entorhinal cortex, the retrosplenial cortex, the hippocampus, and the medial septum. This article will review data concerning the coding of the spatial aspects of animal behavior, including location of the animal within an environment, the speed of movement, the trajectory of movement, the direction of the head in the environment, and the position of barriers and objects both relative to the animal's head direction (egocentric) and relative to the layout of the environment (allocentric). The mechanisms for coding these important spatial representations are not yet fully understood but could involve mechanisms including integration of self-motion information or coding of location based on the angle of sensory features in the environment. We will review available data and theories about the mechanisms for coding of spatial representations. The computation of different aspects of spatial representation from available sensory input requires complex cortical processing mechanisms for transformation from egocentric to allocentric coordinates that will only be understood through a combination of neurophysiological studies and computational modeling.

Humans differ in their individual navigational abilities. These individual differences may exist in part because successful navigation relies on several disparate abilities, which rely on different brain structures. One such navigational capability is path integration, the updating of position and orientation, in which navigators track distances, directions, and locations in space during movement. Although structural differences related to landmark-based navigation have been examined, gray matter volume related to path integration ability has not yet been tested. Here, we examined individual differences in two path integration paradigms: (1) a location tracking task and (2) a task tracking translational and rotational self-motion. Using voxel-based morphometry, we related differences in performance in these path integration tasks to variation in brain morphology in 26 healthy young adults. Performance in the location tracking task positively correlated with individual differences in gray matter volume in three areas critical for path integration: the hippocampus, the retrosplenial cortex, and the medial prefrontal cortex. These regions are consistent with the path integration system known from computational and animal models and provide novel evidence that morphological variability in retrosplenial and medial prefrontal cortices underlies individual differences in human path integration ability. The results for tracking rotational self-motion-but not translation or location-demonstrated that cerebellum gray matter volume correlated with individual performance. Our findings also suggest that these three aspects of path integration are largely independent. Together, the results of this study provide a link between individual abilities and the functional correlates, computational models, and animal models of path integration., Competing Interests: Authors report no conflict of interest.

Path integration, the constant updating of the navigator's knowledge of position and orientation during movement, requires both visuospatial knowledge and memory. This study aimed to develop a systems-level understanding of human path integration by examining the basic building blocks of path integration in humans. To achieve this goal, we used functional imaging to examine the neural mechanisms that support the tracking and memory of translational and rotational components of human path integration. Critically, and in contrast to previous studies, we examined movement in translation and rotation tasks with no defined end-point or goal. Navigators accumulated translational and rotational information during virtual self-motion. Activity in hippocampus, retrosplenial cortex (RSC), and parahippocampal cortex (PHC) increased during both translation and rotation encoding, suggesting that these regions track self-motion information during path integration. These results address current questions regarding distance coding in the human brain. By implementing a modified delayed match to sample paradigm, we also examined the encoding and maintenance of path integration signals in working memory. Hippocampus, PHC, and RSC were recruited during successful encoding and maintenance of path integration information, with RSC selective for tasks that required processing heading rotation changes. These data indicate distinct working memory mechanisms for translation and rotation, which are essential for updating neural representations of current location. The results provide evidence that hippocampus, PHC, and RSC flexibly track task-relevant translation and rotation signals for path integration and could form the hub of a more distributed network supporting spatial navigation. Hum Brain Mapp 37:3636-3655, 2016. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Firing fields of grid cells in medial entorhinal cortex show compression or expansion after manipulations of the location of environmental barriers. This compression or expansion could be selective for individual grid cell modules with particular properties of spatial scaling. We present a model for differences in the response of modules to barrier location that arise from different mechanisms for the influence of visual features on the computation of location that drives grid cell firing patterns. These differences could arise from differences in the position of visual features within the visual field. When location was computed from the movement of visual features on the ground plane (optic flow) in the ventral visual field, this resulted in grid cell spatial firing that was not sensitive to barrier location in modules modeled with small spacing between grid cell firing fields. In contrast, when location was computed from static visual features on walls of barriers, i.e. in the more dorsal visual field, this resulted in grid cell spatial firing that compressed or expanded based on the barrier locations in modules modeled with large spacing between grid cell firing fields. This indicates that different grid cell modules might have differential properties for computing location based on visual cues, or the spatial radius of sensitivity to visual cues might differ between modules.

The spatial firing pattern of entorhinal grid cells may be important for navigation. Many different computational models of grid cell firing use path integration based on movement direction and the associated movement speed to drive grid cells. However, the response of neurons to movement direction has rarely been tested, in contrast to multiple studies showing responses of neurons to head direction. Here, we analyzed the difference between head direction and movement direction during rat movement and analyzed cells recorded from entorhinal cortex for their tuning to movement direction. During foraging behavior, movement direction differs significantly from head direction. The analysis of neuron responses shows that only 5 out of 758 medial entorhinal cells show significant coding for both movement direction and head direction when evaluating periods of rat behavior with speeds above 10 cm/s and ±30° angular difference between movement and head direction. None of the cells coded movement direction alone. In contrast, 21 cells in this population coded only head direction during behavioral epochs with these constraints, indicating much stronger coding of head direction in this population. This suggests that the movement direction signal required by most grid cell models may arise from other brain structures than the medial entorhinal cortex. This article is part of a Special Issue entitled SI: Brain and Memory., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Recent computational models suggest that visual input from optic flow provides information about egocentric (navigator-centered) motion and influences firing patterns in spatially tuned cells during navigation. Computationally, self-motion cues can be extracted from optic flow during navigation. Despite the importance of optic flow to navigation, a functional link between brain regions sensitive to optic flow and brain regions important for navigation has not been established in either humans or animals. Here, we used a beta-series correlation methodology coupled with two fMRI tasks to establish this functional link during goal-directed navigation in humans. Functionally defined optic flow sensitive cortical areas V3A, V6, and hMT+ were used as seed regions. fMRI data was collected during a navigation task in which participants updated position and orientation based on self-motion cues to successfully navigate to an encoded goal location. The results demonstrate that goal-directed navigation requiring updating of position and orientation in the first person perspective involves a cooperative interaction between optic flow sensitive regions V3A, V6, and hMT+ and the hippocampus, retrosplenial cortex, posterior parietal cortex, and medial prefrontal cortex. These functional connections suggest a dynamic interaction between these systems to support goal-directed navigation., (Copyright © 2015 Elsevier Inc. All rights reserved.)

We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model's flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat's point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond., (Copyright © 2014 Elsevier Inc. All rights reserved.)

When navigating our world we often first plan or retrieve an ideal route to our goal, avoiding alternative paths that lead to other destinations. The medial temporal lobe (MTL) has been implicated in processing contextual information, sequence memory, and uniquely retrieving routes that overlap or "cross paths." However, the identity of subregions of the hippocampus and neighboring cortex that support these functions in humans remains unclear. The present study used high-resolution functional magnetic resonance imaging (hr-fMRI) in humans to test whether the CA3/DG hippocampal subfield and parahippocampal cortex are important for processing spatial context and route retrieval, and whether the CA1 subfield facilitates prospective planning of mazes that must be distinguished from alternative overlapping routes. During hr-fMRI scanning, participants navigated virtual mazes that were well-learned from prior training while also learning new mazes. Some routes learned during scanning shared hallways with those learned during pre-scan training, requiring participants to select between alternative paths. Critically, each maze began with a distinct spatial contextual Cue period. Our analysis targeted activity from the Cue period, during which participants identified the current navigational episode, facilitating retrieval of upcoming route components and distinguishing mazes that overlap. Results demonstrated that multiple MTL regions were predominantly active for the contextual Cue period of the task, with specific regions of CA3/DG, parahippocampal cortex, and perirhinal cortex being consistently recruited across trials for Cue periods of both novel and familiar mazes. During early trials of the task, both CA3/DG and CA1 were more active for overlapping than non-overlapping Cue periods. Trial-by-trial Cue period responses in CA1 tracked subsequent overlapping maze performance across runs. Together, our findings provide novel insight into the contributions of MTL subfields to processing spatial context and route retrieval, and support a prominent role for CA1 in distinguishing overlapping episodes during navigational "look-ahead" periods., (© 2014 Wiley Periodicals, Inc.)

Recent computational models suggest that visual input from optic flow provides information about egocentric (navigator-centered) motion and influences firing patterns in spatially tuned cells during navigation. Computationally, self-motion cues can be extracted from optic flow during navigation. Despite the importance of optic flow to navigation, a functional link between brain regions sensitive to optic flow and brain regions important for navigation has not been established in either humans or animals. Here, we used a beta-series correlation methodology coupled with two fMRI tasks to establish this functional link during goal-directed navigation in humans. Functionally defined optic flow sensitive cortical areas V3A, V6, and hMT+ were used as seed regions. fMRI data was collected during a navigation task in which participants updated position and orientation based on self-motion cues to successfully navigate to an encoded goal location. The results demonstrate that goal-directed navigation requiring updating of position and orientation in the first person perspective involves a cooperative interaction between optic flow sensitive regions V3A, V6, and hMT+ and the hippocampus, retrosplenial cortex, posterior parietal cortex, and medial prefrontal cortex. These functional connections suggest a dynamic interaction between these systems to support goal-directed navigation.

Extensive computational modeling has focused on the hippocampal formation and associated cortical structures. This overview describes some of the factors that have motivated the strong focus on these structures, including major experimental findings and their impact on computational models. This overview provides a framework for describing the topics addressed by individual articles in this special issue of the journal Hippocampus. [ABSTRACT FROM AUTHOR]

This article presents a model using cellular resonance and rebound properties to model grid cells in medial entorhinal cortex. The model simulates the intrinsic resonance properties of single layer II stellate cells with different frequencies due to the hyperpolarization activated cation current (h current). The stellate cells generate rebound spikes after a delay interval that differs for neurons with different resonance frequency. Stellate cells drive inhibitory interneurons to cause rebound from inhibition in an alternate set of stellate cells that drive interneurons to activate the first set of cells. This allows maintenance of activity with cycle skipping of the spiking of cells that matches recent physiological data on theta cycle skipping. The rebound spiking interacts with subthreshold oscillatory input to stellate cells or interneurons regulated by medial septal input and defined relative to the spatial location coded by neurons. The timing of rebound determines whether the network maintains the activity for the same location or shifts to phases of activity representing a different location. Simulations show that spatial firing patterns similar to grid cells can be generated with a range of different resonance frequencies, indicating how grid cells could be generated with low frequencies present in bats and in mice with knockout of the HCN1 subunit of the h current. [ABSTRACT FROM AUTHOR]

Action potential timing is thought to play a critical role in neural representation. For example, theta phase precession is a robust phenomenon exhibited by spatial cells of the rat entorhinal-hippocampal circuit. In phase precession, the time a neuron fires relative to the phase of theta rhythm (6-10 Hz) oscillations in the local field potential reduces uncertainty about the position of the animal. This relationship between neural firing and behavior has made precession an important constraint for hypothetical mechanisms of temporal coding. However, challenges exist in identifying what regulates the spike timing of these cells. We have developed novel analytical techniques for mapping between behavior and neural firing that provide sufficient sensitivity to examine features of grid cell phase coding in open environments. Here, we show robust, omnidirectional phase precession by entorhinal grid cells in openfield enclosures. We present evidence that full phase precession persists regardless of how close the animal comes to the center of a firing field. Many conjunctive grid cells, previously thought to be phase locked, also exhibited phase coding. However, we were unable to detect directional- or field-specific phase coding predicted by some variants of models. Finally, we present data that suggest bursting of layer II grid cells contributes to the bimodality of phase precession. We discuss implications of these observations for models of temporal coding and propose the utility of these techniques in other domains where behavior is aligned to neural spiking. [ABSTRACT FROM AUTHOR]

The resonance properties of individual neurons in entorhinal cortex (EC) may contribute to their functional properties in awake, behaving rats. Models propose that entorhinal grid cells could arise from shifts in the intrinsic frequency of neurons caused by changes in membrane potential owing to depolarizing input from neurons coding velocity. To test for potential changes in intrinsic frequency, we measured the resonance properties of neurons at different membrane potentials in neurons in medial and lateral EC. In medial entorhinal neurons, the resonant frequency of individual neurons decreased in a linear manner as the membrane potential was depolarized between −70 and −55 mV. At more hyperpolarized membrane potentials, cells asymptotically approached a maximum resonance frequency. Consistent with the previous studies, near resting potential, the cells of the medial EC possessed a decreasing gradient of resonance frequency along the dorsal to ventral axis, and cells of the lateral EC lacked resonant properties, regardless of membrane potential or position along the medial to lateral axis within lateral EC. Application of 10 μM ZD7288, the H-channel blocker, abolished all resonant properties in MEC cells, and resulted in physiological properties very similar to lateral EC cells. These results on resonant properties show a clear change in frequency response with depolarization that could contribute to the generation of grid cell firing properties in the medial EC. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The entorhinal cortex (EC) receives prominent cholinergic innervation from the medial septum and the vertical limb of the diagonal band of Broca (MSDB). To understand how cholinergic neurotransmission can modulate behavior, research has been directed toward identification of the specific cellular mechanisms in EC that can be modulated through cholinergic activity. This review focuses on intrinsic cellular properties of neurons in EC that may underlie functions such as working memory, spatial processing, and episodic memory. In particular, the study of stellate cells (SCs) in medial entorhinal has resulted in discovery of correlations between physiological properties of these neurons and properties of the unique spatial representation that is demonstrated through unit recordings of neurons in medial entorhinal cortex (mEC) from awake-behaving animals. A separate line of investigation has demonstrated persistent firing behavior among neurons in EC that is enhanced by cholinergic activity and could underlie working memory. There is also evidence that acetylcholine plays a role in modulation of synaptic transmission that could also enhance mnemonic function in EC. Finally, the local circuits of EC demonstrate a variety of interneuron physiology, which is also subject to cholinergic modulation. Together these effects alter the dynamics of EC to underlie the functional role of acetylcholine in memory. [ABSTRACT FROM AUTHOR]

Acetylcholine plays an important role in cognitive function, as shown by pharmacological manipulations that impact working memory, attention, episodic memory, and spatial memory function. Acetylcholine also shows striking modulatory influences on the cellular physiology of hippocampal and cortical neurons. Modeling of neural circuits provides a framework for understanding how the cognitive functions may arise from the influence of acetylcholine on neural and network dynamics. We review the influences of cholinergic manipulations on behavioral performance in working memory, attention, episodic memory, and spatial memory tasks, the physiological effects of acetylcholine on neural and circuit dynamics, and the computational models that provide insight into the functional relationships between the physiology and behavior. Specifically, we discuss the important role of acetylcholine in governing mechanisms of active maintenance in working memory tasks and in regulating network dynamics important for effective processing of stimuli in attention and episodic memory tasks. We also propose that theta rhythm plays a crucial role as an intermediary between the physiological influences of acetylcholine and behavior in episodic and spatial memory tasks. We conclude with a synthesis of the existing modeling work and highlight future directions that are likely to be rewarding given the existing state of the literature for both empiricists and modelers. [ABSTRACT FROM AUTHOR]

Different models have been able to account for different features of the data on grid cell firing properties, including the relationship of grid cells to cellular properties and network oscillations. This paper describes a model that combines elements of two major classes of models of grid cells: models using interactions of oscillations and models using attractor dynamics. This model includes a population of units with oscillatory input representing input from the medial septum. These units are termed heading angle cells because their connectivity depends upon heading angle in the environment as well as the spatial phase coded by the cell. These cells project to a population of grid cells. The sum of the heading angle input results in standing waves of circularly symmetric input to the grid cell population. Feedback from the grid cell population increases the activity of subsets of the heading angle cells, resulting in the network settling into activity patterns that resemble the patterns of firing fields in a population of grid cells. The properties of heading angle cells firing as conjunctive grid-by-head-direction cells can shift the grid cell firing according to movement velocity. The pattern of interaction of oscillations requires use of separate populations that fire on alternate cycles of the net theta rhythmic input to grid cells. [ABSTRACT FROM AUTHOR]

Abstract: We propose a mechanism to explain both retrospective and prospective recall activity found in experimental data from hippocampal regions CA3 and CA1. Our model of temporal context dependent episodic memory replicates reverse recall in CA1, as recently recorded and published [Foster, D., & Wilson, M. (2006). Reverse replay of behavioural sequences in hippocampal place cells during the awake state. Nature, 440, 680–683], as well as the prospective and retrospective activity recorded in region CA3 during spatial tasks [Johnson, A., & Redish, A. (2006). Neural ensembles in ca3 transiently encode paths forward of the animal at a decision point: a possible mechanism for the consideration of alternatives. In 2006 neuroscience meeting planner. Atlanta, GA: Society for Neuroscience. (Program no. 574.2)]. We suppose that CA3 encodes episodic memory of both forward and reversed sequences of perforant path spikes representing place input. Using a persistent firing buffer mechanism in layer II of entorhinal cortex, simulated episodic learning involves dentate gyrus, layer III of entorhinal cortex, and hippocampal regions CA3 and CA1. Associations are formed between buffered episodic cues, unique temporal context specific representations in dentate gyrus, and episodic memory in the CA3 recurrent network. [Copyright &y& Elsevier]

Behavioral data suggest that cholinergic modulation may play a role in certain aspects of spatial memory, and neurophysiological data demonstrate neurons that fire in response to spatial dimensions, including grid cells and place cells that respond on the basis of location and running speed. These neurons show firing responses that depend upon the visual configuration of the environment, due to coding in visually-responsive regions of the neocortex. This review focuses on the physiological effects of acetylcholine that may influence the sensory coding of spatial dimensions relevant to behavior. In particular, the local circuit effects of acetylcholine within the cortex regulate the influence of sensory input relative to internal memory representations via presynaptic inhibition of excitatory and inhibitory synaptic transmission, and the modulation of intrinsic currents in cortical excitatory and inhibitory neurons. In addition, circuit effects of acetylcholine regulate the dynamics of cortical circuits including oscillations at theta and gamma frequencies. These effects of acetylcholine on local circuits and network dynamics could underlie the role of acetylcholine in coding of spatial information for the performance of spatial memory tasks. [ABSTRACT FROM AUTHOR]

[Display omitted] • Immediate-early-gene labeling strategy revealed spatial navigation ensembles in DG. • Sub-ensembles encode separate maze routes within a larger task context. • Ensemble reactivation does not correlate with behavioral variables. The dentate gyrus (DG) of hippocampus is hypothesized to act as a pattern separator that distinguishes between similar input patterns during memory formation and retrieval. Sparse ensembles of DG cells associated with learning and memory, i.e. engrams, have been labeled and manipulated to recall novel context memories. Functional studies of DG cell activity have demonstrated the spatial specificity and stability of DG cells during navigation. To reconcile how the DG contributes to separating global context as well as individual navigational routes, we trained mice to perform a delayed-non-match-to-position (DNMP) T-maze task and labeled DG neurons during performance of this task on a novel T-maze. The following day, mice navigated a second environment: the same T-maze, the same T-maze with one route permanently blocked but still visible, or a novel open field. We found that the degree of engram reactivation across days differed based on the traversal of maze routes, such that mice traversing only one arm had higher ensemble overlap than chance but less overlap than mice running the full two-route task. Mice experiencing the open field had similar ensemble sizes to the other groups but only chance-level ensemble reactivation. Ensemble overlap differences could not be explained by behavioral variability across groups, nor did behavioral metrics correlate to degree of ensemble reactivation. Together, these results support the hypothesis that DG contributes to spatial navigation memory and that partially non-overlapping ensembles encode different routes within the context of an environment. [ABSTRACT FROM AUTHOR]

We investigated the importance of hippocampal theta oscillations and the significance of phase differences of theta modulation in the cortical regions that are involved in goal-directed spatial navigation. Our models used representations of entorhinal cortex layer III (ECIII), hippocampus and prefrontal cortex (PFC) to guide movements of a virtual rat in a virtual environment. The model encoded representations of the environment through long-term potentiation of excitatory recurrent connections between sequentially spiking place cells in ECIII and CA3. This encoding required buffering of place cell activity, which was achieved by a short-term memory (STM) in EC that was regulated by theta modulation and allowed synchronized reactivation with encoding phases in ECIII and CA3. Inhibition at a specific theta phase deactivated the oldest item in the buffer when new input was presented to a full STM buffer. A 180° phase difference separated retrieval and encoding in ECIII and CA3, which enabled us to simulate data on theta phase precession of place cells. Retrieval of known paths was elicited in ECIII by input at the retrieval phase from PFC working memory for goal location, requiring strict theta phase relationships with PFC. Known locations adjacent to the virtual rat were retrieved in CA3. Together, input from ECIII and CA3 activated predictive spiking in cells in CA1 for the next desired place on a shortest path to a goal. Consistent with data, place cell activity in CA1 and CA3 showed smaller place fields than in ECIII. [Copyright &y& Elsevier]