Alternating predictive and short-term memory modes of entorhinal grid cells

Predictive grid coding in the medial entorhinal cortex

The entorhinal cortex represents allocentric spatial geometry and egocentric speed and heading information required for spatial navigation. However, it remains unclear whether it contributes to the prediction of an animal's future location. We discovered grid cells in the medial entorhinal cortex (MEC) that have grid fields representing future locations during goal-directed behavior. These predictive grid cells represented prospective spatial information by shifting their grid fields against the direction of travel. Predictive grid cells discharged at the trough phases of the hippocampal CA1 theta oscillation and, together with other types of grid cells, organized sequences of the trajectory from the current to future positions across each theta cycle. Our results suggest that the MEC provides a predictive map that supports forward planning in spatial navigation.

Simultaneous representation of multiple time horizons by entorhinal grid cells and CA1 place cells

Grid cells and place cells represent the spatiotemporal continuum of an animal's past, present, and future locations. However, their spatiotemporal relationship is unclear. Here, we co-record grid and place cells in freely foraging rats. We show that average time shifts in grid cells tend to be prospective and are proportional to their spatial scale, providing a nearly instantaneous readout of a spectrum of progressively increasing time horizons ranging hundreds of milliseconds. Average time shifts of place cells are generally larger compared to grid cells and also increase with place field sizes. Moreover, time horizons display nonlinear modulation by the animal's trajectories in relation to the local boundaries and locomotion cues. Finally, long and short time horizons occur at different parts of the theta cycle, which may facilitate their readout. Together, these findings suggest that population activity of grid and place cells may represent local trajectories essential for goal-directed navigation and planning.

Theta and gamma hippocampal-neocortical oscillations during the episodic-like memory test: Impairment in epileptogenic rats

Cortical oscillations in different frequency bands have been shown to be intimately involved in exploration of environment and cognition. Here, the local field potentials in the hippocampus, the medial prefrontal cortex (mPFC), and the medial entorhinal cortex (mEC) were recorded simultaneously in rats during the execution of the episodic-like memory task. The power of theta (~4-10 Hz), slow gamma (~25-50 Hz), and fast gamma oscillations (~55-100 Hz) was analyzed in all structures examined. Particular attention was paid to the theta coherence between three mentioned structures. The modulation of the power of gamma rhythms by the phase of theta cycle during the execution of the episodic-like memory test by rats was also closely studied. Healthy rats and rats one month after kainate-induced status epilepticus (SE) were examined. Paroxysmal activity in the hippocampus (high amplitude interictal spikes), excessive excitability of animals, and the death of hippocampal and dentate granular cells in rats with kainate-evoked SE were observed, which indicated the development of seizure focus in the hippocampus (epileptogenesis). One month after SE, the rats exhibited a specific impairment of episodic memory for the what-where-when triad: unlike healthy rats, epileptogenic SE animals did not identify the objects during the test. This impairment was associated with the changes in the characteristics of theta and gamma rhythms and specific violation of theta coherence and theta/gamma coupling in these structures in comparison with the healthy animals. We believe that these disturbances in the cortical areas play a role in episodic memory dysfunction in kainate-treated animals. These findings can shed light on the mechanisms of cognitive deficit during epileptogenesis.

Distance-tuned neurons drive specialized path integration calculations in medial entorhinal cortex

During navigation, animals estimate their position using path integration and landmarks, engaging many brain areas. Whether these areas follow specialized or universal cue integration principles remains incompletely understood. We combine electrophysiology with virtual reality to quantify cue integration across thousands of neurons in three navigation-relevant areas: primary visual cortex (V1), retrosplenial cortex (RSC), and medial entorhinal cortex (MEC). Compared with V1 and RSC, path integration influences position estimates more in MEC, and conflicts between path integration and landmarks trigger remapping more readily. Whereas MEC codes position prospectively, V1 codes position retrospectively, and RSC is intermediate between the two. Lowered visual contrast increases the influence of path integration on position estimates only in MEC. These properties are most pronounced in a population of MEC neurons, overlapping with grid cells, tuned to distance run in darkness. These results demonstrate the specialized role that path integration plays in MEC compared with other navigation-relevant cortical areas.

Riding the slow wave: Exploring the role of entrained low-frequency oscillations in memory formation

Neural oscillations are proposed to support a variety of behaviors, including long-term memory, yet their functional significance remains an active area of research. Here, we explore a potential functional role of low-frequency cortical oscillations in episodic memory formation. Recent theories suggest that low-frequency oscillations orchestrate rhythmic attentional sampling of the environment by dynamically modulating neural excitability across time. When these oscillations entrain to low-frequency rhythms present in the environment, such as speech or music, the brain can build temporal predictions about the onset of relevant events so that these events can be more efficiently processed. Building upon this literature, we propose that entrained low-frequency oscillations may similarly influence the temporal dynamics of episodic memory by rhythmically modulating encoding across time (mnemonic sampling). Central to this proposal is the phenomenon of cross-frequency phase-amplitude coupling, whereby the amplitudes of faster (higher frequency) rhythms, such as gamma oscillations, couple to the phase of slower (lower-frequency) rhythms entrained to environmental stimuli. By imposing temporal structure on higher-frequency oscillatory activity previously linked to memory formation, entrained low-frequency oscillations could dynamically orchestrate memory formation and optimize encoding at specific moments in time. We discuss prior experimental and theoretical work relevant to this proposal.

An uncertainty principle for neural coding: Conjugate representations of position and velocity are mapped onto firing rates and co-firing rates of neural spike trains

The hippocampal system contains neural populations that encode an animal's position and velocity as it navigates through space. Here, we show that such populations can embed two codes within their spike trains: a firing rate code (R) conveyed by within‐cell spike intervals, and a co‐firing rate code (R˙) conveyed by between‐cell spike intervals. These two codes behave as conjugates of one another, obeying an analog of the uncertainty principle from physics: information conveyed in R comes at the expense of information in R˙, and vice versa. An exception to this trade‐off occurs when spike trains encode a pair of conjugate variables, such as position and velocity, which do not compete for capacity across R and R˙. To illustrate this, we describe two biologically inspired methods for decoding R and R˙, referred to as sigma and sigma‐chi decoding, respectively. Simulations of head direction and grid cells show that if firing rates are tuned for position (but not velocity), then position is recovered by sigma decoding, whereas velocity is recovered by sigma‐chi decoding. Conversely, simulations of oscillatory interference among theta‐modulated “speed cells” show that if co‐firing rates are tuned for position (but not velocity), then position is recovered by sigma‐chi decoding, whereas velocity is recovered by sigma decoding. Between these two extremes, information about both variables can be distributed across both channels, and partially recovered by both decoders. These results suggest that populations with different spatial and temporal tuning properties—such as speed versus grid cells—might not encode different information, but rather, distribute similar information about position and velocity in different ways across R and R˙. Such conjugate coding of position and velocity may influence how hippocampal populations are interconnected to form functional circuits, and how biological neurons integrate their inputs to decode information from firing rates and spike correlations.

Untethered firing fields and intermittent silences: Why grid-cell discharge is so variable

Grid cells in medial entorhinal cortex are notoriously variable in their responses, despite the striking hexagonal arrangement of their spatial firing fields. Indeed, when the animal moves through a firing field, grid cells often fire much more vigorously than predicted or do not fire at all. The source of this trial-to-trial variability is not completely understood. By analyzing grid-cell spike trains from mice running in open arenas and on linear tracks, we characterize the phenomenon of "missed" firing fields using the statistical theory of zero inflation. We find that one major cause of grid-cell variability lies in the spatial representation itself: firing fields are not as strongly anchored to spatial location as the averaged grid suggests. In addition, grid fields from different cells drift together from trial to trial, regardless of whether the environment is real or virtual, or whether the animal moves in light or darkness. Spatial realignment across trials sharpens the grid representation, yielding firing fields that are more pronounced and significantly narrower. These findings indicate that ensembles of grid cells encode relative position more reliably than absolute position.

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

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

Parsing Hippocampal Theta Oscillations by Nested Spectral Components during Spatial Exploration and Memory-Guided Behavior

Theta oscillations reflect rhythmic inputs that continuously converge to the hippocampus during exploratory and memory-guided behavior. The theta-nested operations that organize hippocampal spiking could either occur regularly from one cycle to the next or be tuned on a cycle-by-cycle basis. To resolve this, we identified spectral components nested in individual theta cycles recorded from the mouse CA1 hippocampus. Our single-cycle profiling revealed theta spectral components associated with different firing modulations and distinguishable ensembles of principal cells. Moreover, novel co-firing patterns of principal cells in theta cycles nesting mid-gamma oscillations were the most strongly reactivated in subsequent offline sharp-wave/ripple events. Finally, theta-nested spectral components were differentially altered by behavioral stages of a memory task; the 80-Hz mid-gamma component was strengthened during learning, whereas the 22-Hz beta, 35-Hz slow gamma, and 54-Hz mid-gamma components increased during retrieval. We conclude that cycle-to-cycle variability of theta-nested spectral components allows parsing of theta oscillations into transient operating modes with complementary mnemonic roles.

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Spectral profiling of single theta waves enables studying inter-cycle variability

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Theta spectral components feature different spiking patterns and ensembles

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Co-firing in theta cycles nesting mid-gamma undergo enhanced offline reactivation

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Theta components relate differently to learning and memory retrieval demands

Ordering Information in Working Memory and Modulation of Gamma by Theta Oscillations in Humans

Ordering information is a critical process underlying several cognitive functions, especially working memory. Theta phase-gamma amplitude coupling is regarded as a neurophysiological representation of ordering information during working memory performance. However, direct evidence has been lacking in humans. Seventy healthy subjects performed the N-back task, a working memory task that tests ordering information at 3 different levels of difficulties and with 3 different types of trials. Using electroencephalography (EEG) during N-back performance, theta-gamma coupling was assessed during response trials. Multivariate general linear model (GLM) and discriminant analysis were used to assess coupling and theta and gamma power across the N-back conditions and the trial types. During the N-back trials that required ordering of information, N-back condition had independent effects on coupling and on theta and gamma power, with equal contributions among these 3 variables. Theta-gamma coupling contribution declined significantly on the trials that did not require ordering and was intermediate on trials that favored but not necessarily required ordering. Our findings demonstrate for the first time the role of theta-gamma coupling as a mechanism that supports ordering information. They also highlight the potential of using theta-gamma coupling as a neurophysiological marker of brain function in health or disease states.

Experience-dependent trends in CA1 theta and slow gamma rhythms in freely behaving mice

CA1 place cells become more anticipatory with experience, an effect thought to be caused by NMDA receptor-dependent plasticity in the CA3-CA1 network. Theta (~5-12 Hz), slow gamma (~25-50 Hz), and fast gamma (~50-100 Hz) rhythms are thought to route spatial information in the hippocampal formation and to coordinate place cell ensembles. Yet, it is unknown whether these rhythms exhibit experience-dependent changes concurrent with those observed in place cells. Slow gamma rhythms are thought to indicate inputs from CA3 to CA1, and such inputs are thought to be strengthened with experience. Thus, we hypothesized that slow gamma rhythms would become more evident with experience. We tested this hypothesis using mice freely traversing a familiar circular track for three 10-min sessions per day. We found that slow gamma amplitude was reduced in the early minutes of the first session of each day, even though both theta and fast gamma amplitudes were elevated during this same period. However, in the first minutes of the second and third sessions of each day, all three rhythms were elevated. Interestingly, theta was elevated to a greater degree in the first minutes of the first session than in the first minutes of later sessions. Additionally, all three rhythms were strongly influenced by running speed in dynamic ways, with the influence of running speed on theta and slow gamma changing over time within and across sessions. These results raise the possibility that experience-dependent changes in hippocampal rhythms relate to changes in place cell activity that emerge with experience. NEW & NOTEWORTHY We show that CA1 theta, slow gamma, and fast gamma rhythms exhibit characteristic changes over time within sessions in familiar environments. These effects in familiar environments evolve across repeated sessions.

Precise spike timing dynamics of hippocampal place cell activity sensitive to cholinergic disruption

New memory formation depends on both the hippocampus and modulatory effects of acetylcholine. The mechanism by which acetylcholine levels in the hippocampus enable new encoding remains poorly understood. Here, we tested the hypothesis that cholinergic modulation supports memory formation by leading to structured spike timing in the hippocampus. Specifically, we tested if phase precession in dorsal CA1 was reduced under the influence of a systemic cholinergic antagonist. Unit and field potential were recorded from the dorsal CA1 of rats as they completed laps on a circular track for food rewards before and during the influence of the systemically administered acetylcholine muscarinic receptor antagonist scopolamine. We found that scopolamine significantly reduced phase precession of spiking relative to the field theta, and that this was due to a decrease in the frequency of the spiking rhythmicity. We also found that the correlation between position and theta phase was significantly reduced. This effect was not due to changes in spatial tuning as tuning remained stable for those cells analyzed. Similarly, it was not due to changes in lap‐to‐lap reliability of spiking onset or offset relative to either position or phase as the reliability did not decrease following scopolamine administration. These findings support the hypothesis that memory impairments that follow muscarinic blockade are the result of degraded spike timing in the hippocampus.

Theta-Gamma Coding Meets Communication-through-Coherence: Neuronal Oscillatory Multiplexing Theories Reconciled

Several theories have been advanced to explain how cross-frequency coupling, the interaction of neuronal oscillations at different frequencies, could enable item multiplexing in neural systems. The communication-through-coherence theory proposes that phase-matching of gamma oscillations between areas enables selective processing of a single item at a time, and a later refinement of the theory includes a theta-frequency oscillation that provides a periodic reset of the system. Alternatively, the theta-gamma neural code theory proposes that a sequence of items is processed, one per gamma cycle, and that this sequence is repeated or updated across theta cycles. In short, both theories serve to segregate representations via the temporal domain, but differ on the number of objects concurrently represented. In this study, we set out to test whether each of these theories is actually physiologically plausible, by implementing them within a single model inspired by physiological data. Using a spiking network model of visual processing, we show that each of these theories is physiologically plausible and computationally useful. Both theories were implemented within a single network architecture, with two areas connected in a feedforward manner, and gamma oscillations generated by feedback inhibition within areas. Simply increasing the amplitude of global inhibition in the lower area, equivalent to an increase in the spatial scope of the gamma oscillation, yielded a switch from one mode to the other. Thus, these different processing modes may co-exist in the brain, enabling dynamic switching between exploratory and selective modes of attention.

There is a growing consensus that neuronal oscillations constitute a fundamental computational mechanism in the brain. Beyond this, recent experimental evidence has highlighted interactions between oscillations at high and low frequencies (e.g. gamma oscillations, 40–80 Hz, are modulated by theta oscillations, 4–10 Hz), and two major theories have developed regarding the functional role of this kind of cross-frequency coupling. Here, we present a computational modelling study of these theories with strong implications for biological studies. Firstly, we demonstrate for the first time that each of these theories is physiologically plausible, in that they can be implemented in a spiking network model with parameters guided by experimental data. Secondly, we show that they are each computationally useful, able to overcome a feature-binding ambiguity in a presented stimulus. Finally, we implement both theories within a single network model, and find that only a single parameter change is required to switch between the two processing states. This leads to the exciting new proposal that both theories may be correct, both implemented in the brain, with dynamic switching between modes according to processing and attentional requirements.

Potential roles of cholinergic modulation in the neural coding of location and movement speed

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.

Grid-cell representations in mental simulation

Anticipating the future is a key motif of the brain, possibly supported by mental simulation of upcoming events. Rodent single-cell recordings suggest the ability of spatially tuned cells to represent subsequent locations. Grid-like representations have been observed in the human entorhinal cortex during virtual and imagined navigation. However, hitherto it remains unknown if grid-like representations contribute to mental simulation in the absence of imagined movement. Participants imagined directions between building locations in a large-scale virtual-reality city while undergoing fMRI without re-exposure to the environment. Using multi-voxel pattern analysis, we provide evidence for representations of absolute imagined direction at a resolution of 30° in the parahippocampal gyrus, consistent with the head-direction system. Furthermore, we capitalize on the six-fold rotational symmetry of grid-cell firing to demonstrate a 60° periodic pattern-similarity structure in the entorhinal cortex. Our findings imply a role of the entorhinal grid-system in mental simulation and future thinking beyond spatial navigation.

DOI:http://dx.doi.org/10.7554/eLife.17089.001

Recordings of brain activity in moving rats have found neurons that fire when the rat is at specific locations. These neurons are known as grid cells because their activity produces a grid-like pattern. A separate group of neurons, called head direction cells, represents the rat’s facing direction. Functional magnetic resonance imaging (fMRI) studies that have tracked brain activity in humans as they navigate virtual environments have found similar grid-like and direction-related responses. A recent study showed grid-like responses even if the people being studied just imagined moving around an arena while lying still. Theoretical work suggests that spatially tuned cells might generally be important for our ability to imagine and simulate future events. However, it is not clear whether these location- and direction-responsive cells are active when people do not visualize themselves moving.

Bellmund et al. used fMRI to track brain activity in volunteers as they imagined different views in a virtual reality city. Before the fMRI experiment, the volunteers completed extensive training where they learned the layout of the city and the names of its buildings. Then, during the fMRI experiment, the volunteers had to imagine themselves standing in front of certain buildings and facing different directions. Crucially, they did not imagine themselves moving between these buildings.

By using representational similarity analysis, which compares patterns of brain activity, Bellmund et al. could distinguish between the directions the volunteers were imagining. Activity patterns in the parahippocampal gyrus (a brain region known to be important for navigation) were more similar when participants were imagining similar directions.

The fMRI results also show grid-like responses in a brain area called entorhinal cortex, which is known to contain grid cells. While participants were imagining, this region exhibited activity patterns with a six-fold symmetry, as Bellmund et al. predicted from the characteristic firing patterns of grid cells.

The findings presented by Bellmund et al. provide evidence that suggests that grid cells are involved in planning how to navigate, and so support previous theoretical assumptions. The computations of these cells might contribute to other kinds of thinking too, such as remembering the past or imagining future events.

DOI:http://dx.doi.org/10.7554/eLife.17089.002

Activities of visual cortical and hippocampal neurons co-fluctuate in freely moving rats during spatial behavior

Visual cues exert a powerful control over hippocampal place cell activities that encode external spaces. The functional interaction of visual cortical neurons and hippocampal place cells during spatial navigation behavior has yet to be elucidated. Here we show that, like hippocampal place cells, many neurons in the primary visual cortex (V1) of freely moving rats selectively fire at specific locations as animals run repeatedly on a track. The V1 location-specific activity leads hippocampal place cell activity both spatially and temporally. The precise activities of individual V1 neurons fluctuate every time the animal travels through the track, in a correlated fashion with those of hippocampal place cells firing at overlapping locations. The results suggest the existence of visual cortical neurons that are functionally coupled with hippocampal place cells for spatial processing during natural behavior. These visual neurons may also participate in the formation and storage of hippocampal-dependent memories.

DOI:http://dx.doi.org/10.7554/eLife.08902.001

The brain is able to create and maintain a map of our surroundings as we go about our daily activities. It is thought that some of this spatial information is first processed in a region of the brain called the visual cortex, the information is then relayed to a region called the hippocampus, where the map is reliably stored. However, researchers do not fully understand how the brain transfers spatial information between these two regions.

To explore what happens to the information, Haggerty and Ji recorded electrical signals from the brains of rats that were being trained to run back and forth along a C-shaped track. As they ran on the track, the rats gradually developed spatial maps of there surroundings. Electrodes were used to record brain signals from both the visual cortex and the hippocampus as this development took place.

Similar to previous studies, analysis of the recordings showed that a specific population of neurons in the hippocampus, called CA1 neurons, produced an electrical signal whenever the rat ran past specific locations on the track, such as corners. Building on this Haggerty and Ji showed a population of neurons in the visual cortex called V1 neurons also produced location-specific electrical signals at the same time. Moreover, the electrical signals of these two populations of neurons fluctuate together in a coordinated fashion.

The results of Haggerty and Ji support the idea that there exists a specific population of visual cortical neurons that communicate with hippocampal neurons in the development of a particular spatial map.

DOI:http://dx.doi.org/10.7554/eLife.08902.002

Speed cells in the medial entorhinal cortex

Grid cells in the medial entorhinal cortex have spatial firing fields that repeat periodically in a hexagonal pattern. When animals move, activity is translated between grid cells in accordance with the animal's displacement in the environment. For this translation to occur, grid cells must have continuous access to information about instantaneous running speed. However, a powerful entorhinal speed signal has not been identified. Here we show that running speed is represented in the firing rate of a ubiquitous but functionally dedicated population of entorhinal neurons distinct from other cell populations of the local circuit, such as grid, head-direction and border cells. These 'speed cells' are characterized by a context-invariant positive, linear response to running speed, and share with grid cells a prospective bias of ∼50-80 ms. Our observations point to speed cells as a key component of the dynamic representation of self-location in the medial entorhinal cortex.

Two-phase model of the basal ganglia: implications for discontinuous control of the motor system

In this article, I point out that simple one-phase models of the role of the basal ganglia in action selection have a problem. Furthermore, I suggest a solution with major implications for the organization of the action-selection and motor systems. In current models, the striatum evaluates multiple potential actions by adding biases based on previous conditioning. These biases may arise in both the direct (bias for) and indirect (bias against) pathways. Together, these biases influence which action is ultimately chosen. For efficient conditioning to occur, a positive outcome must selectively strengthen the striatal bias for the chosen action (via a dopaminergic mechanism). This is problematic, however, because all potential action choices have influenced firing patterns in striatal cells during the selection process; it is therefore unclear how the synapses that represent the chosen plan could be selectively strengthened. I suggest a simple solution in which the striatum has two functional phases. In the first phase, the basal ganglia provide biases for multiple potential actions (using both the direct and indirect pathways), leading to the choice of a single action in the cortex. In the second phase, an efference copy of the chosen action is sent to the striatum, where it contributes to the establishment of the eligibility trace for that action. This trace, when acted on by subsequent dopaminergic reinforcement, leads to specific strengthening of the bias only for the chosen action. Consistent with this model, recordings show post-choice imposition onto the striatum of signals corresponding to the chosen action. The existence of dual phases of basal ganglia function implies that decisions about action choice are sent to the motor system in a discontinuous manner. This would not be problematic if the motor system also operated discontinuously. I will review evidence suggesting that this is the case, notably that action is organized by approximately 10 Hz oscillations.

The challenge of understanding the brain: where we stand in 2015

Starting with the work of Cajal more than 100 years ago, neuroscience has sought to understand how the cells of the brain give rise to cognitive functions. How far has neuroscience progressed in this endeavor? This Perspective assesses progress in elucidating five basic brain processes: visual recognition, long-term memory, short-term memory, action selection, and motor control. Each of these processes entails several levels of analysis: the behavioral properties, the underlying computational algorithm, and the cellular/network mechanisms that implement that algorithm. At this juncture, while many questions remain unanswered, achievements in several areas of research have made it possible to relate specific properties of brain networks to cognitive functions. What has been learned reveals, at least in rough outline, how cognitive processes can be an emergent property of neurons and their connections.

Grid cell firing patterns may arise from feedback interaction between intrinsic rebound spiking and transverse traveling waves with multiple heading angles

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.

Theta-gamma coupling in the entorhinal-hippocampal system

For decades, theta rhythms (∼5-10Hz) have been thought to play a critical role in memory processing in the entorhinal-hippocampal network. However, recent evidence suggests that successful memory performance also requires coupling of ∼30-100Hz gamma rhythms to particular phases of the theta cycle. Recent insights imply ways in which theta-gamma coupling may facilitate transfer of information throughout the entorhinal-hippocampal network. Activating gamma-modulated cell assemblies at a particular theta phase may allow the network to produce a more powerful output by ensuring that distributed cells fire closely in time. I hypothesize that such a mechanism would serve to facilitate either memory encoding or memory retrieval, depending on which type of gamma rhythms are recruited.

Slow and fast γ rhythms coordinate different spatial coding modes in hippocampal place cells

Previous work has hinted that prospective and retrospective coding modes exist in hippocampus. Prospective coding is believed to reflect memory retrieval processes, whereas retrospective coding is thought to be important for memory encoding. Here, we show in rats that separate prospective and retrospective modes exist in hippocampal subfield CA1 and that slow and fast gamma rhythms differentially coordinate place cells during the two modes. Slow gamma power and phase locking of spikes increased during prospective coding; fast gamma power and phase locking increased during retrospective coding. Additionally, slow gamma spikes occurred earlier in place fields than fast gamma spikes, and cell ensembles retrieved upcoming positions during slow gamma and encoded past positions during fast gamma. These results imply that alternating slow and fast gamma states allow the hippocampus to switch between prospective and retrospective modes, possibly to prevent interference between memory retrieval and encoding.

Theta phase precession of grid and place cell firing in open environments

Place and grid cells in the rodent hippocampal formation tend to fire spikes at successively earlier phases relative to the local field potential theta rhythm as the animal runs through the cell's firing field on a linear track. However, this ‘phase precession’ effect is less well characterized during foraging in two-dimensional open field environments. Here, we mapped runs through the firing fields onto a unit circle to pool data from multiple runs. We asked which of seven behavioural and physiological variables show the best circular–linear correlation with the theta phase of spikes from place cells in hippocampal area CA1 and from grid cells from superficial layers of medial entorhinal cortex. The best correlate was the distance to the firing field peak projected onto the animal's current running direction. This was significantly stronger than other correlates, such as instantaneous firing rate and time-in-field, but similar in strength to correlates with other measures of distance travelled through the firing field. Phase precession was stronger in place cells than grid cells overall, and robust phase precession was seen in traversals through firing field peripheries (although somewhat less than in traversals through the centre), consistent with phase coding of displacement along the current direction. This type of phase coding, of place field distance ahead of or behind the animal, may be useful for allowing calculation of goal directions during navigation.

Modeling of grid cell activity demonstrates in vivo entorhinal 'look-ahead' properties

Recent in vivo data show ensemble activity in medial entorhinal neurons that demonstrates 'look-ahead' activity, decoding spatially to reward locations ahead of a rat deliberating at a choice point while performing a cued, appetitive T-Maze task. To model this experiment's look-ahead results, we adapted previous work that produced a model where scans along equally probable directions activated place cells, associated reward cells, grid cells, and persistent spiking cells along those trajectories. Such look-ahead activity may be a function of animals performing scans to reduce ambiguity while making decisions. In our updated model, look-ahead scans at the choice point can activate goal-associated reward and place cells, which indicate the direction the virtual rat should turn at the choice point. Hebbian associations between stimulus and reward cell layers are learned during training trials, and the reward and place layers are then used during testing to retrieve goal-associated cells based on cue presentation. This system creates representations of location and associated reward information based on only two inputs of heading and speed information which activate grid cell and place cell layers. We present spatial and temporal decoding of grid cell ensembles as rats are tested with perfect and imperfect stimuli. Here, the virtual rat reliably learns goal locations through training sessions and performs both biased and unbiased look-ahead scans at the choice point. Spatial and temporal decoding of simulated medial entorhinal activity indicates that ensembles are representing forward reward locations when the animal deliberates at the choice point, emulating in vivo results.

The θ-γ neural code

Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence for the following hypothesis: that the dual oscillations form a code for representing multiple items in an ordered way. This form of coding has been most clearly demonstrated in the hippocampus, where different spatial information is represented in different gamma subcycles of a theta cycle. Other experiments have tested the functional importance of oscillations and their coupling. These involve correlation of oscillatory properties with memory states, correlation with memory performance, and effects of disrupting oscillations on memory. Recent work suggests that this coding scheme coordinates communication between brain regions and is involved in sensory as well as memory processes.