Interspike Intervals Reveal Functionally Distinct Cell Populations in the Medial Entorhinal Cortex

Left-right-alternating theta sweeps in entorhinal-hippocampal maps of space

Place cells in the hippocampus and grid cells in the entorhinal cortex are elements of a neural map of self position1-5. For these cells to benefit navigation, their representation must be dynamically related to the surrounding locations2. A candidate mechanism for linking places along an animal's path has been described for place cells, in which the sequence of spikes in each cycle of the hippocampal theta oscillation encodes a trajectory from the animal's current location towards upcoming locations6-8. In mazes that bifurcate, such trajectories alternately traverse the two upcoming arms when the animal approaches the choice point9,10, raising the possibility that the trajectories express available forward paths encoded on previous trials10. However, to bridge the animal's path with the wider environment, beyond places previously or subsequently visited, an experience-independent spatial sampling mechanism might be required. Here we show in freely moving rats that in individual theta cycles, ensembles of grid cells and place cells encode a position signal that sweeps linearly outwards from the animal's location into the ambient environment, with sweep direction alternating stereotypically between left and right across successive theta cycles. These sweeps are accompanied by, and aligned with, a similarly alternating directional signal in a discrete population of parasubiculum cells that have putative connections to grid cells via conjunctive grid × direction cells. Sweeps extend into never-visited locations that are inaccessible to the animal. Sweeps persist during REM sleep. The sweep directions can be explained by an algorithm that maximizes the cumulative coverage of the surrounding manifold space. The sustained and unconditional expression of theta-patterned left-right-alternating sweeps in the entorhinal-hippocampal positioning system provides an efficient 'look around' mechanism for sampling locations beyond the travelled path.

IN VIVO CELL-TYPE AND BRAIN REGION CLASSIFICATION VIA MULTIMODAL CONTRASTIVE LEARNING

Current electrophysiological approaches can track the activity of many neurons, yet it is usually unknown which cell-types or brain areas are being recorded without further molecular or histological analysis. Developing accurate and scalable algorithms for identifying the cell-type and brain region of recorded neurons is thus crucial for improving our understanding of neural computation. In this work, we develop a multimodal contrastive learning approach for neural data that can be fine-tuned for different downstream tasks, including inference of cell-type and brain location. We utilize this approach to jointly embed the activity autocorrelations and extracellular waveforms of individual neurons. We demonstrate that our embedding approach, Neuronal Embeddings via MultimOdal contrastive learning (NEMO), paired with supervised fine-tuning, achieves state-of-the-art cell-type classification for an opto-tagged visual cortex dataset and brain region classification for the public International Brain Laboratory brain-wide map dataset. Our method represents a promising step towards accurate cell-type and brain region classification from electrophysiological recordings.

Neuronal Subtypes and Connectivity of the Adult Mouse Paralaminar Amygdala

The paralaminar nucleus of the amygdala (PL) comprises neurons that exhibit delayed maturation. PL neurons are born during gestation but mature during adolescent ages, differentiating into excitatory neurons. These late-maturing PL neurons contribute to the increase in size and cell number of the amygdala between birth and adulthood. However, the function of the PL upon maturation is unknown, as the region has only recently begun to be characterized in detail. In this study, we investigated key defining features of the adult mouse PL; the intrinsic morpho-electric properties of its neurons, and its input and output circuit connectivity. We identify two subtypes of excitatory neurons in the PL based on unsupervised clustering of electrophysiological properties. These subtypes are defined by differential action potential firing properties and dendritic architecture, suggesting divergent functional roles. We further uncover major axonal inputs to the adult PL from the main olfactory network and basolateral amygdala. We also find that axonal outputs from the PL project reciprocally to these inputs and to diverse targets including the amygdala, frontal cortex, hippocampus, hypothalamus, and brainstem. Thus, the adult mouse PL is centrally placed to play a major role in the integration of olfactory sensory information, to coordinate affective and autonomic behavioral responses to salient odor stimuli.

A method to analyze gene expression profiles from hippocampal neurons electrophysiologically recorded in vivo

Hippocampal pyramidal neurons exhibit diverse spike patterns and gene expression profiles. However, their relationships with single neurons are not fully understood. In this study, we designed an electrophysiology-based experimental procedure to identify gene expression profiles using RNA sequencing of single hippocampal pyramidal neurons whose spike patterns were recorded in living mice. This technique involves a sequence of experiments consisting of in vivo juxtacellular recording and labeling, brain slicing, cell collection, and transcriptome analysis. We demonstrated that the expression levels of a subset of genes in individual hippocampal pyramidal neurons were significantly correlated with their spike burstiness, submillisecond-level spike rise times or spike rates, directly measured by in vivo electrophysiological recordings. Because this methodological approach can be applied across a wide range of brain regions, it is expected to contribute to studies on various neuronal heterogeneities to understand how physiological spike patterns are associated with gene expression profiles.

Comparison of head direction cell firing characteristics across thalamo-parahippocampal circuitry

Head direction (HD) cells, which fire persistently when an animal's head is pointed in a particular direction, are widely thought to underlie an animal's sense of spatial orientation and have been identified in several limbic brain regions. Robust HD cell firing is observed throughout the thalamo-parahippocampal system, although recent studies report that parahippocampal HD cells exhibit distinct firing properties, including conjunctive aspects with other spatial parameters, which suggest they play a specialized role in spatial processing. Few studies, however, have quantified these apparent differences. Here, we performed a comparative assessment of HD cell firing characteristics across the anterior dorsal thalamus (ADN), postsubiculum (PoS), parasubiculum (PaS), medial entorhinal (MEC), and postrhinal (POR) cortices. We report that HD cells with a high degree of directional specificity were observed in all five brain regions, but ADN HD cells display greater sharpness and stability in their preferred directions, and greater anticipation of future headings compared to parahippocampal regions. Additional analysis indicated that POR HD cells were more coarsely modulated by other spatial parameters compared to PoS, PaS, and MEC. Finally, our analyses indicated that the sharpness of HD tuning decreased as a function of laminar position and conjunctive coding within the PoS, PaS, and MEC, with cells in the superficial layers along with conjunctive firing properties showing less robust directional tuning. The results are discussed in relation to theories of functional organization of HD cell tuning in thalamo-parahippocampal circuitry.

Grid cells: the missing link in understanding Parkinson's disease?

The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.

Sensory and behavioral modulation of thalamic head-direction cells

Head-direction (HD) neurons are thought to exclusively encode directional heading. In awake mice, we found that sensory stimuli evoked robust short-latency responses in thalamic HD cells, but not in non-HD neurons. The activity of HD cells, but not that of non-HD neurons, was tightly correlated to brain-state fluctuations and dynamically modulated during social interactions. These data point to a new role for the thalamic compass in relaying sensory and behavioral-state information.

Hypothalamic supramammillary neurons that project to the medial septum modulate wakefulness in mice

The hypothalamic supramammillary nucleus (SuM) plays a crucial role in controlling wakefulness, but the downstream target regions participating in this control process remain unknown. Here, using circuit-specific fiber photometry and single-neuron electrophysiology together with electroencephalogram, electromyogram and behavioral recordings, we find that approximately half of SuM neurons that project to the medial septum (MS) are wake-active. Optogenetic stimulation of axonal terminals of SuM-MS projection induces a rapid and reliable transition to wakefulness from non-rapid-eye movement or rapid-eye movement sleep, and chemogenetic activation of SuMMS projecting neurons significantly increases wakefulness time and prolongs latency to sleep. Consistently, chemogenetically inhibiting these neurons significantly reduces wakefulness time and latency to sleep. Therefore, these results identify the MS as a functional downstream target of SuM and provide evidence for the modulation of wakefulness by this hypothalamic-septal projection.

The neural ingredients for a language of thought are available

The classical notion of a 'language of thought' (LoT), advanced prominently by the philosopher Jerry Fodor, is an influential position in cognitive science whereby the mental representations underpinning thought are considered to be compositional and productive, enabling the construction of new complex thoughts from more primitive symbolic concepts. LoT theory has been challenged because a neural implementation has been deemed implausible. We disagree. Examples of critical computational ingredients needed for a neural implementation of a LoT have in fact been demonstrated, in particular in the hippocampal spatial navigation system of rodents. Here, we show that cell types found in spatial navigation (border cells, object cells, head-direction cells, etc.) provide key types of representation and computation required for the LoT, underscoring its neurobiological viability.

Sharp Tuning of Head Direction and Angular Head Velocity Cells in the Somatosensory Cortex

Head direction (HD) cells form a fundamental component in the brain's spatial navigation system and are intricately linked to spatial memory and cognition. Although HD cells have been shown to act as an internal neuronal compass in various cortical and subcortical regions, the neural substrate of HD cells is incompletely understood. It is reported that HD cells in the somatosensory cortex comprise regular-spiking (RS, putative excitatory) and fast-spiking (FS, putative inhibitory) neurons. Surprisingly, somatosensory FS HD cells fire in bursts and display much sharper head-directionality than RS HD cells. These FS HD cells are nonconjunctive, rarely theta rhythmic, sparsely connected and enriched in layer 5. Moreover, sharply tuned FS HD cells, in contrast with RS HD cells, maintain stable tuning in darkness; FS HD cells' coexistence with RS HD cells and angular head velocity (AHV) cells in a layer-specific fashion through the somatosensory cortex presents a previously unreported configuration of spatial representation in the neocortex. Together, these findings challenge the notion that FS interneurons are weakly tuned to sensory stimuli, and offer a local circuit organization relevant to the generation and transmission of HD signaling in the brain.

Microcircuits for spatial coding in the medial entorhinal cortex

The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism's spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.

Toroidal topology of population activity in grid cells

The medial entorhinal cortex is part of a neural system for mapping the position of an individual within a physical environment1. Grid cells, a key component of this system, fire in a characteristic hexagonal pattern of locations2, and are organized in modules3 that collectively form a population code for the animal's allocentric position1. The invariance of the correlation structure of this population code across environments4,5 and behavioural states6,7, independent of specific sensory inputs, has pointed to intrinsic, recurrently connected continuous attractor networks (CANs) as a possible substrate of the grid pattern1,8-11. However, whether grid cell networks show continuous attractor dynamics, and how they interface with inputs from the environment, has remained unclear owing to the small samples of cells obtained so far. Here, using simultaneous recordings from many hundreds of grid cells and subsequent topological data analysis, we show that the joint activity of grid cells from an individual module resides on a toroidal manifold, as expected in a two-dimensional CAN. Positions on the torus correspond to positions of the moving animal in the environment. Individual cells are preferentially active at singular positions on the torus. Their positions are maintained between environments and from wakefulness to sleep, as predicted by CAN models for grid cells but not by alternative feedforward models12. This demonstration of network dynamics on a toroidal manifold provides a population-level visualization of CAN dynamics in grid cells.

Resurgent Sodium Current in Neurons of the Cerebral Cortex

In the late ’90, Dr. Indira Raman, at the time a postdoctoral fellow with Dr. Bruce Bean, at Harvard University, identified a new type of sodium current, flowing through the channels that reopens when the membrane is repolarized. This current, called “resurgent Sodium current,” was originally identified in cerebellar Purkinje neurons and has now been confirmed in around 20 different neuronal types. Since moving to Northwestern University in 1999 to establish her own research group, Dr. Raman has dedicated great efforts in identifying the mechanisms supporting the resurgent Sodium current and how its biophysical properties shape the firing of the different cell types. Her work has impacted greatly the field of cellular neurophysiology, from basic research to translation neuroscience. In fact, alterations in the resurgent sodium currents have been observed in several neuropathologies, from Huntington’s disease to epilepsy. In this Perspective we will focus on the current knowledge on the expression and function of the resurgent Sodium current in neurons of the cerebral cortex and hippocampus. We will also briefly highlight the role of Dr. Raman’s as teacher and mentor, not only for her pupils, but for the whole scientific community.

Neural burst codes disguised as rate codes

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.

Burst activity plays no role in the field-to-field variability and rate remapping of grid cells

Grid cells in rodent medial entorhinal cortex are thought to play a key role for spatial navigation. When the animal is freely moving in an open arena the firing fields of each grid cell tend to form a highly regular, hexagonal lattice spanning the environment. However, firing rates vary from field to field and change under contextual modifications, whereas the field locations shift at most by a small amount under such "rate remapping." The observed differences in firing rate could reflect overall activity changes or changes in the detailed spike-train statistics. As these two alternatives imply distinct neural coding schemes, we investigated whether temporal firing patterns vary from field to field and whether they change under rate remapping. Focusing on short time scales, we found that the proportion of bursts compared to all discharge events is similar in all firing fields of a given grid cell and does not change under rate remapping. For each cell, mean firing rates with bursts are proportional to mean firing rates without bursts. However, this ratio varies across cells. Additionally, we looked at how rate remapping relates to entorhinal theta-frequency oscillations. Theta-phase coding was preserved despite firing-rate changes from rate remapping but we did not observe differences between the first and second half of the theta cycle, as had been reported for CA1. Our results indicate that both, the heterogeneity between firing fields and rate remapping, are not due to altered firing patterns on short time scales but reflect location-specific changes at the firing-rate level.

Altered Sensory Representations in Parkinsonian Cortical and Basal Ganglia Networks

In parkinsonian conditions, network dynamics in the cortical and basal ganglia circuits present abnormal oscillations and periods of high synchrony, affecting the functionality of multiple striatal regions including the sensorimotor striatum. However, it is still unclear how these altered dynamics impact on sensory processing, a key feature for motor control that is severely impaired in parkinsonian patients. A major confound is that pathological dynamics in sensorimotor networks may elicit unspecific motor responses that may alter sensory representations through sensory feedback, making it difficult to disentangle motor and sensory components. To address this issue, we studied sensory processing using an anesthetized model with robust sensory representations throughout cortical and basal ganglia sensory regions and limited motor confounds in control and hemiparkinsonian rats. A general screening of sensory-evoked activity in large populations of neurons recorded in the primary sensory cortex (S1), dorsolateral striatum (DLS) and substantia nigra pars reticulata (SNr) revealed increased excitability and altered sensory representations in the three regions. Further analysis revealed uncoordinated population dynamics between DLS and S1/SNr. Finally, DLS lesions in hemiparkinsonian animals partially recovered population dynamics and execution in the rotarod.

Topography in the Bursting Dynamics of Entorhinal Neurons

Medial entorhinal cortex contains neural substrates for representing space. These substrates include grid cells that fire in repeating locations and increase in scale progressively along the dorsal-to-ventral entorhinal axis, with the physical distance between grid firing nodes increasing from tens of centimeters to several meters in rodents. Whether the temporal scale of grid cell spiking dynamics shows a similar dorsal-to-ventral organization remains unknown. Here, we report the presence of a dorsal-to-ventral gradient in the temporal spiking dynamics of grid cells in behaving mice. This gradient in bursting supports the emergence of a dorsal grid cell population with a high signal-to-noise ratio. In vitro recordings combined with a computational model point to a role for gradients in non-inactivating sodium conductances in supporting the bursting gradient in vivo. Taken together, these results reveal a complementary organization in the temporal and intrinsic properties of entorhinal cells.

Two septal-entorhinal GABAergic projections differentially control coding properties of spatially tuned neurons in the medial entorhinal cortex

Septal parvalbumin-expressing (PV+) and calbindin-expressing (CB+) projections inhibit low-threshold and fast-spiking interneurons, respectively, in the medial entorhinal cortex (MEC). We investigate how the two inputs control neuronal activity in the MEC in freely moving mice. Stimulation of PV+ and CB+ terminals causes disinhibition of spatially tuned MEC neurons, but exerts differential effects on temporal coding and burst firing. Thus, recruitment of PV+ projections disrupts theta-rhythmic firing of MEC neurons, while stimulation of CB+ projections increases burst firing of grid cells and enhances phase precession in a cell-type-specific manner. Inactivation of septal PV+ or CB+ neurons differentially affects context, reference, and working memory. Together, our results reveal how specific connectivity of septal GABAergic projections with MEC interneurons translates into differential modulation of MEC neuronal coding.

Enhancement of Hippocampal Spatial Decoding Using a Dynamic Q-Learning Method With a Relative Reward Using Theta Phase Precession

Hippocampal place cells and interneurons in mammals have stable place fields and theta phase precession profiles that encode spatial environmental information. Hippocampal CA1 neurons can represent the animal's location and prospective information about the goal location. Reinforcement learning (RL) algorithms such as Q-learning have been used to build the navigation models. However, the traditional Q-learning ([Formula: see text]Q-learning) limits the reward function once the animals arrive at the goal location, leading to unsatisfactory location accuracy and convergence rates. Therefore, we proposed a revised version of the Q-learning algorithm, dynamical Q-learning ([Formula: see text]Q-learning), which assigns the reward function adaptively to improve the decoding performance. Firing rate was the input of the neural network of [Formula: see text]Q-learning and was used to predict the movement direction. On the other hand, phase precession was the input of the reward function to update the weights of [Formula: see text]Q-learning. Trajectory predictions using [Formula: see text]Q- and [Formula: see text]Q-learning were compared by the root mean squared error (RMSE) between the actual and predicted rat trajectories. Using [Formula: see text]Q-learning, significantly higher prediction accuracy and faster convergence rate were obtained compared with [Formula: see text]Q-learning in all cell types. Moreover, combining place cells and interneurons with theta phase precession improved the convergence rate and prediction accuracy. The proposed [Formula: see text]Q-learning algorithm is a quick and more accurate method to perform trajectory reconstruction and prediction.

Unbalanced Inhibitory/Excitatory Responses in the Substantia Nigra Pars Reticulata Underlie Cannabinoid-Related Slowness of Movements

The substantia nigra pars reticulata (SNr), where the basal ganglia (BG) direct and indirect pathways converge, contains among the highest expression of cannabinoid receptor type 1 (CB1r) in the brain. Hence, SNr is an ideal locus to study pathway interactions and cannabinergic modulations. The objective of this study was to characterize the effects of systemic injections of the CB1r agonist (CP55940) on the balanced activity of the direct/indirect pathways in the SNr and its associated behaviors. To this aim, we recorded somatosensory and pathway-specific representations in the spiking activity of the SNr of male rats under CP55940. CB1r activation mainly decreased the inhibitory, potentially direct pathway component while sparing the excitatory, potentially indirect pathway component of somatosensory responses. As a result, cutaneous stimulation produced unbalanced responses favoring increased SNr firing rates, suggesting a potential locus for cannabinergic motor-related effects. To test this hypothesis, we implemented an ad hoc behavioral protocol for rats in which systemic administration of CP55940 produced kinematic impairments that were completely reverted by nigral injections of the CB1r antagonist (AM251). Our data suggest that cannabinoid-related motor effects are associated with unbalanced direct/indirect pathway activations that may be reverted by CB1r manipulation at the SNr.SIGNIFICANCE STATEMENT The cannabinergic system has been the target of multiple studies to master its potential use as a therapeutic agent. However, significant advances have been precluded by the lack of mechanistic explanations for the variety of its desirable/undesirable effects. Here, we have combined electrophysiological recordings, pharmacological and optogenetic manipulations, and an ad hoc behavioral protocol to understand how basal ganglia (BG) is affected by cannabinoids. We found that cannabinoids principally affect inhibitory inputs, potentially from the direct pathway, resulting in unbalanced responses in the substantia nigra pars reticulata (SNr) and suggesting a mechanism for the cannabinoid-related slowness of movements. This possibility was confirmed by behavioral experiments in which cannabinoid-related slowness of purposeful movements was reverted by cannabinoid receptor type 1 (CB1r) manipulations directly into the SNr.

Spike Afterpotentials Shape the In Vivo Burst Activity of Principal Cells in Medial Entorhinal Cortex

Principal neurons in rodent medial entorhinal cortex (MEC) generate high-frequency bursts during natural behavior. While in vitro studies point to potential mechanisms that could support such burst sequences, it remains unclear whether these mechanisms are effective under in vivo conditions. In this study, we focused on the membrane-potential dynamics immediately following action potentials (APs), as measured in whole-cell recordings from male mice running in virtual corridors (Domnisoru et al., 2013). These afterpotentials consisted either of a hyperpolarization, an extended ramp-like shoulder, or a depolarization reminiscent of depolarizing afterpotentials (DAPs) recorded in vitro in MEC principal neurons. Next, we correlated the afterpotentials with the cells' propensity to fire bursts. All DAP cells with known location resided in Layer II, generated bursts, and their interspike intervals (ISIs) were typically between 5 and 15 ms. The ISI distributions of Layer-II cells without DAPs peaked sharply at around 4 ms and varied only minimally across that group. This dichotomy in burst behavior is explained by cell-group-specific DAP dynamics. The same two groups of bursting neurons also emerged when we clustered extracellular spike-train autocorrelations measured in real 2D arenas (Latuske et al., 2015). Apart from slight variations in grid spacing, no difference in the spatial coding properties of the grid cells across all three groups was discernible. Layer III neurons were only sparsely bursting (SB) and had no DAPs. As various mechanisms for modulating ion-channels underlying DAPs exist, our results suggest that temporal features of MEC activity can be altered while maintaining the cells' overall spatial tuning characteristics.SIGNIFICANCE STATEMENT Depolarizing afterpotentials (DAPs) are frequently observed in principal neurons from slice preparations of rodent medial entorhinal cortex (MEC), but their functional role in vivo is unknown. Analyzing whole-cell data from mice running on virtual tracks, we show that DAPs do occur during behavior. Cells with prominent DAPs are found in Layer II; their interspike intervals (ISIs) reflect DAP time-scales. In contrast, neither the rarely bursting cells in Layer III, nor the high-frequency bursters in Layer II, have a DAP. Extracellular recordings from mice exploring real 2D arenas demonstrate that grid cells within these three groups have similar spatial coding properties. We conclude that DAPs shape the temporal response characteristics of principal neurons in MEC with little effect on spatial properties.

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.

Multiscale relevance and informative encoding in neuronal spike trains

Neuronal responses to complex stimuli and tasks can encompass a wide range of time scales. Understanding these responses requires measures that characterize how the information on these response patterns are represented across multiple temporal resolutions. In this paper we propose a metric - which we call multiscale relevance (MSR) - to capture the dynamical variability of the activity of single neurons across different time scales. The MSR is a non-parametric, fully featureless indicator in that it uses only the time stamps of the firing activity without resorting to any a priori covariate or invoking any specific structure in the tuning curve for neural activity. When applied to neural data from the mEC and from the ADn and PoS regions of freely-behaving rodents, we found that neurons having low MSR tend to have low mutual information and low firing sparsity across the correlates that are believed to be encoded by the region of the brain where the recordings were made. In addition, neurons with high MSR contain significant information on spatial navigation and allow to decode spatial position or head direction as efficiently as those neurons whose firing activity has high mutual information with the covariate to be decoded and significantly better than the set of neurons with high local variations in their interspike intervals. Given these results, we propose that the MSR can be used as a measure to rank and select neurons for their information content without the need to appeal to any a priori covariate.

Cell type, sub-region, and layer-specific speed representation in the hippocampal-entorhinal circuit

It has been hypothesised that speed information, encoded by ‘speed cells’, is important for updating spatial representation in the hippocampus and entorhinal cortex to reflect ongoing self-movement during locomotion. However, systematic characterisation of speed representation is still lacking. In this study, we compared the speed representation of distinct cell types across sub-regions/layers in the dorsal hippocampus and medial entorhinal cortex of rats during exploration. Our results indicate that the preferred theta phases of individual neurons are correlated with positive/negative speed modulation and a temporal shift of speed representation in a sub-region/layer and cell type-dependent manner. Most speed cells located in entorhinal cortex layer 2 represented speed prospectively, whereas those in the CA1 and entorhinal cortex layers 3 and 5 represented speed retrospectively. In entorhinal cortex layer 2, putative CA1-projecting pyramidal cells, but not putative dentate gyrus/CA3-projecting stellate cells, represented speed prospectively. Among the hippocampal interneurons, approximately one-third of putative dendrite-targeting (somatostatin-expressing) interneurons, but only a negligible fraction of putative soma-targeting (parvalbumin-expressing) interneurons, showed negative speed modulation. Putative parvalbumin-expressing CA1 interneurons and somatostatin-expressing CA3 interneurons represented speed more retrospectively than parvalbumin-expressing CA3 interneurons. These findings indicate that speed representation in the hippocampal-entorhinal circuit is cell-type, pathway, and theta-phase dependent.

Stability of medial entorhinal cortex representations over time

Distinct functional cell types in the medial entorhinal cortex (mEC) have been shown to represent different aspects of experiences. To further characterize mEC cell populations, we examined whether spatial representations of neurons in mEC superficial layers depended on the scale of the environment and changed over extended time periods. Accordingly, mEC cells were recorded while rats repeatedly foraged in a small or a large environment in sessions that were separated by time intervals from minutes to hours. Comparing between large and small environments, we found that the overall precision of grid and non-grid cell spatial maps was higher in smaller environments. When examining the stability of spatial firing patterns over time, differences and similarities were observed across cell types. Within-session stability was higher for grid cells than for non-grid cell populations. Despite differences in baseline stability between cell types, stability levels remained consistent over time between sessions, up to 1 hr. Even for sessions separated by 6 hrs, activity patterns of grid cells and of most non-grid cells lacked any systematic decrease in spatial similarity over time. However, a subset of ~15% of mEC non-grid cells recorded preferentially from layer III exhibited dramatic, time dependent changes in firing patterns across 6 hrs, reminiscent of previous characterizations of the hippocampal CA2 subregion. Collectively, our data suggest that mEC grid cell input to hippocampus in conjunction with many time invariant non-grid cells may aid in stabilizing hippocampal spatial maps, while a subset of time varying non-grid cells could provide complementary temporal information.

Burst Firing and Spatial Coding in Subicular Principal Cells

The subiculum is the major output structure of the hippocampal formation and is involved in learning and memory as well as in spatial navigation. Little is known about how neuronal diversity contributes to function in the subiculum. Previously, in vitro studies have identified distinct bursting patterns in the subiculum. Here, we asked how burst firing is related to spatial coding in vivo. Using juxtacellular recordings in freely moving male rats, we studied the bursting behavior of 102 subicular principal neurons and distinguished two populations: sparsely bursting (∼80%) and dominantly bursting neurons (∼20%). These bursting behaviors were not linked to anatomy: both cell types were found all along the proximodistal and radial axes of the subiculum and all identified cells were pyramidal neurons. However, the distinct burst firing patterns were related to functional differences: the activity of sparsely bursting cells showed a stronger spatial modulation than the activity of dominantly bursting neurons. In addition, all cells classified as boundary cells were sparsely bursting cells. In most sparsely bursting cells, bursts defined sharper firing fields and carried more spatial information than isolated spikes. We conclude that burst firing is functionally relevant to subicular spatially tuned neurons, possibly by serving as a mechanism to transmit spatial information to downstream structures.

SIGNIFICANCE STATEMENT The subiculum is the major output structure of the hippocampal formation and is involved in spatial navigation. In vitro, subicular cells can be distinguished by their ability to initiate bursts as brief sequences of spikes fired at high frequencies. Little is known about the relationship between cellular diversity and spatial coding in the subiculum. We performed high-resolution juxtacellular recordings in freely moving rats and found that bursting behavior predicts functional differences between subicular neurons. Specifically, sparsely bursting cells have lower firing rates and carry more spatial information than dominantly bursting cells. Additionally, bursts fired by sparsely bursting cells encoded spatial information better than isolated spikes, indicating that bursts act as a unit of information dedicated to spatial coding.

Functional properties of stellate cells in medial entorhinal cortex layer II

Layer II of the medial entorhinal cortex (MEC) contains two principal cell types: pyramidal cells and stellate cells. Accumulating evidence suggests that these two cell types have distinct molecular profiles, physiological properties, and connectivity. The observations hint at a fundamental functional difference between the two cell populations but conclusions have been mixed. Here, we used a tTA-based transgenic mouse line to drive expression of ArchT, an optogenetic silencer, specifically in stellate cells. We were able to optogenetically identify stellate cells and characterize their firing properties in freely moving mice. The stellate cell population included cells from a range of functional cell classes. Roughly one in four of the tagged cells were grid cells, suggesting that stellate cells contribute not only to path-integration-based representation of self-location but also have other functions. The data support observations suggesting that grid cells are not the sole determinant of place cell firing.

Interspike interval analysis and spikelets in presubicular head-direction cells

Head-direction (HD) neurons are thought to provide the mammalian brain with an internal sense of direction. These cells, which selectively increase their firing when the animal's head points in a specific direction, use the spike rate to encode HD with a high signal-to-noise ratio. In the present work, we analyzed spike train features of presubicular HD cells recorded juxtacellularly in passively rotated rats. We found that HD neurons could be classified into two groups on the basis of their propensity to fire spikes at short interspike intervals. "Bursty" neurons displayed distinct spike waveforms and were weakly but significantly more modulated by HD compared with "nonbursty" cells. In a subset of HD neurons, we observed the occurrence of spikelets, small-amplitude "spike-like" events, whose HD tuning was highly correlated to that of the co-recorded juxtacellular spikes. Bursty and nonbursty HD cells, as well as spikelets, were also observed in freely moving animals during natural behavior. We speculate that spike bursts and spikelets might contribute to presubicular HD coding by enhancing its accuracy and transmission reliability to downstream targets. NEW & NOTEWORTHY We provide evidence that presubicular head-direction (HD) cells can be classified into two classes (bursty and nonbursty) on the basis of their propensity to fire spikes at short interspike intervals. Bursty cells displayed distinct electrophysiological properties and stronger directional tuning compared with nonbursty neurons. We also provide evidence for the occurrence of spikelets in a subset of HD cells. These electrophysiological features (spike bursts and spikelets) might contribute to the precision and robustness of the presubicular HD code.

Structural modularity and grid activity in the medial entorhinal cortex

Following the groundbreaking discovery of grid cells, the medial entorhinal cortex (MEC) has become the focus of intense anatomical, physiological, and computational investigations. Whether and how grid activity maps onto cell types and cortical architecture is still an open question. Fundamental similarities in microcircuits, function, and connectivity suggest a homology between rodent MEC and human posteromedial entorhinal cortex. Both are specialized for spatial processing and display similar cellular organization, consisting of layer 2 pyramidal/calbindin cell patches superimposed on scattered stellate neurons. Recent data indicate the existence of a further nonoverlapping modular system (zinc patches) within the superficial MEC layers. Zinc and calbindin patches have been shown to receive largely segregated inputs from the presubiculum and parasubiculum. Grid cells are also clustered in the MEC, and we discuss possible structure-function schemes on how grid activity could map onto cortical patch systems. We hypothesize that in the superficial layers of the MEC, anatomical location can be predictive of function; thus relating functional properties and neuronal morphologies to the cortical modules will be necessary for resolving how grid activity maps onto cortical architecture. Imaging or cell identification approaches in freely moving animals will be required for testing this hypothesis.

Spatial representation in the hippocampal formation: a history

Since the first place cell was recorded and the cognitive-map theory was subsequently formulated, investigation of spatial representation in the hippocampal formation has evolved in stages. Early studies sought to verify the spatial nature of place cell activity and determine its sensory origin. A new epoch started with the discovery of head direction cells and the realization of the importance of angular and linear movement-integration in generating spatial maps. A third epoch began when investigators turned their attention to the entorhinal cortex, which led to the discovery of grid cells and border cells. This review will show how ideas about integration of self-motion cues have shaped our understanding of spatial representation in hippocampal-entorhinal systems from the 1970s until today. It is now possible to investigate how specialized cell types of these systems work together, and spatial mapping may become one of the first cognitive functions to be understood in mechanistic detail.

Grid and Nongrid Cells in Medial Entorhinal Cortex Represent Spatial Location and Environmental Features with Complementary Coding Schemes

The medial entorhinal cortex (mEC) has been identified as a hub for spatial information processing by the discovery of grid, border, and head-direction cells. Here we find that in addition to these well-characterized classes, nearly all of the remaining two-thirds of mEC cells can be categorized as spatially selective. We refer to these cells as nongrid spatial cells and confirmed that their spatial firing patterns were unrelated to running speed and highly reproducible within the same environment. However, in response to manipulations of environmental features, such as box shape or box color, nongrid spatial cells completely reorganized their spatial firing patterns. At the same time, grid cells retained their spatial alignment and predominantly responded with redistributed firing rates across their grid fields. Thus, mEC contains a joint representation of both spatial and environmental feature content, with specialized cell types showing different types of integrated coding of multimodal information.

Bursting Neurons in the Hippocampal Formation Encode Features of LFP Rhythms

Burst spike patterns are common in regions of the hippocampal formation such as the subiculum and medial entorhinal cortex (MEC). Neurons in these areas are immersed in extracellular electrical potential fluctuations often recorded as the local field potential (LFP). LFP rhythms within different frequency bands are linked to different behavioral states. For example, delta rhythms are often associated with slow-wave sleep, inactivity and anesthesia; whereas theta rhythms are prominent during awake exploratory behavior and REM sleep. Recent evidence suggests that bursting neurons in the hippocampal formation can encode LFP features. We explored this hypothesis using a two-compartment model of a bursting pyramidal neuron driven by time-varying input signals containing spectral peaks at either delta or theta rhythms. The model predicted a neural code in which bursts represented the instantaneous value, phase, slope and amplitude of the driving signal both in their timing and size (spike number). To verify whether this code is employed in vivo, we examined electrophysiological recordings from the subiculum of anesthetized rats and the MEC of a behaving rat containing prevalent delta or theta rhythms, respectively. In both areas, we found bursting cells that encoded information about the instantaneous voltage, phase, slope and/or amplitude of the dominant LFP rhythm with essentially the same neural code as the simulated neurons. A fraction of the cells encoded part of the information in burst size, in agreement with model predictions. These results provide in-vivo evidence that the output of bursting neurons in the mammalian brain is tuned to features of the LFP.

Visual landmarks sharpen grid cell metric and confer context specificity to neurons of the medial entorhinal cortex

Neurons of the medial entorhinal cortex (MEC) provide spatial representations critical for navigation. In this network, the periodic firing fields of grid cells act as a metric element for position. The location of the grid firing fields depends on interactions between self-motion information, geometrical properties of the environment and nonmetric contextual cues. Here, we test whether visual information, including nonmetric contextual cues, also regulates the firing rate of MEC neurons. Removal of visual landmarks caused a profound impairment in grid cell periodicity. Moreover, the speed code of MEC neurons changed in darkness and the activity of border cells became less confined to environmental boundaries. Half of the MEC neurons changed their firing rate in darkness. Manipulations of nonmetric visual cues that left the boundaries of a 1D environment in place caused rate changes in grid cells. These findings reveal context specificity in the rate code of MEC neurons.

DOI:http://dx.doi.org/10.7554/eLife.16937.001

Cell Type-Specific Differences in Spike Timing and Spike Shape in the Rat Parasubiculum and Superficial Medial Entorhinal Cortex

The medial entorhinal cortex (MEC) and the adjacent parasubiculum are known for their elaborate spatial discharges (grid cells, border cells, etc.) and the precessing of spikes relative to the local field potential. We know little, however, about how spatio-temporal firing patterns map onto cell types. We find that cell type is a major determinant of spatio-temporal discharge properties. Parasubicular neurons and MEC layer 2 (L2) pyramids have shorter spikes, discharge spikes in bursts, and are theta-modulated (rhythmic, locking, skipping), but spikes phase-precess only weakly. MEC L2 stellates and layer 3 (L3) neurons have longer spikes, do not discharge in bursts, and are weakly theta-modulated (non-rhythmic, weakly locking, rarely skipping), but spikes steeply phase-precess. The similarities between MEC L3 neurons and MEC L2 stellates on one hand and parasubicular neurons and MEC L2 pyramids on the other hand suggest two distinct streams of temporal coding in the parahippocampal cortex.

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We find cell type-specific differences in spike shape, burstiness, and phase precession

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In vivo cell type specificity does not match predictions from previous in vitro studies

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Anatomical identity is a major determinant of spike patterns in the parahippocampal cortex