Intrinsic electrophysiological properties of entorhinal cortex stellate cells and their contribution to grid cell firing fields

Gated transformations from egocentric to allocentric reference frames involving retrosplenial cortex, entorhinal cortex, and hippocampus

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.

Heterogeneous stochastic bifurcations explain intrinsic oscillatory patterns in entorhinal cortical stellate cells

Stellate cells (SC) in the medial entorhinal cortex manifest intrinsic membrane potential oscillatory patterns. Although different theoretical frameworks have been proposed to explain these patterns, a robust unifying framework that jointly accounts for intrinsic heterogeneities and stochasticity is missing. Here, we first performed in vitro patch-clamp electrophysiological recordings from rat SCs and found pronounced cell-to-cell variability in their characteristic physiological properties, including peri-threshold oscillatory patterns. We demonstrate that noise introduced into two independent populations (endowed with deterministic or stochastic ion-channel gating kinetics) of heterogeneous biophysical models yielded activity patterns that were qualitatively similar to electrophysiological peri-threshold oscillatory activity in SCs. We developed spectrogram-based quantitative metrics for the identification of valid oscillations and confirmed that these metrics reliably captured the variable-amplitude and arhythmic oscillatory patterns observed in electrophysiological recordings. Using these quantitative metrics, we validated activity patterns from both heterogeneous populations of SC models, with each model assessed with multiple trials of different levels of noise at distinct membrane depolarizations. Our analyses unveiled the manifestation of stochastic resonance (detection of the highest number of valid oscillatory traces at an optimal level of noise) in both heterogeneous populations of SC models. Finally, we show that a generalized network motif comprised of a slow negative feedback loop amplified by a fast positive feedback loop manifested stochastic bifurcations and stochastic resonance in the emergence of oscillations. Together, through a unique convergence of the degeneracy and stochastic resonance frameworks, our unifying framework centered on heterogeneous stochastic bifurcations argues for state-dependent emergence of SC oscillations.

Resonating neurons stabilize heterogeneous grid-cell networks

A central theme that governs the functional design of biological networks is their ability to sustain stable function despite widespread parametric variability. Here, we investigated the impact of distinct forms of biological heterogeneities on the stability of a two-dimensional continuous attractor network (CAN) implicated in grid-patterned activity generation. We show that increasing degrees of biological heterogeneities progressively disrupted the emergence of grid-patterned activity and resulted in progressively large perturbations in low-frequency neural activity. We postulated that targeted suppression of low-frequency perturbations could ameliorate heterogeneity-induced disruptions of grid-patterned activity. To test this, we introduced intrinsic resonance, a physiological mechanism to suppress low-frequency activity, either by adding an additional high-pass filter (phenomenological) or by incorporating a slow negative feedback loop (mechanistic) into our model neurons. Strikingly, CAN models with resonating neurons were resilient to the incorporation of heterogeneities and exhibited stable grid-patterned firing. We found CAN models with mechanistic resonators to be more effective in targeted suppression of low-frequency activity, with the slow kinetics of the negative feedback loop essential in stabilizing these networks. As low-frequency perturbations (1/f noise) are pervasive across biological systems, our analyses suggest a universal role for mechanisms that suppress low-frequency activity in stabilizing heterogeneous biological networks.

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.

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.

Biomimetic FPGA-based spatial navigation model with grid cells and place cells

The mammalian spatial navigation system is characterized by an initial divergence of internal representations, with disparate classes of neurons responding to distinct features including location, speed, borders and head direction; an ensuing convergence finally enables navigation and path integration. Here, we report the algorithmic and hardware implementation of biomimetic neural structures encompassing a feed-forward trimodular, multi-layer architecture representing grid-cell, place-cell and decoding modules for navigation. The grid-cell module comprised of neurons that fired in a grid-like pattern, and was built of distinct layers that constituted the dorsoventral span of the medial entorhinal cortex. Each layer was built as an independent continuous attractor network with distinct grid-field spatial scales. The place-cell module comprised of neurons that fired at one or few spatial locations, organized into different clusters based on convergent modular inputs from different grid-cell layers, replicating the gradient in place-field size along the hippocampal dorso-ventral axis. The decoding module, a two-layer neural network that constitutes the convergence of the divergent representations in preceding modules, received inputs from the place-cell module and provided specific coordinates of the navigating object. After vital design optimizations involving all modules, we implemented the tri-modular structure on Zynq Ultrascale+ field-programmable gate array silicon chip, and demonstrated its capacity in precisely estimating the navigational trajectory with minimal overall resource consumption involving a mere 2.92% Look Up Table utilization. Our implementation of a biomimetic, digital spatial navigation system is stable, reliable, reconfigurable, real-time with execution time of about 32 s for 100k input samples (in contrast to 40 minutes on Intel Core i7-7700 CPU with 8 cores clocking at 3.60 GHz) and thus can be deployed for autonomous-robotic navigation without requiring additional sensors.

Parvalbumin Interneurons Are Differentially Connected to Principal Cells in Inhibitory Feedback Microcircuits along the Dorsoventral Axis of the Medial Entorhinal Cortex

The medial entorhinal cortex (mEC) shows a high degree of spatial tuning, predominantly grid cell activity, which is reliant on robust, dynamic inhibition provided by local interneurons (INs). In fact, feedback inhibitory microcircuits involving fast-spiking parvalbumin (PV) basket cells (BCs) are believed to contribute dominantly to the emergence of grid cell firing in principal cells (PrCs). However, the strength of PV BC-mediated inhibition onto PrCs is not uniform in this region, but high in the dorsal and weak in the ventral mEC. This is in good correlation with divergent grid field sizes, but the underlying morphologic and physiological mechanisms remain unknown. In this study, we examined PV BCs in layer (L)2/3 of the mEC characterizing their intrinsic physiology, morphology and synaptic connectivity in the juvenile rat. We show that while intrinsic physiology and morphology are broadly similar over the dorsoventral axis, PV BCs form more connections onto local PrCs in the dorsal mEC, independent of target cell type. In turn, the major PrC subtypes, pyramidal cell (PC) and stellate cell (SC), form connections onto PV BCs with lower, but equal probability. These data thus identify inhibitory connectivity as source of the gradient of inhibition, plausibly explaining divergent grid field formation along this dorsoventral axis of the mEC.

Single or Double Patch-Clamp Recordings In Ex Vivo Slice Preparation: Functional Connectivity, Synapse Dynamics, and Optogenetics

Patch-clamp recordings are the method of choice to define cell-type specific electrophysiological properties of single neurons and the synaptic connectivity between pairs of connected neurons in brain slices. In combination with optogenetic tools, patch-clamp recordings allow for the investigation of long-range afferent connectivity from identified distant brain areas. Here we describe the necessary equipment to carry out patch clamp recordings, surgical methods for dissection and preparation of horizontal brain slices containing the hippocampus, and a step-by-step guide for establishing patch clamp recordings in the whole-cell configuration. We provide protocols for single neuron stimulation via the patch pipette and for photostimulation experiments that activate axon terminals expressing light sensitive ion channels.

Grid cells are modulated by local head direction

Grid and head direction codes represent cognitive spaces for navigation and memory. Pure grid cells generate grid codes that have been assumed to be independent of head direction, whereas conjunctive cells generate grid representations that are tuned to a single head direction. Here, we demonstrate that pure grid cells also encode head direction, but through distinct mechanisms. We show that individual firing fields of pure grid cells are tuned to multiple head directions, with the preferred sets of directions differing between fields. This local directional modulation is not predicted by previous continuous attractor or oscillatory interference models of grid firing but is accounted for by models in which pure grid cells integrate inputs from co-aligned conjunctive cells with firing rates that differ between their fields. We suggest that local directional signals from grid cells may contribute to downstream computations by decorrelating different points of view from the same location.

Theta resonance and synaptic modulation scale activity patterns in the medial entorhinal cortex stellate cells

Stellate cells (SCs) of the medial entorhinal cortex (MEC) are rich in hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, which are known to effectively shape their activity patterns. The explanatory mechanisms, however, have remained elusive. One important but previously unassessed possibility is that HCN channels control the gain of synaptic inputs to these cells. Here, we test this possibility in rat brain slices, while subjecting SCs to a stochastic synaptic bombardment using the dynamic clamp. We show that in the presence of synaptic noise, HCN channels mainly exert their influence by increasing the relative signal gain in the theta frequency through the theta modulation of stochastic synaptic inputs. This subthreshold synaptic modulation then translates into a spiking resonance, which steepens with excitation in the presence of HCN channels. We present here a systematic assessment of synaptic theta modulation and trace its implications to the suprathreshold control of firing rate motifs. Such analysis was yet lacking in the SC literature. Furthermore, we assess the impact of noise statistics on this gain modulation and indicate possible mechanisms for the emergence of membrane theta oscillations and synaptic ramps, as observed in vivo. We support the data with a computational model that further unveils a competing role of inhibition, suggesting important implications for MEC computations.

Inter- and intra-animal variation in the integrative properties of stellate cells in the medial entorhinal cortex

Distinctions between cell types underpin organizational principles for nervous system function. Functional variation also exists between neurons of the same type. This is exemplified by correspondence between grid cell spatial scales and the synaptic integrative properties of stellate cells (SCs) in the medial entorhinal cortex. However, we know little about how functional variability is structured either within or between individuals. Using ex-vivo patch-clamp recordings from up to 55 SCs per mouse, we found that integrative properties vary between mice and, in contrast to the modularity of grid cell spatial scales, have a continuous dorsoventral organization. Our results constrain mechanisms for modular grid firing and provide evidence for inter-animal phenotypic variability among neurons of the same type. We suggest that neuron type properties are tuned to circuit-level set points that vary within and between animals.

Regional Specialization of Pyramidal Neuron Morphology and Physiology in the Tree Shrew Neocortex

The mammalian cerebral cortex is divided into different areas according to their function and pattern of connections. Studies comparing primary visual (V1) and prefrontal cortex (PFC) of primates have demonstrated striking pyramidal neuron (PN) specialization not present in comparable areas of the mouse neocortex. To better understand PFC evolution and regional PN specialization, we studied the tree shrew, a species with a close phylogenetic relationship to primates. We defined the tree shrew PFC based on cytoarchitectonic borders, thalamic connectivity and characterized the morphology and electrophysiology of layer II/III PNs in V1 and PFC. Similar to primates, the PFC PNs in the tree shrew fire with a regular spiking pattern and have larger dendritic tree and spines than those in V1. However, V1 PNs showed strikingly large basal dendritic arbors with high spine density, firing at higher rates and in a more varied pattern than PFC PNs. Yet, unlike in the mouse and unreported in the primate, medial prefrontal PN are more easily recruited than either the dorsolateral or V1 neurons. This specialization of PN morphology and physiology is likely to be a significant factor in the evolution of cortex, contributing to differences in the computational capacities of individual cortical areas.

Entorhinal Layer II Calbindin-Expressing Neurons Originate Widespread Telencephalic and Intrinsic Projections

In the present study we provide the first systematic and quantitative hodological study of the calbindin-expressing (CB+) principal neurons in layer II of the entorhinal cortex and compared the respective projections of the lateral and medial subdivisions of the entorhinal cortex. Using elaborate quantitative retrograde tracing, complemented by anterograde tracing, we report that the layer II CB+ population comprises neurons with diverse, mainly excitatory projections. At least half of them originate local intrinsic and commissural projections which distribute mainly to layer I and II. We further show that long-range CB+ projections from the two entorhinal subdivisions differ substantially in that MEC projections mainly target field CA1 of the hippocampus, whereas LEC CB+ projections distribute much more widely to a substantial number of known forebrain targets. This connectional difference between the CB+ populations in LEC and MEC is reminiscent of the overall projection pattern of the two entorhinal subdivisions.

Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells

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An SDE model of entorhinal cortex (EC) stellate cells is proposed.

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Experimentally observed action potential clustering is investigated in the model.

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Clusters are generated by subcritical-Hopf/homoclinic type bursting.

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Potential mechanisms underlying changes in EC dynamics in dementia are presented.

The entorhinal cortex is a crucial component of our memory and spatial navigation systems and is one of the first areas to be affected in dementias featuring tau pathology, such as Alzheimer’s disease and frontotemporal dementia. Electrophysiological recordings from principle cells of medial entorhinal cortex (layer II stellate cells, mEC-SCs) demonstrate a number of key identifying properties including subthreshold oscillations in the theta (4–12 Hz) range and clustered action potential firing. These single cell properties are correlated with network activity such as grid firing and coupling between theta and gamma rhythms, suggesting they are important for spatial memory. As such, experimental models of dementia have revealed disruption of organised dorsoventral gradients in clustered action potential firing.

To better understand the mechanisms underpinning these different dynamics, we study a conductance based model of mEC-SCs. We demonstrate that the model, driven by extrinsic noise, can capture quantitative differences in clustered action potential firing patterns recorded from experimental models of tau pathology and healthy animals. The differential equation formulation of our model allows us to perform numerical bifurcation analyses in order to uncover the dynamic mechanisms underlying these patterns. We show that clustered dynamics can be understood as subcritical Hopf/homoclinic bursting in a fast-slow system where the slow sub-system is governed by activation of the persistent sodium current and inactivation of the slow A-type potassium current. In the full system, we demonstrate that clustered firing arises via flip bifurcations as conductance parameters are varied. Our model analyses confirm the experimentally suggested hypothesis that the breakdown of clustered dynamics in disease occurs via increases in AHP conductance.

Degeneracy in the robust expression of spectral selectivity, subthreshold oscillations, and intrinsic excitability of entorhinal stellate cells

Biological heterogeneities are ubiquitous and play critical roles in the emergence of physiology at multiple scales. Although neurons in layer II (LII) of the medial entorhinal cortex (MEC) express heterogeneities in channel properties, the impact of such heterogeneities on the robustness of their cellular-scale physiology has not been assessed. Here, we performed a 55-parameter stochastic search spanning nine voltage- or calcium-activated channels to assess the impact of channel heterogeneities on the concomitant emergence of 10 in vitro electrophysiological characteristics of LII stellate cells (SCs). We generated 150,000 models and found a heterogeneous subpopulation of 449 valid models to robustly match all electrophysiological signatures. We employed this heterogeneous population to demonstrate the emergence of cellular-scale degeneracy in SCs, whereby disparate parametric combinations expressing weak pairwise correlations resulted in similar models. We then assessed the impact of virtually knocking out each channel from all valid models and demonstrate that the mapping between channels and measurements was many-to-many, a critical requirement for the expression of degeneracy. Finally, we quantitatively predict that the spike-triggered average of SCs should be endowed with theta-frequency spectral selectivity and coincidence detection capabilities in the fast gamma-band. We postulate this fast gamma-band coincidence detection as an instance of cellular-scale-efficient coding, whereby SC response characteristics match the dominant oscillatory signals in LII MEC. The heterogeneous population of valid SC models built here unveils the robust emergence of cellular-scale physiology despite significant channel heterogeneities, and forms an efficacious substrate for evaluating the impact of biological heterogeneities on entorhinal network function.

NEW & NOTEWORTHY We assessed the impact of heterogeneities in channel properties on the robustness of cellular-scale physiology of medial entorhinal cortical stellate neurons. We demonstrate that neuronal models with disparate channel combinations were endowed with similar physiological characteristics, as a consequence of the many-to-many mapping between channel properties and the physiological characteristics that they modulate. We predict that the spike-triggered average of stellate cells should be endowed with theta-frequency spectral selectivity and fast gamma-band coincidence detection capabilities.

Initiation and slow propagation of epileptiform activity from ventral to dorsal medial entorhinal cortex is constrained by an inhibitory gradient

KEY POINTS

The medial entorhinal cortex (mEC) has an important role in initiation and propagation of seizure activity. Several anatomical relationships exist in neurophysiological properties of mEC neurons; however, in the context of hyperexcitability, previous studies often considered it as a homogeneous structure. Using multi-site extracellular recording techniques, ictal-like activity was observed along the dorso-ventral axis of the mEC in vitro in response to various ictogenic stimuli. This originated predominantly from ventral areas, spreading to dorsal mEC with a surprisingly slow velocity. Modulation of inhibitory tone was capable of changing the slope of ictal initiation, suggesting seizure propagation behaviours are highly dependent on levels of GABAergic function in this region. A distinct disinhibition model also showed, in the absence of inhibition, a prevalence for interictal-like initiation in ventral mEC, reflecting the intrinsic differences in mEC neurons. These findings suggest the ventral mEC is more prone to hyperexcitable discharge than the dorsal mEC, which may be relevant under pathological conditions.

ABSTRACT

The medial entorhinal cortex (mEC) has an important role in the generation and propagation of seizure activity. The organization of the mEC is such that a number of dorso-ventral relationships exist in neurophysiological properties of neurons. These range from intrinsic and synaptic properties to density of inhibitory connectivity. We examined the influence of these gradients on generation and propagation of epileptiform activity in the mEC. Using a 16-shank silicon probe array to record along the dorso-ventral axis of the mEC in vitro, we found 4-aminopyridine application produces ictal-like activity originating predominantly in ventral areas. This activity spreads to dorsal mEC at a surprisingly slow velocity (138 μm s^-1 ), while cross-site interictal-like activity appeared relatively synchronous. We propose that ictal propagation is constrained by differential levels of GABAergic control since increasing (diazepam) or decreasing (Ro19-4603) GABA_A receptor activation, respectively, reduced or increased the slope of ictal initiation. The observation that ictal activity is predominately generated in ventral mEC was replicated using a separate 0-Mg²⁺ model of epileptiform activity in vitro. By using a distinct disinhibition model (co-application of kainate and picrotoxin) we show that additional physiological features (for example intrinsic properties of mEC neurons) still produce a prevalence for interictal-like initiation in ventral mEC. These findings suggest that the ventral mEC is more likely to initiate hyperexcitable discharges than the dorsal mEC, and that seizure propagation is highly dependent on levels of GABAergic expression across the mEC.

Synaptic integrative mechanisms for spatial cognition

Synaptic integrative mechanisms have profound effects on electrical signaling in the brain that, although largely hidden from recording methods that observe the spiking activity of neurons, may be critical for the encoding, storage and retrieval of information. Here we review roles for synaptic integrative mechanisms in the selection, generation and plasticity of place and grid fields, and in related temporal codes for the representation of space. We outline outstanding questions and challenges in the testing of hypothesized models for spatial computation and memory.

A single-cell spiking model for the origin of grid-cell patterns

Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity.

An Analysis of Waves Underlying Grid Cell Firing in the Medial Enthorinal Cortex

Layer II stellate cells in the medial enthorinal cortex (MEC) express hyperpolarisation-activated cyclic-nucleotide-gated (HCN) channels that allow for rebound spiking via an [Formula: see text] current in response to hyperpolarising synaptic input. A computational modelling study by Hasselmo (Philos. Trans. R. Soc. Lond. B, Biol. Sci. 369:20120523, 2013) showed that an inhibitory network of such cells can support periodic travelling waves with a period that is controlled by the dynamics of the [Formula: see text] current. Hasselmo has suggested that these waves can underlie the generation of grid cells, and that the known difference in [Formula: see text] resonance frequency along the dorsal to ventral axis can explain the observed size and spacing between grid cell firing fields. Here we develop a biophysical spiking model within a framework that allows for analytical tractability. We combine the simplicity of integrate-and-fire neurons with a piecewise linear caricature of the gating dynamics for HCN channels to develop a spiking neural field model of MEC. Using techniques primarily drawn from the field of nonsmooth dynamical systems we show how to construct periodic travelling waves, and in particular the dispersion curve that determines how wave speed varies as a function of period. This exhibits a wide range of long wavelength solutions, reinforcing the idea that rebound spiking is a candidate mechanism for generating grid cell firing patterns. Importantly we develop a wave stability analysis to show how the maximum allowed period is controlled by the dynamical properties of the [Formula: see text] current. Our theoretical work is validated by numerical simulations of the spiking model in both one and two dimensions.

Active dendritic integration as a mechanism for robust and precise grid cell firing

Understanding how active dendrites are exploited for behaviorally relevant computations is a fundamental challenge in neuroscience. Grid cells in medial entorhinal cortex are an attractive model system for addressing this question, as the computation they perform is clear: they convert synaptic inputs into spatially modulated, periodic firing. Whether active dendrites contribute to the generation of the dual temporal and rate codes characteristic of grid cell output is unknown. We show that dendrites of medial entorhinal cortex neurons are highly excitable and exhibit a supralinear input-output function in vitro, while in vivo recordings reveal membrane potential signatures consistent with recruitment of active dendritic conductances. By incorporating these nonlinear dynamics into grid cell models, we show that they can sharpen the precision of the temporal code and enhance the robustness of the rate code, thereby supporting a stable, accurate representation of space under varying environmental conditions. Our results suggest that active dendrites may therefore constitute a key cellular mechanism for ensuring reliable spatial navigation.

Physiological roles of Kv2 channels in entorhinal cortex layer II stellate cells revealed by Guangxitoxin-1E

KEY POINTS

Kv2 channels underlie delayed-rectifier potassium currents in various neurons, although their physiological roles often remain elusive. Almost nothing is known about Kv2 channel functions in medial entorhinal cortex (mEC) neurons, which are involved in representing space, memory formation, epilepsy and dementia. Stellate cells in layer II of the mEC project to the hippocampus and are considered to be space-representing grid cells. We used the new Kv2 blocker Guangxitoxin-1E (GTx) to study Kv2 functions in these neurons. Voltage clamp recordings from mEC stellate cells in rat brain slices showed that GTx inhibited delayed-rectifier K+ current but not transient A-type current. In current clamp, GTx had multiple effects: (i) increasing excitability and bursting at moderate spike rates but reducing firing at high rates; (ii) enhancing after-depolarizations; (iii) reducing the fast and medium after-hyperpolarizations; (iv) broadening action potentials; and (v) reducing spike clustering. GTx is a useful tool for studying Kv2 channels and their functions in neurons.

ABSTRACT

The medial entorhinal cortex (mEC) is strongly involved in spatial navigation, memory, dementia and epilepsy. Although potassium channels shape neuronal activity, their roles in mEC are largely unknown. We used the new Kv2 blocker Guangxitoxin-1E (GTx; 10-100 nm) in rat brain slices to investigate Kv2 channel functions in mEC layer II stellate cells (SCs). These neurons project to the hippocampus and are considered to be grid cells representing space. Voltage clamp recordings from SCs nucleated patches showed that GTx inhibited a delayed rectifier K+ current activating beyond -30 mV but not transient A-type current. In current clamp, GTx (i) had almost no effect on the first action potential but markedly slowed repolarization of late spikes during repetitive firing; (ii) enhanced the after-depolarization (ADP); (iii) reduced fast and medium after-hyperpolarizations (AHPs); (iv) strongly enhanced burst firing and increased excitability at moderate spike rates but reduced spiking at high rates; and (v) reduced spike clustering and rebound potentials. The changes in bursting and excitability were related to the altered ADPs and AHPs. Kv2 channels strongly shape the activity of mEC SCs by affecting spike repolarization, after-potentials, excitability and spike patterns. GTx is a useful tool and may serve to further clarify Kv2 channel functions in neurons. We conclude that Kv2 channels in mEC SCs are important determinants of intrinsic properties that allow these neurons to produce spatial representation. The results of the present study may also be important for the accurate modelling of grid cells.

Physiological Properties of Neurons in Bat Entorhinal Cortex Exhibit an Inverse Gradient along the Dorsal-Ventral Axis Compared to Entorhinal Neurons in Rat

Medial entorhinal cortex (MEC) grid cells exhibit firing fields spread across the environment on the vertices of a regular tessellating triangular grid. In rodents, the size of the firing fields and the spacing between the firing fields are topographically organized such that grid cells located more ventrally in MEC exhibit larger grid fields and larger grid-field spacing compared with grid cells located more dorsally. Previous experiments in brain slices from rodents have shown that several intrinsic cellular electrophysiological properties of stellate cells in layer II of MEC change systematically in neurons positioned along the dorsal-ventral axis of MEC, suggesting that these intrinsic cellular properties might control grid-field spacing. In the bat, grid cells in MEC display a functional topography in terms of grid-field spacing, similar to what has been reported in rodents. However, it is unclear whether neurons in bat MEC exhibit similar gradients of cellular physiological properties, which may serve as a conserved mechanism underlying grid-field spacing in mammals. To test whether entorhinal cortex (EC) neurons in rats and bats exhibit similar electrophysiological gradients, we performed whole-cell patch recordings along the dorsal-ventral axis of EC in bats. Surprisingly, our data demonstrate that the sag response properties and the resonance properties recorded in layer II neurons of entorhinal cortex in the Egyptian fruit bat demonstrate an inverse relationship along the dorsal-ventral axis compared with the rat.

SIGNIFICANCE STATEMENT

As animals navigate, neurons in medial entorhinal cortex (MEC), termed grid cells, discharge at regular spatial intervals. In bats and rats, the spacing between the firing fields of grid cells changes systematically along the dorsal-ventral axis of MEC. It has been proposed that these changes could be generated by systematic differences in the intrinsic cellular physiology of neurons distributed along the dorsal-ventral axis of MEC. The results from our study show that key intrinsic physiological properties of neurons in entorhinal cortex of the bat and rat change in the opposite direction along the dorsal-ventral axis of entorhinal cortex, suggesting that these intrinsic physiological properties cannot account in the same way across species for the change in grid-field spacing shown along the dorsal-ventral axis.

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

Electrical and Network Neuronal Properties Are Preferentially Disrupted in Dorsal, But Not Ventral, Medial Entorhinal Cortex in a Mouse Model of Tauopathy

The entorhinal cortex (EC) is one of the first areas to be disrupted in neurodegenerative diseases such as Alzheimer's disease and frontotemporal dementia. The responsiveness of individual neurons to electrical and environmental stimuli varies along the dorsal-ventral axis of the medial EC (mEC) in a manner that suggests this topographical organization plays a key role in neural encoding of geometric space. We examined the cellular properties of layer II mEC stellate neurons (mEC-SCs) in rTg4510 mice, a rodent model of neurodegeneration. Dorsoventral gradients in certain intrinsic membrane properties, such as membrane capacitance and afterhyperpolarizations, were flattened in rTg4510 mEC-SCs, while other cellular gradients [e.g., input resistance (Ri), action potential properties] remained intact. Specifically, the intrinsic properties of rTg4510 mEC-SCs in dorsal aspects of the mEC were preferentially affected, such that action potential firing patterns in dorsal mEC-SCs were altered, while those in ventral mEC-SCs were unaffected. We also found that neuronal oscillations in the gamma frequency band (30-80 Hz) were preferentially disrupted in the dorsal mEC of rTg4510 slices, while those in ventral regions were comparatively preserved. These alterations corresponded to a flattened dorsoventral gradient in theta-gamma cross-frequency coupling of local field potentials recorded from the mEC of freely moving rTg4510 mice. These differences were not paralleled by changes to the dorsoventral gradient in parvalbumin staining or neurodegeneration. We propose that the selective disruption to dorsal mECs, and the resultant flattening of certain dorsoventral gradients, may contribute to disturbances in spatial information processing observed in this model of dementia.

SIGNIFICANCE STATEMENT

The medial entorhinal cortex (mEC) plays a key role in spatial memory and is one of the first areas to express the pathological features of dementia. Neurons of the mEC are anatomically arranged to express functional dorsoventral gradients in a variety of neuronal properties, including grid cell firing field spacing, which is thought to encode geometric scale. We have investigated the effects of tau pathology on functional dorsoventral gradients in the mEC. Using electrophysiological approaches, we have shown that, in a transgenic mouse model of dementia, the functional properties of the dorsal mEC are preferentially disrupted, resulting in a flattening of some dorsoventral gradients. Our data suggest that neural signals arising in the mEC will have a reduced spatial content in dementia.

Continuous attractor network models of grid cell firing based on excitatory-inhibitory interactions

Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid‐like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid‐like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state. We focus on properties of continuous attractor networks that are revealed by explicitly considering excitatory and inhibitory neurons, their connectivity and their membrane potential dynamics. Models at this level of detail can account for theta‐nested gamma oscillations as well as grid firing, predict spatial firing of interneurons as well as excitatory cells, show how gamma oscillations can be modulated independently from spatial computations, reveal critical roles for neuronal noise, and demonstrate that only a subset of excitatory cells in a network need have grid‐like firing fields. Evaluating experimental data against predictions from detailed network models will be important for establishing the mechanisms mediating grid firing.

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

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

Molecularly Defined Circuitry Reveals Input-Output Segregation in Deep Layers of the Medial Entorhinal Cortex

Deep layers of the medial entorhinal cortex are considered to relay signals from the hippocampus to other brain structures, but pathways for routing of signals to and from the deep layers are not well established. Delineating these pathways is important for a circuit level understanding of spatial cognition and memory. We find that neurons in layers 5a and 5b have distinct molecular identities, defined by the transcription factors Etv1 and Ctip2, and divergent targets, with extensive intratelencephalic projections originating in layer 5a, but not 5b. This segregation of outputs is mirrored by the organization of glutamatergic input from stellate cells in layer 2 and from the hippocampus, with both preferentially targeting layer 5b over 5a. Our results suggest a molecular and anatomical organization of input-output computations in deep layers of the MEC, reveal precise translaminar microcircuitry, and identify molecularly defined pathways for spatial signals to influence computation in deep layers.

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The transcription factors Etv1 and Ctip2 distinguish entorhinal layers 5a and 5b

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Layer 5a has extensive intratelencephalic projections, but layer 5b does not

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Terminals of layer 2 stellate, but not pyramidal cells, are enriched in deep layers

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Hippocampal and stellate cell inputs preferentially target layer 5b neurons

If I had a million neurons: Potential tests of cortico-hippocampal theories

Considerable excitement surrounds new initiatives to develop techniques for simultaneous recording of large populations of neurons in cortical structures. This chapter focuses on the potential value of large-scale simultaneous recording for advancing research on current issues in the function of cortical circuits, including the interaction of the hippocampus with cortical and subcortical structures. The review describes specific research questions that could be answered using large-scale population recording, including questions about the circuit dynamics underlying coding of dimensions of space and time for episodic memory, the role of GABAergic and cholinergic innervation from the medial septum, the functional role of spatial representations coded by grid cells, boundary cells, head direction cells, and place cells, and the fact that many models require cells coding movement direction.

Current questions on space and time encoding

The Nobel Prize in Physiology or Medicine 2014 celebrated the groundbreaking findings on place cells and grid cells by John O'Keefe and May-Britt Moser and Edvard Moser. These findings provided an essential foothold for understanding the cognitive encoding of space and time in episodic memory function. This foothold provides a closer view of a broad new world of important research questions raised by the phenomena of place cells and grid cells. These questions concern the mechanisms of generation of place and grid cell firing, including sensory influences, circuit dynamics and intrinsic properties. Similar questions concern the generation of time cells. In addition, questions concern the functional role of place cells, grid cells and time cells in mediating goal-directed behavior and episodic memory function.

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.

Nonlinear properties of medial entorhinal cortex neurons reveal frequency selectivity during multi-sinusoidal stimulation

The neurons in layer II of the medial entorhinal cortex are part of the grid cell network involved in the representation of space. Many of these neurons are likely to be stellate cells with specific oscillatory and firing properties important for their function. A fundamental understanding of the nonlinear basis of these oscillatory properties is critical for the development of theories of grid cell firing. In order to evaluate the behavior of stellate neurons, measurements of their quadratic responses were used to estimate a second order Volterra kernel. This paper uses an operator theory, termed quadratic sinusoidal analysis (QSA), which quantitatively determines that the quadratic response accounts for a major part of the nonlinearity observed at membrane potential levels characteristic of normal synaptic events. Practically, neurons were probed with multi-sinusoidal stimulations to determine a Hermitian operator that captures the quadratic function in the frequency domain. We have shown that the frequency content of the stimulation plays an important role in the characteristics of the nonlinear response, which can distort the linear response as well. Stimulations with enhanced low frequency amplitudes evoked a different nonlinear response than broadband profiles. The nonlinear analysis was also applied to spike frequencies and it was shown that the nonlinear response of subthreshold membrane potential at resonance frequencies near the threshold is similar to the nonlinear response of spike trains.

Membrane potential-dependent integration of synaptic inputs in entorhinal stellate neurons

Stellate cells (SCs) of the medial entorhinal cortex exhibit robust spontaneous membrane-potential oscillations (MPOs) in the theta (4-12 Hz) frequency band as well as theta-frequency resonance in their membrane impedance spectra. Past experimental and modeling work suggests that these features may contribute to the phase-locking of SCs to the entorhinal theta rhythm and may be important for forming the hexagonally tiled grid cell place fields exhibited by these neurons in vivo. Among the major biophysical mechanisms contributing to MPOs is a population of persistent (non-inactivating or slowly inactivating) sodium channels. The resulting persistent sodium conductance (GNaP ) gives rise to an apparent increase in input resistance as the cell approaches threshold. In this study, we used dynamic clamp to test the hypothesis that this increased input resistance gives rise to voltage-dependent, and thus MPO phase-dependent, changes in the amplitude of excitatory and inhibitory post-synaptic potential (PSP) amplitudes. We find that PSP amplitude depends on membrane potential, exhibiting a 5-10% increase in amplitude per mV depolarization. The effect is larger than-and sums quasi-linearly with-the effect of the synaptic driving force, V - Esyn . Given that input-driven MPOs 10 mV in amplitude are commonly observed in MEC stellate cells in vivo, this voltage- and phase-dependent synaptic gain is large enough to modulate PSP amplitude by over 50% during theta-frequency MPOs. Phase-dependent synaptic gain may therefore impact the phase locking and phase precession of grid cells in vivo to ongoing network oscillations. © 2014 Wiley Periodicals, Inc.

DC-shifts in amplitude in-field generated by an oscillatory interference model of grid cell firing

Oscillatory interference models propose a mechanism by which the spatial firing pattern of grid cells can arise from the interaction of multiple oscillators that shift in relative phase. These models produce aspects of the physiological data such as the phase precession dynamics observed in grid cells. However, existing oscillatory interference models did not predict the in-field DC shifts in the membrane potential of grid cells that have been observed during intracellular recordings in navigating animals. Here, we demonstrate that DC shifts can be generated in an oscillatory interference model when half-wave rectified oscillatory inputs are summed by a leaky integrate-and-fire neuron with a long membrane decay constant (100 ms). The non-linear mean of the half-wave rectified input signal is reproduced in the grid cell's membrane potential trace producing the DC shift within field. For shorter values of the decay constant integration is more effective if the input signal, comprising input from 6 head direction selective populations, is temporally spread during in-field epochs; this requires that the head direction selective populations act as velocity controlled oscillators with baseline oscillations that are phase offset from one another. The resulting simulated membrane potential matches several properties of the empirical intracellular recordings, including: in-field DC-shifts, theta-band oscillations, phase precession of both membrane potential oscillations and grid cell spiking activity relative to network theta and a stronger correlation between DC-shift amplitude and firing-rate than between theta-band oscillation amplitude and firing-rate. This work serves to demonstrate that oscillatory interference models can account for the DC shifts in the membrane potential observed during intracellular recordings of grid cells without the need to appeal to attractor dynamics.

Neuronal rebound spiking, resonance frequency and theta cycle skipping may contribute to grid cell firing in medial entorhinal cortex

Data show a relationship of cellular resonance and network oscillations in the entorhinal cortex to the spatial periodicity of grid cells. This paper presents a model that simulates the resonance and rebound spiking properties of entorhinal neurons to generate spatial periodicity dependent upon phasic input from medial septum. The model shows that a difference in spatial periodicity can result from a difference in neuronal resonance frequency that replicates data from several experiments. The model also demonstrates a functional role for the phenomenon of theta cycle skipping in the medial entorhinal cortex.

How to build a grid cell

Neurons in the medial entorhinal cortex fire action potentials at regular spatial intervals, creating a striking grid-like pattern of spike rates spanning the whole environment of a navigating animal. This remarkable spatial code may represent a neural map for path integration. Recent advances using patch-clamp recordings from entorhinal cortex neurons in vitro and in vivo have revealed how the microcircuitry in the medial entorhinal cortex may contribute to grid cell firing patterns, and how grid cells may transform synaptic inputs into spike output during firing field crossings. These new findings provide key insights into the ingredients necessary to build a grid cell.

Firing properties of entorhinal cortex neurons and early alterations in an Alzheimer's disease transgenic model

The entorhinal cortex (EC) is divided into medial (MEC) and lateral (LEC) anatomical areas, and layer II neurons of these two regions project to granule cells of the dentate gyrus through the medial and lateral perforant pathways (MPP and LPP), respectively. Stellate cells (SCs) represent the main neurons constituting the MPP inputs, while fan cells (FCs) represent the main LPP inputs. Here, we first characterized the excitability properties of SCs and FCs in adult wild-type (WT) mouse brain. Our data indicate that, during sustained depolarization, action potentials (APs) generated by SCs exhibit increased fast afterhyperpolarization and overshoot, making them able to fire at higher frequencies and to exhibit higher spike frequency adaptation (SFA) than FCs. Since the EC is one of the earliest brain regions affected during Alzheimer's disease (AD) progression, we compared SCs and FCs firing in 4-month-old WT and transgenic Tg2576 mice, a well-established AD mouse model. Tg2576-SCs displayed a slight increase in firing frequency during mild depolarization but otherwise normal excitability properties during higher stimulations. On the contrary, Tg2576-FCs exhibited a decreased firing frequency during mild and higher depolarizations, as well as an increased SFA. Our data identify the FCs as a neuronal population particularly sensitive to early pathological effects of chronic accumulation of APP-derived peptides, as it occurs in Tg2576 mice. As FCs represent the major input of sensory information to the hippocampus during memory acquisition, early alterations in their excitability profile could significantly contribute to the onset of cognitive decline in AD.

Comparison of properties of medial entorhinal cortex layer II neurons in two anatomical dimensions with and without cholinergic activation

Mechanisms underlying grid cell firing in the medial entorhinal cortex (MEC) still remain unknown. Computational modeling studies have suggested that cellular properties such as spike frequency adaptation and persistent firing might underlie the grid cell firing. Recent in vivo studies also suggest that cholinergic activation influences grid cell firing. Here we investigated the anatomical distribution of firing frequency adaptation, the medium spike after hyperpolarization potential (mAHP), subthreshold membrane potential oscillations, sag potential, input resistance and persistent firing, in MEC layer II principal cells using in vitro whole-cell patch clamp recordings in rats. Anatomical distributions of these properties were compared along both the dorso-ventral and medio-lateral axes, both with and without the cholinergic receptor agonist carbachol. We found that spike frequency adaptation is significantly stronger in ventral than in dorsal neurons both with and without carbachol. Spike frequency adaptation was significantly correlated with the duration of the mAHP, which also showed a gradient along the dorso-ventral axis. In carbachol, we found that about 50% of MEC layer II neurons show persistent firing which lasted more than 30 seconds. Persistent firing of MEC layer II neurons might contribute to grid cell firing by providing the excitatory drive. Dorso-ventral differences in spike frequency adaptation we report here are opposite from previous predictions by a computational model. We discuss an alternative mechanism as to how dorso-ventral differences in spike frequency adaptation could contribute to different scales of grid spacing.

Theta rhythm and the encoding and retrieval of space and time

Physiological data demonstrates theta frequency oscillations associated with memory function and spatial behavior. Modeling and data from animals provide a perspective on the functional role of theta rhythm, including correlations with behavioral performance and coding by timing of spikes relative to phase of oscillations. Data supports a theorized role of theta rhythm in setting the dynamics for encoding and retrieval within cortical circuits. Recent data also supports models showing how network and cellular theta rhythmicity allows neurons in the entorhinal cortex and hippocampus to code time and space as a possible substrate for encoding events in episodic memory. Here we discuss these models and relate them to current physiological and behavioral data.

Feedback inhibition enables θ-nested γ oscillations and grid firing fields

Cortical circuits are thought to multiplex firing rate codes with temporal codes that rely on oscillatory network activity, but the circuit mechanisms that combine these coding schemes are unclear. We establish with optogenetic activation of layer II of the medial entorhinal cortex that theta frequency drive to this circuit is sufficient to generate nested gamma frequency oscillations in synaptic activity. These nested gamma oscillations closely resemble activity during spatial exploration, are generated by local feedback inhibition without recurrent excitation, and have clock-like features suitable as reference signals for multiplexing temporal codes within rate-coded grid firing fields. In network models deduced from our data, feedback inhibition supports coexistence of theta-nested gamma oscillations with attractor states that generate grid firing fields. These results indicate that grid cells communicate primarily via inhibitory interneurons. This circuit mechanism enables multiplexing of oscillation-based temporal codes with rate-coded attractor states.

Contribution of near-threshold currents to intrinsic oscillatory activity in rat medial entorhinal cortex layer II stellate cells

The temporal lobe is well known for its oscillatory activity associated with exploration, navigation, and learning. Intrinsic membrane potential oscillations (MPOs) and resonance of stellate cells (SCs) in layer II of the entorhinal cortex are thought to contribute to network oscillations and thereby to the encoding of spatial information. Generation of both MPOs and resonance relies on the expression of specific voltage-dependent ion currents such as the hyperpolarization-activated cation current (I(H)), the persistent sodium current (I(NaP)), and the noninactivating muscarine-modulated potassium current (I(M)). However, the differential contributions of these currents remain a matter of debate. We therefore examined how they modify neuronal excitability near threshold and generation of near-threshold MPOs and resonance in vitro. We found that resonance mainly relied on I(H) and was reduced by I(H) blockers and modulated by cAMP and an I(M) enhancer but that neither of the currents exhibited full control over MPOs in these cells. As previously reported, I(H) controlled a theta-frequency component of MPOs such that blockade of I(H) resulted in fewer regular oscillations that retained low-frequency components and high peak amplitude. However, pharmacological inhibition and augmentation of I(M) also affected MPO frequencies and amplitudes. In contrast to other cell types, inhibition of I(NaP) did not result in suppression of MPOs but only in a moderation of their properties. We reproduced the experimentally observed effects in a single-compartment stochastic model of SCs, providing further insight into the interactions between different ionic conductances.