Tuning of synaptic integration in the medial entorhinal cortex to the organization of grid cell firing fields

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

Environmental boundaries as an error correction mechanism for grid cells

Medial entorhinal grid cells fire in periodic, hexagonally patterned locations and are proposed to support path-integration-based navigation. The recursive nature of path integration results in accumulating error and, without a corrective mechanism, a breakdown in the calculation of location. The observed long-term stability of grid patterns necessitates that the system either performs highly precise internal path integration or implements an external landmark-based error correction mechanism. To distinguish these possibilities, we examined grid cells in behaving rodents as they made long trajectories across an open arena. We found that error accumulates relative to time and distance traveled since the animal last encountered a boundary. This error reflects coherent drift in the grid pattern. Further, interactions with boundaries yield direction-dependent error correction, suggesting that border cells serve as a neural substrate for error correction. These observations, combined with simulations of an attractor network grid cell model, demonstrate that landmarks are crucial to grid stability.

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.

Dorsoventral differences in Kv7/M-current and its impact on resonance, temporal summation and excitability in rat hippocampal pyramidal cells

In rodent hippocampi, the connections, gene expression and functions differ along the dorsoventral (D-V) axis. CA1 pyramidal cells show increasing excitability along the D-V axis, although the underlying mechanism is not known. In the present study, we investigated how the M-current (IM ), caused by Kv7/M (KCNQ) potassium channels, and known to often control neuronal excitability, contributes to D-V differences in intrinsic properties of CA1 pyramidal cells. Using whole-cell patch clamp recordings and the selective Kv7/M blocker 10,10-bis(4-pyridinylmethyl)-9(10H)-anthracenone dihydrochloride (XE991) in hippocampal slices from 3- to 4-week-old rats, we found that: (i) IM had a stronger impact on subthreshold electrical properties in dorsal than ventral CA1 pyramidal cells, including input resistance, temporal summation of artificial synaptic potentials, and M-resonance; (ii) IM activated at more negative potentials (left-shifted) and had larger peak amplitude in the dorsal than ventral CA1; and (iii) the initial spike threshold (during ramp depolarizations) was elevated, and the medium after-hyperpolarization and spike frequency adaptation were increased (i.e. excitability was lower) in the dorsal rather than ventral CA1. These differences were abolished or reduced by application of XE991, indicating that they were caused by IM . Thus, it appears that IM has stronger effects in dorsal than in ventral rat CA1 pyramidal cells because of a larger maximal M-conductance and left-shifted activation curve in the dorsal cells. These mechanisms may contribute to D-V differences in the rate and phase coding of position by CA1 place cells, and may also enhance epileptiform activity in ventral CA1.

GABAergic projections from the medial septum selectively inhibit interneurons in the medial entorhinal cortex

The medial septum (MS) is required for theta rhythmic oscillations and grid cell firing in the medial entorhinal cortex (MEC). While GABAergic, glutamatergic, and cholinergic neurons project from the MS to the MEC, their synaptic targets are unknown. To investigate whether MS neurons innervate specific layers and cell types in the MEC, we expressed channelrhodopsin-2 in mouse MS neurons and used patch-clamp recording in brain slices to determine the response to light activation of identified cells in the MEC. Following activation of MS axons, we observed fast monosynaptic GABAergic IPSPs in the majority (>60%) of fast-spiking (FS) and low-threshold-spiking (LTS) interneurons in all layers of the MEC, but in only 1.5% of nonstellate principal cells (NSPCs) and in no stellate cells. We also observed fast glutamatergic responses to MS activation in a minority (<5%) of NSPCs, FS, and LTS interneurons. During stimulation of MS inputs at theta frequency (10 Hz), the amplitude of GABAergic IPSPs was maintained, and spike output from LTS and FS interneurons was entrained at low (25-60 Hz) and high (60-180 Hz) gamma frequencies, respectively. By demonstrating cell type-specific targeting of the GABAergic projection from the MS to the MEC, our results support the idea that the MS controls theta frequency activity in the MEC through coordination of inhibitory circuits.

Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression

Neural circuits in the medial entorhinal cortex (MEC) encode an animal's position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations.

The functional micro-organization of grid cells revealed by cellular-resolution imaging

Establishing how grid cells are anatomically arranged, on a microscopic scale, in relation to their firing patterns in the environment would facilitate a greater microcircuit-level understanding of the brain's representation of space. However, all previous grid cell recordings used electrode techniques that provide limited descriptions of fine-scale organization. We therefore developed a technique for cellular-resolution functional imaging of medial entorhinal cortex (MEC) neurons in mice navigating a virtual linear track, enabling a new experimental approach to study MEC. Using these methods, we show that grid cells are physically clustered in MEC compared to nongrid cells. Additionally, we demonstrate that grid cells are functionally micro-organized: the similarity between the environment firing locations of grid cell pairs varies as a function of the distance between them according to a "Mexican hat"-shaped profile. This suggests that, on average, nearby grid cells have more similar spatial firing phases than those further apart.

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.

A model of grid cell development through spatial exploration and spike time-dependent plasticity

Grid cell responses develop gradually after eye opening, but little is known about the rules that govern this process. We present a biologically plausible model for the formation of a grid cell network. An asymmetric spike time-dependent plasticity rule acts upon an initially unstructured network of spiking neurons that receive inputs encoding animal velocity and location. Neurons develop an organized recurrent architecture based on the similarity of their inputs, interacting through inhibitory interneurons. The mature network can convert velocity inputs into estimates of animal location, showing that spatially periodic responses and the capacity of path integration can arise through synaptic plasticity, acting on inputs that display neither. The model provides numerous predictions about the necessity of spatial exploration for grid cell development, network topography, the maturation of velocity tuning and neural correlations, the abrupt transition to stable patterned responses, and possible mechanisms to set grid period across grid modules.

Contribution of Ih to the relative facilitation of synaptic responses induced by carbachol in the entorhinal cortex during repetitive stimulation of the parasubiculum

Neurons in the superficial layers of the entorhinal cortex provide the hippocampus with the majority of its cortical sensory input, and also receive the major output projection from the parasubiculum. This puts the parasubiculum in a position to modulate the activity of entorhinal neurons that project to the hippocampus. These brain areas receive cholinergic projections that are active during periods of theta- and gamma-frequency electroencephalographic (EEG) activity. The purpose of this study was to investigate how cholinergic receptor activation affects the strength of repetitive synaptic responses at these frequencies in the parasubiculo-entorhinal pathway and the cellular mechanisms involved. Whole-cell patch-clamp recordings of rat layer II medial entorhinal neurons were conducted using an acute slice preparation, and responses to 5-pulse trains of stimulation at theta- and gamma-frequency delivered to the parasubiculum were recorded. The cholinergic agonist carbachol (CCh) suppressed the amplitude of single synaptic responses, but also produced a relative facilitation of synaptic responses evoked during stimulation trains. The N-methyl-d-aspartate (NMDA) glutamate receptor blocker APV did not significantly reduce the relative facilitation effect. However, the hyperpolarization-activated cationic current (Ih) channel blocker ZD7288 mimicked the relative facilitation induced by CCh, suggesting that CCh-induced inhibition of Ih could produce the effect by increasing dendritic input resistance (Rin). Inward-rectifying and leak K(+) currents are known to interact with Ih to affect synaptic excitability. Application of the K(+) channel antagonist Ba(2+) depolarized neurons and enhanced temporal summation, but did not block further facilitation of train-evoked responses by ZD7288. The Ih-dependent facilitation of synaptic responses can therefore occur during reductions in inward-rectifying potassium current (IKir) associated with dendritic depolarization. Thus, in addition to cholinergic reductions in transmitter release that are known to facilitate train-evoked responses, these findings emphasize the role of inhibition of Ih in the integration of synaptic inputs within the entorhinal cortex during cholinergically-induced oscillatory states, likely due to enhanced summation of excitatory postsynaptic potentials (EPSPs) induced by increases in dendritic Rin.

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.

Expression and functional roles of Kv7/KCNQ/M-channels in rat medial entorhinal cortex layer II stellate cells

The medial entorhinal cortex (MEC) is important for spatial navigation and memory. Stellate cells (SCs) of MEC layer II provide major input to the hippocampus, and are thought to be the neuronal correlate of the grid cells. Their electrophysiological properties have been used to explain grid field formation. However, little is known about the functional roles of potassium channels in SCs. M-current is a slowly activating potassium current, active at subthreshold potentials. Although some studies have suggested that Kv7/M-channels may affect subthreshold resonance in SCs, others have found no Kv7/M-current in these cells, so the expression and roles of Kv7/M-channels in SCs are still debated. Using whole-cell voltage-clamp, we have identified a typical M-current with pharmacological properties characteristic of Kv7/M-channels in rat MEC SCs. Current-clamp experiments showed that the specific Kv7/M-channel blocker XE991 increased SCs excitability, and reduced spike frequency adaptation. Our results demonstrate that Kv7/M-channels are expressed in SCs and contribute substantially to regulation of excitability in these cells.

Controlling phase noise in oscillatory interference models of grid cell firing

Oscillatory interference models account for the spatial firing properties of grid cells in terms of neuronal oscillators with frequencies modulated by the animal's movement velocity. The phase of such a "velocity-controlled oscillator" (VCO) relative to a baseline (theta-band) oscillation tracks displacement along a preferred direction. Input from multiple VCOs with appropriate preferred directions causes a grid cell's grid-like firing pattern. However, accumulating phase noise causes the firing pattern to drift and become corrupted. Here we show how multiple redundant VCOs can automatically compensate for phase noise. By entraining the baseline frequency to the mean VCO frequency, VCO phases remain consistent, ensuring a coherent grid pattern and reducing its spatial drift. We show how the spatial stability of grid firing depends on the variability in VCO phases, e.g., a phase SD of 3 ms per 125 ms cycle results in stable grids for 1 min. Finally, coupling N VCOs with similar preferred directions as a ring attractor, so that their relative phases remain constant, produces grid cells with consistently offset grids, and reduces VCO phase variability of the order square root of N. The results suggest a viable functional organization of the grid cell network, and highlight the benefit of integrating displacement along multiple redundant directions for the purpose of path integration.

How does the modular organization of entorhinal grid cells develop?

The entorhinal-hippocampal system plays a crucial role in spatial cognition and navigation. Since the discovery of grid cells in layer II of medial entorhinal cortex (MEC), several types of models have been proposed to explain their development and operation; namely, continuous attractor network models, oscillatory interference models, and self-organizing map (SOM) models. Recent experiments revealing the in vivo intracellular signatures of grid cells (Domnisoru et al., 2013; Schmidt-Heiber and Hausser, 2013), the primarily inhibitory recurrent connectivity of grid cells (Couey et al., 2013; Pastoll et al., 2013), and the topographic organization of grid cells within anatomically overlapping modules of multiple spatial scales along the dorsoventral axis of MEC (Stensola et al., 2012) provide strong constraints and challenges to existing grid cell models. This article provides a computational explanation for how MEC cells can emerge through learning with grid cell properties in modular structures. Within this SOM model, grid cells with different rates of temporal integration learn modular properties with different spatial scales. Model grid cells learn in response to inputs from multiple scales of directionally-selective stripe cells (Krupic et al., 2012; Mhatre et al., 2012) that perform path integration of the linear velocities that are experienced during navigation. Slower rates of grid cell temporal integration support learned associations with stripe cells of larger scales. The explanatory and predictive capabilities of the three types of grid cell models are comparatively analyzed in light of recent data to illustrate how the SOM model overcomes problems that other types of models have not yet handled.

A unified mathematical framework for coding time, space, and sequences in the hippocampal region

The medial temporal lobe (MTL) is believed to support episodic memory, vivid recollection of a specific event situated in a particular place at a particular time. There is ample neurophysiological evidence that the MTL computes location in allocentric space and more recent evidence that the MTL also codes for time. Space and time represent a similar computational challenge; both are variables that cannot be simply calculated from the immediately available sensory information. We introduce a simple mathematical framework that computes functions of both spatial location and time as special cases of a more general computation. In this framework, experience unfolding in time is encoded via a set of leaky integrators. These leaky integrators encode the Laplace transform of their input. The information contained in the transform can be recovered using an approximation to the inverse Laplace transform. In the temporal domain, the resulting representation reconstructs the temporal history. By integrating movements, the equations give rise to a representation of the path taken to arrive at the present location. By modulating the transform with information about allocentric velocity, the equations code for position of a landmark. Simulated cells show a close correspondence to neurons observed in various regions for all three cases. In the temporal domain, novel secondary analyses of hippocampal time cells verified several qualitative predictions of the model. An integrated representation of spatiotemporal context can be computed by taking conjunctions of these elemental inputs, leading to a correspondence with conjunctive neural representations observed in dorsal CA1.

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.

Grid-layout and theta-modulation of layer 2 pyramidal neurons in medial entorhinal cortex

Little is known about how microcircuits are organized in layer 2 of the medial entorhinal cortex. We visualized principal cell microcircuits and determined cellular theta-rhythmicity in freely moving rats. Non-dentate-projecting, calbindin-positive pyramidal cells bundled dendrites together and formed patches arranged in a hexagonal grid aligned to layer 1 axons, parasubiculum, and cholinergic inputs. Calbindin-negative, dentate-gyrus-projecting stellate cells were distributed across layer 2 but avoided centers of calbindin-positive patches. Cholinergic drive sustained theta-rhythmicity, which was twofold stronger in pyramidal than in stellate neurons. Theta-rhythmicity was cell-type-specific but not distributed as expected from cell-intrinsic properties. Layer 2 divides into a weakly theta-locked stellate cell lattice and spatiotemporally highly organized pyramidal grid. It needs to be assessed how these two distinct principal cell networks contribute to grid cell activity.

Topography of head direction cells in medial entorhinal cortex

BACKGROUND

Neural circuits in the medial entorhinal cortex (MEC) support translation of the external environment to an internal map of space, with grid and head direction neurons providing metrics for distance and orientation.

RESULTS

We show here that head direction cells in MEC are organized topographically. Head direction tuning varies widely across the entire dorsoventral MEC axis, but in layer III there is a gradual dorsal-to-ventral increase in the average width of the directional firing field. Sharply tuned cells were encountered only at the dorsal end of MEC. Similar topography was not observed among head direction cells in layers V-VI. At all MEC locations, in all layers, the preferred firing direction (directional phase) showed a uniform distribution. The continuity of the dorsoventral tuning gradient coexisted with discrete topography in the spatial scale of simultaneously recorded grid cells.

CONCLUSIONS

The findings point to dorsoventral gradients as a fundamental property of entorhinal circuits, upon which modular organization may be expressed in select subpopulations.

An isomorphic mapping hypothesis of the grid representation

We introduce a grid cell microcircuit hypothesis. We propose the ‘grid in the world’ (evident in grid cell discharges) is generated by a ‘grid in the cortex’. This cortical grid is formed by patches of calbindin-positive pyramidal neurons in layer 2 of medial entorhinal cortex (MEC). Our isomorphic mapping hypothesis assumes three types of isomorphism: (i) metric correspondence of neural space (the two-dimensional cortical sheet) and the external two-dimensional space within patches; (ii) isomorphism between cellular connectivity matrix and firing field; (iii) isomorphism between single cell and population activity. Each patch is a grid cell lattice arranged in a two-dimensional map of space with a neural : external scale of approximately 1 : 2000 in the dorsal part of rat MEC. The lattice behaves like an excitable medium with neighbouring grid cells exciting each other. Spatial scale is implemented as an intrinsic scaling factor for neural propagation speed. This factor varies along the dorsoventral cortical axis. A connectivity scheme of the grid system is described. Head direction input specifies the direction of activity propagation. We extend the theory to neurons between grid patches and predict a rare discharge pattern (inverted grid cells) and the relative location and proportion of grid cells and spatial band cells.

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

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.

How reduction of theta rhythm by medial septum inactivation may covary with disruption of entorhinal grid cell responses due to reduced cholinergic transmission

Oscillations in the coordinated firing of brain neurons have been proposed to play important roles in perception, cognition, attention, learning, navigation, and sensory-motor control. The network theta rhythm has been associated with properties of spatial navigation, as has the firing of entorhinal grid cells and hippocampal place cells. Two recent studies reduced the theta rhythm by inactivating the medial septum (MS) and demonstrated a correlated reduction in the characteristic hexagonal spatial firing patterns of grid cells. These results, along with properties of intrinsic membrane potential oscillations (MPOs) in slice preparations of medial entorhinal cortex (MEC), have been interpreted to support oscillatory interference models of grid cell firing. The current article shows that an alternative self-organizing map (SOM) model of grid cells can explain these data about intrinsic and network oscillations without invoking oscillatory interference. In particular, the adverse effects of MS inactivation on grid cells can be understood in terms of how the concomitant reduction in cholinergic inputs may increase the conductances of leak potassium (K⁺) and slow and medium after-hyperpolarization (sAHP and mAHP) channels. This alternative model can also explain data that are problematic for oscillatory interference models, including how knockout of the HCN1 gene in mice, which flattens the dorsoventral gradient in MPO frequency and resonance frequency, does not affect the development of the grid cell dorsoventral gradient of spatial scales, and how hexagonal grid firing fields in bats can occur even in the absence of theta band modulation. These results demonstrate how models of grid cell self-organization can provide new insights into the relationship between brain learning and oscillatory dynamics.

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.

Tonotopic organization of the hyperpolarization-activated current (Ih) in the mammalian medial superior olive

Neuronal membrane properties can largely vary even within distinct morphological cell classes. The mechanisms and functional consequences of this diversity, however, are little explored. In the medial superior olive (MSO), a brainstem nucleus that performs binaural coincidence detection, membrane properties at rest are largely governed by the hyperpolarization-activated inward current (I_h) which enables the temporally precise integration of excitatory and inhibitory inputs. Here, we report that I_h density varies along the putative tonotopic axis of the MSO with I_h being largest in ventral, high-frequency (HF) processing neurons. Also I_h half-maximal activation voltage and time constant are differentially distributed such that I_h of the putative HF processing neurons activate faster and at more depolarized levels. Intracellular application of saturating concentrations of cyclic AMP removed the regional difference in hyperpolarization-activated cyclic nucleotide gated (HCN) channel activation, but not I_h density. Experimental data in conjunction with a computational model suggest that increased I_h levels are helpful in counteracting temporal summation of phase-locked inhibitory inputs which is particularly prominent in HF neurons.

Entorhinal stellate cells show preferred spike phase-locking to theta inputs that is enhanced by correlations in synaptic activity

In active networks, excitatory and inhibitory synaptic inputs generate membrane voltage fluctuations that drive spike activity in a probabilistic manner. Despite this, some cells in vivo show a strong propensity to precisely lock to the local field potential and maintain a specific spike-phase relationship relative to other cells. In recordings from rat medial entorhinal cortical stellate cells, we measured spike phase-locking in response to sinusoidal "test" inputs in the presence of different forms of background membrane voltage fluctuations, generated via dynamic clamp. We find that stellate cells show strong and robust spike phase-locking to theta (4-12 Hz) inputs. This response occurs under a wide variety of background membrane voltage fluctuation conditions that include a substantial increase in overall membrane conductance. Furthermore, the IH current present in stellate cells is critical to the enhanced spike phase-locking response at theta. Finally, we show that correlations between inhibitory and excitatory conductance fluctuations, which can arise through feedback and feedforward inhibition, can substantially enhance the spike phase-locking response. The enhancement in locking is a result of a selective reduction in the size of low-frequency membrane voltage fluctuations due to cancellation of inhibitory and excitatory current fluctuations with correlations. Hence, our results demonstrate that stellate cells have a strong preference for spike phase-locking to theta band inputs and that the absolute magnitude of locking to theta can be modulated by the properties of background membrane voltage fluctuations.

Using diffusion anisotropy to characterize neuronal morphology in gray matter: the orientation distribution of axons and dendrites in the NeuroMorpho.org database

Accurate mathematical modeling is integral to the ability to interpret diffusion magnetic resonance (MR) imaging data in terms of cellular structure in brain gray matter (GM). In previous work, we derived expressions to facilitate the determination of the orientation distribution of axonal and dendritic processes from diffusion MR data. Here we utilize neuron reconstructions available in the NeuroMorpho database (www.neuromorpho.org) to assess the validity of the model we proposed by comparing morphological properties of the neurons to predictions based on diffusion MR simulations using the reconstructed neuron models. Initially, the method for directly determining neurite orientation distributions is shown to not depend on the line length used to quantify cylindrical elements. Further variability in neuron morphology is characterized relative to neuron type, species, and laboratory of origin. Subsequently, diffusion MR signals are simulated based on human neocortical neuron reconstructions. This reveals a bias in which diffusion MR data predict neuron orientation distributions to have artificially low anisotropy. This bias is shown to arise from shortcomings (already at relatively low diffusion weighting) in the Gaussian approximation of diffusion, in the presence of restrictive barriers, and data analysis methods involving higher moments of the cumulant expansion are shown to be capable of reducing the magnitude of the observed bias.

Bat and rat neurons differ in theta-frequency resonance despite similar coding of space

Both bats and rats exhibit grid cells in medial entorhinal cortex that fire as they visit a regular array of spatial locations. In rats, grid-cell firing field properties correlate with theta-frequency rhythmicity of spiking and membrane-potential resonance; however, bat grid cells do not exhibit theta rhythmic spiking, generating controversy over the role of theta rhythm. To test whether this discrepancy reflects differences in rhythmicity at a cellular level, we performed whole-cell patch recordings from entorhinal neurons in both species to record theta-frequency resonance. Bat neurons showed no theta-frequency resonance, suggesting grid-cell coding via different mechanisms in bats and rats or lack of theta rhythmic contributions to grid-cell firing in either species.

All layers of medial entorhinal cortex receive presubicular and parasubicular inputs

The medial entorhinal cortex (MEC), presubiculum (PrS), and parasubiculum (PaS) are interconnected components of the hippocampal-parahippocampal spatial-representation system. Principal cells in all layers of MEC show signs of directional tuning, overt in head direction cells present in all layers except for layer II, and covert in grid cells, which are the major spatially modulated cell type in layer II. Directional information likely originates in the head direction-vestibular system and PrS and PaS are thought to provide this information to MEC. Efferents from PaS and PrS show a selective laminar terminal distribution in MEC superficial layers II and III, respectively. We hypothesized that this anatomically determined laminar distribution does not preclude monosynaptic interaction with neurons located in deeper layers of MEC in view of the extensive apical dendrites from deeper cells reaching layers II and III. This hypothesis was tested in the rat using tilted in vitro slices in which origins and terminations of PrS and PaS fibers were maintained, as assessed using anterograde anatomical tracing. Based on voltage-sensitive dye imaging, multipatch single-cell recordings, and scanning photostimulation of caged glutamate, we report first that principal neurons in all layers of MEC receive convergent monosynaptic inputs from PrS and PaS and second, that elicited responses show layer-specific decay times and frequency-dependent facilitation. These results indicate that regardless of their selective laminar terminal distribution, PrS and PaS inputs may monosynaptically convey directional information to principal neurons in all layers of MEC through synapses on their extensive dendritic arbors.

Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells

Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous adaptive robots capable of spatial navigation.

Differential expression of HCN subunits alters voltage-dependent gating of h-channels in CA1 pyramidal neurons from dorsal and ventral hippocampus

The rodent hippocampus can be divided into dorsal (DHC) and ventral (VHC) domains on the basis of behavioral, anatomical, and biochemical differences. Recently, we reported that CA1 pyramidal neurons from the VHC were intrinsically more excitable than DHC neurons, but the specific ionic conductances contributing to this difference were not determined. Here we investigated the hyperpolarization-activated current (I(h)) and the expression of HCN1 and HCN2 channel subunits in CA1 pyramidal neurons from the DHC and VHC. Measurement of Ih with cell-attached patches revealed a significant depolarizing shift in the V(1/2) of activation for dendritic h-channels in VHC neurons (but not DHC neurons), and ultrastructural immunolocalization of HCN1 and HCN2 channels revealed a significantly larger HCN1-to-HCN2 ratio for VHC neurons (but not DHC neurons). These observations suggest that a shift in the expression of HCN1 and HCN2 channels drives functional changes in I(h) for VHC neurons (but not DHC neurons) and could thereby significantly alter the capacity for dendritic integration of these neurons.

In vivo cholinergic modulation of the cellular properties of medial entorhinal cortex neurons

Extensive in vitro data and modeling studies suggest that intrinsic properties of medial entorhinal cortex (MEC) neurons contribute to the spiking behaviour of functional cell types of MEC neurons, such as grid cells, recorded in behaving animals. It remains unclear, however, how intrinsic properties of MEC neurons influence cellular dynamics in intact networks in vivo. In order to begin to bridge the gap between electrophysiological data sets from brain slices and behaving animals, in the present study we performed intracellular recordings using sharp electrodes in urethane-anaesthetized rats to elucidate the cellular dynamics of MEC neurons in vivo. We focused on the h-current-dependent sag potential during hyperpolarizing current steps, subthreshold resonance in response to oscillatory frequency sweeps (chirp stimuli), persistent spiking in response to brief depolarizing inputs and the relationship between firing frequency and input (f-I curve), each of which is sensitive to cholinergic modulation in vitro. Consistent with data from in vitro studies, cholinergic activation by systemic application of the acetylcholinesterase inhibitor, physostigmine, resulted in decreased sag amplitude, increased sag time constant and a decrease of the peak resonance frequency. The f-I curve was also modulated by physostigmine in many neurons, but persistent spiking was not observed in any of our recordings, even when picrotoxin, a GABAA blocker, was included in the internal solution of the recording pipette to reduce possible effects of network inhibition. These results suggest that intrinsic oscillatory and rate-coding mechanisms, but not intrinsic bistability, are significantly modulated by acetylcholine in the intact entorhinal network.

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.

Cellular mechanisms of spatial navigation in the medial entorhinal cortex

Neurons in the medial entorhinal cortex exhibit a grid-like spatial pattern of spike rates that has been proposed to represent a neural code for path integration. To understand how grid cell firing arises from the combination of intrinsic conductances and synaptic input in medial entorhinal stellate cells, we performed patch-clamp recordings in mice navigating in a virtual-reality environment. We found that the membrane potential signature of stellate cells during firing field crossings consisted of a slow depolarization driving spike output. This was best predicted by network models in which neurons receive sustained depolarizing synaptic input during a field crossing, such as continuous attractor network models of grid cell firing. Another key feature of the data, phase precession of intracellular theta oscillations and spiking with respect to extracellular theta oscillations, was best captured by an oscillatory interference model. Thus, these findings provide crucial new information for a quantitative understanding of the cellular basis of spatial navigation in the entorhinal cortex.

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.

How entorhinal grid cells may learn multiple spatial scales from a dorsoventral gradient of cell response rates in a self-organizing map

Place cells in the hippocampus of higher mammals are critical for spatial navigation. Recent modeling clarifies how this may be achieved by how grid cells in the medial entorhinal cortex (MEC) input to place cells. Grid cells exhibit hexagonal grid firing patterns across space in multiple spatial scales along the MEC dorsoventral axis. Signals from grid cells of multiple scales combine adaptively to activate place cells that represent much larger spaces than grid cells. But how do grid cells learn to fire at multiple positions that form a hexagonal grid, and with spatial scales that increase along the dorsoventral axis? In vitro recordings of medial entorhinal layer II stellate cells have revealed subthreshold membrane potential oscillations (MPOs) whose temporal periods, and time constants of excitatory postsynaptic potentials (EPSPs), both increase along this axis. Slower (faster) subthreshold MPOs and slower (faster) EPSPs correlate with larger (smaller) grid spacings and field widths. A self-organizing map neural model explains how the anatomical gradient of grid spatial scales can be learned by cells that respond more slowly along the gradient to their inputs from stripe cells of multiple scales, which perform linear velocity path integration. The model cells also exhibit MPO frequencies that covary with their response rates. The gradient in intrinsic rhythmicity is thus not compelling evidence for oscillatory interference as a mechanism of grid cell firing. A response rate gradient combined with input stripe cells that have normalized receptive fields can reproduce all known spatial and temporal properties of grid cells along the MEC dorsoventral axis. This spatial gradient mechanism is homologous to a gradient mechanism for temporal learning in the lateral entorhinal cortex and its hippocampal projections. Spatial and temporal representations may hereby arise from homologous mechanisms, thereby embodying a mechanistic “neural relativity” that may clarify how episodic memories are learned.

Spatial navigation is a critical competence of all higher mammals, and place cells in the hippocampus represent the large spaces in which they navigate. Recent modeling clarifies how this may occur via interactions between grid cells in the medial entorhinal cortex (MEC) and place cells. Grid cells exhibit hexagonal grid firing patterns across space and come in multiple spatial scales that increase along the dorsoventral axis of MEC. Signals from multiple scales of grid cells combine to activate place cells that represent much larger spaces than grid cells. This article shows how a gradient of cell response rates along the dorsoventral axis enables the learning of grid cells with the observed gradient of spatial scales as an animal navigates realistic trajectories. The observed gradient of grid cell membrane potential oscillation frequencies is shown to be a direct result of the gradient of response rates. This gradient mechanism for spatial learning is homologous to a gradient mechanism for temporal learning in the lateral entorhinal cortex and its hippocampal projections, thereby clarifying why both spatial and temporal representations are found in the entorhinal-hippocampal system.

Grid alignment in entorhinal cortex

The spatial responses of many of the cells recorded in all layers of rodent medial entorhinal cortex (mEC) show mutually aligned grid patterns. Recent experimental findings have shown that grids can often be better described as elliptical rather than purely circular and that, beyond the mutual alignment of their grid axes, ellipses tend to also orient their long axis along preferred directions. Are grid alignment and ellipse orientation aspects of the same phenomenon? Does the grid alignment result from single-unit mechanisms or does it require network interactions? We address these issues by refining a single-unit adaptation model of grid formation, to describe specifically the spontaneous emergence of conjunctive grid-by-head-direction cells in layers III, V, and VI of mEC. We find that tight alignment can be produced by recurrent collateral interactions, but this requires head-direction (HD) modulation. Through a competitive learning process driven by spatial inputs, grid fields then form already aligned, and with randomly distributed spatial phases. In addition, we find that the self-organization process is influenced by any anisotropy in the behavior of the simulated rat. The common grid alignment often orients along preferred running directions (RDs), as induced in a square environment. When speed anisotropy is present in exploration behavior, the shape of individual grids is distorted toward an ellipsoid arrangement. Speed anisotropy orients the long ellipse axis along the fast direction. Speed anisotropy on its own also tends to align grids, even without collaterals, but the alignment is seen to be loose. Finally, the alignment of spatial grid fields in multiple environments shows that the network expresses the same set of grid fields across environments, modulo a coherent rotation and translation. Thus, an efficient metric encoding of space may emerge through spontaneous pattern formation at the single-unit level, but it is coherent, hence context-invariant, if aided by collateral interactions.

A biophysical signature of network affiliation and sensory processing in mitral cells

One defining characteristic of the mammalian brain is its neuronal diversity. For a given region, substructure, layer or even cell type, variability in neuronal morphology and connectivity persists. Although it is well known that such cellular properties vary considerably according to neuronal type, the substantial biophysical diversity of neurons of the same morphological class is typically averaged out and ignored. Here we show that the amplitude of hyperpolarization-evoked sag of membrane potential recorded in olfactory bulb mitral cells is an emergent, homotypic property of local networks and sensory information processing. Simultaneous whole-cell recordings from pairs of cells show that the amount of hyperpolarization-evoked sag potential and current (Ih) is stereotypic for mitral cells belonging to the same glomerular circuit. This is corroborated by a mosaic, glomerulus-based pattern of expression of the HCN2 (hyperpolarization-activated cyclic nucleotide-gated channel 2) subunit of the Ih channel. Furthermore, inter-glomerular differences in both membrane potential sag and HCN2 protein are diminished when sensory input to glomeruli is genetically and globally altered so that only one type of odorant receptor is universally expressed. Population diversity in this intrinsic property therefore reflects differential expression between local mitral cell networks processing distinct odour-related information.

The Role of HCN Channels on Membrane Excitability in the Nervous System

Hyperpolarization-activated and cyclic nucleotide-gated (HCN) channels were first reported in heart cells and are recently known to be involved in a variety of neural functions in healthy and diseased brains. HCN channels generate inward currents when the membrane potential is hyperpolarized. Voltage dependence of HCN channels is regulated by intracellular signaling cascades, which contain cyclic AMP, PIP(2), and TRIP8b. In addition, voltage-gated potassium channels have a strong influence on HCN channel activity. Because of these funny features, HCN channel currents, previously called funny currents, can have a wide range of functions that are determined by a delicate balance of modulatory factors. These multifaceted features also make it difficult to predict and elucidate the functional role of HCN channels in actual neurons. In this paper, we focus on the impacts of HCN channels on neural activity. The functions of HCN channels reported previously will be summarized, and their mechanisms will be explained by using numerical simulation of simplified model neurons.

Effects of acetylcholine on neuronal properties in entorhinal cortex

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

Neuromodulation of I(h) in layer II medial entorhinal cortex stellate cells: a voltage-clamp study

Stellate cells in layer II of medial entorhinal cortex (mEC) are endowed with a large hyperpolarization-activated cation current [h current (I(h))]. Recent work using in vivo recordings from awake behaving rodents demonstrate that I(h) plays a significant role in regulating the characteristic spatial periodicity of "grid cells" in mEC. A separate, yet related, line of research demonstrates that grid field spacing changes as a function of behavioral context. To understand the neural mechanism or mechanisms that could be underlying these changes in grid spacing, we have conducted voltage-clamp recordings of I(h) in layer II stellate cells. In particular, we have studied I(h) under the influence of several neuromodulators. The results demonstrate that I(h) amplitude can be both upregulated and downregulated through activation of distinct neuromodulators in mEC. Activation of muscarinic acetylcholine receptors produces a significant decrease in the I(h) tail current and a hyperpolarizing shift in the activation, whereas upregulation of cAMP through application of forskolin produces a significant increase in the I(h) amplitude and a depolarizing shift in I(h) activation curve. In addition, there was evidence of differential modulation of I(h) along the dorsal-ventral axis of mEC. Voltage-clamp protocols were also used to determine whether M current is present in stellate cells. In contrast to CA1 pyramidal neurons, which express M current, the data demonstrate that M current is not present in stellate cells. The results from this study provide key insights into a potential mechanism that could be underlying changes seen in grid field spacing during distinct behavioral contexts.

Diversity and excitability of deep-layer entorhinal cortical neurons in a model of temporal lobe epilepsy

The entorhinal cortex (ERC) is critically implicated in temporal lobe epileptogenesis--the most common type of adult epilepsy. Previous studies have suggested that epileptiform discharges likely initiate in seizure-sensitive deep layers (V-VI) of the medial entorhinal area (MEA) and propagate into seizure-resistant superficial layers (II-III) and hippocampus, establishing a lamina-specific distinction between activities of deep- versus superficial-layer neurons and their seizure susceptibilities. While layer II stellate cells in MEA have been shown to be hyperexcitable and hypersynchronous in patients and animal models of temporal lobe epilepsy (TLE), the fate of neurons in the deep layers under epileptic conditions and their overall contribution to epileptogenicity of this region have remained unclear. We used whole cell recordings from slices of the ERC in normal and pilocarpine-treated epileptic rats to characterize the electrophysiological properties of neurons in this region and directly assess changes in their excitatory and inhibitory synaptic drive under epileptic conditions. We found a surprising heterogeneity with at least three major types and two subtypes of functionally distinct excitatory neurons. However, contrary to expectation, none of the major neuron types characterized showed any significant changes in their excitability, barring loss of excitatory and inhibitory inputs in a subtype of neurons whose dendrite extended into layer III, where neurons are preferentially lost during TLE. We confirmed hyperexcitability of layer II neurons in the same slices, suggesting minimal influence of deep-layer input on superficial-layer neuron excitability under epileptic conditions. These data show that deep layers of ERC contain a more diverse population of excitatory neurons than previously envisaged that appear to belie their seizure-sensitive reputation.

Optimal population codes for space: grid cells outperform place cells

Rodents use two distinct neuronal coordinate systems to estimate their position: place fields in the hippocampus and grid fields in the entorhinal cortex. Whereas place cells spike at only one particular spatial location, grid cells fire at multiple sites that correspond to the points of an imaginary hexagonal lattice. We study how to best construct place and grid codes, taking the probabilistic nature of neural spiking into account. Which spatial encoding properties of individual neurons confer the highest resolution when decoding the animal's position from the neuronal population response? A priori, estimating a spatial position from a grid code could be ambiguous, as regular periodic lattices possess translational symmetry. The solution to this problem requires lattices for grid cells with different spacings; the spatial resolution crucially depends on choosing the right ratios of these spacings across the population. We compute the expected error in estimating the position in both the asymptotic limit, using Fisher information, and for low spike counts, using maximum likelihood estimation. Achieving high spatial resolution and covering a large range of space in a grid code leads to a trade-off: the best grid code for spatial resolution is built of nested modules with different spatial periods, one inside the other, whereas maximizing the spatial range requires distinct spatial periods that are pairwisely incommensurate. Optimizing the spatial resolution predicts two grid cell properties that have been experimentally observed. First, short lattice spacings should outnumber long lattice spacings. Second, the grid code should be self-similar across different lattice spacings, so that the grid field always covers a fixed fraction of the lattice period. If these conditions are satisfied and the spatial "tuning curves" for each neuron span the same range of firing rates, then the resolution of the grid code easily exceeds that of the best possible place code with the same number of neurons.

Dorsoventral differences in intrinsic properties in developing CA1 pyramidal cells

The dorsoventral and developmental gradients of entorhinal layer II cell grid properties correlate with their resonance properties and with their hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channel current characteristics. We investigated whether such correlation existed in rat hippocampal CA1 pyramidal cells, where place fields also show spatial and temporal gradients. Resonance was absent during the first postnatal week, and emerged during the second week. Resonance was stronger in dorsal than ventral cells, in accord with HCN current properties. Resonance responded to cAMP in ventral but not in dorsal cells. The dorsoventral distribution of HCN1 and HCN2 subunits and of the auxiliary protein tetratricopeptide repeat-containing Rab8b-interacting protein (TRIP8b) could account for these differences between dorsal and ventral cells. The analogous distribution of the intrinsic properties of entorhinal stellate and hippocampal cells suggests the existence of general rules of organization among structures that process complementary features of the environment.

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

The medial entorhinal cortex (MEC) is an increasingly important focus for investigation of mechanisms for spatial representation. Grid cells found in layer II of the MEC are likely to be stellate cells, which form a major projection to the dentate gyrus. Entorhinal stellate cells are distinguished by distinct intrinsic electrophysiological properties, but how these properties contribute to representation of space is not yet clear. Here, we review the ionic conductances, synaptic, and excitable properties of stellate cells, and examine their implications for models of grid firing fields. We discuss why existing data are inconsistent with models of grid fields that require stellate cells to generate periodic oscillations. An alternative possibility is that the intrinsic electrophysiological properties of stellate cells are tuned specifically to control integration of synaptic input. We highlight recent evidence that the dorsal-ventral organization of synaptic integration by stellate cells, through differences in currents mediated by HCN and leak potassium channels, influences the corresponding organization of grid fields. Because accurate cellular data will be important for distinguishing mechanisms for generation of grid fields, we introduce new data comparing properties measured with whole-cell and perforated patch-clamp recordings. We find that clustered patterns of action potential firing and the action potential after-hyperpolarization (AHP) are particularly sensitive to recording condition. Nevertheless, with both methods, these properties, resting membrane properties and resonance follow a dorsal-ventral organization. Further investigation of the molecular basis for synaptic integration by stellate cells will be important for understanding mechanisms for generation of grid fields.