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

Impaired In Vivo Gamma Oscillations in the Medial Entorhinal Cortex of Knock-in Alzheimer Model

The entorhinal cortex (EC) has bidirectional connections with the hippocampus and plays a critical role in memory formation and retrieval. EC is one of the most vulnerable regions in the brain in early stages of Alzheimer’s disease (AD), a neurodegenerative disease with progressive memory impairments. Accumulating evidence from healthy behaving animals indicates gamma oscillations (30–100 Hz) as critical for mediating interactions in the circuit between EC and hippocampus. However, it is still unclear whether gamma oscillations have causal relationship with memory impairment in AD. Here we provide the first evidence that in vivo gamma oscillations in the EC are impaired in an AD mouse model. Cross-frequency coupling of gamma (30–100 Hz) oscillations to theta oscillations was reduced in the medial EC of anesthetized amyloid precursor protein knock-in (APP-KI) mice. Phase locking of spiking activity of layer II/III pyramidal cells to the gamma oscillations was significantly impaired. These data indicate that the neural circuit activities organized by gamma oscillations were disrupted in the medial EC of AD mouse model, and point to gamma oscillations as one of possible mechanisms for cognitive dysfunction in AD patients.

Architecture of the Entorhinal Cortex A Review of Entorhinal Anatomy in Rodents with Some Comparative Notes

The entorhinal cortex (EC) is the major input and output structure of the hippocampal formation, forming the nodal point in cortico-hippocampal circuits. Different division schemes including two or many more subdivisions have been proposed, but here we will argue that subdividing EC into two components, the lateral EC (LEC) and medial EC (MEC) might suffice to describe the functional architecture of EC. This subdivision then leads to an anatomical interpretation of the different phenotypes of LEC and MEC. First, we will briefly summarize the cytoarchitectonic differences and differences in hippocampal projection patterns on which the subdivision between LEC and MEC traditionally is based and provide a short comparative perspective. Second, we focus on main differences in cortical connectivity, leading to the conclusion that the apparent differences may well correlate with the functional differences. Cortical connectivity of MEC is features interactions with areas such as the presubiculum, parasubiculum, retrosplenial cortex (RSC) and postrhinal cortex, all areas that are considered to belong to the "spatial processing domain" of the cortex. In contrast, LEC is strongly connected with olfactory areas, insular, medial- and orbitofrontal areas and perirhinal cortex. These areas are likely more involved in processing of object information, attention and motivation. Third, we will compare the intrinsic networks involving principal- and inter-neurons in LEC and MEC. Together, these observations suggest that the different phenotypes of both EC subdivisions likely depend on the combination of intrinsic organization and specific sets of inputs. We further suggest a reappraisal of the notion of EC as a layered input-output structure for the hippocampal formation.

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.

Acetylcholine modulates gamma frequency oscillations in the hippocampus by activation of muscarinic M1 receptors

Modulation of gamma oscillations is important for the processing of information and the disruption of gamma oscillations is a prominent feature of schizophrenia and Alzheimer's disease. Gamma oscillations are generated by the interaction of excitatory and inhibitory neurons where their precise frequency and amplitude are controlled by the balance of excitation and inhibition. Acetylcholine enhances the intrinsic excitability of pyramidal neurons and suppresses both excitatory and inhibitory synaptic transmission, but the net modulatory effect on gamma oscillations is not known. Here, we find that the power, but not frequency, of optogenetically induced gamma oscillations in the CA3 region of mouse hippocampal slices is enhanced by low concentrations of the broad‐spectrum cholinergic agonist carbachol but reduced at higher concentrations. This bidirectional modulation of gamma oscillations is replicated within a mathematical model by neuronal depolarisation, but not by reducing synaptic conductances, mimicking the effects of muscarinic M1 receptor activation. The predicted role for M1 receptors was supported experimentally; bidirectional modulation of gamma oscillations by acetylcholine was replicated by a selective M1 receptor agonist and prevented by genetic deletion of M1 receptors. These results reveal that acetylcholine release in CA3 of the hippocampus modulates gamma oscillation power but not frequency in a bidirectional and dose‐dependent manner by acting primarily through muscarinic M1 receptors.

Hippocampal function in rodents

The hippocampus is crucial for the formation and recall of long-term memories about people, places, objects, and events. Capitalizing on high-resolution microscopy, in vivo electrophysiology, and genetic manipulation, recent research in rodents provides evidence for hippocampal ensemble coding on the spatial, episodic, and contextual dimensions. Here we highlight the functional contribution of newly described long-range connections between hippocampus and cortical areas, and the relative impact of inhibitory and excitatory dynamics in generating behaviorally relevant population activity. Our goal is to provide an integrated view of hippocampal circuit function to understand mnemonic computations at the systems and cellular levels that underlie adaptive learned behaviors.

Post-Inhibitory Rebound Spikes in Rat Medial Entorhinal Layer II/III Principal Cells: In Vivo, In Vitro, and Computational Modeling Characterization

Medial entorhinal cortex Layer-II stellate cells (mEC-LII-SCs) primarily interact via inhibitory interneurons. This suggests the presence of alternative mechanisms other than excitatory synaptic inputs for triggering action potentials (APs) in stellate cells during spatial navigation. Our intracellular recordings show that the hyperpolarization-activated cation current (Ih) allows post-inhibitory-rebound spikes (PIRS) in mEC-LII-SCs. In vivo, strong inhibitory-post-synaptic potentials immediately preceded most APs shortening their delay and enhancing excitability. In vitro experiments showed that inhibition initiated spikes more effectively than excitation and that more dorsal mEC-LII-SCs produced faster and more synchronous spikes. In contrast, PIRS in Layer-II/III pyramidal cells were harder to evoke, voltage-independent, and slower in dorsal mEC. In computational simulations, mEC-LII-SCs morphology and Ih homeostatically regulated the dorso-ventral differences in PIRS timing and most dendrites generated PIRS with a narrow range of stimulus amplitudes. These results suggest inhibitory inputs could mediate the emergence of grid cell firing in a neuronal network.

A Multiplexed, Heterogeneous, and Adaptive Code for Navigation in Medial Entorhinal Cortex

Medial entorhinal grid cells display strikingly symmetric spatial firing patterns. The clarity of these patterns motivated the use of specific activity pattern shapes to classify entorhinal cell types. While this approach successfully revealed cells that encode boundaries, head direction, and running speed, it left a majority of cells unclassified, and its pre-defined nature may have missed unconventional, yet important coding properties. Here, we apply an unbiased statistical approach to search for cells that encode navigationally relevant variables. This approach successfully classifies the majority of entorhinal cells and reveals unsuspected entorhinal coding principles. First, we find a high degree of mixed selectivity and heterogeneity in superficial entorhinal neurons. Second, we discover a dynamic and remarkably adaptive code for space that enables entorhinal cells to rapidly encode navigational information accurately at high running speeds. Combined, these observations advance our current understanding of the mechanistic origins and functional implications of the entorhinal code for navigation. VIDEO ABSTRACT.

Distinct gamma oscillations in the distal dendritic fields of the dentate gyrus and the CA1 area of mouse hippocampus

The molecular layer of the dentate gyrus and the anatomically adjacent stratum lacunosum-moleculare of CA1 area, represent afferent areas at distinct levels of the hippocampal trisynaptic loop. Afferents to the dentate gyrus and CA1 area originate from different cell populations, including projection cells in entorhinal cortex layers two and three, respectively. To determine the organization of oscillatory activities along these terminal fields, we recorded local field potentials from multiple sites in the dentate gyrus and CA1 area of the awake mice, and localized gamma frequency (30–150 Hz) oscillations in different layers by means of current source density analysis. During theta oscillations, we observed different temporal and spectral organization of gamma oscillations in the dendritic layers of the dentate gyrus and CA1 area, with a sharp transition across the hippocampal fissure. In CA1 stratum lacunosum-moleculare, transient mid-frequency gamma oscillations (CA1-gamma_M; 80 Hz) occurred on theta cycle peaks, while in the dentate gyrus, fast (DG-gamma_F; 110 Hz), and slow (DG-gamma_S; 40 Hz) gamma oscillations preferentially occurred on troughs of theta waves. Units in dentate gyrus, in contrast to units in CA1 pyramidal layer, phase-coupled to DG-gamma_F, which was largely independent from CA1 fast gamma oscillations (CA1-gamma_F) of similar frequency and timing. Spike timing of units recorded in either CA1 area or dentate gyrus were modulated by CA1-gamma_M. Our experiments disclosed a set of gamma oscillations that differentially regulate neuronal activity in the dentate gyrus and CA1 area, and may allow flexible segregation and integration of information across different levels of hippocampal circuitry.

Layer-Specific Organization of Local Excitatory and Inhibitory Synaptic Connectivity in the Rat Presubiculum

The presubiculum is part of the parahippocampal spatial navigation system and contains head direction and grid cells upstream of the medial entorhinal cortex. This position within the parahippocampal cortex renders the presubiculum uniquely suited for analyzing the circuit requirements underlying the emergence of spatially tuned neuronal activity. To identify the local circuit properties, we analyzed the topology of synaptic connections between pyramidal cells and interneurons in all layers of the presubiculum by testing 4250 potential synaptic connections using multiple whole-cell recordings of up to 8 cells simultaneously. Network topology showed layer-specific organization of microcircuits consistent with the prevailing distinction of superficial and deep layers. While connections among pyramidal cells were almost absent in superficial layers, deep layers exhibited an excitatory connectivity of 3.9%. In contrast, synaptic connectivity for inhibition was higher in superficial layers though markedly lower than in other cortical areas. Finally, synaptic amplitudes of both excitatory and inhibitory connections showed log-normal distributions suggesting a nonrandom functional connectivity. In summary, our study provides new insights into the microcircuit organization of the presubiculum by revealing area- and layer-specific connectivity rules and sets new constraints for future models of the parahippocampal navigation system.

Single or multiple frequency generators in on-going brain activity: A mechanistic whole-brain model of empirical MEG data

During rest, envelopes of band-limited on-going MEG signals co-vary across the brain in consistent patterns, which have been related to resting-state networks measured with fMRI. To investigate the genesis of such envelope correlations, we consider a whole-brain network model assuming two distinct fundamental scenarios: one where each brain area generates oscillations in a single frequency, and a novel one where each brain area can generate oscillations in multiple frequency bands. The models share, as a common generator of damped oscillations, the normal form of a supercritical Hopf bifurcation operating at the critical border between the steady state and the oscillatory regime. The envelopes of the simulated signals are compared with empirical MEG data using new methods to analyse the envelope dynamics in terms of their phase coherence and stability across the spectrum of carrier frequencies. Considering the whole-brain model with a single frequency generator in each brain area, we obtain the best fit with the empirical MEG data when the fundamental frequency is tuned at 12Hz. However, when multiple frequency generators are placed at each local brain area, we obtain an improved fit of the spatio-temporal structure of on-going MEG data across all frequency bands. Our results indicate that the brain is likely to operate on multiple frequency channels during rest, introducing a novel dimension for future models of large-scale brain activity.

Modeling fast and slow gamma oscillations with interneurons of different subtype

Experimental and theoretical studies demonstrate that neuronal gamma oscillations crucially depend on interneurons, but current models do not consider the diversity of known interneuron subtypes. Moreover, in CA1 of the hippocampus, experimental evidence indicates the presence of multiple gamma oscillators, two of which may be coordinated by differing interneuron populations. In this article, we show that models of networks with competing interneuron populations with different postsynaptic effects are sufficient to generate, within CA1, distinct oscillatory regimes. We find that strong mutual inhibition between the interneuron populations permits distinct fast and slow gamma states, whereas weak mutual inhibition generates mixed gamma states. We develop idealized firing rate models to illuminate dynamic properties of these competitive gamma networks, and reinforce these concepts with basic spiking models. The models make several explicit predictions about gamma oscillators in CA1. Specifically, interneurons of different subtype phase-lock to different gamma states, and one population of interneurons is silenced and the other active during fast and slow gamma events. Finally, mutual inhibition between interneuron populations is necessary to generate distinct gamma states. Previous experimental studies indicate that fast and slow gamma oscillations reflect different information processing modes, although it is unclear whether these rhythms are intrinsic or imposed. The models outlined demonstrate that basic architectures can locally generate these oscillations, as well as capture other features of fast and slow gamma, including theta-phase preference and spontaneous transitions between gamma states. These models may extend to describe general dynamics in networks with diverse interneuron populations.NEW & NOTEWORTHY The oscillatory coordination of neural signals is crucial to healthy brain function. We have developed an idealized neuronal model that generates distinct fast and slow gamma oscillations, a known feature of the rodent hippocampus. Our work provides a mechanism of this phenomenon, as well as a theoretical framework for future experiments concerning hippocampal gamma. It moreover offers a tractable model of competitive gamma oscillations that is generalizable across the nervous system.

Probabilistic Learning by Rodent Grid Cells

Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population readout of a set of probabilistic spatial computations.

Cells in the mammalian hippocampal formation are thought to be central for spatial learning and stable spatial representations. Of the known spatial cells, grid cells form strikingly regular and stable patterns of activity, even in darkness. Hence, grid cells may provide the universal metric upon which spatial cognition is based. However, a more fundamental problem is how grids themselves may form and stabilise, since sensory information is noisy and can vary tremendously with environmental conditions. Furthermore, the same grid cell can display substantially different yet stable patterns of activity in different environments. Currently, no model explains how vastly different sensory cues can give rise to the diverse but stable grid patterns. Here, a new probabilistic model is proposed which combines information encoded by grid cells and boundary cells. This noise-tolerant model performs robust spatial learning, under a variety of conditions, and produces varied yet stable grid cell response patterns like rodent grid cells. Across numerous experimental manipulations, rodent and probabilistic grid cell responses are similar or even statistically indistinguishable. These results complement a growing body of evidence suggesting that mammalian brains are inherently probabilistic, and suggest for the first time that grid cells may be involved.

Sniff-Like Patterned Input Results in Long-Term Plasticity at the Rat Olfactory Bulb Mitral and Tufted Cell to Granule Cell Synapse

During odor sensing the activity of principal neurons of the mammalian olfactory bulb, the mitral and tufted cells (MTCs), occurs in repetitive bursts that are synchronized to respiration, reminiscent of hippocampal theta-gamma coupling. Axonless granule cells (GCs) mediate self- and lateral inhibitory interactions between the excitatory MTCs via reciprocal dendrodendritic synapses. We have explored long-term plasticity at this synapse by using a theta burst stimulation (TBS) protocol and variations thereof. GCs were excited via glomerular stimulation in acute brain slices. We find that TBS induces exclusively long-term depression in the majority of experiments, whereas single bursts ("single-sniff paradigm") can elicit both long-term potentiation and depression. Statistical analysis predicts that the mechanism underlying this bidirectional plasticity involves the proportional addition or removal of presynaptic release sites. Gamma stimulation with the same number of APs as in TBS was less efficient in inducing plasticity. Both TBS- and "single-sniff paradigm"-induced plasticity depend on NMDA receptor activation. Since the onset of plasticity is very rapid and requires little extra activity, we propose that these forms of plasticity might play a role already during an ongoing search for odor sources. Our results imply that components of both short-term and long-term olfactory memory may be encoded at this synapse.

Intrinsic Cornu Ammonis Area 1 Theta-Nested Gamma Oscillations Induced by Optogenetic Theta Frequency Stimulation

Gamma oscillations (30-120 Hz) are thought to be important for various cognitive functions, including perception and working memory, and disruption of these oscillations has been implicated in brain disorders, such as schizophrenia and Alzheimer's disease. The cornu ammonis area 1 (CA1) of the hippocampus receives gamma frequency inputs from upstream regions (cornu ammonis area 3 and medial entorhinal cortex) and generates itself a faster gamma oscillation. The exact nature and origin of the intrinsic CA1 gamma oscillation is still under debate. Here, we expressed channel rhodopsin-2 under the CaMKIIα promoter in mice and prepared hippocampal slices to produce a model of intrinsic CA1 gamma oscillations. Sinusoidal optical stimulation of CA1 at theta frequency was found to induce robust theta-nested gamma oscillations with a temporal and spatial profile similar to CA1 gamma in vivo The results suggest the presence of a single gamma rhythm generator with a frequency range of 65-75 Hz at 32 °C. Pharmacological analysis found that the oscillations depended on both AMPA and GABAA receptors. Cell-attached and whole-cell recordings revealed that excitatory neuron firing slightly preceded interneuron firing within each gamma cycle, suggesting that this intrinsic CA1 gamma oscillation is generated with a pyramidal-interneuron circuit mechanism.

SIGNIFICANCE STATEMENT

This study demonstrates that the cornu ammonis area 1 (CA1) is capable of generating intrinsic gamma oscillations in response to theta input. This gamma generator is independent of activity in the upstream regions, highlighting that CA1 can produce its own gamma oscillation in addition to inheriting activity from the upstream regions. This supports the theory that gamma oscillations predominantly function to achieve local synchrony, and that a local gamma generated in each area conducts the signal to the downstream region.

Absence of Visual Input Results in the Disruption of Grid Cell Firing in the Mouse

Grid cells are spatially modulated neurons within the medial entorhinal cortex whose firing fields are arranged at the vertices of tessellating equilateral triangles [1]. The exquisite periodicity of their firing has led to the suggestion that they represent a path integration signal, tracking the organism’s position by integrating speed and direction of movement [2, 3, 4, 5, 6, 7, 8, 9, 10]. External sensory inputs are required to reset any errors that the path integrator would inevitably accumulate. Here we probe the nature of the external sensory inputs required to sustain grid firing, by recording grid cells as mice explore familiar environments in complete darkness. The absence of visual cues results in a significant disruption of grid cell firing patterns, even when the quality of the directional information provided by head direction cells is largely preserved. Darkness alters the expression of velocity signaling within the entorhinal cortex, with changes evident in grid cell firing rate and the local field potential theta frequency. Short-term (<1.5 s) spike timing relationships between grid cell pairs are preserved in the dark, indicating that network patterns of excitatory and inhibitory coupling between grid cells exist independently of visual input and of spatially periodic firing. However, we find no evidence of preserved hexagonal symmetry in the spatial firing of single grid cells at comparable short timescales. Taken together, these results demonstrate that visual input is required to sustain grid cell periodicity and stability in mice and suggest that grid cells in mice cannot perform accurate path integration in the absence of reliable visual cues.

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Grid cell firing patterns are disrupted in darkness in the mouse

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Grid cells are disrupted even when head direction cell signaling is preserved

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Absence of visual input alters movement velocity modulation of theta frequency

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Temporal firing relationships between grid cell pairs are preserved in the dark

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

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

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

Modelling effects on grid cells of sensory input during self-motion

The neural coding of spatial location for memory function may involve grid cells in the medial entorhinal cortex, but the mechanism of generating the spatial responses of grid cells remains unclear. This review describes some current theories and experimental data concerning the role of sensory input in generating the regular spatial firing patterns of grid cells, and changes in grid cell firing fields with movement of environmental barriers. As described here, the influence of visual features on spatial firing could involve either computations of self-motion based on optic flow, or computations of absolute position based on the angle and distance of static visual cues. Due to anatomical selectivity of retinotopic processing, the sensory features on the walls of an environment may have a stronger effect on ventral grid cells that have wider spaced firing fields, whereas the sensory features on the ground plane may influence the firing of dorsal grid cells with narrower spacing between firing fields. These sensory influences could contribute to the potential functional role of grid cells in guiding goal-directed navigation.

Functional Architecture of the Rat Parasubiculum

The parasubiculum is a major input structure of layer 2 of medial entorhinal cortex, where most grid cells are found. Here we investigated parasubicular circuits of the rat by anatomical analysis combined with juxtacellular recording/labeling and tetrode recordings during spatial exploration. In tangential sections, the parasubiculum appears as a linear structure flanking the medial entorhinal cortex mediodorsally. With a length of ∼5.2 mm and a width of only ∼0.3 mm (approximately one dendritic tree diameter), the parasubiculum is both one of the longest and narrowest cortical structures. Parasubicular neurons span the height of cortical layers 2 and 3, and we observed no obvious association of deep layers to this structure. The "superficial parasubiculum" (layers 2 and 1) divides into ∼15 patches, whereas deeper parasubicular sections (layer 3) form a continuous band of neurons. Anterograde tracing experiments show that parasubicular neurons extend long "circumcurrent" axons establishing a "global" internal connectivity. The parasubiculum is a prime target of GABAergic and cholinergic medial septal inputs. Other input structures include the subiculum, presubiculum, and anterior thalamus. Functional analysis of identified and unidentified parasubicular neurons shows strong theta rhythmicity of spiking, a large fraction of head-direction selectivity (50%, 34 of 68), and spatial responses (grid, border and irregular spatial cells, 57%, 39 of 68). Parasubicular output preferentially targets patches of calbindin-positive pyramidal neurons in layer 2 of medial entorhinal cortex, which might be relevant for grid cell function. These findings suggest the parasubiculum might shape entorhinal theta rhythmicity and the (dorsoventral) integration of information across grid scales.

SIGNIFICANCE STATEMENT

Grid cells in medial entorhinal cortex (MEC) are crucial components of an internal navigation system of the mammalian brain. The parasubiculum is a major input structure of layer 2 of MEC, where most grid cells are found. Here we provide a functional and anatomical characterization of the parasubiculum and show that parasubicular neurons display unique features (i.e., strong theta rhythmicity of firing, prominent head-direction selectivity, and output selectively targeted to layer 2 pyramidal cell patches of MEC). These features could contribute to shaping the temporal and spatial code of downstream grid cells in entorhinal 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.

Framing the grid: effect of boundaries on grid cells and navigation

Cells in the mammalian hippocampal formation subserve neuronal representations of environmental location and support navigation in familiar environments. Grid cells constitute one of the main cell types in the hippocampal formation and are widely believed to represent a universal metric of space independent of external stimuli. Recent evidence showing that grid symmetry is distorted in non-symmetrical environments suggests that a re-examination of this hypothesis is warranted. In this review we will discuss behavioural and physiological evidence for how environmental shape and in particular enclosure boundaries influence grid cell firing properties. We propose that grid cells encode the geometric layout of enclosures.

Excitatory Postrhinal Projections to Principal Cells in the Medial Entorhinal Cortex

The postrhinal cortex (POR) provides substantial input to the entorhinal cortex, mainly targeting superficial layers of the medial entorhinal cortex (MEC). Major inputs to POR originate in the visual and parietal cortex, thus providing neurons in MEC with a subset of cortical information relevant to their spatial firing properties. The POR takes a position that is comparable with that of the perirhinal cortex (PER) with regard to the lateral entorhinal cortex (LEC). Neurons in LEC and MEC show different functional properties likely reflecting differences in their respective inputs. Projections from PER to LEC exert a main inhibitory influence, which may relate to the sparse object-selective firing in LEC. In view of the continuous, spatially modulated firing properties of principal neurons in MEC, we tested in rats the hypothesis that projections from POR to MEC are functionally different from the PER-to-LEC counterpart in providing an excitatory drive to MEC. Our combined confocal and quantitative electron-microscopic observations indicated that POR projections target mainly principal cells in MEC, including neurons that project to the hippocampus. The ultrastructure of the majority of the synapses indicated that they are excitatory. Voltage-sensitive dye imaging in sagittal slices confirmed this morphologically derived conclusion, showing that the MEC network always responded with an overall depolarization, indicative for net excitatory transmission. In vitro single-cell recordings from principal cells showed only excitatory responses upon POR stimulation. These results show that POR provides an excitatory projection to MEC, differing fundamentally from the inhibitory projection of PER to LEC.

Synaptic Targets of Medial Septal Projections in the Hippocampus and Extrahippocampal Cortices of the Mouse

Temporal coordination of neuronal assemblies among cortical areas is essential for behavioral performance. GABAergic projections from the medial septum and diagonal band complex exclusively innervate GABAergic interneurons in the rat hippocampus, contributing to the coordination of neuronal activity, including the generation of theta oscillations. Much less is known about the synaptic target neurons outside the hippocampus. To reveal the contribution of synaptic circuits involving the medial septum of mice, we have identified postsynaptic cortical neurons in wild-type and parvalbumin-Cre knock-in mice. Anterograde axonal tracing from the septum revealed extensive innervation of the hippocampus as well as the subiculum, presubiculum, parasubiculum, the medial and lateral entorhinal cortices, and the retrosplenial cortex. In all examined cortical regions, many septal GABAergic boutons were in close apposition to somata or dendrites immunopositive for interneuron cell-type molecular markers, such as parvalbumin, calbindin, calretinin, N-terminal EF-hand calcium-binding protein 1, cholecystokinin, reelin, or a combination of these molecules. Electron microscopic observations revealed septal boutons forming axosomatic or axodendritic type II synapses. In the CA1 region of hippocampus, septal GABAergic projections exclusively targeted interneurons. In the retrosplenial cortex, 93% of identified postsynaptic targets belonged to interneurons and the rest to pyramidal cells. These results suggest that the GABAergic innervation from the medial septum and diagonal band complex contributes to temporal coordination of neuronal activity via several types of cortical GABAergic interneurons in both hippocampal and extrahippocampal cortices. Oscillatory septal neuronal firing at delta, theta, and gamma frequencies may phase interneuron activity.

Rhythms of the hippocampal network

The hippocampal local field potential (LFP) shows three major types of rhythms: theta, sharp wave-ripples and gamma. These rhythms are defined by their frequencies, they have behavioural correlates in several species including rats and humans, and they have been proposed to carry out distinct functions in hippocampal memory processing. However, recent findings have challenged traditional views on these behavioural functions. In this Review, I discuss our current understanding of the origins and the mnemonic functions of hippocampal theta, sharp wave-ripples and gamma rhythms on the basis of findings from rodent studies. In addition, I present an updated synthesis of their roles and interactions within the hippocampal network.

Grid-like Processing of Imagined Navigation

Grid cells in the entorhinal cortex (EC) of rodents [1] and humans [2] fire in a hexagonally distributed spatially periodic manner. In concert with other spatial cells in the medial temporal lobe (MTL) [3, 4, 5, 6], they provide a representation of our location within an environment [7, 8] and are specifically thought to allow the represented location to be updated by self-motion [9]. Grid-like signals have been seen throughout the autobiographical memory system [10], suggesting a much more general role in memory [11, 12]. Grid cells may allow us to move our viewpoint in imagination [13], a useful function for goal-directed navigation and planning [12, 14, 15, 16], and episodic future thinking more generally [17, 18]. We used fMRI to provide evidence for similar grid-like signals in human entorhinal cortex during both virtual navigation and imagined navigation of the same paths. We show that this signal is present in periods of active navigation and imagination, with a similar orientation in both and with the specifically 6-fold rotational symmetry characteristic of grid cell firing. We therefore provide the first evidence suggesting that grid cells are utilized during movement of viewpoint within imagery, potentially underpinning our more general ability to mentally traverse possible routes in the service of planning and episodic future thinking.

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Grid cells fire in a spatial pattern as mammals actively navigate their environment

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Grid cells might move the viewpoint of imagination, aiding goal-directed navigation

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Human entorhinal cortex shows a grid-like fMRI signal during imagined navigation

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This signal is similar to that seen in the same people during virtual navigation

A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior

Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets: (1) set a "neural context" in terms of narrow band frequencies that uniquely characterizes the activated circuits; (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances; (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior.

Impaired theta-gamma coupling in APP-deficient mice

Amyloid precursor protein (APP) is critically involved in the pathophysiology of Alzheimer's disease, but its physiological functions remain elusive. Importantly, APP knockout (APP-KO) mice exhibit cognitive deficits, suggesting that APP plays a role at the neuronal network level. To investigate this possibility, we recorded local field potentials (LFPs) from the posterior parietal cortex, dorsal hippocampus and lateral prefrontal cortex of freely moving APP-KO mice. Spectral analyses showed that network oscillations within the theta- and gamma-frequency bands were not different between APP-KO and wild-type mice. Surprisingly, however, while gamma amplitude coupled to theta phase in all recorded regions of wild-type animals, in APP-KO mice theta-gamma coupling was strongly diminished in recordings from the parietal cortex and hippocampus, but not in LFPs recorded from the prefrontal cortex. Thus, lack of APP reduces oscillatory coupling in LFP recordings from specific brain regions, despite not affecting the amplitude of the oscillations. Together, our findings reveal reduced cross-frequency coupling as a functional marker of APP deficiency at the network level.

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.

How environment and self-motion combine in neural representations of space

Estimates of location or orientation can be constructed solely from sensory information representing environmental cues. In unfamiliar or sensory-poor environments, these estimates can also be maintained and updated by integrating self-motion information. However, the accumulation of error dictates that updated representations of heading direction and location become progressively less reliable over time, and must be corrected by environmental sensory inputs when available. Anatomical, electrophysiological and behavioural evidence indicates that angular and translational path integration contributes to the firing of head direction cells and grid cells. We discuss how sensory inputs may be combined with self-motion information in the firing patterns of these cells. For head direction cells, direct projections from egocentric sensory representations of distal cues can help to correct cumulative errors. Grid cells may benefit from sensory inputs via boundary vector cells and place cells. However, the allocentric code of boundary vector cells and place cells requires consistent head-direction information in order to translate the sensory signal of egocentric boundary distance into allocentric boundary vector cell firing, suggesting that the different spatial representations found in and around the hippocampal formation are interdependent. We conclude that, rather than representing pure path integration, the firing of head-direction cells and grid cells reflects the interface between self-motion and environmental sensory information. Together with place cells and boundary vector cells they can support a coherent unitary representation of space based on both environmental sensory inputs and path integration signals.

Environmental boundaries as a mechanism for correcting and anchoring spatial maps

Ubiquitous throughout the animal kingdom, path integration-based navigation allows an animal to take a circuitous route out from a home base and using only self-motion cues, calculate a direct vector back. Despite variation in an animal's running speed and direction, medial entorhinal grid cells fire in repeating place-specific locations, pointing to the medial entorhinal circuit as a potential neural substrate for path integration-based spatial navigation. Supporting this idea, grid cells appear to provide an environment-independent metric representation of the animal's location in space and preserve their periodic firing structure even in complete darkness. However, a series of recent experiments indicate that spatially responsive medial entorhinal neurons depend on environmental cues in a more complex manner than previously proposed. While multiple types of landmarks may influence entorhinal spatial codes, environmental boundaries have emerged as salient landmarks that both correct error in entorhinal grid cells and bind internal spatial representations to the geometry of the external spatial world. The influence of boundaries on error correction and grid symmetry points to medial entorhinal border cells, which fire at a high rate only near environmental boundaries, as a potential neural substrate for landmark-driven control of spatial codes. The influence of border cells on other entorhinal cell populations, such as grid cells, could depend on plasticity, raising the possibility that experience plays a critical role in determining how external cues influence internal spatial representations.

Local and Distant Input Controlling Excitation in Layer II of the Medial Entorhinal Cortex

Layer II (LII) of the medial entorhinal cortex (MEC) comprises grid cells that support spatial navigation. The firing pattern of grid cells might be explained by attractor dynamics in a network, which requires either direct excitatory connectivity between phase-specific grid cells or indirect coupling via interneurons. However, knowledge regarding local networks that support in vivo activity is incomplete. Here we identified essential components of LII networks in the MEC. We distinguished four types of excitatory neurons that exhibit cell-type-specific local excitatory and inhibitory connectivity. Furthermore, we found that LII neurons contribute to the excitation of contralateral neurons in the corresponding layer. Finally, we demonstrated that the medial septum controls excitation in the MEC via two subpopulations of long-range GABAergic neurons that target distinct interneurons in LII, thereby disinhibiting local circuits. We thus identified local connections that could support attractor dynamics and external inputs that likely govern excitation in LII.

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LII MEC excitatory neurons can be classified into four cell types

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The four cell types exhibit specific local excitatory and inhibitory connectivity

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LII neurons contribute to the excitation of contralateral LII neurons

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Distinct septal GABAergic neurons exhibit cell-type-specific inhibition in LII MEC

Anatomical Organization and Spatiotemporal Firing Patterns of Layer 3 Neurons in the Rat Medial Entorhinal Cortex

Layer 3 of the medial entorhinal cortex is a major gateway from the neocortex to the hippocampus. Here we addressed structure-function relationships in medial entorhinal cortex layer 3 by combining anatomical analysis with juxtacellular identification of single neurons in freely behaving rats. Anatomically, layer 3 appears as a relatively homogeneous cell sheet. Dual-retrograde neuronal tracing experiments indicate a large overlap between layer 3 pyramidal populations, which project to ipsilateral hippocampus, and the contralateral medial entorhinal cortex. These cells were intermingled within layer 3, and had similar morphological and intrinsic electrophysiological properties. Dendritic trees of layer 3 neurons largely avoided the calbindin-positive patches in layer 2. Identification of layer 3 neurons during spatial exploration (n = 17) and extracellular recordings (n = 52) pointed to homogeneous spatial discharge patterns. Layer 3 neurons showed only weak spiking theta rhythmicity and sparse head-direction selectivity. A majority of cells (50 of 69) showed no significant spatial modulation. All of the ∼28% of neurons that carried significant amounts of spatial information (19 of 69) discharged in irregular spatial patterns. Thus, layer 3 spatiotemporal firing properties are remarkably different from those of layer 2, where theta rhythmicity is prominent and spatially modulated cells often discharge in grid or border patterns. Significance statement: Neurons within the superficial layers of the medial entorhinal cortex (MEC) often discharge in border, head-direction, and theta-modulated grid patterns. It is still largely unknown how defined discharge patterns relate to cellular diversity in the superficial layers of the MEC. In the present study, we addressed this issue by combining anatomical analysis with juxtacellular identification of single layer 3 neurons in freely behaving rats. We provide evidence that the anatomical organization and spatiotemporal firing properties of layer 3 neurons are remarkably different from those in layer 2. Specifically, most layer 3 neurons discharged in spatially irregular firing patterns, with weak theta-modulation and head-directional selectivity. This work thus poses constraints on the spatiotemporal patterns reaching downstream targets, like the hippocampus.

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

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

The superficial layers of the medial entorhinal cortex (MEC) contain spatially selective neurons that are crucial for spatial navigation and memory. These highly specialized neurons include grid cells, border cells, head-direction cells, and irregular spatially selective cells. In addition, MEC neurons display a large variability in their spike patterns at a millisecond time scale. In this study, we analyzed spike trains of neurons in the MEC superficial layers of mice and found that these neurons can be classified into two groups based on their propensity to fire spike doublets at 125-250 Hz. The two groups, labeled "bursty" and "non-bursty" neurons, differed in their spike waveforms and interspike interval adaptation but displayed a similar mean firing rate. Grid cell spatial periodicity was more commonly observed in bursty than in non-bursty neurons. In contrast, most neurons with head-direction selectivity or those that fired at the border of the environment were non-bursty neurons. During theta oscillations, both bursty and non-bursty neurons fired preferentially near the end of the descending phase of the cycle, but the spikes of bursty neurons occurred at an earlier phase than those of non-bursty neurons. Finally, analysis of spike-time crosscorrelations between simultaneously recorded neurons suggested that the two cell classes are differentially coupled to fast-spiking interneurons: bursty neurons were twice as likely to have excitatory interactions with putative interneurons as non-bursty neurons. These results demonstrate that bursty and non-bursty neurons are differentially integrated in the MEC network and preferentially encode distinct spatial signals.

SIGNIFICANCE STATEMENT

We report that neurons in the superficial layers of the medial entorhinal cortex can be classified based on their tendency to fire bursts of action potentials at 125-250 Hz. The relevance of this classification is demonstrated by the types of spatial information preferentially encoded by bursty and non-bursty neurons. Grid-like spatial periodicity is more commonly observed in bursty neurons, whereas most cells with head-direction selectivity or those that are firing at the border of the environment are non-bursty neurons. This work indicates that the spatial firing patterns of neurons in the medial entorhinal cortex can be predicted by electrophysiological features reflecting the synaptic inputs and/or integrating properties of the neurons.

Rebound spiking in layer II medial entorhinal cortex stellate cells: Possible mechanism of grid cell function

Rebound spiking properties of medial entorhinal cortex (mEC) stellate cells induced by inhibition may underlie their functional properties in awake behaving rats, including the temporal phase separation of distinct grid cells and differences in grid cell firing properties. We investigated rebound spiking properties using whole cell patch recording in entorhinal slices, holding cells near spiking threshold and delivering sinusoidal inputs, superimposed with realistic inhibitory synaptic inputs to test the capacity of cells to selectively respond to specific phases of inhibitory input. Stellate cells showed a specific phase range of hyperpolarizing inputs that elicited spiking, but non-stellate cells did not show phase specificity. In both cell types, the phase range of spiking output occurred between the peak and subsequent descending zero crossing of the sinusoid. The phases of inhibitory inputs that induced spikes shifted earlier as the baseline sinusoid frequency increased, while spiking output shifted to later phases. Increases in magnitude of the inhibitory inputs shifted the spiking output to earlier phases. Pharmacological blockade of h-current abolished the phase selectivity of hyperpolarizing inputs eliciting spikes. A network computational model using cells possessing similar rebound properties as found in vitro produces spatially periodic firing properties resembling grid cell firing when a simulated animal moves along a linear track. These results suggest that the ability of mEC stellate cells to fire rebound spikes in response to a specific range of phases of inhibition could support complex attractor dynamics that provide completion and separation to maintain spiking activity of specific grid cell populations.

Optogenetics: 10 years of microbial opsins in neuroscience

Over the past 10 years, the development and convergence of microbial opsin engineering, modular genetic methods for cell-type targeting and optical strategies for guiding light through tissue have enabled versatile optical control of defined cells in living systems, defining modern optogenetics. Despite widespread recognition of the importance of spatiotemporally precise causal control over cellular signaling, for nearly the first half (2005-2009) of this 10-year period, as optogenetics was being created, there were difficulties in implementation, few publications and limited biological findings. In contrast, the ensuing years have witnessed a substantial acceleration in the application domain, with the publication of thousands of discoveries and insights into the function of nervous systems and beyond. This Historical Commentary reflects on the scientific landscape of this decade-long transition.

Noise promotes independent control of gamma oscillations and grid firing within recurrent attractor networks

Neural computations underlying cognitive functions require calibration of the strength of excitatory and inhibitory synaptic connections and are associated with modulation of gamma frequency oscillations in network activity. However, principles relating gamma oscillations, synaptic strength and circuit computations are unclear. We address this in attractor network models that account for grid firing and theta-nested gamma oscillations in the medial entorhinal cortex. We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation. With moderate noise, variation in excitatory or inhibitory synaptic strength tunes the amplitude and frequency of gamma activity without disrupting grid firing. This beneficial role for noise results from disruption of epileptic-like network states. Thus, moderate noise promotes independent control of multiplexed firing rate- and gamma-based computational mechanisms. Our results have implications for tuning of normal circuit function and for disorders associated with changes in gamma oscillations and synaptic strength.

DOI:http://dx.doi.org/10.7554/eLife.06444.001

When electrodes are placed on the scalp, or lowered into the brain itself, rhythmic waves of electrical activity are seen that reflect the coordinated firing of large numbers of neurons. The pattern of the waves varies between different brain regions, and according to what the animal or person is doing. During sleep and quiet wakefulness, slower brain waves predominate, whereas faster waves called gamma oscillations emerge during cognition—the act of processing knowledge.

Gamma waves can be readily detected in a region of the brain called the medial entorhinal cortex (MEC). This brain region is also known for its role in forming the spatial memories that allow an individual to remember how to navigate around an area they have previously visited. Individual MEC cells increase their firing rates whenever an individual is at specific locations. When these locations are plotted in two dimensions, they form a hexagonal grid: this ‘grid cell map’ enables the animal to keep track of its position as it navigates through its environment.

To determine how MEC neurons can simultaneously encode spatial locations and generate the gamma waves implicated in cognition, Solanka et al. have used supercomputing to simulate the activity of more than 1.5 million connections between MEC cells. Changing the strength of these connections had different effects on the ability of the MEC to produce gamma waves or spatial maps. However, adjusting the model to include random fluctuations in neuronal firing, or ‘noise’, was beneficial for both types of output. This is partly because noise prevented neuronal firing from becoming excessively synchronized, which would otherwise have caused seizures.

Although noise is generally regarded as disruptive, the results of Solanka et al. suggest that it helps the MEC to perform its two distinct roles. Specifically, the presence of noise enables relatively small changes in the strength of the connections between neurons to alter gamma waves—and thus affect cognition—without disrupting the neurons' ability to encode spatial locations. Given that noise reduces the likelihood of seizures, the results also raise the possibility that introducing noise into the brain in a controlled way could have therapeutic benefits for individuals with epilepsy.

DOI:http://dx.doi.org/10.7554/eLife.06444.002

Theta-gamma coordination between anterior cingulate and prefrontal cortex indexes correct attention shifts

Anterior cingulate and lateral prefrontal cortex (ACC/PFC) are believed to coordinate activity to flexibly prioritize the processing of goal-relevant over irrelevant information. This between-area coordination may be realized by common low-frequency excitability changes synchronizing segregated high-frequency activations. We tested this coordination hypothesis by recording in macaque ACC/PFC during the covert utilization of attention cues. We found robust increases of 5-10 Hz (theta) to 35-55 Hz (gamma) phase-amplitude correlation between ACC and PFC during successful attention shifts but not before errors. Cortical sites providing theta phases (i) showed a prominent cue-induced phase reset, (ii) were more likely in ACC than PFC, and (iii) hosted neurons with burst firing events that synchronized to distant gamma activity. These findings suggest that interareal theta-gamma correlations could follow mechanistically from a cue-triggered reactivation of rule memory that synchronizes theta across ACC/PFC.

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.

Navigating the circuitry of the brain's GPS system: Future challenges for neurophysiologists

The discovery of the brain's navigation system creates a compelling challenge for neurophysiologists: how do we map the circuitry of a system that can only be definitively identified in awake, behaving animals? Do grid and border cells in the entorhinal cortex correspond to the two classes of principal cell found there, stellate and pyramidal cells? In the hippocampus, does the diversity seen in pyramidal cell subtypes have functional correlates in the place cell system? How do interneurons regulate the activity of spatially tuned principal cells in the hippocampal and entorhinal circuits? Here, we discuss recent literature relating the cellular circuitry of these circuits to in vivo studies of the brain's navigation system, and the role that interneurons have in regulating the activity of principal cells in these circuits. We propose that studying in vitro models of neuronal oscillations in the entorhinal cortex and hippocampus can provide useful insights for bridging the gap in understanding that exists in relating in vivo and behavioral studies to circuit function at the cellular level.

Hippocampal network oscillations - recent insights from in vitro experiments

Network oscillations are present throughout the mammalian brain. They are important for certain cognitive functions, such as learning and memory. The hippocampus exhibits prominent oscillations similar to those seen in other parts of the cortex. Due to its highly organised lamellar structure, ex vivo and in vitro preparations from the hippocampus have provided experimental models within which to study network oscillations. As such, experiments in hippocampal slices continue to progress our understanding about both the mechanisms and functions of cortical network oscillations. Here, advances from the past two years are summarised, and the current state of the field discussed.

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.