Cellular mechanisms of spatial navigation in the medial entorhinal cortex

Lateral Entorhinal Cortex Dysfunction in Alzheimer's disease Mice

In Alzheimer's disease (AD), the formation of amyloid beta (A β ) and neurofibrillary tangles (NFTs) leads to neuronal loss in entorhinal cortex (EC), a crucial brain region involved in memory and navigation. These pathological changes are concurrent with the onset of memory-related issues in AD patients with symptoms of forgetfulness such as misplacing items, disorientation in familiar environments etc. The lateral EC (LEC) is associated with non-spatial memory processing including object recognition. Since in LEC, neurons fire in response to objects (object cells) and at locations previously occupied by objects (trace cells), pathology in this region could lead to dysfunction in object location coding. In this paper we show that a transgenic mouse model, EC-App/Tau, which expresses both APP and tau primarily in the EC region, have deficits in LEC-specific memory tasks. Using in vivo single-unit electrophysiology recordings we show that the LEC neurons are hyperactive with low information content and high sparsity compared to the controls indicating poor firing fidelity. We finally show that object cells and trace cells fire less precisely in the EC-App/Tau mice compared to controls indicating poor encoding of objects. Overall, we show that AD pathology causes erratic firing of LEC neurons and object coding defects leading to LEC-specific memory impairment.

Spatial memory requires hypocretins to elevate medial entorhinal gamma oscillations

The hypocretin (Hcrt) (also known as orexin) neuropeptidic wakefulness-promoting system is implicated in the regulation of spatial memory, but its specific role and mechanisms remain poorly understood. In this study, we revealed the innervation of the medial entorhinal cortex (MEC) by Hcrt neurons in mice. Using the genetically encoded G-protein-coupled receptor activation-based Hcrt sensor, we observed a significant increase in Hcrt levels in the MEC during novel object-place exploration. We identified the function of Hcrt at presynaptic glutamatergic terminals, where it recruits fast-spiking parvalbumin-positive neurons and promotes gamma oscillations. Bidirectional manipulations of Hcrt neurons' projections from the lateral hypothalamus (LHHcrt) to MEC revealed the essential role of this pathway in regulating object-place memory encoding, but not recall, through the modulation of gamma oscillations. Our findings highlight the significance of the LHHcrt-MEC circuitry in supporting spatial memory and reveal a unique neural basis for the hypothalamic regulation of spatial memory.

Ketamine evoked disruption of entorhinal and hippocampal spatial maps

Ketamine, a rapid-acting anesthetic and acute antidepressant, carries undesirable spatial cognition side effects including out-of-body experiences and spatial memory impairments. The neural substrates that underlie these alterations in spatial cognition however, remain incompletely understood. Here, we used electrophysiology and calcium imaging to examine ketamine's impacts on the medial entorhinal cortex and hippocampus, which contain neurons that encode an animal's spatial position, as mice navigated virtual reality and real world environments. Ketamine acutely increased firing rates, degraded cell-pair temporal firing-rate relationships, and altered oscillations, leading to longer-term remapping of spatial representations. In the reciprocally connected hippocampus, the activity of neurons that encode the position of the animal was suppressed after ketamine administration. Together, these findings demonstrate ketamine-induced dysfunction of the MEC-hippocampal circuit at the single cell, local-circuit population, and network levels, connecting previously demonstrated physiological effects of ketamine on spatial cognition to alterations in the spatial navigation circuit.

Retrosplenial inputs drive diverse visual representations in the medial entorhinal cortex

The ability of rodents to use visual cues for successful navigation and goal-directed behavior has been long appreciated, although the neural mechanisms supporting sensory representations in navigational circuits are largely unknown. Navigation is fundamentally dependent on the hippocampus and closely connected entorhinal cortex, whose neurons exhibit characteristic firing patterns corresponding to the animal's location. The medial entorhinal cortex (MEC) receives direct projections from sensory areas in the neocortex, suggesting the ability to encode sensory information. To examine this possibility, we performed high-density recordings of MEC neurons in awake, head-fixed mice presented with simple visual stimuli and assessed the dynamics of sensory-evoked activity. We found a large fraction of neurons exhibited robust responses to visual input that shaped activity relative to ongoing network dynamics. Visually responsive cells could be separated into subgroups based on functional and molecular properties within deep layers of the dorsal MEC, suggesting diverse populations within the MEC contribute to sensory encoding. We then showed that optogenetic suppression of retrosplenial cortex afferents within the MEC strongly reduced visual responses. Overall, our results demonstrate the the MEC can encode simple visual cues in the environment that can contribute to neural representations of location necessary for accurate navigation.

Phase information is conserved in sparse, synchronous population-rate-codes via phase-to-rate recoding

Neural computation is often traced in terms of either rate- or phase-codes. However, most circuit operations will simultaneously affect information across both coding schemes. It remains unclear how phase and rate coded information is transmitted, in the face of continuous modification at consecutive processing stages. Here, we study this question in the entorhinal cortex (EC)- dentate gyrus (DG)- CA3 system using three distinct computational models. We demonstrate that DG feedback inhibition leverages EC phase information to improve rate-coding, a computation we term phase-to-rate recoding. Our results suggest that it i) supports the conservation of phase information within sparse rate-codes and ii) enhances the efficiency of plasticity in downstream CA3 via increased synchrony. Given the ubiquity of both phase-coding and feedback circuits, our results raise the question whether phase-to-rate recoding is a recurring computational motif, which supports the generation of sparse, synchronous population-rate-codes in areas beyond the DG.

Simulation of oscillatory dynamics induced by an approximation of grid cell output

Grid cells, in entorhinal cortex (EC) and related structures, signal animal location relative to hexagonal tilings of 2D space. A number of modeling papers have addressed the question of how grid firing behaviors emerge using (for example) ideas borrowed from dynamical systems (attractors) or from coupled oscillator theory. Here we use a different approach: instead of asking how grid behavior emerges, we take as a given the experimentally observed intracellular potentials of superficial medial EC neurons during grid firing. Employing a detailed neural circuit model modified from a lateral EC model, we then ask how the circuit responds when group of medial EC principal neurons exhibit such potentials, simultaneously with a simulated theta frequency input from the septal nuclei. The model predicts the emergence of robust theta-modulated gamma/beta oscillations, suggestive of oscillations observed in an in vitro medial EC experimental model (Cunningham, M.O., Pervouchine, D.D., Racca, C., Kopell, N.J., Davies, C.H., Jones, R.S.G., Traub, R.D., and Whittington, M.A. (2006). Neuronal metabolism governs cortical network response state. Proc. Natl. Acad. Sci. U S A 103: 5597-5601). Such oscillations result because feedback interneurons tightly synchronize with each other - despite the varying phases of the grid cells - and generate a robust inhibition-based rhythm. The lack of spatial specificity of the model interneurons is consistent with the lack of spatial periodicity in parvalbumin interneurons observed by Buetfering, C., Allen, K., and Monyer, H. (2014). Parvalbumin interneurons provide grid cell-driven recurrent inhibition in the medial entorhinal cortex. Nat. Neurosci. 17: 710-718. If in vivo EC gamma rhythms arise during exploration as our model predicts, there could be implications for interpreting disrupted spatial behavior and gamma oscillations in animal models of Alzheimer's disease and schizophrenia. Noting that experimental intracellular grid cell potentials closely resemble cortical Up states and Down states, during which fast oscillations also occur during Up states, we propose that the co-occurrence of slow principal cell depolarizations and fast network oscillations is a general property of the telencephalon, in both waking and sleep states.

Effects of the Light/Dark Phase and Constant Light on Spatial Working Memory and Spine Plasticity in the Mouse Hippocampus

Circadian rhythms in behavior and physiology such as rest/activity and hormones are driven by an internal clock and persist in the absence of rhythmic environmental cues. However, the period and phase of the internal clock are entrained by the environmental light/dark cycle. Consequently, aberrant lighting conditions, which are increasing in modern society, have a strong impact on rhythmic body and brain functions. Mice were exposed to three different lighting conditions, 12 h light/12 h dark cycle (LD), constant darkness (DD), and constant light (LL), to study the effects of the light/dark cycle and aberrant lighting on the hippocampus, a critical structure for temporal and spatial memory formation and navigation. Locomotor activity and plasma corticosterone levels were analyzed as readouts for circadian rhythms. Spatial working memory via Y-maze, spine morphology of Golgi-Cox-stained hippocampi, and plasticity of excitatory synapses, measured by number and size of synaptopodin and GluR1-immunreactive clusters, were analyzed. Our results indicate that the light/dark cycle drives diurnal differences in synaptic plasticity in hippocampus. Moreover, spatial working memory, spine density, and size and number of synaptopodin and GluR1 clusters were reduced in LL, while corticosterone levels were increased. This indicates that acute constant light affects hippocampal function and synaptic plasticity.

Grid cell disruption in a mouse model of early Alzheimer's disease reflects reduced integration of self-motion cues

Converging evidence from human and rodent studies suggests that disrupted grid cell coding in the medial entorhinal cortex (MEC) underlies path integration behavioral deficits during early Alzheimer's disease (AD). However, grid cell firing relies on both self-motion cues and environmental features, and it remains unclear whether disrupted grid coding can account for specific path integration deficits reported during early AD. Here, we report in the J20 transgenic amyloid beta (Aβ) mouse model of early AD that grid cells were spatially unstable toward the center of the arena, had qualitatively different spatial components that aligned parallel to the borders of the environment, and exhibited impaired integration of distance traveled via reduced theta phase precession. Our results suggest that disrupted early AD grid coding reflects reduced integration of self-motion cues but not environmental information via geometric boundaries, providing evidence that grid cell impairments underlie path integration deficits during early AD.

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

This paper reviews the recent experimental finding that neurons in behaving rodents show egocentric coding of the environment in a number of structures associated with the hippocampus. Many animals generating behavior on the basis of sensory input must deal with the transformation of coordinates from the egocentric position of sensory input relative to the animal, into an allocentric framework concerning the position of multiple goals and objects relative to each other in the environment. Neurons in retrosplenial cortex show egocentric coding of the position of boundaries in relation to an animal. These neuronal responses are discussed in relation to existing models of the transformation from egocentric to allocentric coordinates using gain fields and a new model proposing transformations of phase coding that differ from current models. The same type of transformations could allow hierarchical representations of complex scenes. The responses in rodents are also discussed in comparison to work on coordinate transformations in humans and non-human primates.

The chicken and egg problem of grid cells and place cells

Place cells and grid cells are major building blocks of the hippocampal cognitive map. The prominent forward model postulates that grid-cell modules are generated by a continuous attractor network; that a velocity signal evoked during locomotion moves entorhinal activity bumps; and that place-cell activity constitutes summation of entorhinal grid-cell modules. Experimental data support the first postulate, but not the latter two. Several families of solutions that depart from these postulates have been put forward. We suggest a modified model (spatial modulation continuous attractor network; SCAN), whereby place cells are generated from spatially selective nongrid cells. Locomotion causes these cells to move the hippocampal activity bump, leading to movement of the entorhinal manifolds. Such inversion accords with the shift of hippocampal thought from navigation to more abstract functions.

Naturalistic neuroscience and virtual reality

Virtual reality (VR) is one of the techniques that became particularly popular in neuroscience over the past few decades. VR experiments feature a closed-loop between sensory stimulation and behavior. Participants interact with the stimuli and not just passively perceive them. Several senses can be stimulated at once, large-scale environments can be simulated as well as social interactions. All of this makes VR experiences more natural than those in traditional lab paradigms. Compared to the situation in field research, a VR simulation is highly controllable and reproducible, as required of a laboratory technique used in the search for neural correlates of perception and behavior. VR is therefore considered a middle ground between ecological validity and experimental control. In this review, I explore the potential of VR in eliciting naturalistic perception and behavior in humans and non-human animals. In this context, I give an overview of recent virtual reality approaches used in neuroscientific research.

Cell-Type Specific Inhibition Controls the High-Frequency Oscillations in the Medial Entorhinal Cortex

The medial entorhinal cortex (mEC) plays a critical role for spatial navigation and memory. While many studies have investigated the principal neurons within the entorhinal cortex, much less is known about the inhibitory circuitries within this structure. Here, we describe for the first time in the mEC a subset of parvalbumin-positive (PV+) interneurons (INs)-stuttering cells (STUT)-with morphological, intrinsic electrophysiological, and synaptic properties distinct from fast-spiking PV+ INs. In contrast to the fast-spiking PV+ INs, the axon of the STUT INs also terminated in layer 3 and showed subthreshold membrane oscillations at gamma frequencies. Whereas the synaptic output of the STUT INs was only weakly reduced by a μ-opioid agonist, their inhibitory inputs were strongly suppressed. Given these properties, STUT are ideally suited to entrain gamma activity in the pyramidal cell population of the mEC. We propose that activation of the μ-opioid receptors decreases the GABA release from the PV+ INs onto the STUT, resulting in disinhibition of the STUT cell population and the consequent increase in network gamma power. We therefore suggest that the opioid system plays a critical role, mediated by STUT INs, in the neural signaling and oscillatory network activity within the mEC.

Disrupted-in-schizophrenia-1 is required for normal pyramidal cell-interneuron communication and assembly dynamics in the prefrontal cortex

We interrogated prefrontal circuit function in mice lacking Disrupted-in-schizophrenia-1 (Disc1-mutant mice), a risk factor for psychiatric disorders. Single-unit recordings in awake mice revealed reduced average firing rates of fast-spiking interneurons (INTs), including optogenetically identified parvalbumin-positive cells, and a lower proportion of INTs phase-coupled to ongoing gamma oscillations. Moreover, we observed decreased spike transmission efficacy at local pyramidal cell (PYR)-INT connections in vivo, suggesting a reduced excitatory effect of local glutamatergic inputs as a potential mechanism of lower INT rates. On the network level, impaired INT function resulted in altered activation of PYR assemblies: While assembly activations defined as coactivations within 25 ms were observed equally often, the expression strength of individual assembly patterns was significantly higher in Disc1-mutant mice. Our data, thus, reveal a role of Disc1 in shaping the properties of prefrontal assembly patterns by setting INT responsiveness to glutamatergic drive.

A synaptic signal for novelty processing in the hippocampus

Episodic memory formation and recall are complementary processes that rely on opposing neuronal computations in the hippocampus. How this conflict is resolved in hippocampal circuits is unclear. To address this question, we obtained in vivo whole-cell patch-clamp recordings from dentate gyrus granule cells in head-fixed mice trained to explore and distinguish between familiar and novel virtual environments. We find that granule cells consistently show a small transient depolarisation upon transition to a novel environment. This synaptic novelty signal is sensitive to local application of atropine, indicating that it depends on metabotropic acetylcholine receptors. A computational model suggests that the synaptic response to novelty may bias granule cell population activity, which can drive downstream attractor networks to a new state, favouring the switch from recall to new memory formation when faced with novelty. Such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Memory formation and recall are complementary processes within the hippocampus. Here the authors demonstrate a synaptic signal of novelty in the hippocampus and provide a computational framework for how such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons

Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.

Theta and gamma oscillatory dynamics in mouse models of Alzheimer's disease: A path to prospective therapeutic intervention

Understanding the neural basis of cognitive deficits, a key feature of Alzheimer's disease (AD), is imperative for achieving the therapy of the disease. Rhythmic oscillatory activities in neural systems are a fundamental mechanism for diverse brain functions, including cognition. In several neurological conditions like AD, aberrant neural oscillations have been shown to play a central role. Furthermore, manipulation of brain oscillations in animals has confirmed their impact on cognition and disease. In this article, we review the evidence from mouse models that shows how synchronized oscillatory activity is intricately linked to AD machinery. We primarily focus on recent reports showing abnormal oscillatory activities at theta and gamma frequencies in AD condition and their influence on cellular disturbances and cognitive impairments. A thorough comprehension of the role that neuronal oscillations play in AD pathology should pave the way to therapeutic interventions that can curb the disease.

Phase-specific pooling of sparse assembly activity by respiration-related brain oscillations

Neuronal assemblies activate phase-coupled to ongoing respiration-related oscillations (RROs) in the medial prefrontal cortex of mice. The phase coupling strength of assemblies exceeds that of individual neurons. Assemblies preferentially activate during the descending phase of RRO. Despite higher assembly frequency during descending RRO, overlap between active assemblies remains constant across RRO phase. Putative GABAergic interneurons are preferentially recruited by assembly neurons during descending RRO, suggesting that interneurons might contribute to the segregation of active assemblies during the descending phase of RRO. ABSTRACT: Nasal breathing affects cognitive functions, but it has remained largely unclear how respiration-driven inputs shape information processing in neuronal circuits. Current theories emphasize the role of neuronal assemblies, coalitions of transiently active pyramidal cells, as the core unit of cortical network computations. Here, we show that the phase of respiration-related oscillations (RROs) influences the likelihood of activation of a subset of neuronal assemblies in the medial prefrontal cortex (mPFC) of awake mice. RROs bias the activation of neuronal assemblies more efficiently than that of individual neurons by entraining the coactivity of assembly neurons. Moreover, the activation of assemblies is moderately biased towards the descending phase of RROs. Despite the enriched activation of assemblies during descending RRO, the overlap between individual assemblies remains constant across RRO phases. Putative GABAergic interneurons are shown to coactivate with assemblies and receive enhanced excitatory drive from assembly neurons during descending RRO, suggesting that the phase-specific recruitment of putative interneurons might help to keep the activation of different assemblies separated from each other during times of preferred assembly activation. Our results thus identify respiration-synchronized brain rhythms as drivers of neuronal assemblies and point to a role of RROs in defining time windows of enhanced yet segregated assembly activity. Abstract figure legend. Nasal breathing affects cognitive functions, but it has remained largely unclear how respiration-driven inputs shape information processing in neuronal circuits. We show that the phase of respiration-related oscillations (RROs) influences the likelihood of the activation of a subset of neuronal assemblies in the medial prefrontal cortex (mPFC) of awake mice. The activation of assemblies is moderately biased towards the descending phase of RROs, while the overlap between individual assemblies remains constant across RRO phases. Putative GABAergic interneurons are shown to coactivate with assemblies and receive enhanced excitatory drive from assembly neurons during descending RRO, suggesting that the phase-specific recruitment of putative interneurons might help to keep the activation of different assemblies separated from each other. This article is protected by copyright. All rights reserved.

Topographically organized representation of space and context in the medial prefrontal cortex

The neocortex is composed of areas with specialized functions (e.g., sensory versus associational). Despite this functional diversity, emerging evidence suggests that the encoding of space might be a universal feature of cortical circuits. Here, we identified a gradient of spatial tuning depth along the dorsoventral axis. A complex topography of spatial tuning properties might support a division of labor among medial prefrontal cortical subnetworks to support local circuit computation relevant for the execution of context-dependent behavioral outcomes.

Spatial tuning of neocortical pyramidal cells has been observed in diverse cortical regions and is thought to rely primarily on input from the hippocampal formation. Despite the well-studied hippocampal place code, many properties of the neocortical spatial tuning system are still insufficiently understood. In particular, it has remained unclear how the topography of direct anatomical connections from hippocampus to neocortex affects spatial tuning depth, and whether the dynamics of spatial coding in the hippocampal output region CA1, such as remapping in novel environments, is transmitted to the neocortex. Using mice navigating through virtual environments, we addressed these questions in the mouse medial prefrontal cortex, which receives direct input from the hippocampus. We found a rapidly emerging prefrontal representation of space in the absence of task rules, which discriminates familiar from novel environments and is reinstated upon reexposure to the same familiar environment. Topographical analysis revealed a dorsoventral gradient in the representation of the own position, which runs opposite to the innervation density of hippocampal inputs. Jointly, these results reveal a dynamically emerging and topographically organized prefrontal place code during spontaneous locomotion.

Inhibitory control of synaptic signals preceding locomotion in mouse frontal cortex

The frontal cortex is essential for organizing voluntary movement. The secondary motor cortex (MOs) is a frontal subregion thought to integrate internal and external inputs before motor action. However, how excitatory and inhibitory synaptic inputs to MOs neurons are integrated preceding movement remains unclear. Here, we address this question by performing in vivo whole-cell recordings from MOs neurons of head-fixed mice moving on a treadmill. We find that principal neurons produce slowly increasing membrane potential and spike ramps preceding spontaneous running. After goal-directed training, ramps show larger amplitudes and accelerated kinetics. Chemogenetic suppression of interneurons combined with modeling suggests that the interplay between parvalbumin-positive (PV+) and somatostatin-positive (SOM+) interneurons, along with principal neuron recurrent connectivity, shape ramping signals. Plasticity of excitatory synapses on SOM+ interneurons can explain the ramp acceleration after training. Altogether, our data reveal that local interneurons differentially control task-dependent ramping signals when MOs neurons integrate inputs preceding movement.

Learning differentially shapes prefrontal and hippocampal activity during classical conditioning

The ability to use sensory cues to inform goal-directed actions is a critical component of behavior. To study how sounds guide anticipatory licking during classical conditioning, we employed high-density electrophysiological recordings from the hippocampal CA1 area and the prefrontal cortex (PFC) in mice. CA1 and PFC neurons undergo distinct learning-dependent changes at the single-cell level and maintain representations of cue identity at the population level. In addition, reactivation of task-related neuronal assemblies during hippocampal awake Sharp-Wave Ripples (aSWRs) changed within individual sessions in CA1 and over the course of multiple sessions in PFC. Despite both areas being highly engaged and synchronized during the task, we found no evidence for coordinated single cell or assembly activity during conditioning trials or aSWR. Taken together, our findings support the notion that persistent firing and reactivation of task-related neural activity patterns in CA1 and PFC support learning during classical conditioning.

Resurgent Sodium Current in Neurons of the Cerebral Cortex

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

Feature selectivity can explain mismatch signals in mouse visual cortex

Sensory experience often depends on one's own actions, including self-motion. Theories of predictive coding postulate that actions are regulated by calculating prediction error, which is the difference between sensory experience and expectation based on self-generated actions. Signals consistent with prediction error have been reported in the mouse visual cortex (V1) when visual flow coupled to running was unexpectedly stopped. Here, we show that such signals can be elicited by visual stimuli uncoupled to an animal running. We record V1 neurons while presenting drifting gratings that unexpectedly stop. We find strong responses to visual perturbations, which are enhanced during running. Perturbation responses are strongest in the preferred orientation of individual neurons, and perturbation-responsive neurons are more likely to prefer slow visual speeds. Our results indicate that prediction error signals can be explained by the convergence of known motor and sensory signals, providing a purely sensory and motor explanation for purported mismatch signals.

The grid code for ordered experience

Entorhinal cortical grid cells fire in a periodic pattern that tiles space, which is suggestive of a spatial coordinate system. However, irregularities in the grid pattern as well as responses of grid cells in contexts other than spatial navigation have presented a challenge to existing models of entorhinal function. In this Perspective, we propose that hippocampal input provides a key informative drive to the grid network in both spatial and non-spatial circumstances, particularly around salient events. We build on previous models in which neural activity propagates through the entorhinal-hippocampal network in time. This temporal contiguity in network activity points to temporal order as a necessary characteristic of representations generated by the hippocampal formation. We advocate that interactions in the entorhinal-hippocampal loop build a topological representation that is rooted in the temporal order of experience. In this way, the structure of grid cell firing supports a learned topology rather than a rigid coordinate frame that is bound to measurements of the physical world.

Resonating neurons stabilize heterogeneous grid-cell networks

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

Microcircuits for spatial coding in the medial entorhinal cortex

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

Spatially structured inhibition defined by polarized parvalbumin interneuron axons promotes head direction tuning

In cortical microcircuits, it is generally assumed that fast-spiking parvalbumin interneurons mediate dense and nonselective inhibition. Some reports indicate sparse and structured inhibitory connectivity, but the computational relevance and the underlying spatial organization remain unresolved. In the rat superficial presubiculum, we find that inhibition by fast-spiking interneurons is organized in the form of a dominant super-reciprocal microcircuit motif where multiple pyramidal cells recurrently inhibit each other via a single interneuron. Multineuron recordings and subsequent 3D reconstructions and analysis further show that this nonrandom connectivity arises from an asymmetric, polarized morphology of fast-spiking interneuron axons, which individually cover different directions in the same volume. Network simulations assuming topographically organized input demonstrate that such polarized inhibition can improve head direction tuning of pyramidal cells in comparison to a "blanket of inhibition." We propose that structured inhibition based on asymmetrical axons is an overarching spatial connectivity principle for tailored computation across brain regions.

Development of the Entorhinal Cortex Occurs via Parallel Lamination During Neurogenesis

The entorhinal cortex (EC) is the spatial processing center of the brain and structurally is an interface between the three layered paleocortex and six layered neocortex, known as the periarchicortex. Limited studies indicate peculiarities in the formation of the EC such as early emergence of cells in layers (L) II and late deposition of LIII, as well as divergence in the timing of maturation of cell types in the superficial layers. In this study, we examine developmental events in the entorhinal cortex using an understudied model in neuroanatomy and development, the pig and supplement the research with BrdU labeling in the developing mouse EC. We determine the pig serves as an excellent anatomical model for studying human neurogenesis, given its long gestational length, presence of a moderate sized outer subventricular zone and early cessation of neurogenesis during gestation. Immunohistochemistry identified prominent clusters of OLIG2+ oligoprogenitor-like cells in the superficial layers of the lateral EC (LEC) that are sparser in the medial EC (MEC). These are first detected in the subplate during the early second trimester. MRI analyses reveal an acceleration of EC growth at the end of the second trimester. BrdU labeling of the developing MEC, shows the deeper layers form first and prior to the superficial layers, but the LV/VI emerges in parallel and the LII/III emerges later, but also in parallel. We coin this lamination pattern parallel lamination. The early born Reln+ stellate cells in the superficial layers express the classic LV marker, Bcl11b (Ctip2) and arise from a common progenitor that forms the late deep layer LV neurons. In summary, we characterize the developing EC in a novel animal model and outline in detail the formation of the EC. We further provide insight into how the periarchicortex forms in the brain, which differs remarkably to the inside-out lamination of the neocortex.

Optogenetic pacing of medial septum parvalbumin-positive cells disrupts temporal but not spatial firing in grid cells

Grid cells in the medial entorhinal cortex (MEC) exhibit remarkable spatial activity patterns with spikes coordinated by theta oscillations driven by the medial septal area (MSA). Spikes from grid cells progress relative to the theta phase in a phenomenon called phase precession, which is suggested as essential to create the spatial periodicity of grid cells. Here, we show that optogenetic activation of parvalbumin-positive (PV⁺) cells in the MSA enabled selective pacing of local field potential (LFP) oscillations in MEC. During optogenetic stimulation, the grid cells were locked to the imposed pacing frequency but kept their spatial patterns. Phase precession was abolished, and speed information was no longer reflected in the LFP oscillations but was still carried by rate coding of individual MEC neurons. Together, these results support that theta oscillations are not critical to the spatial pattern of grid cells and do not carry a crucial velocity signal.

Creating and controlling visual environments using BonVision

Real-time rendering of closed-loop visual environments is important for next-generation understanding of brain function and behaviour, but is often prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source software for the display of virtual or augmented reality, as well as standard visual stimuli. BonVision has been tested on humans and mice, and is capable of supporting new experimental designs in other animal models of vision. As the architecture is based on the open-source Bonsai graphical programming language, BonVision benefits from native integration with experimental hardware. BonVision therefore enables easy implementation of closed-loop experiments, including real-time interaction with deep neural networks, and communication with behavioural and physiological measurement and manipulation devices.

Virtual Morris water maze: opportunities and challenges

The ability to accurately recall locations and navigate our environment relies on multiple cognitive mechanisms. The behavioural and neural correlates of spatial navigation have been repeatedly examined using different types of mazes and tasks with animals. Accurate performances of many of these tasks have proven to depend on specific circuits and brain structures and some have become the standard test of memory in many disease models. With the introduction of virtual reality (VR) to neuroscience research, VR tasks have become a popular method of examining human spatial memory and navigation. However, the types of VR tasks used to examine navigation across laboratories appears to greatly differ, from open arena mazes and virtual towns to driving simulators. Here, we examined over 200 VR navigation papers, and found that the most popular task used is the virtual analogue of the Morris water maze (VWM). Although we highlight the many advantages of using the VWM task, there are also some major difficulties related to the widespread use of this behavioural method. Despite the task's popularity, we demonstrate an inconsistency of use - particularly with respect to the environmental setup and procedures. Using different versions of the virtual water maze makes replication of findings and comparison of results across researchers very difficult. We suggest the need for protocol and design standardisation, alongside other difficulties that need to be addressed, if the virtual water maze is to become the 'gold standard' for human spatial research similar to its animal counterpart.

Distinct cortical thickness patterns link disparate cerebral cortex regions to select mobility domains

The cortical control of gait and mobility involves multiple brain regions. Therefore, one could speculate that the association between specific spatial patterns of cortical thickness may be differentially associated with different mobility domains. To test this possibility, 115 healthy participants aged 27–82 (mean 60.5 ± 13.8) underwent a mobility assessment (usual-walk, dual-task walk, Timed Up and Go) and MRI scan. Ten mobility domains of relatively simple (e.g., usual-walking) and complex tasks (i.e., dual task walking, turns, transitions) and cortical thickness of 68 ROIs were extracted. All associations between mobility and cortical thickness were controlled for age and gender. Scaled Subprofile Modelling (SSM), a PCA-regression, identified thickness patterns that were correlated with the individual mobility domains, controlling for multiple comparisons. We found that lower mean global cortical thickness was correlated with worse general mobility (r = − 0.296, p = 0.003), as measured by the time to complete the Timed Up and Go test. Three distinct patterns of cortical thickness were associated with three different gait domains during simple, usual-walking: pace, rhythm, and symmetry. In contrast, cortical thickness patterns were not related to the more complex mobility domains. These findings demonstrate that robust and topographically distinct cortical thickness patterns are linked to select mobility domains during relatively simple walking, but not to more complex aspects of mobility. Functional connectivity may play a larger role in the more complex aspects of mobility.

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

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

Presynaptic endoplasmic reticulum regulates short-term plasticity in hippocampal synapses

Short-term plasticity preserves a brief history of synaptic activity that is communicated to the postsynaptic neuron. This is primarily regulated by a calcium signal initiated by voltage dependent calcium channels in the presynaptic terminal. Imaging studies of CA3-CA1 synapses reveal the presence of another source of calcium, the endoplasmic reticulum (ER) in all presynaptic terminals. However, the precise role of the ER in modifying STP remains unexplored. We performed in-silico experiments in synaptic geometries based on reconstructions of the rat CA3-CA1 synapses to investigate the contribution of ER. Our model predicts that presynaptic ER is critical in generating the observed short-term plasticity profile of CA3-CA1 synapses and allows synapses with low release probability to operate more reliably. Blocking the ER lowers facilitation in a manner similar to what has been previously characterized in animal models of Alzheimer's disease and underscores the important role played by presynaptic stores in normal function.

In Vivo Whole-Cell Patch-Clamp Methods: Recent Technical Progress and Future Perspectives

Brain functions are fundamental for the survival of organisms, and they are supported by neural circuits consisting of a variety of neurons. To investigate the function of neurons at the single-cell level, researchers often use whole-cell patch-clamp recording techniques. These techniques enable us to record membrane potentials (including action potentials) of individual neurons of not only anesthetized but also actively behaving animals. This whole-cell recording method enables us to reveal how neuronal activities support brain function at the single-cell level. In this review, we introduce previous studies using in vivo patch-clamp recording techniques and recent findings primarily regarding neuronal activities in the hippocampus for behavioral function. We further discuss how we can bridge the gap between electrophysiology and biochemistry.

Spatial modulation of visual responses arises in cortex with active navigation

During navigation, the visual responses of neurons in mouse primary visual cortex (V1) are modulated by the animal's spatial position. Here we show that this spatial modulation is similarly present across multiple higher visual areas but negligible in the main thalamic pathway into V1. Similar to hippocampus, spatial modulation in visual cortex strengthens with experience and with active behavior. Active navigation in a familiar environment, therefore, enhances the spatial modulation of visual signals starting in the cortex.

Dentate Granule Cells Recruited in the Home Environment Display Distinctive Properties

The dentate granule cells (DGCs) play a crucial role in learning and memory. Many studies have described the role and physiological properties of these sparsely active neurons using different behavioral contexts. However, the morpho-functional features of DGCs recruited in mice maintained in their home cage (without training), considered as a baseline condition, have not yet been established. Using fosGFP transgenic mice, we observed ex vivo that DGCs recruited in animals maintained in the home cage condition are mature neurons that display a longer dendritic tree and lower excitability compared with non-activated cells. The higher GABA_A receptor-mediated shunting inhibition contributes to the lower excitability of DGCs activated in the home environment by shifting the input resistance towards lower values. Remarkably, that shunting inhibition is neither observed in non-activated DGCs nor in DGCs activated during training in virtual reality. In short, our results suggest that strong shunting inhibition and reduced excitability could constitute a distinctive neural signature of mature DGCs recruited in the context of the home environment.

Perineuronal nets stabilize the grid cell network

Grid cells are part of a widespread network which supports navigation and spatial memory. Stable grid patterns appear late in development, in concert with extracellular matrix aggregates termed perineuronal nets (PNNs) that condense around inhibitory neurons. It has been suggested that PNNs stabilize synaptic connections and long-term memories, but their role in the grid cell network remains elusive. We show that removal of PNNs leads to lower inhibitory spiking activity, and reduces grid cells' ability to create stable representations of a novel environment. Furthermore, in animals with disrupted PNNs, exposure to a novel arena corrupted the spatiotemporal relationships within grid cell modules, and the stored representations of a familiar arena. Finally, we show that PNN removal in entorhinal cortex distorted spatial representations in downstream hippocampal neurons. Together this work suggests that PNNs provide a key stabilizing element for the grid cell network.

Goal-directed interaction of stimulus and task demand in the parahippocampal region

The hippocampus and parahippocampal region are essential for representing episodic memories involving various spatial locations and objects, and for using those memories for future adaptive behavior. The “dual‐stream model” was initially formulated based on anatomical characteristics of the medial temporal lobe, dividing the parahippocampal region into two streams that separately process and relay spatial and nonspatial information to the hippocampus. Despite its significance, the dual‐stream model in its original form cannot explain recent experimental results, and many researchers have recognized the need for a modification of the model. Here, we argue that dividing the parahippocampal region into spatial and nonspatial streams a priori may be too simplistic, particularly in light of ambiguous situations in which a sensory cue alone (e.g., visual scene) may not allow such a definitive categorization. Upon reviewing evidence, including our own, that reveals the importance of goal‐directed behavioral responses in determining the relative involvement of the parahippocampal processing streams, we propose the Goal‐directed Interaction of Stimulus and Task‐demand (GIST) model. In the GIST model, input stimuli such as visual scenes and objects are first processed by both the postrhinal and perirhinal cortices—the postrhinal cortex more heavily involved with visual scenes and perirhinal cortex with objects—with relatively little dependence on behavioral task demand. However, once perceptual ambiguities are resolved and the scenes and objects are identified and recognized, the information is then processed through the medial or lateral entorhinal cortex, depending on whether it is used to fulfill navigational or non‐navigational goals, respectively. As complex sensory stimuli are utilized for both navigational and non‐navigational purposes in an intermixed fashion in naturalistic settings, the hippocampus may be required to then put together these experiences into a coherent map to allow flexible cognitive operations for adaptive behavior to occur.

Differential Relation between Neuronal and Behavioral Discrimination during Hippocampal Memory Encoding

How are distinct memories formed and used for behavior? To relate neuronal and behavioral discrimination during memory formation, we use in vivo 2-photon Ca2+ imaging and whole-cell recordings from hippocampal subregions in head-fixed mice performing a spatial virtual reality task. We find that subthreshold activity as well as population codes of dentate gyrus neurons robustly discriminate across different spatial environments, whereas neuronal remapping in CA1 depends on the degree of difference between visual cues. Moreover, neuronal discrimination in CA1, but not in the dentate gyrus, reflects behavioral performance. Our results suggest that CA1 weights the decorrelated information from the dentate gyrus according to its relevance, producing a map of memory representations that can be used by downstream circuits to guide learning and behavior.

Targeted Activation of Hippocampal Place Cells Drives Memory-Guided Spatial Behavior

The hippocampus is crucial for spatial navigation and episodic memory formation. Hippocampal place cells exhibit spatially selective activity within an environment and have been proposed to form the neural basis of a cognitive map of space that supports these mnemonic functions. However, the direct influence of place cell activity on spatial navigation behavior has not yet been demonstrated. Using an 'all-optical' combination of simultaneous two-photon calcium imaging and two-photon optogenetics, we identified and selectively activated place cells that encoded behaviorally relevant locations in a virtual reality environment. Targeted stimulation of a small number of place cells was sufficient to bias the behavior of animals during a spatial memory task, providing causal evidence that hippocampal place cells actively support spatial navigation and memory.

Novel Virtual Reality System for Auditory Tasks in Head-fixed Mice

An emerging corpus of research seeks to use virtual realities (VRs) to understand the neural mechanisms underlying spatial navigation and decision making in rodents. These studies have primarily used visual stimuli to represent the virtual world. However, auditory cues play an important role in navigation for animals, especially when the visual system cannot detect objects or predators. We have developed a virtual reality environment defined exclusively by free-field acoustic landmarks for head-fixed mice. We trained animals to run in a virtual environment with 3 acoustic landmarks. We present evidence that they can learn to navigate in our context: we observed anticipatory licking and modest anticipatory slowing preceding the reward region. Furthermore, we found that animals were highly aware of changes in landmark cues: licking behavior changed dramatically when the familiar virtual environment was switched to a novel one, and then rapidly reverted to normal when the familiar virtual environment was re-introduced, all within the same session. Finally, while animals executed the task, we performed in-vivo calcium imaging in the CA1 region of the hippocampus using a modified Miniscope.org system. Our experiments point to a future in which auditory virtual reality can be used to expand our understanding of the neural bases of audition in locomoting animals and the variety of sensory cues which anchor spatial representations in a new virtual environment.

Exploring the Spatial Relationships Between Real and Virtual Experiences: What Transfers and What Doesn't

Virtual environments are commonly used to assess spatial cognition in humans. For the past few decades, researchers have used virtual environments to investigate how people navigate, learn, and remember their surrounding environment. In combination with tools such as electroencephalogram, neuroimaging, and electrophysiology, these virtual environments have proven invaluable in their ability to help elucidate the underlying neural mechanisms of spatial learning and memory in humans. However, a critical assumption that is made whenever using virtual experiences is that the spatial abilities used in the navigation of these virtual environments accurately represents the spatial abilities used in the real-world. The aim of the current study is to investigate the spatial relationships between real and virtual environments to better understand how well the virtual experiences parallel the same experiences in the real-world. Here, we performed three independent experiments to examine whether spatial information about object location, environment layout, and navigation strategy transfers between parallel real-world and virtual-world experiences. We show that while general spatial information does transfer between real and virtual environments, there are several limitations of the virtual experience. Compared to the real-world, the use of information in the virtual-world is less flexible, especially when testing spatial memory from a novel location, and the way in which we navigate these experiences are different as the perceptual and proprioceptive feedback gained from the real-world experience can influence navigation strategy.

Grid cells are modulated by local head direction

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

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

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

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

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

Current approaches to modeling the virtual reality in rodents for the assessment of brain plasticity and behavior

Virtual reality (VR) and augmented reality (AR) have become valuable tools to study brains and behaviors resulting in development of new methods of diagnostics and treatment. Neurodegenerаtion is one of the best examples demonstrating efficacy of VR/АR technologies in modern neurology. Development of novel VR systems for rodents and combination of VR tools with up-to-date imaging techniques (i.e. MRI, imaging of neural networks etc.), brain electrophysiology (EEG, patch-clamp), precise analytics (microdialysis) allowed implementing of VR protocols into the animal neurobiology to study brain plasticity, sensorimotor integration, spatial navigation, memory, and decision-making. VR/AR for rodents is а young field of experimental neuroscience and has already provided more consistent testing conditions, less human-animal interaction, opportunities to use a wider variety of experimental parameters. Here we discuss present and future perspectives of using VR/AR to assess brain plasticity, neurogenesis and complex behavior in rodent and human study, and their advantages for translational neuroscience.

A computational model for grid maps in neural populations

Grid cells in the entorhinal cortex, together with head direction, place, speed and border cells, are major contributors to the organization of spatial representations in the brain. In this work we introduce a novel theoretical and algorithmic framework able to explain the optimality of hexagonal grid-like response patterns. We show that this pattern is a result of minimal variance encoding of neurons together with maximal robustness to neurons' noise and minimal number of encoding neurons. The novelty lies in the formulation of the encoding problem considering neurons as an overcomplete basis (a frame) where the position information is encoded. Through the modern Frame Theory language, specifically that of tight and equiangular frames, we provide new insights about the optimality of hexagonal grid receptive fields. The proposed model is based on the well-accepted and tested hypothesis of Hebbian learning, providing a simplified cortical-based framework that does not require the presence of velocity-driven oscillations (oscillatory model) or translational symmetries in the synaptic connections (attractor model). We moreover demonstrate that the proposed encoding mechanism naturally explains axis alignment of neighbor grid cells and maps shifts, rotations and scaling of the stimuli onto the shape of grid cells' receptive fields, giving a straightforward explanation of the experimental evidence of grid cells remapping under transformations of environmental cues.

Probing Cortical Activity During Head-Fixed Behavior

The cortex is crucial for many behaviors, ranging from sensory-based behaviors to working memory and social behaviors. To gain an in-depth understanding of the contribution to these behaviors, cellular and sub-cellular recordings from both individual and populations of cortical neurons are vital. However, techniques allowing such recordings, such as two-photon imaging and whole-cell electrophysiology, require absolute stability of the head, a requirement not often fulfilled in freely moving animals. Here, we review and compare behavioral paradigms that have been developed and adapted for the head-fixed preparation, which together offer the needed stability for live recordings of neural activity in behaving animals. We also review how the head-fixed preparation has been used to explore the function of primary sensory cortices, posterior parietal cortex (PPC) and anterior lateral motor (ALM) cortex in sensory-based behavioral tasks, while also discussing the considerations of performing such recordings. Overall, this review highlights the head-fixed preparation as allowing in-depth investigation into the neural activity underlying behaviors by providing highly controllable settings for precise stimuli presentation which can be combined with behavioral paradigms ranging from simple sensory detection tasks to complex, cross-modal, memory-guided decision-making tasks.

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

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