What grid cells convey about rat location

We characterize the relationship between the simultaneously recorded quantities of rodent grid cell firing and the position of the rat. The formalization reveals various properties of grid cell activity when considered as a neural code for representing and updating estimates of the rat's location. We show that, although the spatially periodic response of grid cells appears wasteful, the code is fully combinatorial in capacity. The resulting range for unambiguous position representation is vastly greater than the ≈1–10 m periods of individual lattices, allowing for unique high-resolution position specification over the behavioral foraging ranges of rats, with excess capacity that could be used for error correction. Next, we show that the merits of the grid cell code for position representation extend well beyond capacity and include arithmetic properties that facilitate position updating. We conclude by considering the numerous implications, for downstream readouts and experimental tests, of the properties of the grid cell code

A new class of neural architectures to model episodic memory : computational studies of distal reward learning

A computational cognitive neuroscience model is proposed, which models episodic memory based on the mammalian brain. A computational neural architecture instantiates the proposed model and is tested on a particular task of distal reward learning. Categorical Neural Semantic Theory informs the architecture design. To experiment upon the computational brain model, embodiment and an environment in which the embodiment exists are simulated. This simulated environment realizes the Morris Water Maze task, a well established biological experimental test of distal reward learning. The embodied neural architecture is treated as a virtual rat and the environment it acts in as a virtual water tank. Performance levels of the neural architectures are evaluated through analysis of embodied behavior in the distal reward learning task. Comparison is made to biological rat experimental data, as well as comparison to other published models. In addition, differences in performance are compared between the normal and categorically informed versions of the architecture

An oscillatory interference model of grid cell firing

We expand upon our proposal that the oscillatory interference mechanism proposed for the phase precession effect in place cells underlies the grid-like firing pattern of dorsomedial entorhinal grid cells (O'Keefe and Burgess (2005) Hippocampus 15:853-866). The original one-dimensional interference model is generalized to an appropriate two-dimensional mechanism. Specifically, dendritic subunits of layer 11 medial entorhinal stellate cells provide multiple linear interference patterns along different directions, with their product determining the firing of the cell. Connection of appropriate speed- and direction- dependent inputs onto dendritic subunits could result from an unsupervised learning rule which maximizes postsynaptic firing (e.g. competitive learning). These inputs cause the intrinsic oscillation of subunit membrane potential to. increase above theta frequency by an amount proportional to the animal's speed of running in the "preferred" direction. The phase difference between this oscillation and a somatic input at theta-frequency essentially integrates velocity so that the interference of the two oscillations reflects distance traveled in the preferred direction. The overall grid pattern is maintained in environmental location by phase reset of the grid cell by place cells receiving sensory input from the environment, and environmental boundaries in particular. We also outline possible variations on the basic model, including the generation of grid-like firing via the interaction of multiple cells rather than via multiple dendritic subunits. Predictions of the interference model are given for the frequency composition of EEG power spectra and temporal autocorrelograms of grid cell firing as functions of the speed and direction of running and the novelty of the environment. (C) 2007 Wiley-Liss, Inc

Contribution of Cerebellar Sensorimotor Adaptation to Hippocampal Spatial Memory

Complementing its primary role in motor control, cerebellar learning has also a bottom-up influence on cognitive functions, where high-level representations build up from elementary sensorimotor memories. In this paper we examine the cerebellar contribution to both procedural and declarative components of spatial cognition. To do so, we model a functional interplay between the cerebellum and the hippocampal formation during goal-oriented navigation. We reinterpret and complete existing genetic behavioural observations by means of quantitative accounts that cross-link synaptic plasticity mechanisms, single cell and population coding properties, and behavioural responses. In contrast to earlier hypotheses positing only a purely procedural impact of cerebellar adaptation deficits, our results suggest a cerebellar involvement in high-level aspects of behaviour. In particular, we propose that cerebellar learning mechanisms may influence hippocampal place fields, by contributing to the path integration process. Our simulations predict differences in place-cell discharge properties between normal mice and L7-PKCI mutant mice lacking long-term depression at cerebellar parallel fibre-Purkinje cell synapses. On the behavioural level, these results suggest that, by influencing the accuracy of hippocampal spatial codes, cerebellar deficits may impact the exploration-exploitation balance during spatial navigation

Contribution of the idiothetic and the allothetic information to the hippocampal place code

Hippocampal cells exhibit preference to be active at a specific place in a familiar environment, enabling them to encode the representation of space within the brain at the population level (J. O’Keefe and Dostrovsky 1971). These cells rely on the external sensory inputs and self-motion cues, however, it is still not known how exactly these inputs interact to build a stable representation of a certain location (“place field”). Existing studies suggest that both proprioceptive and other idiothetic types of information are continuously integrated to update the self-position (e.g. implementing “path integration”) while other stable sensory cues provide references to update the allocentric position of self and correct it for the collected integration-related errors. It was shown that both allocentric and idiothetic types of information influence positional cell firing, however in most of the studies these inputs were firmly coupled. The use of virtual reality setups (Thurley and Ayaz 2016) made it possible to separate the influence of vision and proprioception for the price of not keeping natural conditions - the animal is usually head- or body-fixed (Hölscher et al. 2005; Ravassard A. 2013; Jayakumar et al. 2018a; Haas et al. 2019), which introduces vestibular motor- and visual- conflicts, providing a bias for space encoding. Here we use the novel CAVE Virtual Reality system for freely-moving rodents (Del Grosso 2018) that allows to investigate the effect of visual- and positional- (vestibular) manipulation on the hippocampal space code while keeping natural behaving conditions. In this study, we focus on the dynamic representation of space when the visual- cue-defined and physical-boundary-defined reference frames are in conflict. We confirm the dominance of one reference frame over the other on the level of place fields, when the information about one reference frame is absent (Gothard et al. 2001). We show that the hippocampal cells form adjacent categories by their input preference - surprisingly, not only that they are being driven either by visual / allocentric information or by the distance to the physical boundaries and path integration, but also by a specific combination of both. We found a large category of units integrating inputs from both allocentric and idiothetic pathways that are able to represent an intermediate position between two reference frames, when they are in conflict. This experimental evidence suggests that most of the place cells are involved in representing both reference frames using a weighted combination of sensory inputs. In line with the studies showing dominance of the more reliable sensory modality (Kathryn J. Jeffery and J. M. O’Keefe 1999; Gothard et al. 2001), our data is consistent (although not proving it) with CA1 cells implementing an optimal Bayesian coding given the idiothetic and allocentric inputs with weights inversely proportional to the availability of the input, as proposed for other sensory systems (Kate J. Jeffery, Page, and Simon M. Stringer 2016). This mechanism of weighted sensory integration, consistent with recent dynamic loop models of the hippocampal-entorhinal network (Li, Arleo, and Sheynikhovich 2020), can contribute to the physiological explanation of Bayesian inference and optimal combination of spatial cues for localization (Cheng et al. 2007)

Theta-modulated place-by-direction cells in the hippocampal formation in the rat

We report the spatial and temporal properties of a class of cells termed theta-modulated place-by-direction (TPD) cells recorded from the presubicular and parasubicular cortices of the rat. The firing characteristics of TPD cells in open-field enclosures were compared with those of the following two other well characterized cell classes in the hippocampal formation: place and head-direction cells. Unlike place cells, which code only for the animal's location, or head-direction cells, which code only for the animal's directional heading, TPD cells code for both the location and the head direction of the animal. Their firing is also strongly theta modulated, firing primarily at the negative-to-positive phase of the locally recorded theta wave. TPD theta modulation is significantly stronger than that of place cells. In contrast, the firing of head-direction cells is not modulated by theta at all. In repeated exposures to the same environment, the locational and directional signals of TPD cells are stable. When recorded in different environments, TPD locational and directional fields can uncouple, with the locational field shifting unpredictably ("remapping"), whereas the directional preference remains similar across environments

A hierarchical anti-Hebbian network model for the formation of spatial cells in three-dimensional space.

Three-dimensional (3D) spatial cells in the mammalian hippocampal formation are believed to support the existence of 3D cognitive maps. Modeling studies are crucial to comprehend the neural principles governing the formation of these maps, yet to date very few have addressed this topic in 3D space. Here we present a hierarchical network model for the formation of 3D spatial cells using anti-Hebbian network. Built on empirical data, the model accounts for the natural emergence of 3D place, border, and grid cells, as well as a new type of previously undescribed spatial cell type which we call plane cells. It further explains the plausible reason behind the place and grid-cell anisotropic coding that has been observed in rodents and the potential discrepancy with the predicted periodic coding during 3D volumetric navigation. Lastly, it provides evidence for the importance of unsupervised learning rules in guiding the formation of higher-dimensional cognitive maps

Gravin orchestrates protein kinase A and 2-adrenergic receptor signaling critical for synaptic plasticity and memory

A kinase-anchoring proteins (AKAPs) organize compartmentalized pools of protein kinase A (PKA) to enable localized signaling events within neurons. However, it is unclear which of the many expressed AKAPs in neurons target PKA to signaling complexes important for long-lasting forms of synaptic plasticity and memory storage. In the forebrain, the anchoring protein gravin recruits a signaling complex containing PKA, PKC, calmodulin, and PDE4D (phosphodiesterase 4D) to the β2-adrenergic receptor. Here, we show that mice lacking the α-isoform of gravin have deficits in PKA-dependent long-lasting forms of hippocampal synaptic plasticity including β2-adrenergic receptor-mediated plasticity, and selective impairments of long-term memory storage. Furthermore, both hippocampal β2-adrenergic receptor phosphorylation by PKA, and learning-induced activation of ERK in the CA1 region of the hippocampus are attenuated in mice lacking gravin-α. We conclude that gravin compartmentalizes a significant pool of PKA that regulates learning-induced β2-adrenergic receptor signaling and ERK activation in the hippocampus in vivo, thereby organizing molecular interactions between glutamatergic and noradrenergic signaling pathways for long-lasting synaptic plasticity, and memory storage