Different CA1 and CA3 representations of novel routes in a shortcut situation

Remapping revisited: how the hippocampus represents different spaces

The representation of distinct spaces by hippocampal place cells has been linked to changes in their place fields (the locations in the environment where the place cells discharge strongly), a phenomenon that has been termed 'remapping'. Remapping has been assumed to be accompanied by the reorganization of subsecond cofiring relationships among the place cells, potentially maximizing hippocampal information coding capacity. However, several observations challenge this standard view. For example, place cells exhibit mixed selectivity, encode non-positional variables, can have multiple place fields and exhibit unreliable discharge in fixed environments. Furthermore, recent evidence suggests that, when measured at subsecond timescales, the moment-to-moment cofiring of a pair of cells in one environment is remarkably similar in another environment, despite remapping. Here, I propose that remapping is a misnomer for the changes in place fields across environments and suggest instead that internally organized manifold representations of hippocampal activity are actively registered to different environments to enable navigation, promote memory and organize knowledge.

A map of spatial navigation for neuroscience

Spatial navigation has received much attention from neuroscientists, leading to the identification of key brain areas and the discovery of numerous spatially selective cells. Despite this progress, our understanding of how the pieces fit together to drive behavior is generally lacking. We argue that this is partly caused by insufficient communication between behavioral and neuroscientific researchers. This has led the latter to under-appreciate the relevance and complexity of spatial behavior, and to focus too narrowly on characterizing neural representations of space-disconnected from the computations these representations are meant to enable. We therefore propose a taxonomy of navigation processes in mammals that can serve as a common framework for structuring and facilitating interdisciplinary research in the field. Using the taxonomy as a guide, we review behavioral and neural studies of spatial navigation. In doing so, we validate the taxonomy and showcase its usefulness in identifying potential issues with common experimental approaches, designing experiments that adequately target particular behaviors, correctly interpreting neural activity, and pointing to new avenues of research.

Disarrangement and reorganization of the hippocampal functional connectivity during the spatial path adjustment of pigeons

Background

The hippocampus plays an important role to support path planning and adjustment in goal-directed spatial navigation. While we still only have limited knowledge about how do the hippocampal neural activities, especially the functional connectivity patterns, change during the spatial path adjustment. In this study, we measured the behavioural indicators and local field potentials of the pigeon (Columba livia, male and female) during a goal-directed navigational task with the detour paradigm, exploring the changing patterns of the hippocampal functional network connectivity of the bird during the spatial path learning and adjustment.

Results

Our study demonstrates that the pigeons progressively learned to solve the path adjustment task after the preferred path is blocked suddenly. Behavioural results show that both the total duration and the path lengths pigeons completed the task during the phase of adjustment are significantly longer than those during the acquisition and recovery phases. Furthermore, neural results show that hippocampal functional connectivity selectively changed during path adjustment. Specifically, we identified depressed connectivity in lower bands (delta and theta) and elevated connectivity in higher bands (slow-gamma and fast-gamma).

Conclusions

These results feature both the behavioural response and neural representation of the avian spatial cognitive learning process, suggesting that the functional disarrangement and reorganization of the connectivity in the avian hippocampus during different phases may contribute to our further understanding of the potential mechanism of path learning and adjustment.

Predictive maps in rats and humans for spatial navigation

Much of our understanding of navigation comes from the study of individual species, often with specific tasks tailored to those species. Here, we provide a novel experimental and analytic framework integrating across humans, rats, and simulated reinforcement learning (RL) agents to interrogate the dynamics of behavior during spatial navigation. We developed a novel open-field navigation task ("Tartarus maze") requiring dynamic adaptation (shortcuts and detours) to frequently changing obstructions on the path to a hidden goal. Humans and rats were remarkably similar in their trajectories. Both species showed the greatest similarity to RL agents utilizing a "successor representation," which creates a predictive map. Humans also displayed trajectory features similar to model-based RL agents, which implemented an optimal tree-search planning procedure. Our results help refine models seeking to explain mammalian navigation in dynamic environments and highlight the utility of modeling the behavior of different species to uncover the shared mechanisms that support behavior.

Glutamate Receptor Interacting Protein 1 in the Dorsal CA1 Drives Alpha-amino-3-hydroxy-5-methyl-4-Isoxazolepropionic Acid Receptor Endocytosis and Exocytosis Bidirectionally and Mediates Forgetting, Exploratory, and Anxiety-like Behavior

Endocytosis of GluA2-containing alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) in CA1 of the hippocampus regulates forgetting; deficits in forgetting nociceptive memory can induce serious stress disorders. As a transporter of GluA2-containing AMPAR, the functions of glutamate receptor interacting protein 1 (GRIP1) in forgetting and possible stress responses remain unclear. Lentivirus-mediated interference of GRIP1 expression or function in the dorsal CA1 of the hippocampus in mice indicated that GRIP1 overexpression enhanced spatial memory, impaired forgetting in a Barnes maze, and induced anxiety-like behavior in the open field and elevated plus-maze test. In contrast, GRIP1 knockdown impaired learning capacity. Furthermore, inhibition of the PDZ2 and PDZ4/5 domains of GRIP1 and GluA2-dn enhanced learning capacity, whereas GluA2-dn impaired spatial memory; inhibition of the PDZ2 and PDZ4/5 domains of GRIP1 also decreased forgetting capacity to some extent. Importantly, inhibition of both the PDZ2 and PDZ4/5 domains of GRIP1 induced anxiety-like behavior but not GluA2-dn. Furthermore, optogenetic control of both GluA1 and GluA2 insertion into the postsynaptic membrane impaired memory and induced anxiety-like behavior. In vitro experiments showed that GRIP1-ov and -dn, inhibition of PDZ2 and PDZ4/5 domains of GRIP1, and GluA2-dn decreased glycine-induced GluA1 and GluA2 exocytosis; meanwhile, GRIP1-ov and -dn, and interference of PDZ2 and PDZ4/5 domains of GRIP1 blocked AMPA- and NMDA-induced GluA1 and GluA2 endocytosis. Overall, these results suggest that GRIP1 drives AMPA receptor endocytosis and exocytosis bidirectionally; furthermore, GRIP1-induced stabilization of anchoring postsynaptic GluA1 and GluA2 impairs forgetting and induces anxiety-like behavior. GRIP1 may provide a potential therapeutic target in posttraumatic syndromes and anxiety disorders.

Elevated Gamma Connectivity in Nidopallium Caudolaterale of Pigeons during Spatial Path Adjustment

Previous studies showed that spatial navigation depends on a local network including multiple brain regions with strong interactions. However, it is still not fully understood whether and how the neural patterns in avian nidopallium caudolaterale (NCL), which is suggested to play a key role in navigation as a higher cognitive structure, are modulated by the behaviors during spatial navigation, especially involved path adjustment needs. Hence, we examined neural activity in the NCL of pigeons and explored the local field potentials' (LFPs) spectral and functional connectivity patterns in a goal-directed spatial cognitive task with the detour paradigm. We found the pigeons progressively learned to solve the path adjustment task when the learned path was blocked suddenly. Importantly, the behavioral changes during the adjustment were accompanied by the modifications in neural patterns in the NCL. Specifically, the spectral power in lower bands (1-4 Hz and 5-12 Hz) decreased as the pigeons were tested during the adjustment. Meanwhile, an elevated gamma (31-45 Hz and 55-80 Hz) connectivity in the NCL was also detected. These results and the partial least square discriminant analysis (PLS-DA) modeling analysis provide insights into the neural activities in the avian NCL during the spatial path adjustment, contributing to understanding the potential mechanism of avian spatial encoding. This study suggests the important role of the NCL in spatial learning, especially path adjustment in avian navigation.

Flexible rerouting of hippocampal replay sequences around changing barriers in the absence of global place field remapping

Flexibility is a hallmark of memories that depend on the hippocampus. For navigating animals, flexibility is necessitated by environmental changes such as blocked paths and extinguished food sources. To better understand the neural basis of this flexibility, we recorded hippocampal replays in a spatial memory task where barriers as well as goals were moved between sessions to see whether replays could adapt to new spatial and reward contingencies. Strikingly, replays consistently depicted new goal-directed trajectories around each new barrier configuration and largely avoided barrier violations. Barrier-respecting replays were learned rapidly and did not rely on place cell remapping. These data distinguish sharply between place field responses, which were largely stable and remained tied to sensory cues, and replays, which changed flexibly to reflect the learned contingencies in the environment and suggest sequenced activations such as replay to be an important link between the hippocampus and flexible memory.

Hippocampal place cells encode global location but not connectivity in a complex space

Flexible navigation relies on a cognitive map of space, thought to be implemented by hippocampal place cells: neurons that exhibit location-specific firing. In connected environments, optimal navigation requires keeping track of one's location and of the available connections between subspaces. We examined whether the dorsal CA1 place cells of rats encode environmental connectivity in four geometrically identical boxes arranged in a square. Rats moved between boxes by pushing saloon-type doors that could be locked in one or both directions. Although rats demonstrated knowledge of environmental connectivity, their place cells did not respond to connectivity changes, nor did they represent doorways differently from other locations. Place cells coded location in a global reference frame, with a different map for each box and minimal repetitive fields despite the repetitive geometry. These results suggest that CA1 place cells provide a spatial map that does not explicitly include connectivity.

The Versatile Wayfinder: Prefrontal Contributions to Spatial Navigation

The prefrontal cortex (PFC) supports decision-making, goal tracking, and planning. Spatial navigation is a behavior that taxes these cognitive processes, yet the role of the PFC in models of navigation has been largely overlooked. In humans, activity in dorsolateral PFC (dlPFC) and ventrolateral PFC (vlPFC) during detours, reveal a role in inhibition and replanning. Dorsal anterior cingulate cortex (dACC) is implicated in planning and spontaneous internally-generated changes of route. Orbitofrontal cortex (OFC) integrates representations of the environment with the value of actions, providing a 'map' of possible decisions. In rodents, medial frontal areas interact with hippocampus during spatial decisions and switching between navigation strategies. In reviewing these advances, we provide a framework for how different prefrontal regions may contribute to different stages of navigation.

Hippocampal Hyperactivity as a Druggable Circuit-Level Origin of Aberrant Salience in Schizophrenia

The development of current neuroleptics was largely aiming to decrease excessive dopaminergic signaling in the striatum. However, the notion that abnormal dopamine creates psychotic symptoms by causing an aberrant assignment of salience that drives maladaptive learning chronically during disease development suggests a therapeutic value of early interventions that correct salience-related neural processing. The mesolimbic dopaminergic output is modulated by several interconnected brain-wide circuits centrally involving the hippocampus and key relays like the ventral and associative striatum, ventral pallidum, amygdala, bed nucleus of the stria terminalis, nucleus reuniens, lateral and medial septum, prefrontal and cingulate cortex, among others. Unraveling the causal relationships between these circuits using modern neuroscience techniques holds promise for identifying novel cellular-and ultimately molecular-treatment targets for reducing transition to psychosis and symptoms of schizophrenia. Imaging studies in humans have implicated a hyperactivity of the hippocampus as a robust and early endophenotype in schizophrenia. Experiments in rodents, in turn, suggested that the activity of its output region-the ventral subiculum-may modulate dopamine release from ventral tegmental area (VTA) neurons in the ventral striatum. Even though these observations suggested a novel circuit-level target for anti-psychotic action, no therapy has yet been developed along this rationale. Recently evaluated treatment strategies-at least in part-target excess glutamatergic activity, e.g. N-acetyl-cysteine (NAC), levetiracetam, and mGluR2/3 modulators. We here review the evidence for the central implication of the hippocampus-VTA axis in schizophrenia-related pathology, discuss its symptom-related implications with a particular focus on aberrant assignment of salience, and evaluate some of its short-comings and prospects for drug discovery.

Time as the fourth dimension in the hippocampus

Experiences of animal and human beings are structured by the continuity of space and time coupled with the uni-directionality of time. In addition to its pivotal position in spatial processing and navigation, the hippocampal system also plays a central, multiform role in several types of temporal processing. These include timing and sequence learning, at scales ranging from meso-scales of seconds to macro-scales of minutes, hours, days and beyond, encompassing the classical functions of short term memory, working memory, long term memory, and episodic memories (comprised of information about when, what, and where). This review article highlights the principal findings and behavioral contexts of experiments in rats showing: 1) timing: tracking time during delays by hippocampal 'time cells' and during free behavior by hippocampal-afferent lateral entorhinal cortex ramping cells; 2) 'online' sequence processing: activity coding sequences of events during active behavior; 3) 'off-line' sequence replay: during quiescence or sleep, orderly reactivation of neuronal assemblies coding awake sequences. Studies in humans show neurophysiological correlates of episodic memory comparable to awake replay. Neural mechanisms are discussed, including ion channel properties, plateau and ramping potentials, oscillations of excitation and inhibition of population activity, bursts of high amplitude discharges (sharp wave ripples), as well as short and long term synaptic modifications among and within cell assemblies. Specifically conceived neural network models will suggest processes supporting the emergence of scalar properties (Weber's law), and include different classes of feedforward and recurrent network models, with intrinsic hippocampal coding for 'transitions' (sequencing of events or places).

Three brain states in the hippocampus and cortex

Contemporary brain research seeks to understand how cognition is reducible to neural activity. Crucially, much of this effort is guided by a scientific paradigm that views neural activity as essentially driven by external stimuli. In contrast, recent perspectives argue that this paradigm is by itself inadequate and that understanding patterns of activity intrinsic to the brain is needed to explain cognition. Yet, despite this critique, the stimulus-driven paradigm still dominates-possibly because a convincing alternative has not been clear. Here, we review a series of findings suggesting such an alternative. These findings indicate that neural activity in the hippocampus occurs in one of three brain states that have radically different anatomical, physiological, representational, and behavioral correlates, together implying different functional roles in cognition. This three-state framework also indicates that neural representations in the hippocampus follow a surprising pattern of organization at the timescale of ∼1 s or longer. Lastly, beyond the hippocampus, recent breakthroughs indicate three parallel states in the cortex, suggesting shared principles and brain-wide organization of intrinsic neural activity.

Prefrontal Dynamics Associated with Efficient Detours and Shortcuts: A Combined Functional Magnetic Resonance Imaging and Magnetoencenphalography Study

Central to the concept of the “cognitive map” is that it confers behavioral flexibility, allowing animals to take efficient detours, exploit shortcuts, and avoid alluring, but unhelpful, paths. The neural underpinnings of such naturalistic and flexible behavior remain unclear. In two neuroimaging experiments, we tested human participants on their ability to navigate to a set of goal locations in a virtual desert island riven by lava, which occasionally spread to block selected paths (necessitating detours) or receded to open new paths (affording real shortcuts or false shortcuts to be avoided). Detours activated a network of frontal regions compared with shortcuts. Activity in the right dorsolateral PFC specifically increased when participants encountered tempting false shortcuts that led along suboptimal paths that needed to be differentiated from real shortcuts. We also report modulation in event-related fields and theta power in these situations, providing insight to the temporal evolution of response to encountering detours and shortcuts. These results help inform current models as to how the brain supports navigation and planning in dynamic environments.

Robust spatial memory maps encoded by networks with transient connections

The spiking activity of principal cells in mammalian hippocampus encodes an internalized neuronal representation of the ambient space—a cognitive map. Once learned, such a map enables the animal to navigate a given environment for a long period. However, the neuronal substrate that produces this map is transient: the synaptic connections in the hippocampus and in the downstream neuronal networks never cease to form and to deteriorate at a rapid rate. How can the brain maintain a robust, reliable representation of space using a network that constantly changes its architecture? We address this question using a computational framework that allows evaluating the effect produced by the decaying connections between simulated hippocampal neurons on the properties of the cognitive map. Using novel Algebraic Topology techniques, we demonstrate that emergence of stable cognitive maps produced by networks with transient architectures is a generic phenomenon. The model also points out that deterioration of the cognitive map caused by weakening or lost connections between neurons may be compensated by simulating the neuronal activity. Lastly, the model explicates the importance of the complementary learning systems for processing spatial information at different levels of spatiotemporal granularity.

The reliability of our memories is nothing short of remarkable. Synaptic connections between neurons appear and disappear at a rapid rate, and the resulting networks constantly change their architecture due to various forms of neural plasticity. How can the brain develop a reliable representation of the world, learn and retain memories despite, or perhaps due to, such complex dynamics? Below we address these questions by modeling mechanisms of spatial learning in the hippocampal network, using novel algebraic topology methods. We demonstrate that although the functional units of the hippocampal network—the place cell assemblies—are unstable structures that may appear and disappear, the spatial memory map produced by a sufficiently large population of such assemblies robustly captures the topological structure of the environment.

To take or not to take the shortcut: Flexible spatial behaviour of rats based on cognitive map in a lattice maze

To examine the flexibility of rats' spatial behaviour, we required rats to navigate to one of four boxes on the corners of a lattice maze. The maze consisted of five vertical and five horizontal corridors on a plane parallel to the ground and allowed us to design diverse routes. One box was set as goal and the other three were set as starting points. Both the time to arrive at the goal and the number of errors at the intersections on the route decreased, suggesting that the rats learned the route. As the goal boxes were successively changed, the decrease in the errors and the time to reach the goal became faster. This suggests that the rats learned the spatial layout of the maze, i.e., developed a cognitive map. We then carried out a shortcut test by removing one wall located near the centre of the maze. The rats took the shortcut route when passing through the location around the removed wall made the entire route shorter, but did not pass through the location when passing through the location made the entire route longer. These suggest that rats can flexibly utilize their internal representation of a spatial structure to respond to a change in a learned environment.

Inhibition shapes the organization of hippocampal representations

Hippocampal neurons become tuned to stimuli that predict behaviorally salient outcomes. This plasticity suggests that memory formation depends upon shifts in how different anatomical inputs can drive hippocampal activity. Here, I present evidence that inhibitory neurons can provide such a mechanism for learning-related changes in the tuning of pyramidal cells. Inhibitory currents arriving on the dendrites of pyramidal cells determine whether an excitatory input can drive action potential output. Specificity and plasticity of this dendritic modulation allows for precise, modifiable changes in how afferent inputs are integrated, a process that defines a neuron's receptive field. In addition, feedback inhibition plays a fundamental role in biasing which excitatory neurons may be co-active. By defining the rules of synchrony and the rules of input integration, interneurons likely play an important role in the organization of memory representation within the hippocampus.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

A map of abstract relational knowledge in the human hippocampal-entorhinal cortex

The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal-entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns.

Network mechanisms of hippocampal laterality, place coding, and goal-directed navigation

The hippocampus and associated structures are responsible for episodic memory in humans. In rodents, the most prominent behavioral correlate of hippocampal neural activity is place coding, which is thought to underlie spatial navigation. While episodic memory is considered to be unique to humans in a restricted context, it has been proposed that the same neural circuitry and algorithms that enable spatial coding and navigation also support episodic memory. Here we review the recent progress in neural circuit mechanisms of hippocampal activity by introducing several topics: (1) cooperation and specialization of the bilateral hippocampi, (2) the role of synaptic plasticity in gamma phase-locking of spikes and place cell formation, (3) impaired goal-related activity and oscillations in a mouse model of mental disorders, and (4) a prefrontal-thalamo-hippocampal circuit for goal-directed spatial navigation.

Unlocking neural complexity with a robotic key

Complex brains evolved in order to comprehend and interact with complex environments in the real world. Despite significant progress in our understanding of perceptual representations in the brain, our understanding of how the brain carries out higher level processing remains largely superficial. This disconnect is understandable, since the direct mapping of sensory inputs to perceptual states is readily observed, while mappings between (unknown) stages of processing and intermediate neural states is not. We argue that testing theories of higher level neural processing on robots in the real world offers a clear path forward, since (1) the complexity of the neural robotic controllers can be staged as necessary, avoiding the almost intractable complexity apparent in even the simplest current living nervous systems; (2) robotic controller states are fully observable, avoiding the enormous technical challenge of recording from complete intact brains; and (3) unlike computational modelling, the real world can stand for itself when using robots, avoiding the computational intractability of simulating the world at an arbitrary level of detail. We suggest that embracing the complex and often unpredictable closed-loop interactions between robotic neuro-controllers and the physical world will bring about deeper understanding of the role of complex brain function in the high-level processing of information and the control of behaviour.

Detour Behavior of Mice Trained with Transparent, Semitransparent and Opaque Barriers

Detour tasks are commonly used to study problem solving skills and inhibitory control in canids and primates. However, there is no comparable detour test designed for rodents despite its significance for studying the development of executive skills. Furthermore, mice offer research opportunities that are not currently possible to achieve when primates are used. Therefore, the aim of the study was to translate the classic detour task to mice and to compare obtained data with key findings obtained previously in other mammals. The experiment was performed with V-shaped barriers and was based on the water escape paradigm. The study showed that an apparently simple task requiring mice to move around a small barrier constituted in fact a challenge that was strongly affected by the visibility of the target. The most difficult task involved a completely transparent barrier, which forced the mice to resolve a conflict between vision and tactile perception. The performance depended both on the inhibitory skills and on previous experiences. Additionally, all mice displayed a preference for one side of the barrier and most of them relied on the egocentric strategy. Obtained results show for the first time that the behavior of mice subjected to the detour task is comparable to the behavior of other mammals tested previously with free-standing barriers. This detailed characterization of the detour behavior of mice constitutes the first step toward the substitution of rodents for primates in laboratory experiments employing the detour task.

Early Failures Benefit Subsequent Task Performance

Animals navigate using cognitive maps. However, how they adaptively exploit these maps in changing environments is not fully understood. In this study, we investigated the problem-solving behaviors of mice in a complicated maze in which multiple routes with different intersections were available (Test 1). Although all mice eventually settled on the shortest route, mice that initially exhibited more trial-and-error exploration solved the maze more rapidly. We then introduced one or two barriers that obstructed learned routes such that mice had to establish novel roundabout detours (Tests 2/3). Solutions varied among mice but were predictable based on individual early trial-and-error patterns observed in Test 1: mice that had initially explored more extensively found better solutions. Finally, when the barriers were removed (Test 4), all mice reverted to the best solution after active exploration. Thus, early active exploration helps mice to develop optimal strategies.

Is there a pilot in the brain? Contribution of the self-positioning system to spatial navigation

Since the discovery of place cells, the hippocampus is thought to be the neural substrate of a cognitive map. The later discovery of head direction cells, grid cells and border cells, as well as of cells with more complex spatial signals, has led to the idea that there is a brain system devoted to providing the animal with the information required to achieve efficient navigation. Current questioning is focused on how these signals are integrated in the brain. In this review, we focus on the issue of how self-localization is performed in the hippocampal place cell map. To do so, we first shortly review the sensory information used by place cells and then explain how this sensory information can lead to two coding modes, respectively based on external landmarks (allothetic information) and self-motion cues (idiothetic information). We hypothesize that these two modes can be used concomitantly with the rat shifting from one mode to the other during its spatial displacements. We then speculate that sequential reactivation of place cells could participate in the resetting of self-localization under specific circumstances and in learning a new environment. Finally, we provide some predictions aimed at testing specific aspects of the proposed ideas.

Possible cause for altered spatial cognition of prepubescent rats exposed to chronic radiofrequency electromagnetic radiation

The effects of chronic and repeated radiofrequency electromagnetic radiation (RFEMR) exposure on spatial cognition and hippocampal architecture were investigated in prepubescent rats. Four weeks old male Wistar rats were exposed to RF-EMR (900 MHz; SAR-1.15 W/kg with peak power density of 146.60 μW/cm(2)) for 1 h/day, for 28 days. Followed by this, spatial cognition was evaluated by Morris water maze test. To evaluate the hippocampal morphology; H&E staining, cresyl violet staining, and Golgi-Cox staining were performed on hippocampal sections. CA3 pyramidal neuron morphology and surviving neuron count (in CA3 region) were studied using H&E and cresyl violet stained sections. Dendritic arborization pattern of CA3 pyramidal neuron was investigated by concentric circle method. Progressive learning abilities were found to be decreased in RF-EMR exposed rats. Memory retention test performed 24 h after the last training revealed minor spatial memory deficit in RF-EMR exposed group. However, RF-EMR exposed rats exhibited poor spatial memory retention when tested 48 h after the final trial. Hirano bodies and Granulovacuolar bodies were absent in the CA3 pyramidal neurons of different groups studied. Nevertheless, RF-EMR exposure affected the viable cell count in dorsal hippocampal CA3 region. RF-EMR exposure influenced dendritic arborization pattern of both apical and basal dendritic trees in RF-EMR exposed rats. Structural changes found in the hippocampus of RF-EMR exposed rats could be one of the possible reasons for altered cognition.

Solving the detour problem in navigation: a model of prefrontal and hippocampal interactions

Adapting behavior to accommodate changes in the environment is an important function of the nervous system. A universal problem for motile animals is the discovery that a learned route is blocked and a detour is required. Given the substantial neuroscience research on spatial navigation and decision-making it is surprising that so little is known about how the brain solves the detour problem. Here we review the limited number of relevant functional neuroimaging, single unit recording and lesion studies. We find that while the prefrontal cortex (PFC) consistently responds to detours, the hippocampus does not. Recent evidence suggests the hippocampus tracks information about the future path distance to the goal. Based on this evidence we postulate a conceptual model in which: Lateral PFC provides a prediction error signal about the change in the path, frontopolar and superior PFC support the re-formulation of the route plan as a novel subgoal and the hippocampus simulates the new path. More data will be required to validate this model and understand (1) how the system processes the different options; and (2) deals with situations where a new path becomes available (i.e., shortcuts).

Principles of goal-directed spatial robot navigation in biomimetic models

Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in 'real-world' environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

Relative contributions of CA3 and medial entorhinal cortex to memory in rats

The hippocampal CA1 field processes spatial information, but the relative importance of intra- vs. extra-hippocampal sources of input into CA1 for spatial behavior is unclear. To characterize the relative roles of these two sources of input, originating in the hippocampal field CA3 and in the medial entorhinal cortex (MEC), we studied effects of discrete neurotoxic lesions of CA3 or MEC on concurrent spatial and nonspatial navigation tasks, and on synaptic transmission in afferents to CA1. Lesions in CA3 or MEC regions that abolished CA3-CA1, or reduced MEC-CA1 synaptic transmission, respectively, impaired spatial navigation and unexpectedly interfered with cue response, suggesting that in certain conditions of training regimen, hippocampal activity may influence behavior otherwise supported by nonhippocampal neural networks. MEC lesions had milder and temporary behavioral effects, but also markedly amplified transmission in the CA3-CA1 pathway. Extensive behavioral training had a similar, but more modest effect on CA3-CA1 transmission. Thus, cortical input to the hippocampus modulates CA1 activity both directly and indirectly, through heterosynaptic interaction, to control information flow in the hippocampal loop. Following damage to hippocampal cortical input, the functional coupling of separate intra- and extra-hippocampal inputs to CA1 involved in normal learning may initiate processes that support recovery of behavioral function. Such a process may explain how CA3 lesions, which do not significantly modify the basic features of CA1 neural activity, nonetheless impair spatial recall, whereas lesions of EC input to CA1, which reduce the spatial selectivity of CA1 firing in foraging rats, have only mild effects on spatial navigation.

Complementary roles of human hippocampal subregions during retrieval of spatiotemporal context

Current evidence strongly supports the central involvement of the human medial temporal lobes (MTL) in storing and retrieving memories for recently experienced events. However, a critical remaining question regards exactly how the hippocampus and surrounding cortex represents spatiotemporal context defining an event in memory. Competing accounts suggest that this process may be accomplished by the following: (1) an overall increase in neural similarity of representations underlying spatial and temporal context, (2) a differentiation of competing spatiotemporal representations, or (3) a combination of the two processes, with different subregions performing these two functions within the MTL. To address these competing proposals, we used high-resolution functional magnetic resonance imaging targeting the MTL along with a multivariate pattern similarity approach with 19 participants. While undergoing imaging, participants performed a task in which they retrieved spatial and temporal contextual representations from a recently learned experience. Results showed that successfully retrieving spatiotemporal context defining an episode involved a decrease in pattern similarity between putative spatial and temporal contextual representations in hippocampal subfields CA2/CA3/DG, whereas the parahippocampal cortex (PHC) showed the opposite pattern. These findings could not be accounted for by differences in univariate activations for complete versus partial retrieval nor differences in correlations for correct or incorrect retrieval. Together, these data suggest that the CA2/CA3/DG serves to differentiate competing contextual representations, whereas the PHC stores a comparatively integrated trace of scene-specific context, both of which likely play important roles in successful episodic memory retrieval.

Hippocampal representation of related and opposing memories develop within distinct, hierarchically organized neural schemas

Recent evidence suggests that the hippocampus may integrate overlapping memories into relational representations, or schemas, that link indirectly related events and support flexible memory expression. Here we explored the nature of hippocampal neural population representations for multiple features of events and the locations and contexts in which they occurred. Hippocampal networks developed hierarchical organizations of associated elements of related but separately acquired memories within a context, and distinct organizations for memories where the contexts differentiated object-reward associations. These findings reveal neural mechanisms for the development and organization of relational representations.

Place cell rate remapping by CA3 recurrent collaterals

Episodic-like memory is thought to be supported by attractor dynamics in the hippocampus. A possible neural substrate for this memory mechanism is rate remapping, in which the spatial map of place cells encodes contextual information through firing rate variability. To test whether memories are stored as multimodal attractors in populations of place cells, recent experiments morphed one familiar context into another while observing the responses of CA3 cell ensembles. Average population activity in CA3 was reported to transition gradually rather than abruptly from one familiar context to the next, suggesting a lack of attractive forces associated with the two stored representations. On the other hand, individual CA3 cells showed a mix of gradual and abrupt transitions at different points along the morph sequence, and some displayed hysteresis which is a signature of attractor dynamics. To understand whether these seemingly conflicting results are commensurate with attractor network theory, we developed a neural network model of the CA3 with attractors for both position and discrete contexts. We found that for memories stored in overlapping neural ensembles within a single spatial map, position-dependent context attractors made transitions at different points along the morph sequence. Smooth transition curves arose from averaging across the population, while a heterogeneous set of responses was observed on the single unit level. In contrast, orthogonal memories led to abrupt and coherent transitions on both population and single unit levels as experimentally observed when remapping between two independent spatial maps. Strong recurrent feedback entailed a hysteretic effect on the network which diminished with the amount of overlap in the stored memories. These results suggest that context-dependent memory can be supported by overlapping local attractors within a spatial map of CA3 place cells. Similar mechanisms for context-dependent memory may also be found in other regions of the cerebral cortex.

The activity of ‘place cells’ in hippocampal area CA3 systematically changes as a function of the animal's position in an arena as well as contextual variables like the color or shape of enclosing walls. Large changes to the local environment, e.g. moving the animal to a different room, can induce a complete reorganization of place-cell firing locations. Such ‘global remapping’ reveals that memory for different environments is encoded as separate spatial maps. Smaller changes to features within an environment can induce a modulation of place cell firing rates without affecting their firing locations. This kind of ‘rate remapping’ is still poorly understood. In this paper we describe a computational model in which discrete memories for contextual features were stored locally within a spatial map of place cells. This network structure supports retrieval of both positional and contextual information from an arbitrary cue, as required by an episodic memory structure. The activity of the network qualitatively matches empirical data from rate remapping experiments, both on the population level and the level of single place cells. The results support the idea that CA3 rate remapping reflects content-addressable memories stored as multimodal attractor states in the hippocampus.

Memory consolidation in humans: new evidence and opportunities

We are endlessly fascinated by memory; we desire to improve it and fear its loss. While it has long been recognized that brain regions such as the hippocampus are vital for supporting memories of our past experiences (autobiographical memories), we still lack fundamental knowledge about the mechanisms involved. This is because the study of specific neural signatures of autobiographical memories in vivo in humans presents a significant challenge. However, recent developments in high-resolution structural and functional magnetic resonance imaging coupled with advanced analytical methods now permit access to the neural substrates of memory representations that has hitherto been precluded in humans. Here, I describe how the application of 'decoding' techniques to brain-imaging data is beginning to disclose how individual autobiographical memory representations evolve over time, deepening our understanding of systems-level consolidation. In particular, this prompts new questions about the roles of the hippocampus and ventromedial prefrontal cortex and offers new opportunities to interrogate the elusive memory trace that has for so long confounded neuroscientists.

Forward and backward inference in spatial cognition

This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.

Representations of recent and remote autobiographical memories in hippocampal subfields

The hippocampus has long been implicated in supporting autobiographical memories, but little is known about how they are instantiated in hippocampal subfields. Using high-resolution functional magnetic resonance imaging (fMRI) combined with multivoxel pattern analysis we found that it was possible to detect representations of specific autobiographical memories in individual hippocampal subfields. Moreover, while subfields in the anterior hippocampus contained information about both recent (2 weeks old) and remote (10 years old) autobiographical memories, posterior CA3 and DG only contained information about the remote memories. Thus, the hippocampal subfields are differentially involved in the representation of recent and remote autobiographical memories during vivid recall.

Place field repetition and purely local remapping in a multicompartment environment

Hippocampal place cells support spatial memory using sensory information from the environment and self-motion information to localize their firing fields. Currently, there is disagreement about whether CA1 place cells can use pure self-motion information to disambiguate different compartments in environments containing multiple visually identical compartments. Some studies report that place cells can disambiguate different compartments, while others report that they do not. Furthermore, while numerous studies have examined remapping, there has been little examination of remapping in different subregions of a single environment. Is remapping purely local or do place fields in neighboring, unaffected, regions detect the change? We recorded place cells as rats foraged across a 4-compartment environment and report 3 new findings. First, we find that, unlike studies in which rats foraged in 2 compartments, place fields showed a high degree of spatial repetition with a slight degree of rate-based discrimination. Second, this repetition does not diminish with extended experience. Third, remapping was found to be purely local for both geometric change and contextual change. Our results reveal the limited capacity of the path integrator to drive pattern separation in hippocampal representations, and suggest that doorways may play a privileged role in segmenting the neural representation of space.

Rapid, parallel path planning by propagating wavefronts of spiking neural activity

Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative routes using propagating waves of neural activity. A wave of spiking activity propagates through a hippocampus-like network, altering the synaptic connectivity. The resulting vector field of synaptic change then guides a simulated animal to the appropriate selected target locations. We demonstrate that the navigation problem can be solved using realistic, local synaptic plasticity rules during a single passage of a wavefront. Our model can find optimal solutions for competing possible targets or learn and navigate in multiple environments. The model provides a hypothesis on the possible computational mechanisms for optimal path planning in the brain, at the same time it is useful for neuromorphic implementations, where the parallelism of information processing proposed here can fully be harnessed in hardware.

The hippocampo-cortical loop: spatio-temporal learning and goal-oriented planning in navigation

We present a neural network model where the spatial and temporal components of a task are merged and learned in the hippocampus as chains of associations between sensory events. The prefrontal cortex integrates this information to build a cognitive map representing the environment. The cognitive map can be used after latent learning to select optimal actions to fulfill the goals of the animal. A simulation of the architecture is made and applied to learning and solving tasks that involve both spatial and temporal knowledge. We show how this model can be used to solve the continuous place navigation task, where a rat has to navigate to an unmarked goal and wait for 2 seconds without moving to receive a reward. The results emphasize the role of the hippocampus for both spatial and timing prediction, and the prefrontal cortex in the learning of goals related to the task.

Multi-voxel pattern analysis in human hippocampal subfields

A complete understanding of the hippocampus depends on elucidating the representations and computations that exist in its anatomically distinct subfields. High-resolution structural and functional MRI scanning is starting to permit insights into hippocampal subfields in humans. In parallel, such scanning has facilitated the use of multi-voxel pattern analysis (MVPA) to examine information present in the distributed pattern of activity across voxels. The aim of this study was to combine these two relatively new innovations and deploy MVPA in the hippocampal subfields. Delineating subregions of the human hippocampus, a prerequisite for our study, remains a significant challenge, with extant methods often only examining part of the hippocampus, or being unable to differentiate CA3 and dentate gyrus (DG). We therefore devised a new high-resolution anatomical scanning and subfield segmentation protocol that allowed us to overcome these issues, and separately identify CA1, CA3, DG, and subiculum (SUB) across the whole hippocampus using a standard 3T MRI scanner. We then used MVPA to examine fMRI data associated with a decision-making paradigm involving highly similar scenes that had relevance for the computations that occur in hippocampal subfields. Intra- and inter-rater scores for subfield identification using our procedure confirmed its reliability. Moreover, we found that decoding of information within hippocampal subfields was possible using MVPA, with findings that included differential effects for CA3 and DG. We suggest that MVPA in human hippocampal subfields may open up new opportunities to examine how different types of information are represented and processed at this fundamental level.

A goal-directed spatial navigation model using forward trajectory planning based on grid cells

A goal-directed navigation model is proposed based on forward linear look-ahead probe of trajectories in a network of head direction cells, grid cells, place cells and prefrontal cortex (PFC) cells. The model allows selection of new goal-directed trajectories. In a novel environment, the virtual rat incrementally creates a map composed of place cells and PFC cells by random exploration. After exploration, the rat retrieves memory of the goal location, picks its next movement direction by forward linear look-ahead probe of trajectories in several candidate directions while stationary in one location, and finds the one activating PFC cells with the highest reward signal. Each probe direction involves activation of a static pattern of head direction cells to drive an interference model of grid cells to update their phases in a specific direction. The updating of grid cell spiking drives place cells along the probed look-ahead trajectory similar to the forward replay during waking seen in place cell recordings. Directions are probed until the look-ahead trajectory activates the reward signal and the corresponding direction is used to guide goal-finding behavior. We report simulation results in several mazes with and without barriers. Navigation with barriers requires a PFC map topology based on the temporal vicinity of visited place cells and a reward signal diffusion process. The interaction of the forward linear look-ahead trajectory probes with the reward diffusion allows discovery of never-before experienced shortcuts towards a goal location.

Activity dynamics and behavioral correlates of CA3 and CA1 hippocampal pyramidal neurons

The CA3 and CA1 pyramidal neurons are the major principal cell types of the hippocampus proper. The strongly recurrent collateral system of CA3 cells and the largely parallel-organized CA1 neurons suggest that these regions perform distinct computations. However, a comprehensive comparison between CA1 and CA3 pyramidal cells in terms of firing properties, network dynamics, and behavioral correlations is sparse in the intact animal. We performed large-scale recordings in the dorsal hippocampus of rats to quantify the similarities and differences between CA1 (n > 3,600) and CA3 (n > 2,200) pyramidal cells during sleep and exploration in multiple environments. CA1 and CA3 neurons differed significantly in firing rates, spike burst propensity, spike entrainment by the theta rhythm, and other aspects of spiking dynamics in a brain state-dependent manner. A smaller proportion of CA3 than CA1 cells displayed prominent place fields, but place fields of CA3 neurons were more compact, more stable, and carried more spatial information per spike than those of CA1 pyramidal cells. Several other features of the two cell types were specific to the testing environment. CA3 neurons showed less pronounced phase precession and a weaker position versus spike-phase relationship than CA1 cells. Our findings suggest that these distinct activity dynamics of CA1 and CA3 pyramidal cells support their distinct computational roles.

Memory-guided learning: CA1 and CA3 neuronal ensembles differentially encode the commonalities and differences between situations

Memory influences learning, but how neural signals support such transfer are unknown. To investigate these mechanisms, we trained rats to perform a standard spatial memory task in a plus maze and tested how training affected learning and neural coding in two new task variants. A switch task exchanged the start and goal locations in the same environment, whereas, an altered environment task contained unfamiliar local and distal cues. Learning was facilitated in both variants compared with the acquisition of the standard task. In the switch task, performance was largely maintained, and was accompanied by immediate and stable place-field remapping. Place-field maps in CA1 were anticorrelated in the standard and switch sessions, and the anticorrelation covaried with switch performance. Simultaneously, CA3 maps were uncorrelated overall in the standard and switch, though many CA3 cells had fields in shifted locations in the same maze arms. In the altered environment, performance was initially impaired, and place fields changed dynamically. CA1 fields were initially unstable, and their stabilization correlated with improving performance. Most CA3 cells, however, stopped firing on the maze in the altered environment, even as the same cells maintained prominent fields in standard sessions recorded before and after. CA1 and CA3 place fields thus revealed different coding dynamics that correlated with both learning and memory performance. Together, CA1 and CA3 ensembles represented the similarities and differences between new and familiar situations through concurrent rate and place remapping.

Learning-facilitated synaptic plasticity at CA3 mossy fiber and commissural-associational synapses reveals different roles in information processing

Subregion-dependent differences in the role of the hippocampus in information processing exist. Recently, it has emerged that a special relationship exists between the expression of persistent forms of synaptic plasticity in hippocampal subregions and the encoding of different types of spatial information. Little is known about this type of information processing at CA3 synapses. We report that in freely behaving rats, long-term potentiation (LTP) is facilitated at both mossy fiber (mf)-CA3 and commissural-associational (AC)-CA3 synapses by exploration of a novel (empty) environment. Exploration of large spatial landmarks facilitates long-term depression (LTD) at mf-CA3 synapses and impairs synaptic depression at AC-CA3 synapses. Novel exploration of small environmental features does not facilitate LTD at mf synapses but facilitates persistent LTD at AC synapses. Thus, depending on the quality of the information synaptic plasticity at AC-CA3 and mf-CA3 synapses is differentially modulated. These data suggest that expression of LTP as a result of environmental change is a common property of hippocampal synapses. However, LTD at mf synapses or AC synapses may subserve distinct and separate functions within the CA3 region.

Rats build and update topological representations through exploration

Although rats are able to build complex spatial representations of their surroundings during exploration, the nature of the encoded information is still a matter for debate. In particular, it is not well established if rats can process the topological structure of the environment in such a way that they are aware of the connections existing between remote places. Here, rats were first exposed for four 5-min trials to a complex environment divided into several sectors that were separated by doors allowing either unrestricted or restricted access to other sectors. In the fifth test trial, we measured the behavior of the animals while they explored the same environment in which, however, they faced changes that either altered or did not alter the topological structure of the environment. In experiment 1, closing previously opened doors prevented the rat from having direct access between corresponding sectors. In experiment 2, opening previously closed doors allowed direct access between sectors that had not been directly accessible. In each experiment, control doors allowed us to discard the mere influence of door manipulation. We compared the rats' exploratory behavior in response to door manipulations that either strongly altered or did not alter the ability to commute between sectors and found evidence that the animals displayed differential reactions to the two types of door manipulations. This implies that during exploration rats build a precise map of the connectivity of space that can be flexibly updated and used for efficient navigation.

Stability and variability of place cell activity during behavior: functional implications for dynamic coding of spatial information

In addition to their discharge strongly related to a rat's location in the environment, hippocampal place cells have recently been discovered to carry other more subtle signals. For instance, place cells exhibit overdispersion, i.e., a tendency to have highly variable firing rates across successive passes in the firing field, which may reflect the processing of different classes of cues. In addition, the place cell population tends to fire synchronously during specific phases of place navigation, presumably signaling the animal's arrival at the goal location, or to be reactivated during either sleep or wakefulness following exposure to a new environment, a process thought to be important for memory consolidation. Although these various phenomena are expressed at different timescales, it is very likely that they can occur at the same time during an animal's exposure to a spatial environment. The advantage of such simultaneous processing is that it permits the organism both to be aware of its own location in the environment, and to attend to other environmental features and to store multiple experiences. However its pitfall is that it may result in noisy signals that are difficult to decipher by output structures. Therefore the question is asked of how the information carried by each process can be disentangled. We provide some examples from recent research work showing that this problem is far from being trivial and we propose an explanatory framework in which place cell activity at different timescales could be viewed as a series of dynamic attractors nested within each other.

Linking context with reward: a functional circuit from hippocampal CA3 to ventral tegmental area

Reward-motivated behavior is strongly influenced by the learned significance of contextual stimuli in the environment. However, the neural pathways that mediate context-reward relations are not well understood. We have identified a circuit from area CA3 of dorsal hippocampus to ventral tegmental area (VTA) that uses lateral septum (LS) as a relay. Theta frequency stimulation of CA3 excited VTA dopamine (DA) neurons and inhibited non-DA neurons. DA neuron excitation was likely mediated by disinhibition because local antagonism of γ-aminobutyric acid receptors blocked responses to CA3 stimulation. Inactivating components of the CA3-LS-VTA pathway blocked evoked responses in VTA and also reinstatement of cocaine-seeking by contextual stimuli. This transsynaptic link between hippocampus and VTA appears to be an important substrate by which environmental context regulates goal-directed behavior.

Spatial learning and action planning in a prefrontal cortical network model

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates.

We study spatial cognition, a high-level brain function based upon the ability to elaborate mental representations of the environment supporting goal-oriented navigation. Spatial cognition involves parallel information processing across a distributed network of interrelated brain regions. Depending on the complexity of the spatial navigation task, different neural circuits may be primarily involved, corresponding to different behavioral strategies. Navigation planning, one of the most flexible strategies, is based on the ability to prospectively evaluate alternative sequences of actions in order to infer optimal trajectories to a goal. The hippocampal formation and the prefrontal cortex are two neural substrates likely involved in navigation planning. We adopt a computational modeling approach to show how the interactions between these two brain areas may lead to learning of topological representations suitable to mediate action planning. Our model suggests plausible neural mechanisms subserving the cognitive spatial capabilities attributed to rodents. We provide a functional framework for interpreting the activity of prefrontal and hippocampal neurons recorded during navigation tasks. Akin to integrative neuroscience approaches, we illustrate the link from single unit activity to behavioral responses while solving spatial learning tasks.

[The hippocampus and the neural code of spatial memory]

Recent work on the neural substrate of spatial memory strongly suggests the existence of a neuronal network dedicated to the coding of spatial information and allowing the subject to orient in space. This network includes place cells of the hippocampus, head direction cells which are found in several brain regions and particularly the post-subiculum, and grid cells in the entorhinal cortex. Several recently discovered features of place cell activity shed light on how the hippocampus contributes to memory construction. For instance, learning a novel environment relies on a dynamic population code in which place cell activity suddenly changes towards stable states built during previous experience. We briefly review these properties to show how they constrain the hippocampal memory code.

Hippocampal replay is not a simple function of experience

Replay of behavioral sequences in the hippocampus during sharp wave ripple complexes (SWRs) provides a potential mechanism for memory consolidation and the learning of knowledge structures. Current hypotheses imply that replay should straightforwardly reflect recent experience. However, we find these hypotheses to be incompatible with the content of replay on a task with two distinct behavioral sequences (A and B). We observed forward and backward replay of B even when rats had been performing A for >10 min. Furthermore, replay of nonlocal sequence B occurred more often when B was infrequently experienced. Neither forward nor backward sequences preferentially represented highly experienced trajectories within a session. Additionally, we observed the construction of never-experienced novel-path sequences. These observations challenge the idea that sequence activation during SWRs is a simple replay of recent experience. Instead, replay reflected all physically available trajectories within the environment, suggesting a potential role in active learning and maintenance of the cognitive map.