Robust path integration in the entorhinal grid cell system with hippocampal feed-back

Animals are able to update their knowledge about their current position solely by integrating the speed and the direction of their movement, which is known as path integration. Recent discoveries suggest that grid cells in the medial entorhinal cortex might perform some of the essential underlying computations of path integration. However, a major concern over path integration is that as the measurement of speed and direction is inaccurate, the representation of the position will become increasingly unreliable. In this paper, we study how allothetic inputs can be used to continually correct the accumulating error in the path integrator system. We set up the model of a mobile agent equipped with the entorhinal representation of idiothetic (grid cell) and allothetic (visual cells) information and simulated its place learning in a virtual environment. Due to competitive learning, a robust hippocampal place code emerges rapidly in the model. At the same time, the hippocampo-entorhinal feed-back connections are modified via Hebbian learning in order to allow hippocampal place cells to influence the attractor dynamics in the entorhinal cortex. We show that the continuous feed-back from the integrated hippocampal place representation is able to stabilize the grid cell code. This research was supported by the EU Framework 6 ICEA project (IST-4-027819-IP).     

From spreading depression to spatial cognition

The Laboratory of Neurophysiology of Memory started its existence in 1954 by systematic research into spreading depression of EEG activity of laboratory rodents and by the use of this remarkable phenomenon as a functional ablation method in behavioral research. Its main contributions were in the study of memory formation and consolidation, interhemispheric transfer, motor learning, conditioned taste aversion and spatial orientation and navigation. In the last five years it concentrated on navigation of rats in multiple reference frames, on electrophysiological evidence for the role of hippocampal place cells support of behavior in such dissociated frames, on the analysis of idiothetic and allothetic forms of navigation and on the mathematical methods allowing assessment of the contribution of goal directed locomotion to place cell activity. The methods used in spatial memory research in rats were used for examination of human subjects in a laboratory equipped with a tracking system for humans in the hospital Homolka. Animal models of Alzheimer disease were studied in transgenic mice with the human gene for the beta amyloid precursor protein.     

Lesions of the Basal Forebrain Cholinergic System in Mice Disrupt Idiothetic Navigation

Loss of integrity of the basal forebrain cholinergic neurons is a consistent feature of Alzheimer’s disease, and measurement of basal forebrain degeneration by magnetic resonance imaging is emerging as a sensitive diagnostic marker for prodromal disease. It is also known that Alzheimer’s disease patients perform poorly on both real space and computerized cued (allothetic) or uncued (idiothetic) recall navigation tasks. Although the hippocampus is required for allothetic navigation, lesions of this region only mildly affect idiothetic navigation. Here we tested the hypothesis that the cholinergic medial septo-hippocampal circuit is important for idiothetic navigation. Basal forebrain cholinergic neurons were selectively lesioned in mice using the toxin saporin conjugated to a basal forebrain cholinergic neuronal marker, the p75 neurotrophin receptor. Control animals were able to learn and remember spatial information when tested on a modified version of the passive place avoidance test where all extramaze cues were removed, and animals had to rely on idiothetic signals. However, the exploratory behaviour of mice with cholinergic basal forebrain lesions was highly disorganized during this test. By contrast, the lesioned animals performed no differently from controls in tasks involving contextual fear conditioning and spatial working memory (Y maze), and displayed no deficits in potentially confounding behaviours such as motor performance, anxiety, or disturbed sleep/wake cycles. These data suggest that the basal forebrain cholinergic system plays a specific role in idiothetic navigation, a modality that is impaired early in Alzheimer’s disease.     

What can the hippocampal representation of environmental geometry tell us about Hebbian learning?

 The importance of the hippocampus in spatial representation is well established. It is suggested that the rodent hippocampal network should provide an optimal substrate for the study of unsupervised Hebbian learning. We focus on the firing characteristics of hippocampal place cells in morphologically different environments. A hard-wired quantitative geometric model of individual place fields is reviewed and presented as the framework in which to understand the additional effects of synaptic plasticity. Existent models employing Hebbian learning are also reviewed. New information is presented regarding the dynamics of place field plasticity over short and long time scales in experiments using barriers and differently shaped walled environments. It is argued that aspects of the temporal dynamics of stability and plasticity in the hippocampal place cell representation both indicate modifications to, and inform the nature of, the synaptic plasticity in place cell models. Our results identify a potential neural basis for long-term incidental learning of environments and provide strong constraints for the way the unsupervised learning in cell assemblies envisaged by Hebb might occur within the hippocampus. Received: 8 March 2002 / Accepted: 13 June 2002 Acknowledgements. This work was supported by the Medical Research Council of the United Kingdom. Correspondence to: C. Lever or N. Burgess (e-mail: colin.lever@ucl.ac.uk; n.burgess@ucl.ac.uk, Tel.: +44-20-76793388 or 1147, Fax: +44-20-76791306 or 1145)     

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.     

Animat navigation using a cognitive graph

 This article describes a computational model of the hippocampus that makes it possible for a simulated rat to navigate in a continuous environment containing obstacles. This model views the hippocampus as a “cognitive graph”, that is, a hetero-associative network that learns temporal sequences of visited places and stores a topological representation of the environment. Calling upon place cells, head direction cells, and “goal cells”, it suggests a biologically plausible way of exploiting such a spatial representation for navigation that does not require complicated graph-search algorithms. Moreover, it permits “latent learning” during exploration, that is, the building of a spatial representation without the need of any reinforcement. When the rat occasionally discovers some rewarding place it may wish to rejoin subsequently, it simply records within its cognitive graph, through a series of goal and sub-goal cells, the direction in which to move from any given start place. Accordingly, the model implements a simple “place-recognition-triggered response” navigation strategy. Two implementations of place cell management are studied in parallel. The first one associates place cells with place fields that are given a priori and that are uniformly distributed in the environment. The second one dynamically recruits place cells as exploration proceeds and adjusts the density of such cells to the local complexity of the environment. Both implementations lead to identical results. The article ends with a few predictions about results to be expected in experiments involving simultaneous recordings of multiple cells in the rat hippocampus. Received: 25 June 1999 / Accepted in revised form: 20 March 2000     

Representing episodes in the mammalian brain

Memory lets the past inform the present so that we can attain future goals. In many species, these abilities require the hippocampus. Recent experiments, in which memory demand was varied while overt behavior and the environment were kept constant, have revealed firing patterns of hippocampal neurons that corresponded with memory demands and predicted performance. Although the active population appeared to be 'place cells' that signalled location, it actually included cells the activity patterns of which distinguished the recent or pending history of behavior during identical actions that occurred in the same place. Different populations of hippocampal cells fired as a rat walked along the same spatial path on the way to different goals, and coded past, present and pending events. Other experiments provide converging data that neuronal activity is modulated by goal-directed behavioral episodes. Together, these firing patterns suggest a testable mechanism of episodic memory coding: that hippocampal dynamics encode a temporally extended, hierarchically organized representation of goal-directed behavior.     

Combination and competition between path integration and landmark navigation in the estimation of heading direction

Successful navigation requires the ability to compute one’s location and heading from incoming multisensory information. Previous work has shown that this multisensory input comes in two forms: body-based idiothetic cues, from one’s own rotations and translations, and visual allothetic cues, from the environment (usually visual landmarks). However, exactly how these two streams of information are integrated is unclear, with some models suggesting the body-based idiothetic and visual allothetic cues are combined, while others suggest they compete. In this paper we investigated the integration of body-based idiothetic and visual allothetic cues in the computation of heading using virtual reality. In our experiment, participants performed a series of body turns of up to 360 degrees in the dark with only a brief flash (300ms) of visual feedback en route. Because the environment was virtual, we had full control over the visual feedback and were able to vary the offset between this feedback and the true heading angle. By measuring the effect of the feedback offset on the angle participants turned, we were able to determine the extent to which they incorporated visual feedback as a function of the offset error. By further modeling this behavior we were able to quantify the computations people used. While there were considerable individual differences in performance on our task, with some participants mostly ignoring the visual feedback and others relying on it almost entirely, our modeling results suggest that almost all participants used the same strategy in which idiothetic and allothetic cues are combined when the mismatch between them is small, but compete when the mismatch is large. These findings suggest that participants update their estimate of heading using a hybrid strategy that mixes the combination and competition of cues.     

Sequence learning and the role of the hippocampus in rodent navigation

The hippocampus has long been associated with navigation and spatial representations, but it has been difficult to link directly the neurophysiological correlates of hippocampal place cells with navigational planning and action. In recent years, large-scale population recordings of place cells have revealed that spatial sequences are stored and activated in ways that may support navigational strategies. Plasticity mechanisms allow the hippocampus to store learned sequences of locations that may allow predictions of future locations based on past experience. These sequences can also be activated during navigational behavior in ways that may allow the animal to learn trajectories toward goals. Task-dependent alterations in place cell firing patterns may reflect the operation of the hippocampus in associating locations with navigationally relevant decision variables.     

海马位置细胞对空间信息的处理

海马位置细胞接收各种来源的空间信息后,可对这些信息进行加工处理,在海马内形成认知地图或加强联合皮层内细胞集群的突触联系以形成对空间位置的永久记忆。海马内的空间信息输出后,在伏核（nucleus accumbens,NAC）。内与其它来源的信息进行整合,最终通过运动环路形成目标指向性行为。     

Uncovering spatial topology represented by rat hippocampal population neuronal codes

Hippocampal population codes play an important role in representation of spatial environment and spatial navigation. Uncovering the internal representation of hippocampal population codes will help understand neural mechanisms of the hippocampus. For instance, uncovering the patterns represented by rat hippocampus (CA1) pyramidal cells during periods of either navigation or sleep has been an active research topic over the past decades. However, previous approaches to analyze or decode firing patterns of population neurons all assume the knowledge of the place fields, which are estimated from training data a priori. The question still remains unclear how can we extract information from population neuronal responses either without a priori knowledge or in the presence of finite sampling constraint. Finding the answer to this question would leverage our ability to examine the population neuronal codes under different experimental conditions. Using rat hippocampus as a model system, we attempt to uncover the hidden "spatial topology" represented by the hippocampal population codes. We develop a hidden Markov model (HMM) and a variational Bayesian (VB) inference algorithm to achieve this computational goal, and we apply the analysis to extensive simulation and experimental data. Our empirical results show promising direction for discovering structural patterns of ensemble spike activity during periods of active navigation. This study would also provide useful insights for future exploratory data analysis of population neuronal codes during periods of sleep.     

Repeated cocaine enhances ventral hippocampal‐stimulated dopamine efflux in the nucleus accumbens and alters ventral hippocampal NMDA receptor subunit expression

Dopaminergic neurotransmission in the nucleus accumbens is important for various reward‐related cognitive processes including reinforcement learning. Repeated cocaine enhances hippocampal synaptic plasticity, and phasic elevations of accumbal dopamine evoked by unconditioned stimuli are dependent on impulse flow from the ventral hippocampus. Therefore, sensitized hippocampal activity may be one mechanism by which drugs of abuse enhance limbic dopaminergic activity. In this study, in vivo microdialysis in freely moving adult male Sprague–Dawley rats was used to investigate the effect of repeated cocaine on ventral hippocampus‐mediated dopaminergic transmission within the medial shell of the nucleus accumbens. Following seven daily injections of saline or cocaine (20 mg/kg, ip), unilateral infusion of N‐methyl‐d ‐aspartate (NMDA, 0.5 μg) into the ventral hippocampus transiently increased both motoric activity and ipsilateral dopamine efflux in the medial shell of the nucleus accumbens, and this effect was greater in rats that received repeated cocaine compared to controls that received repeated saline. In addition, repeated cocaine altered NMDA receptor subunit expression in the ventral hippocampus, reducing the NR2A : NR2B subunit ratio. Together, these results suggest that repeated exposure to cocaine produces maladaptive ventral hippocampal‐nucleus accumbens communication, in part through changes in glutamate receptor composition.

     

Predictions derived from modelling the hippocampal role in navigation

 A computational model of the lesion and single unit data from navigation in rats is reviewed. The model uses external (visual) and internal (odometric) information from the environment to drive the firing of simulated hippocampal place cells. Constraints on the functional form of these inputs are drawn from experiments using an environment of modifiable shape. The place cell representation is used to guide navigation via the creation of a representation of goal location via Hebbian modification of synaptic strengths. The model includes consideration of the phase of firing of place cells with respect to the theta rhythm of hippocampal EEG. A series of predictions for behavioural and single-unit data in rats are derived from the input and output representations of the model. Received: 15 July 1999 / Accepted in revised form: 20 March 2000     

A computational model of the hippocampus that represents environmental structure and goal location,and guides movement

Hippocampal place cells (PCs) are believed to represent environmental structure. However, it is unclear how and which brain regions represent goals and guide movements. Recently, another type of cells that fire around a goal was found in rat hippocampus (we designate these cells as goal place cells, GPCs). This suggests that the hippocampus is also involved in goal representation. Assuming that the activities of GPCs depend on the distance to a goal, we propose an adaptive navigation model. By monitoring the population activity of GPCs, the model navigates to shorten the distance to the goal. To achieve the distance-dependent activities of GPCs, plastic connections are assumed between PCs and GPCs, which are modified depending on two reward-triggered activities: activity propagation through PC–PC network representing the topological environmental structure, and the activity of GPCs with different durations. The former activity propagation is regarded as a computational interpretation of “reverse replay” phenomenon found in rat hippocampus. Simulation results confirm that after reaching a goal only once, the model can navigate to the goal along almost the shortest path from arbitrary places in the environment. This indicates that the hippocampus might play a primary role in the representation of not only the environmental structure but also the goal, in addition to guiding the movement. This navigation strategy using the population activity of GPCs is equivalent to the taxis strategy, the simplest and most basic for biological systems. Our model is unique because this simple strategy allows the model to follow the shortest path in the topological map of the environment.     

Sensory feedback in a bump attractor model of path integration

Mammalian spatial navigation systems utilize several different sensory information channels. This information is converted into a neural code that represents the animal’s current position in space by engaging place cell, grid cell, and head direction cell networks. In particular, sensory landmark (allothetic) cues can be utilized in concert with an animal’s knowledge of its own velocity (idiothetic) cues to generate a more accurate representation of position than path integration provides on its own (Battaglia et al. The Journal of Neuroscience 24(19):4541–4550 (2004)). We develop a computational model that merges path integration with feedback from external sensory cues that provide a reliable representation of spatial position along an annular track. Starting with a continuous bump attractor model, we explore the impact of synaptic spatial asymmetry and heterogeneity, which disrupt the position code of the path integration process. We use asymptotic analysis to reduce the bump attractor model to a single scalar equation whose potential represents the impact of asymmetry and heterogeneity. Such imperfections cause errors to build up when the network performs path integration, but these errors can be corrected by an external control signal representing the effects of sensory cues. We demonstrate that there is an optimal strength and decay rate of the control signal when cues appear either periodically or randomly. A similar analysis is performed when errors in path integration arise from dynamic noise fluctuations. Again, there is an optimal strength and decay of discrete control that minimizes the path integration error.     

Dopamine-dependent interactions between limbic and prefrontal cortical plasticity in the nucleus accumbens: disruption by cocaine sensitization

The prefrontal cortex and the hippocampus exhibit converging projections to the nucleus accumbens and have functional reciprocal connections via indirect pathways. As a result, information processing between these structures is likely to be bidirectional. Using evoked potential measures, we examined the interactions of these inputs on synaptic plasticity within the accumbens. Our results show that the direction of information flow between the prefrontal cortex and limbic structures determines the synaptic plasticity that these inputs exhibit within the accumbens. Moreover, this synaptic plasticity at hippocampal and prefrontal inputs selectively involves dopamine D1 and D2 activation or inactivation, respectively. Repeated cocaine administration disrupted this synaptic plasticity at hippocampal and prefrontal cortical inputs and goal-directed behavior in the spatial maze task. Thus, interactions of limbic-prefrontal cortical synaptic plasticity and its dysfunction within the accumbens could underlie complex information processing deficits observed in individuals following psychostimulant administration.     

Participation of the nucleus accumbens in acquisition of spatial choice behavior in rats performing in a radial plus maze

The role of medial shell of the nucleus accumbens in acquisition of spatial behavior was studied in rats performing choice task in radial maze with asymmetrical water reinforcement. It has been found that the nucleus accumbens lesioned rats failed in finding larger rewards but preserve their reward-seeking behavior guided by visual discriminative stimuli. The results obtained are in good agreement with suggestion that the nucleus accumbens is a site of convergence of spatial information (from hippocampus) with reward information (from amygdala and VTA), providing bridge for effective limbic-motor interface underlying motivated goal-directed behavior in animals.     

A topological paradigm for hippocampal spatial map formation using persistent homology

An animal's ability to navigate through space rests on its ability to create a mental map of its environment. The hippocampus is the brain region centrally responsible for such maps, and it has been assumed to encode geometric information (distances, angles). Given, however, that hippocampal output consists of patterns of spiking across many neurons, and downstream regions must be able to translate those patterns into accurate information about an animal's spatial environment, we hypothesized that 1) the temporal pattern of neuronal firing, particularly co-firing, is key to decoding spatial information, and 2) since co-firing implies spatial overlap of place fields, a map encoded by co-firing will be based on connectivity and adjacency, i.e., it will be a topological map. Here we test this topological hypothesis with a simple model of hippocampal activity, varying three parameters (firing rate, place field size, and number of neurons) in computer simulations of rat trajectories in three topologically and geometrically distinct test environments. Using a computational algorithm based on recently developed tools from Persistent Homology theory in the field of algebraic topology, we find that the patterns of neuronal co-firing can, in fact, convey topological information about the environment in a biologically realistic length of time. Furthermore, our simulations reveal a "learning region" that highlights the interplay between the parameters in combining to produce hippocampal states that are more or less adept at map formation. For example, within the learning region a lower number of neurons firing can be compensated by adjustments in firing rate or place field size, but beyond a certain point map formation begins to fail. We propose that this learning region provides a coherent theoretical lens through which to view conditions that impair spatial learning by altering place cell firing rates or spatial specificity.     

From Rapid Place Learning to Behavioral Performance: A Key Role for the Intermediate Hippocampus

Rapid place encoding by hippocampal neurons, as reflected by place-related firing, has been intensely studied, whereas the substrates that translate hippocampal place codes into behavior have received little attention. A key point relevant to this translation is that hippocampal organization is characterized by functional–anatomical gradients along the septotemporal axis: Whereas the ability of hippocampal neurons to encode accurate place information declines from the septal to temporal end, hippocampal connectivity to prefrontal and subcortical sites that might relate such place information to behavioral-control processes shows an opposite gradient. We examined in rats the impact of selective lesions to relevant parts of the hippocampus on behavioral tests requiring place learning (watermaze procedures) and on in vivo electrophysiological models of hippocampal encoding (long-term potentiation [LTP], place cells). We found that the intermediate hippocampus is necessary and largely sufficient for behavioral performance based on rapid place learning. In contrast, a residual septal pole of the hippocampus, although displaying intact electrophysiological indices of rapid information encoding (LTP, precise place-related firing, and rapid remapping), failed to sustain watermaze performance based on rapid place learning. These data highlight the important distinction between hippocampal encoding and the behavioral performance based on such encoding, and suggest that the intermediate hippocampus, where substrates of rapid accurate place encoding converge with links to behavioral control, is critical to translate rapid (one-trial) place learning into navigational performance.     

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

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