Conjoint control of hippocampal place cell firing by two visual stimuli. I. The effects of moving the stimuli on firing field positions

To better understand how hippocampal place cell activity is controlled by sensory stimuli, and to further elucidate the nature of the environmental representation provided by place cells, we have made recordings in the presence of two distinct visual stimuli under standard conditions and after several manipulations of these stimuli. In line with a great deal of earlier work, we find that place cell activity is constant when repeated recordings are made in the standard conditions in which the centers of the two stimuli, a black card and a white card, are separated by 135 degrees on the wall of a cylindrical recording chamber. Rotating the two stimuli by 45 degrees causes equal rotations of place cell firing fields. Removing either card and rotating the other card also causes fields to rotate equally, showing that the two stimuli are individually salient. Increasing or decreasing the card separation (card reconfiguration) causes a topological distortion of the representation of the cylinder floor such that field centers move relative to each other. We also found that either kind of reconfiguration induces a position-independent decrease in the intensity of place cell firing. We argue that these results are not compatible with either of two previously stated views of the place cell representation; namely, a nonspatial theory in which each place cell is tuned to an arbitrarily selected subset of available stimuli or a rigid map theory. We propose that our results imply that the representation is map-like but not rigid; it is capable of undergoing stretches without altering the local arrangement of firing fields.     

Spiking Neurons in a Hierarchical Self-Organizing Map Model Can Learn to Develop Spatial and Temporal Properties of Entorhinal Grid Cells and Hippocampal Place Cells

Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning 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 these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous adaptive robots capable of spatial navigation.     

A feedforward model for the formation of a grid field where spatial information is provided solely from place cells

Grid cells (GCs) in the medial entorhinal cortex (mEC) have the property of having their firing activity spatially tuned to a regular triangular lattice. Several theoretical models for grid field formation have been proposed, but most assume that place cells (PCs) are a product of the grid cell system. There is, however, an alternative possibility that is supported by various strands of experimental data. Here we present a novel model for the emergence of gridlike firing patterns that stands on two key hypotheses: (1) spatial information in GCs is provided from PC activity and (2) grid fields result from a combined synaptic plasticity mechanism involving inhibitory and excitatory neurons mediating the connections between PCs and GCs. Depending on the spatial location, each PC can contribute with excitatory or inhibitory inputs to GC activity. The nature and magnitude of the PC input is a function of the distance to the place field center, which is inferred from rate decoding. A biologically plausible learning rule drives the evolution of the connection strengths from PCs to a GC. In this model, PCs compete for GC activation, and the plasticity rule favors efficient packing of the space representation. This leads to gridlike firing patterns. In a new environment, GCs continuously recruit new PCs to cover the entire space. The model described here makes important predictions and can represent the feedforward connections from hippocampus CA1 to deeper mEC layers.     

Variable place-cell coupling to a continuously viewed stimulus: evidence that the hippocampus acts as a perceptual system.

A key feature of perception is that the interpretation of a single, continuously available stimulus can change from time to time. This aspect of perception is well illustrated by the use of ambiguous figures that can be seen in two different ways. When people view such a stimulus they almost universally describe what they are seeing as jumping between two states. If it is agreed that this perceptual phenomenon is causally linked to the activity of nerve cells, the state jumps would have to occur in conjunction with changes in neural activity somewhere in the nervous system. Our experiments suggest that hippocampal place cells are part of a perceptual system. We conducted variations of a ''cue-card rotation'' experiment on rats in which the angular position of a prominent visual stimulus on the wall of cylinder is changed in the rat''s presence. The three main results are that (i) place-cell firing fields remain stationary if the cue is rotated by 180 degrees, so the relation between the cue and the field is altered; (ii) firing fields rotate by 45 degrees when the cue is rotated by 45 degrees, so the relation between the field and the card is maintained; and (iii) if the cue is first rotated by 180 degrees and then rotated in a series of 45 degrees steps, the field winds up at a different angular position relative to the card when the card is back in its original position. Thus, place cells can fire in two different ways in response to a continuously viewed stimulus. We conclude that place cells reveal that the hippocampal mapping system also has properties expected of a perceptual system.     

Increased attention to spatial context increases both place field stability and spatial memory

The hippocampal formation is critical for the acquisition and consolidation of memories. When recorded in freely moving animals, hippocampal pyramidal neurons fire in a location-specific manner: they are "place" cells, comprising a hippocampal representation of the animal's environment. To explore the relationship between place cells and spatial memory, we recorded from mice in several behavioral contexts. We found that long-term stability of place cell firing fields correlates with the degree of attentional demands and that successful spatial task performance was associated with stable place fields. Furthermore, conditions that maximize place field stability greatly increase orientation to novel cues. This suggests that storage and retrieval of place cells is modulated by a top-down cognitive process resembling attention and that place cells are neural correlates of spatial memory. We propose a model whereby attention provides the requisite neuromodulatation to switch short-term homosynaptic plasticity to long-term heterosynaptic plasticity, and we implicate dopamine in this process.     

Cell-type specific dendritic contacts between retinal ganglion cells during development.

The extent of a neuron's dendritic field defines the region within which information is processed. The dendritic fields of functionally distinct ON and OFF center retinal ganglion cells (RGCs) form separate mosaics across the retina. Within each mosaic, neighboring dendritic fields overlap by a constant amount, sampling the visual field with the appropriate coverage. Contact-mediated lateral inhibition between neighboring RGCs has long been thought to regulate both the extent and overlap of dendritic fields during development. Here we show that dendro-dendritic contact exists between developing RGCs and occurs in a manner that would regulate the formation of ON and OFF mosaics separately. Dye-filled neighboring ON and OFF ferret alpha RGCs were reconstructed using multiphoton microscopy. At all neonatal ages examined, we observed dendro-dendritic contacts between RGCs of the same sign (ON/ON; OFF/OFF), but never between cells of opposite signs (ON/OFF). Terminal dendrites of one cell often touched a dendrite of its neighbor as they intersected. In some instances, the distal dendrite of one cell formed a fascicle with the proximal process of its neighbor. Alpha cells did not form contacts with neighboring beta cells of the same sign. Together, these observations suggest that dendro-dendritic contact between RGCs is cell-type specific. Dendritic contacts were observed even before the alpha cell arbors were completely stratified, suggesting that cell-cell recognition may take place early in their development. For each cell type, the relative overlap of dendritic fields was constant with age, despite a two-fold increase in field area. We suggest that dendro-dendritic contacts may be sites of intercellular signaling that could regulate local extension of dendrites to maintain the relative overlap of RGCs within a mosaic during development.     

Place representation within hippocampal networks is modified by long-term potentiation

In the brain, information is encoded by the firing patterns of neuronal ensembles and the strength of synaptic connections between individual neurons. We report here that representation of the environment by "place" cells is altered by changing synaptic weights within hippocampal networks. Long-term potentiation (LTP) of intrinsic hippocampal pathways abolished existing place fields, created new place fields, and rearranged the temporal relationship within the affected population. The effect of LTP on neuron discharge was rate and context dependent. The LTP-induced "remapping" occurred without affecting the global firing rate of the network. The findings support the view that learned place representation can be accomplished by LTP-like synaptic plasticity within intrahippocampal networks.     

Computational models of grid cells

Grid cells are space-modulated neurons with periodic firing fields. In moving animals, the multiple firing fields of an individual grid cell form a triangular pattern tiling the entire space available to the animal. Collectively, grid cells are thought to provide a context-independent metric representation of the local environment. Since the discovery of grid cells in 2005, a number of models have been proposed to explain the formation of spatially repetitive firing patterns as well as the conversion of these signals to place signals one synapse downstream in the hippocampus. The present article reviews the most recent developments in our understanding of how grid patterns are generated, maintained, and transformed, with particular emphasis on second-generation computational models that have emerged during the past 2-3 years in response to criticism and new data.     

Independence of the unimodal tuning of firing rate from theta phase precession in hippocampal place cells

There are two prominent features for place cells in rat hippocampus. The firing rate remarkably increases when rat enters the cell’s place field and reaches a maximum around the center of place field, and it decreases when the animal approaches the end of the place field. Simultaneously the spikes gradually and monotonically advance to earlier phase relative to hippocampal theta rhythm as the rat traverses along the cell’s place field, known as temporal coding. In this paper, we investigate whether two main characteristics of place cell firing are independent or not by mainly focusing on the generation mechanism of the unimodal tuning of firing rate by using a reduced CA1 two-compartment neuron model. Based on recent evidences, we hypothesize that the coupling of dendritic with the somatic compartment is not constant but dynamically regulated as the animal moves further along the place field, in contrast to previous two-compartment modeling. Simulations show that the regulable coupling is critically responsible for the generation of unimodal firing rate profile in place cells, independent of phase precession. Predictions of our model accord well with recent observations like occurrence of phase precession with very low as well as high firing rate (Huxter et al. Nature 425:828–832, 2003) and persistency of phase precession after transient silence of hippocampus activity (Zugaro et al. Nat Neurosci 8:67–71, 2005.     

Theta phase precession of grid and place cell firing in open environments

Place and grid cells in the rodent hippocampal formation tend to fire spikes at successively earlier phases relative to the local field potential theta rhythm as the animal runs through the cell''s firing field on a linear track. However, this ‘phase precession’ effect is less well characterized during foraging in two-dimensional open field environments. Here, we mapped runs through the firing fields onto a unit circle to pool data from multiple runs. We asked which of seven behavioural and physiological variables show the best circular–linear correlation with the theta phase of spikes from place cells in hippocampal area CA1 and from grid cells from superficial layers of medial entorhinal cortex. The best correlate was the distance to the firing field peak projected onto the animal''s current running direction. This was significantly stronger than other correlates, such as instantaneous firing rate and time-in-field, but similar in strength to correlates with other measures of distance travelled through the firing field. Phase precession was stronger in place cells than grid cells overall, and robust phase precession was seen in traversals through firing field peripheries (although somewhat less than in traversals through the centre), consistent with phase coding of displacement along the current direction. This type of phase coding, of place field distance ahead of or behind the animal, may be useful for allowing calculation of goal directions during navigation.     

细胞离子在振荡电磁场作用下的受力模型分析

本文通过生物细胞模型,研究振荡电场、振荡磁场以及振荡磁场产生的感应电场对细胞离子的作用机理。模型分析结果表明,电场力和罗仑兹力对细胞膜两侧的自由离子将产生加速度,振荡离子将产生周期性电位移。该模型同时也解释了脉冲电磁场比同参教的连续场产生更多的生物效应,以及连续场在开始施加和切除时的效应最大。     

Place cells, neocortex and spatial navigation: a short review

Hippocampal place cells are characterized by location-specific firing, that is each cell fires in a restricted region of the environment explored by the rat. In this review, we briefly examine the sensory information used by place cells to anchor their firing fields in space and show that, among the various sensory cues that can influence place cell activity, visual and motion-related cues are the most relevant. We then explore the contribution of several cortical areas to the generation of the place cell signal with an emphasis on the role of the visual cortex and parietal cortex. Finally, we address the functional significance of place cell activity and demonstrate the existence of a clear relationship between place cell positional activity and spatial navigation performance. We conclude that place cells, together with head direction cells, provide information useful for spatially guided movements, and thus provide a unique model of how spatial information is encoded in the brain.     

A Temporal Mechanism for Generating the Phase Precession of Hippocampal Place Cells

The phase relationship between the activity of hippocampal place cells and the hippocampal theta rhythm systematically precesses as the animal runs through the region in an environment called the place field of the cell. We present a minimal biophysical model of the phase precession of place cells in region CA3 of the hippocampus. The model describes the dynamics of two coupled point neurons—namely, a pyramidal cell and an interneuron, the latter of which is driven by a pacemaker input. Outside of the place field, the network displays a stable, background firing pattern that is locked to the theta rhythm. The pacemaker input drives the interneuron, which in turn activates the pyramidal cell. A single stimulus to the pyramidal cell from the dentate gyrus, simulating entrance into the place field, reorganizes the functional roles of the cells in the network for a number of cycles of the theta rhythm. In the reorganized network, the pyramidal cell drives the interneuron at a higher frequency than the theta frequency, thus causing a systematic precession relative to the theta input. The frequency of the pyramidal cell can vary to account for changes in the animal's running speed. The transient dynamics end after up to 360 degrees of phase precession when the pacemaker input to the interneuron occurs at a phase to return the network to the stable background firing pattern, thus signaling the end of the place field. Our model, in contrast to others, reports that phase precession is a temporally, and not spatially, controlled process. We also predict that like pyramidal cells, interneurons phase precess. Our model provides a mechanism for shutting off place cell firing after the animal has crossed the place field, and it explains the observed nearly 360 degrees of phase precession. We also describe how this model is consistent with a proposed autoassociative memory role of the CA3 region.     

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 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.     

A computational grid-to-place-cell transformation model indicates a synaptic driver of place cell impairment in early-stage Alzheimer’s Disease

Alzheimer’s Disease (AD) is characterized by progressive neurodegeneration and cognitive impairment. Synaptic dysfunction is an established early symptom, which correlates strongly with cognitive decline, and is hypothesised to mediate the diverse neuronal network abnormalities observed in AD. However, how synaptic dysfunction contributes to network pathology and cognitive impairment in AD remains elusive. Here, we present a grid-cell-to-place-cell transformation model of long-term CA1 place cell dynamics to interrogate the effect of synaptic loss on network function and environmental representation. Synapse loss modelled after experimental observations in the APP/PS1 mouse model was found to induce firing rate alterations and place cell abnormalities that have previously been observed in AD mouse models, including enlarged place fields and lower across-session stability of place fields. Our results support the hypothesis that synaptic dysfunction underlies cognitive deficits, and demonstrate how impaired environmental representation may arise in the early stages of AD. We further propose that dysfunction of excitatory and inhibitory inputs to CA1 pyramidal cells may cause distinct impairments in place cell function, namely reduced stability and place map resolution.     

Hippocampal Remapping Is Constrained by Sparseness rather than Capacity

Grid cells in the medial entorhinal cortex encode space with firing fields that are arranged on the nodes of spatial hexagonal lattices. Potential candidates to read out the space information of this grid code and to combine it with other sensory cues are hippocampal place cells. In this paper, we investigate a population of grid cells providing feed-forward input to place cells. The capacity of the underlying synaptic transformation is determined by both spatial acuity and the number of different spatial environments that can be represented. The codes for different environments arise from phase shifts of the periodical entorhinal cortex patterns that induce a global remapping of hippocampal place fields, i.e., a new random assignment of place fields for each environment. If only a single environment is encoded, the grid code can be read out at high acuity with only few place cells. A surplus in place cells can be used to store a space code for more environments via remapping. The number of stored environments can be increased even more efficiently by stronger recurrent inhibition and by partitioning the place cell population such that learning affects only a small fraction of them in each environment. We find that the spatial decoding acuity is much more resilient to multiple remappings than the sparseness of the place code. Since the hippocampal place code is sparse, we thus conclude that the projection from grid cells to the place cells is not using its full capacity to transfer space information. Both populations may encode different aspects of space.     

Place-selective firing of CA1 pyramidal cells during sharp wave/ripple network patterns in exploratory behavior

We observed sharp wave/ripples (SWR) during exploration within brief (<2.4 s) interruptions of or during theta oscillations. CA1 network responses of SWRs occurring during exploration (eSWR) and SWRs detected in waking immobility or sleep were similar. However, neuronal activity during eSWR was location dependent, and eSWR-related firing was stronger inside the place field than outside. The eSPW-related firing increase was stronger than the baseline increase inside compared to outside, suggesting a "supralinear" summation of eSWR and place-selective inputs. Pairs of cells with similar place fields and/or correlated firing during exploration showed stronger coactivation during eSWRs and subsequent sleep-SWRs. Sequential activation of place cells was not required for the reactivation of waking co-firing patterns; cell pairs with symmetrical cross-correlations still showed reactivated waking co-firing patterns during sleep-SWRs. We suggest that place-selective firing during eSWRs facilitates initial associations between cells with similar place fields that enable place-related ensemble patterns to recur during subsequent sleep-SWRs.     

Computing the direction of heading from affine image flow

Observers moving through a three-dimensional environment can use optic flow to determine their direction of heading. Existing heading algorithms use cartesian flow fields in which image flow is the displacement of image features over time. I explore a heading algorithm that uses affine flow instead. The affine flow at an image feature is its displacement modulo an affine transformation defined by its neighborhood. Modeling the observer's instantaneous motion by a translation and a rotation about an axis through its eye, affine flow is tangent to the translational field lines on the observer's viewing sphere. These field lines form a radial flow field whose center is the direction of heading. The affine flow heading algorithm has characteristics that can be used to determine whether the human visual system relies on it. The algorithm is immune to observer rotation and arbitrary affine transformations of its input images; its accuracy improves with increasing variation in environmental depth; and it cannot recover heading in an environment consisting of a single plane because affine flow vanishes in this case. Translational field lines can also be approximated through differential cartesian motion. I compare the performance of heading algorithms based on affine flow, differential cartesian flow, and least-squares search.     

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