Sensory Feedback, Error Correction, and Remapping in a Multiple Oscillator Model of Place-Cell Activity

Mammals navigate by integrating self-motion signals (“path integration”) and occasionally fixing on familiar environmental landmarks. The rat hippocampus is a model system of spatial representation in which place cells are thought to integrate both sensory and spatial information from entorhinal cortex. The localized firing fields of hippocampal place cells and entorhinal grid-cells demonstrate a phase relationship with the local theta (6–10 Hz) rhythm that may be a temporal signature of path integration. However, encoding self-motion in the phase of theta oscillations requires high temporal precision and is susceptible to idiothetic noise, neuronal variability, and a changing environment. We present a model based on oscillatory interference theory, previously studied in the context of grid cells, in which transient temporal synchronization among a pool of path-integrating theta oscillators produces hippocampal-like place fields. We hypothesize that a spatiotemporally extended sensory interaction with external cues modulates feedback to the theta oscillators. We implement a form of this cue-driven feedback and show that it can retrieve fixed points in the phase code of position. A single cue can smoothly reset oscillator phases to correct for both systematic errors and continuous noise in path integration. Further, simulations in which local and global cues are rotated against each other reveal a phase-code mechanism in which conflicting cue arrangements can reproduce experimentally observed distributions of “partial remapping” responses. This abstract model demonstrates that phase-code feedback can provide stability to the temporal coding of position during navigation and may contribute to the context-dependence of hippocampal spatial representations. While the anatomical substrates of these processes have not been fully characterized, our findings suggest several signatures that can be evaluated in future experiments

An oscillatory interference model of grid cell firing

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

Hippocampal Global Remapping Can Occur without Input from the Medial Entorhinal Cortex.

The high storage capacity of the episodic memory system relies on distinct representations for events that are separated in time and space. The spatial component of these computations includes the formation of independent maps by hippocampal place cells across environments, referred to as global remapping. Such remapping is thought to emerge by the switching of input patterns from specialized spatially selective cells in medial entorhinal cortex (mEC), such as grid and border cells. Although it has been shown that acute manipulations of mEC firing patterns are sufficient for inducing hippocampal remapping, it remains unknown whether specialized spatial mEC inputs are necessary for the reorganization of hippocampal spatial representations. Here, we examined remapping in rats without mEC input to the hippocampus and found that highly distinct spatial maps emerged rapidly in every individual rat. Our data suggest that hippocampal spatial computations do not depend on inputs from specialized cell types in mEC

Models of spatial representation in the medial entorhinal cortex

Komplexe kognitive Funktionen wie Gedächtnisbildung, Navigation und Entscheidungsprozesse hängen von der Kommunikation zwischen Hippocampus und Neokortex ab. An der Schnittstelle dieser beiden Gehirnregionen liegt der entorhinale Kortex - ein Areal, das Neurone mit bemerkenswerten räumlichen Repräsentationen enthält: Gitterzellen. Gitterzellen sind Neurone, die abhängig von der Position eines Tieres in seiner Umgebung feuern und deren Feuerfelder ein dreieckiges Muster bilden. Man vermutet, dass Gitterzellen Navigation und räumliches Gedächtnis unterstützen, aber die Mechanismen, die diese Muster erzeugen, sind noch immer unbekannt. In dieser Dissertation untersuche ich mathematische Modelle neuronaler Schaltkreise, um die Entstehung, Weitervererbung und Verstärkung von Gitterzellaktivität zu erklären. Zuerst konzentriere ich mich auf die Entstehung von Gittermustern. Ich folge der Idee, dass periodische Repräsentationen des Raumes durch Konkurrenz zwischen dauerhaft aktiven, räumlichen Inputs und der Tendenz eines Neurons, durchgängiges Feuern zu vermeiden, entstehen könnten. Aufbauend auf vorangegangenen theoretischen Arbeiten stelle ich ein Einzelzell-Modell vor, das gitterartige Aktivität allein durch räumlich-irreguläre Inputs, Feuerratenadaptation und Hebbsche synaptische Plastizität erzeugt. Im zweiten Teil der Dissertation untersuche ich den Einfluss von Netzwerkdynamik auf das Gitter-Tuning. Ich zeige, dass Gittermuster zwischen neuronalen Populationen weitervererbt werden können und dass sowohl vorwärts gerichtete als auch rekurrente Verbindungen die Regelmäßigkeit von räumlichen Feuermustern verbessern können. Schließlich zeige ich, dass eine entsprechende Konnektivität, die diese Funktionen unterstützt, auf unüberwachte Weise entstehen könnte. Insgesamt trägt diese Arbeit zu einem besseren Verständnis der Prinzipien der neuronalen Repräsentation des Raumes im medialen entorhinalen Kortex bei.High-level cognitive abilities such as memory, navigation, and decision making rely on the communication between the hippocampal formation and the neocortex. At the interface between these two brain regions is the entorhinal cortex, a multimodal association area where neurons with remarkable representations of self-location have been discovered: the grid cells. Grid cells are neurons that fire according to the position of an animal in its environment and whose firing fields form a periodic triangular pattern. Grid cells are thought to support animal's navigation and spatial memory, but the cellular mechanisms that generate their tuning are still unknown. In this thesis, I study computational models of neural circuits to explain the emergence, inheritance, and amplification of grid-cell activity. In the first part of the thesis, I focus on the initial formation of grid-cell tuning. I embrace the idea that periodic representations of space could emerge via a competition between persistently-active spatial inputs and the reluctance of a neuron to fire for long stretches of time. Building upon previous theoretical work, I propose a single-cell model that generates grid-like activity solely form spatially-irregular inputs, spike-rate adaptation, and Hebbian synaptic plasticity. In the second part of the thesis, I study the inheritance and amplification of grid-cell activity. Motivated by the architecture of entorhinal microcircuits, I investigate how feed-forward and recurrent connections affect grid-cell tuning. I show that grids can be inherited across neuronal populations, and that both feed-forward and recurrent connections can improve the regularity of spatial firing. Finally, I show that a connectivity supporting these functions could self-organize in an unsupervised manner. Altogether, this thesis contributes to a better understanding of the principles governing the neuronal representation of space in the medial entorhinal cortex

Hippocampal Spatial Representation: Integrating Environmental and Self-motion Signals

Electrophysiological recording in freely-moving rodents has established that place cells fire when the animal occupies a specific location and grid cells fire when at several locations, arranged on a regular triangular grid. Experiments and theories suggest that place cells and grid cells 1) receive inputs reflecting both environmental and self-motion information, and 2) are functionally connected to each other. Yet it remains elusive how the environmental and self-motion inputs dictate either place cell or grid cell firing. In a series of experiments, I address this question by manipulating the inputs independently while simultaneously recording place and grid cells activity. Firstly, I introduce our visual 2-d virtual reality system, in which mice run on an air-supported Styrofoam ball with their head held but allowed to rotate in the horizontal plane. The virtual arena is projected on surrounding screens and on the floor at a viewpoint that shifts with the rotation of the ball. With sufficient training, mice can navigate freely in the virtual environment and successfully retrieve rewards from an unmarked location. Electrophysiological data confirms that place, grid, and head-direction cells show characteristic spatial tuning in VR. In a second experiment, the gain factor that maps mice’s running speed to the visual translation of the virtual environment is manipulated. Results show that place cell firings are more driven by vision while grid cells incorporate self-motion inputs better. The last experiment had mice navigate in darkness. Without visual input co-recorded place cells and grid cells both suffer disruption in spatial tuning, albeit tuning is better preserved near to environmental boundaries. These results demonstrated that environmental and self-motion signals contribute to place and grid cells’ spatial representation of different significance, and constrain models with presumptions about how the place cells and grid cells integrate inputs and interact with each other

Cortical-hippocampal processing: prefrontal-hippocampal contributions to the spatiotemporal relationship of events

The hippocampus and prefrontal cortex play distinct roles in the generation and retrieval of episodic memory. The hippocampus is crucial for binding inputs across behavioral timescales, whereas the prefrontal cortex is found to influence retrieval. Spiking of hippocampal principal neurons contains environmental information, including information about the presence of specific objects and their spatial or temporal position relative to environmental and behavioral cues. Neural activity in the prefrontal cortex is found to map behavioral sequences that share commonalities in sensory input, movement, and reward valence. Here I conducted a series of four experiments to test the hypothesis that external inputs from cortex update cell assemblies that are organized within the hippocampus. I propose that cortical inputs coordinate with CA3 to rapidly integrate information at fine timescales. Extracellular tetrode recordings of neurons in the orbitofrontal cortex were performed in rats during a task where object valences were dictated by the spatial context in which they were located. Orbitofrontal ensembles, during object sampling, were found to organize all measured task elements in inverse rank relative to the rank previously observed in the hippocampus, whereby orbitofrontal ensembles displayed greater differentiation for object valence and its contextual identity than spatial position. Using the same task, a follow-up experiment assessed coordination between prefrontal and hippocampal networks by simultaneously recording medial prefrontal and hippocampal activity. The circuit was found to coordinate at theta frequencies, whereby hippocampal theta engaged prefrontal signals during contextual sampling, and the order of engagement reversed during object sampling. Two additional experiments investigated hippocampal temporal representations. First, hippocampal patterns were found to represent conjunctions of time and odor during a head-fixed delayed match-to-sample task. Lastly, I assessed the dependence of hippocampal firing patterns on intrinsic connectivity during the delay period versus active navigation of spatial routes, as rats performed a delayed-alternation T-maze. Stimulation of the ventral hippocampal commissure induced remapping of hippocampal activity during the delay period selectively. Despite temporal reorganization, different hippocampal populations emerged to predict temporal position. These results show hippocampal representations are guided by stable cortical signals, but also, coordination between cortical and intrinsic circuitry stabilizes flexible CA1 temporal representations

Controlling Phase Noise in Oscillatory Interference Models of Grid Cell Firing

Oscillatory interference models account for the spatial firing properties of grid cells in terms of neuronal oscillators with frequencies modulated by the animal's movement velocity. The phase of such a "velocity-controlled oscillator" (VCO) relative to a baseline (theta-band) oscillation tracks displacement along a preferred direction. Input from multiple VCOs with appropriate preferred directions causes a grid cell's grid-like firing pattern. However, accumulating phase noise causes the firing pattern to drift and become corrupted. Here we show how multiple redundant VCOs can automatically compensate for phase noise. By entraining the baseline frequency to the mean VCO frequency, VCO phases remain consistent, ensuring a coherent grid pattern and reducing its spatial drift. We show how the spatial stability of grid firing depends on the variability in VCO phases, e.g., a phase SD of 3 ms per 125 ms cycle results in stable grids for 1 min. Finally, coupling N VCOs with similar preferred directions as a ring attractor, so that their relative phases remain constant, produces grid cells with consistently offset grids, and reduces VCO phase variability of the order square root of N. The results suggest a viable functional organization of the grid cell network, and highlight the benefit of integrating displacement along multiple redundant directions for the purpose of path integration

Controlling Phase Noise in Oscillatory Interference Models of Grid Cell Firing.

Oscillatory interference models account for the spatial firing properties of grid cells in terms of neuronal oscillators with frequencies modulated by the animal's movement velocity. The phase of such a "velocity-controlled oscillator" (VCO) relative to a baseline (theta-band) oscillation tracks displacement along a preferred direction. Input from multiple VCOs with appropriate preferred directions causes a grid cell's grid-like firing pattern. However, accumulating phase noise causes the firing pattern to drift and become corrupted. Here we show how multiple redundant VCOs can automatically compensate for phase noise. By entraining the baseline frequency to the mean VCO frequency, VCO phases remain consistent, ensuring a coherent grid pattern and reducing its spatial drift. We show how the spatial stability of grid firing depends on the variability in VCO phases, e.g., a phase SD of 3 ms per 125 ms cycle results in stable grids for 1 min. Finally, coupling N VCOs with similar preferred directions as a ring attractor, so that their relative phases remain constant, produces grid cells with consistently offset grids, and reduces VCO phase variability of the order square root of N. The results suggest a viable functional organization of the grid cell network, and highlight the benefit of integrating displacement along multiple redundant directions for the purpose of path integration