Entorhinal cortex grid cells can map to hippocampal place cells by competitive learning

Rolls, Edmund T.; Stringer, Simon M.; Elliot, Thomas

doi:10.1080/09548980601064846

Cited by 208 publications

(212 citation statements)

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“…Models have shown that individual fields can be generated by a combination of only 10-50 grid cells with variable grid spacing and grid orientation but overlapping spatial phase (Solstad et al, 2006). In a second type of mechanism, place cells receive inputs from grid cells with variable spacing, orientation, and spatial phase (Rolls et al, 2006). Single-peaked place fields are generated from the resulting distribution of activity peaks by competitive Hebbian learning processes.…”

Section: From Grid Cells To Place Cells or Vice Versamentioning

confidence: 99%

A metric for space

2008

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ABSTRACT:Not all areas of neuronal systems investigation have matured to the stage where computation can be understood at the microcircuit level. In mammals, insights into cortical circuit functions have been obtained for the early stages of sensory systems, where signals can be followed through networks of increasing complexity from the receptors to the primary sensory cortices. These studies have suggested how neurons and neuronal networks extract features from the external world, but how the brain generates its own codes, in the higher-order nonsensory parts of the cortex, has remained deeply mysterious. In this terra incognita, a path was opened by the discovery of grid cells, place-modulated entorhinal neurons whose firing locations define a periodic triangular or hexagonal array covering the entirety of the animal's available environment. This array of firing is maintained in spite of ongoing changes in the animal's speed and direction, suggesting that grid cells are part of the brain's metric for representation of space. Because the crystal-like structure of the firing fields is created within the nervous system itself, grid cells may provide scientists with direct access to some of the most basic operational principles of cortical circuits. V

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Section: From Grid Cells To Place Cells or Vice Versamentioning

confidence: 99%

A metric for space

2008

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“…First, weak spatial inputs may be sufficient for place-cell formation. Sharply confined firing fields may be generated by local mechanisms in the hippocampal network, such as recurrent inhibition (de Almeida et al 2009;Monaco and Abbott 2011), Hebbian plasticity (Rolls et al 2006;Savelli and Knierim 2010), or active dendritic properties (Smith et al 2013). Alternatively, place cells may be generated from other classes of spatially modulated cells, such as border cells, which have adult-like properties from the very first day of exploration outside the nest (Bjerknes et al 2014).…”

Section: Upstream Of Place Cells: Grid Cells and Other Cell Typesmentioning

confidence: 99%

Place Cells, Grid Cells, and Memory

Moser

Rowland

Moser

2015

Cold Spring Harb Perspect Biol

423

267

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The hippocampal system is critical for storage and retrieval of declarative memories, including memories for locations and events that take place at those locations. Spatial memories place high demands on capacity. Memories must be distinct to be recalled without interference and encoding must be fast. Recent studies have indicated that hippocampal networks allow for fast storage of large quantities of uncorrelated spatial information. The aim of the this article is to review and discuss some of this work, taking as a starting point the discovery of multiple functionally specialized cell types of the hippocampal-entorhinal circuit, such as place, grid, and border cells. We will show that grid cells provide the hippocampus with a metric, as well as a putative mechanism for decorrelation of representations, that the formation of environment-specific place maps depends on mechanisms for long-term plasticity in the hippocampus, and that long-term spatiotemporal memory storage may depend on offline consolidation processes related to sharp-wave ripple activity in the hippocampus. The multitude of representations generated through interactions between a variety of functionally specialized cell types in the entorhinal-hippocampal circuit may be at the heart of the mechanism for declarative memory formation.T he scientific study of human memory started with Herman Ebbinghaus, who initiated the quantitative investigation of associative memory processes as they take place (Ebbinghaus 1885). Ebbinghaus described the conditions that influence memory formation and he determined several basic principles of encoding and recall, such as the law of frequency and the effect of time on forgetting. With Ebbinghaus, higher mental functions were brought to the laboratory. In parallel with the human learning tradition that Ebbinghaus started, a new generation of experimental psychologists described the laws of associative learning in animals. With behaviorists like Pavlov, Watson, Hull, Skinner, and Tolman, a rigorous program for identifying the laws of animal learning was initiated. By the middle of the 20th century, a language for associative learning processes had been developed, and many of the fundamental relationships between environment and behavior had been described. What was completely missing, though, was an understanding of the neural activity underlying the formation of the memory. The behaviorists had deliberately shied away from physiological explanations because of the intangible nature of neural activity at that time.Then the climate began to change. Karl Lashley had shown that lesions in the cerebral cortex had predictable effects on behavior in Editors: Eric R. Kandel, Yadin Dudai, and Mark R. Mayford Additional Perspectives on Learning and Memory available at

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“…This indicates that with the population code expressed by grid cells it is possible to keep a unique orientation correspondence across environments in spite of the orientation symmetry of the grids, and to differentiate locations in an environment by the relative spatial phases of the grid fields. To represent places on a larger scale, multiple grid spacings are needed [37][38][39][40] .…”

Section: Grid Realignment In Multiple Environmentsmentioning

confidence: 99%

Grid alignment in entorhinal cortex

Kropff

Treves

2012

Biol Cybern

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The spatial responses of many of the cells recorded in all layers of rodent medial entorhinal cortex (mEC) show a triangular grid pattern, which appears to provide an accurate population code for position, and once established might be based in part on path-integration mechanisms. Competing models, each partially contradicted by experimental observations, try to explain how the grid-like pattern emerges in terms of network interactions, or of interactions with theta oscillations or, the one we have proposed, of mere single-unit mechanisms.Grid axes are tightly aligned across simultaneously recorded units. Recent experimental findings have shown that grids can often be better described as elliptical rather than purely circular and that, beyond the mutual alignment of their grid axes, ellipses tend to also orient their long axis along preferred directions. Are grid alignment and ellipse orientation the same phenomenon? Does the grid alignment result from single-unit mechanisms or does it require network interactions?We address these issues by refining our model, to describe specifically the spontaneous emergence of conjunctive grid-by-head-direction cells in layers III, V and VI of mEC. We find that tight alignment can be produced by recurrent collateral interactions, but this requires head-direction modulation. Through a competitive learning process driven by spatial inputs, grid fields then form already aligned, and with randomly distributed spatial phases. In addition, we find that the selforganization process is influenced by the behavior of the simulated rat. The common grid alignment often orients along preferred running directions. The shape of individual grids is distorted towards an ellipsoid arrangement when some speed anisotropy is present in exploration behavior. Speed anisotropy on its own also tends to align grids, even without collaterals, but the alignment is seen to be loose. Finally, the alignment of spatial grid fields in multiple environments shows that the network expresses the same set of grid fields across environments, modulo a coherent rotation and translation. Thus, an efficient metric encoding of space may emerge through spontaneous pattern formation at the single-unit level, but it is coherent, hence context-invariant, if aided by collateral interactions.

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Entorhinal cortex grid cells can map to hippocampal place cells by competitive learning

Cited by 208 publications

References 43 publications

A metric for space

A metric for space

Place Cells, Grid Cells, and Memory

Grid alignment in entorhinal cortex

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