scholarly journals A geometric attractor mechanism for self-organization of entorhinal grid modules

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Louis Kang ◽  
Vijay Balasubramanian
Keyword(s):  
Entorhinal Cortex ◽  
Network Models ◽  
Recurrent Inhibition ◽  
Modular Structure ◽  
Self Organization ◽  
Periodic Lattice ◽  
Grid Cells ◽  
Medial Entorhinal Cortex ◽  
Attractor Network ◽  
Discrete Values

Grid cells in the medial entorhinal cortex (MEC) respond when an animal occupies a periodic lattice of ‘grid fields’ in the environment. The grids are organized in modules with spatial periods, or scales, clustered around discrete values separated on average by ratios in the range 1.4–1.7. We propose a mechanism that produces this modular structure through dynamical self-organization in the MEC. In attractor network models of grid formation, the grid scale of a single module is set by the distance of recurrent inhibition between neurons. We show that the MEC forms a hierarchy of discrete modules if a smooth increase in inhibition distance along its dorso-ventral axis is accompanied by excitatory interactions along this axis. Moreover, constant scale ratios between successive modules arise through geometric relationships between triangular grids and have values that fall within the observed range. We discuss how interactions required by our model might be tested experimentally.

scholarly journals A geometric attractor mechanism for self-organization of entorhinal grid modules

2018 ◽  
Author(s):  
Louis Kang ◽  
Vijay Balasubramanian
Keyword(s):  
Entorhinal Cortex ◽  
Network Models ◽  
Recurrent Inhibition ◽  
Modular Structure ◽  
Self Organization ◽  
Periodic Lattice ◽  
Grid Cells ◽  
Medial Entorhinal Cortex ◽  
Attractor Network ◽  
Discrete Values

Grid cells in the medial entorhinal cortex (MEC) respond when an animal occupies a periodic lattice of “grid fields” in the environment. The grids are organized in modules with spatial periods, or scales, clustered around discrete values separated by ratios in the range 1.2–2.0. We propose a mechanism that produces this modular structure through dynamical self-organization in the MEC. In attractor network models of grid formation, the grid scale of a single module is set by the distance of recurrent inhibition between neurons. We show that the MEC forms a hierarchy of discrete modules if a smooth increase in inhibition distance along its dorso-ventral axis is accompanied by excitatory interactions along this axis. Moreover, constant scale ratios between successive modules arise through geometric relationships between triangular grids and have values that fall within the observed range. We discuss how interactions required by our model might be tested experimentally.

scholarly journals Shedding light on stellate cells

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Andrew S Alexander ◽  
Michael E Hasselmo
Keyword(s):  
Entorhinal Cortex ◽  
Stellate Cells ◽  
Grid Cells ◽  
Medial Entorhinal Cortex ◽  
The Relationship

The relationship between grid cells and two types of neurons found in the medial entorhinal cortex has been clarified.

scholarly journals ARM-Cortex M3-Based Two-Wheel Robot for Assessing Grid Cell Model of Medial Entorhinal Cortex: Progress towards Building Robots with Biologically Inspired Navigation-Cognitive Maps

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
J. Cuneo ◽  
L. Barboni ◽  
N. Blanco ◽  
M. del Castillo ◽  
J. Quagliotti
Keyword(s):  
Embedded System ◽  
Entorhinal Cortex ◽  
Cell Model ◽  
Systems Design ◽  
Grid Cell ◽  
Network Models ◽  
Time Algorithm ◽  
Neural Network Models ◽  
Biologically Inspired ◽  
Medial Entorhinal Cortex

This article presents the implementation and use of a two-wheel autonomous robot and its effectiveness as a tool for studying the recently discovered use of grid cells as part of mammalian’s brains space-mapping circuitry (specifically the medial entorhinal cortex). A proposed discrete-time algorithm that emulates the medial entorhinal cortex is programed into the robot. The robot freely explores a limited laboratory area in the manner of a rat or mouse and reports information to a PC, thus enabling research without the use of live individuals. Position coordinate neural maps are achieved as mathematically predicted although for a reduced number of implemented neurons (i.e., 200 neurons). However, this type of computational embedded system (robot’s microcontroller) is found to be insufficient for simulating huge numbers of neurons in real time (as in the medial entorhinal cortex). It is considered that the results of this work provide an insight into achieving an enhanced embedded systems design for emulating and understanding mathematical neural network models to be used as biologically inspired navigation system for robots.

scholarly journals Non-rhythmic head-direction cells in the parahippocampal region are not constrained by attractor network dynamics

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Olga Kornienko ◽  
Patrick Latuske ◽  
Mathis Bassler ◽  
Laura Kohler ◽  
Kevin Allen
Keyword(s):  
Entorhinal Cortex ◽  
Computational Models ◽  
Tuning Curve ◽  
Rhythmic Activity ◽  
External World ◽  
Head Direction ◽  
Visual Landmarks ◽  
Head Direction Cells ◽  
Medial Entorhinal Cortex ◽  
Attractor Network

Computational models postulate that head-direction (HD) cells are part of an attractor network integrating head turns. This network requires inputs from visual landmarks to anchor the HD signal to the external world. We investigated whether information about HD and visual landmarks is integrated in the medial entorhinal cortex and parasubiculum, resulting in neurons expressing a conjunctive code for HD and visual landmarks. We found that parahippocampal HD cells could be divided into two classes based on their theta-rhythmic activity: non-rhythmic and theta-rhythmic HD cells. Manipulations of the visual landmarks caused tuning curve alterations in most HD cells, with the largest visually driven changes observed in non-rhythmic HD cells. Importantly, the tuning modifications of non-rhythmic HD cells were often non-coherent across cells, refuting the notion that attractor-like dynamics control non-rhythmic HD cells. These findings reveal a new population of non-rhythmic HD cells whose malleable organization is controlled by visual landmarks.

scholarly journals Dynamic self-organized error-correction of grid cells by border cells

2018 ◽  
Author(s):  
Eli Pollock ◽  
Niral Desai ◽  
Xue-xin Wei ◽  
Vijay Balasubramanian
Keyword(s):  
Error Correction ◽  
Entorhinal Cortex ◽  
Path Integration ◽  
Network Models ◽  
Cell Types ◽  
Border Cells ◽  
Grid Cells ◽  
Spatially Correlated ◽  
Self Organized ◽  
Hebbian Plasticity

Grid cells in the entorhinal cortex are believed to establish their regular, spatially correlated firing patterns by path integration of the animal’s motion. Mechanisms for path integration, e.g. in attractor network models, predict stochastic drift of grid responses, which is not observed experimentally. We demonstrate a biologically plausible mechanism of dynamic self-organization by which border cells, which fire at environmental boundaries, can correct such drift in grid cells. In our model, experience-dependent Hebbian plasticity during exploration allows border cells to learn connectivity to grid cells. Border cells in this learned network reset the phase of drifting grids. This error-correction mechanism is robust to environmental shape and complexity, including enclosures with interior barriers, and makes distinctive predictions for environmental deformation experiments. Our work demonstrates how diverse cell types in the entorhinal cortex could interact dynamically and adaptively to achieve robust path integration.

scholarly journals Spike afterpotentials shape the in-vivo burst activity of principal cells in medial entorhinal cortex

2019 ◽  
Author(s):  
Dóra É. Csordás ◽  
Caroline Fischer ◽  
Johannes Nagele ◽  
Martin Stemmler ◽  
Andreas V.M. Herz
Keyword(s):  
Entorhinal Cortex ◽  
High Frequency ◽  
Cell Group ◽  
Two Dimensional ◽  
Grid Cells ◽  
Spatial Coding ◽  
Medial Entorhinal Cortex ◽  
Whole Cell

AbstractPrincipal neurons in rodent medial entorhinal cortex (MEC) generate high-frequency bursts during natural behavior. While in vitro studies point to potential mechanisms that could support such burst sequences, it remains unclear whether these mechanisms are effective under in-vivo conditions. In this study, we focused on the membrane-potential dynamics immediately following action potentials, as measured in whole-cell recordings from male mice running in virtual corridors (Domnisoru et al., 2013). These afterpotentials consisted either of a hyperpolarization, an extended ramp-like shoulder, or a depolarization reminiscent of depolarizing afterpotentials (DAPs) recorded in vitro in MEC stellate and pyramidal neurons. Next, we correlated the afterpotentials with the cells’ propensity to fire bursts. All DAP cells with known location resided in Layer II, generated bursts, and their inter-spike intervals (ISIs) were typically between five and fifteen milliseconds. The ISI distributions of Layer-II cells without DAPs peaked sharply at around four milliseconds and varied only minimally across that group. This dichotomy in burst behavior is explained by cell-group-specific DAP dynamics. The same two groups of bursting neurons also emerged when we clustered extracellular spike-train autocorrelations measured in real two-dimensional arenas (Latuske et al., 2015). No difference in the spatial coding properties of the grid cells across all three groups was discernible. Layer III neurons were only sparsely bursting and had no DAPs. As various mechanisms for modulating the ion-channels underlying DAPs exist, our results suggest that the temporal features of MEC activity can be altered while maintaining the cells’ spatial tuning characteristics.Significance StatementDepolarizing afterpotentials (DAPs) are frequently observed in principal neurons from slice preparations of rodent medial entorhinal cortex (MEC), but their functional role in vivo is unknown. Analyzing whole-cell data from mice running on virtual tracks, we show that DAPs do occur during behavior. Cells with prominent DAPs are found in Layer II; their inter-spike intervals reflect DAP time-scales. In contrast, neither the rarely bursting cells in Layer III, nor the high-frequency bursters in Layer II, have a DAP. Extracellular recordings from mice exploring real two-dimensional arenas demonstrate that grid cells within these three groups have rather similar spatial coding properties. We conclude that DAPs shape the temporal but not the spatial response characteristics of principal neurons in MEC.Author contributionsAll authors designed research. DÉC, CF, and JN performed research and analyzed data (equal contribution). AVMH wrote and edited the paper with support from MS and the other authors.

scholarly journals A Map-like Micro-Organization of Grid Cells in the Medial Entorhinal Cortex

Cell ◽  
2018 ◽  
Vol 175 (3) ◽  
pp. 736-750.e30 ◽  
Author(s):  
Yi Gu ◽  
Sam Lewallen ◽  
Amina A. Kinkhabwala ◽  
Cristina Domnisoru ◽  
Kijung Yoon ◽  
...  
Keyword(s):  
Entorhinal Cortex ◽  
Grid Cells ◽  
Medial Entorhinal Cortex

scholarly journals Home, head direction stability, and grid cell distortion

2020 ◽  
Vol 123 (4) ◽  
pp. 1392-1406 ◽  
Author(s):  
Juan Ignacio Sanguinetti-Scheck ◽  
Michael Brecht
Keyword(s):  
Entorhinal Cortex ◽  
Home Cage ◽  
Cell Activity ◽  
Grid Cell ◽  
Head Direction ◽  
Grid Cells ◽  
Head Direction Cells ◽  
Medial Entorhinal Cortex ◽  
Abstract Approach ◽  
Globally Stable

The home is a unique location in the life of humans and animals. In rats, home presents itself as a multicompartmental space that involves integrating navigation through subspaces. Here we embedded the laboratory rat’s home cage in the arena, while recording neurons in the animal’s parasubiculum and medial entorhinal cortex, two brain areas encoding the animal’s location and head direction. We found that head direction signals were unaffected by home cage presence or translocation. Head direction cells remain globally stable and have similar properties inside and outside the embedded home. We did not observe egocentric bearing encoding of the home cage. However, grid cells were distorted in the presence of the home cage. While they did not globally remap, single firing fields were translocated toward the home. These effects appeared to be geometrical in nature rather than a home-specific distortion and were not dependent on explicit behavioral use of the home cage during a hoarding task. Our work suggests that medial entorhinal cortex and parasubiculum do not remap after embedding the home, but local changes in grid cell activity overrepresent the embedded space location and might contribute to navigation in complex environments. NEW & NOTEWORTHY Neural findings in the field of spatial navigation come mostly from an abstract approach that separates the animal from even a minimally biological context. In this article we embed the home cage of the rat in the environment to address some of the complexities of natural navigation. We find no explicit home cage representation. While both head direction cells and grid cells remain globally stable, we find that embedded spaces locally distort grid cells.

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