Head direction cells, grid cells, and the neural basis of spatial orientation

2011 ◽  
Author(s):  
Benjamin Joseph Clark
Keyword(s):  
Spatial Orientation ◽  
Head Direction ◽  
Grid Cells ◽  
Neural Basis ◽  
Head Direction Cells

scholarly journals Functional connectivity of the entorhinal–hippocampal space circuit

2014 ◽  
Vol 369 (1635) ◽  
pp. 20120516 ◽  
Author(s):  
Sheng-Jia Zhang ◽  
Jing Ye ◽  
Jonathan J. Couey ◽  
Menno Witter ◽  
Edvard I. Moser ◽  
...  
Keyword(s):  
Entorhinal Cortex ◽  
Cell Types ◽  
Place Cells ◽  
Projection Neurons ◽  
Border Cells ◽  
Head Direction ◽  
Grid Cells ◽  
Head Direction Cells ◽  
Dynamic Interactions ◽  
Cell Groups

The mammalian space circuit is known to contain several functionally specialized cell types, such as place cells in the hippocampus and grid cells, head-direction cells and border cells in the medial entorhinal cortex (MEC). The interaction between the entorhinal and hippocampal spatial representations is poorly understood, however. We have developed an optogenetic strategy to identify functionally defined cell types in the MEC that project directly to the hippocampus. By expressing channelrhodopsin-2 (ChR2) selectively in the hippocampus-projecting subset of entorhinal projection neurons, we were able to use light-evoked discharge as an instrument to determine whether specific entorhinal cell groups—such as grid cells, border cells and head-direction cells—have direct hippocampal projections. Photoinduced firing was observed at fixed minimal latencies in all functional cell categories, with grid cells as the most abundant hippocampus-projecting spatial cell type. We discuss how photoexcitation experiments can be used to distinguish the subset of hippocampus-projecting entorhinal neurons from neurons that are activated indirectly through the network. The functional breadth of entorhinal input implied by this analysis opens up the potential for rich dynamic interactions between place cells in the hippocampus and different functional cell types in the entorhinal cortex (EC).

scholarly journals Spatial orientation in navigating agents: Modeling head-direction cells

2001 ◽  
Vol 38-40 ◽  
pp. 1059-1065 ◽  
Author(s):  
Angelo Arleo ◽  
Wulfram Gerstner
Keyword(s):  
Spatial Orientation ◽  
Head Direction ◽  
Head Direction Cells

Bio-Inspired Robotics: A Spatial Cognition Model integrating Place Cells, Grid Cells and Head Direction Cells

2018 ◽  
Vol 91 (1) ◽  
pp. 85-99 ◽  
Author(s):  
Gonzalo Tejera ◽  
Martin Llofriu ◽  
Alejandra Barrera ◽  
Alfredo Weitzenfeld
Keyword(s):  
Spatial Cognition ◽  
Place Cells ◽  
Head Direction ◽  
Grid Cells ◽  
Head Direction Cells ◽  
Cognition Model

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.

scholarly journals Representation of Borders and Swimming Kinematics in the Brain of Freely-Navigating Fish

2018 ◽  
Author(s):  
Ehud Vinepinsky ◽  
Lear Cohen ◽  
Shay Perchik ◽  
Ohad Ben-Shahar ◽  
Opher Donchin ◽  
...  
Keyword(s):  
Brain Region ◽  
Building Blocks ◽  
Neural Representation ◽  
Water Tank ◽  
Border Cells ◽  
Head Direction ◽  
Neural Basis ◽  
Head Direction Cells ◽  
Swimming Kinematics ◽  
The Brain

AbstractLike most animals, the survival of fish depends crucially on navigation in space. This capacity has been documented in numerous behavioral studies that have revealed navigation strategies and the sensory modalities used for navigation. However, virtually nothing is known about how freely swimming fish represent space and locomotion in the brain to enable successful navigation. Using a novel wireless neural recording system, we measured the activity of single neurons in the goldfish lateral pallium, a brain region known to be involved in spatial memory and navigation, while the fish swam freely in a two-dimensional water tank. Four cell types were identified: border cells, head direction cells, speed cells and conjunction head direction with speed. Border cells were active when the fish was near the boundary of the environment. Head direction cells were shown to encode head direction. Speed cells only encoded the absolute speed independent of direction suggestive of an odometry signal. Finally, the conjunction of head direction with speed cells represented the velocity of the fish. This study thus sheds light on how information related to navigation is represented in the brain of swimming fish, and addresses the fundamental question of the neural basis of navigation in this diverse group of vertebrates. The similarities between our observations in fish and earlier findings in mammals may indicate that the networks controlling navigation in vertebrate originate from an ancient circuit common across vertebrates.SummaryNavigation is a fundamental behavioral capacity facilitating survival in many animal species. Fish is one lineage where navigation has been explored behaviorally, but it remains unclear how freely swimming fish represent space and locomotion in the brain. This is a key open question in our understanding of navigation in fish and more generally in understanding the evolutionary origin of the brain’s navigation system. To address this issue, we recorded neuronal signals from the brain of freely swimming goldfish and successfully identified representations of border and swimming kinematics in a brain region known to be associated with navigation. Our findings thus provide a glimpse into the building blocks of the neural representation underlying fish navigation. The similarity of the representation in fish with that of mammals may be key evidence supporting a preserved ancient mechanism across brain evolution.

scholarly journals Middle-scale navigation: the vertebrate case

1996 ◽  
Vol 199 (1) ◽  
pp. 163-164
Author(s):  
DF Sherry
Keyword(s):  
Path Integration ◽  
Brain Regions ◽  
Place Cells ◽  
Cognitive Map ◽  
Head Direction ◽  
Neural Basis ◽  
Head Direction Cells ◽  
Complete Rejection ◽  
Neural Bases

Few ideas have had a greater impact on the study of navigation at the middle scale than the theory of the cognitive map. As papers in this section show, current views of the cognitive map range from complete rejection of the idea (Bennett, 1996) to new proposals for the behavioural and neural bases of the cognitive map (Gallistel and Cramer, 1996; McNaughton et al. 1996). The papers in this section also make it clear that path integration has taken centre stage in theorizing about navigation at the middle scale. Path integration is the use of information generated by locomotion to determine the current distance and direction to the origin of the path. Etienne (1980) provided one of the first experimental demonstrations of path integration by a vertebrate, and in this section Etienne et al. (1996) describe recent research with animals and humans on the interaction between path integration and landmark information. Path integration is also the fundamental means of navigation in the model described by Gallistel and Cramer (1996). McNaughton et al. (1996) suggest that the neural basis of path integration is found in the place cells and head direction cells of the hippocampus and associated brain regions.

scholarly journals Head-direction cells escaping attractor dynamics in the parahippocampal region

2018 ◽  
Author(s):  
Olga Kornienko ◽  
Patrick Latuske ◽  
Laura Kohler ◽  
Kevin Allen
Keyword(s):  
Entorhinal Cortex ◽  
Computational Models ◽  
Head Direction ◽  
Grid Cells ◽  
Visual Landmarks ◽  
Head Direction Cells ◽  
Medial Entorhinal Cortex ◽  
Attractor Dynamics ◽  
Freely Moving ◽  
Uniform Population

AbstractNavigation depends on the activity of head-direction (HD) cells. Computational models postulate that HD cells form a uniform population that reacts coherently to changes in landmarks. We tested whether this applied to HD cells of the medial entorhinal cortex and parasubiculum, areas where the HD signal contributes to the periodic firing of grid cells. Manipulations of the visual landmarks surrounding freely-moving mice altered the tuning of HD cells. Importantly, these tuning modifications were often non-coherent across cells, refuting the notion that HD cells form a uniform population constrained by attractor-like dynamics. Instead, examination of theta rhythmicity 1revealed two types of HD cells, theta rhythmic and non-rhythmic cells. Larger tuning alterations were observed predominantly in non-rhythmic HD cells. Moreover, only non-rhythmic HD cells reorganized their firing associations in response to visual land-mark changes. These findings reveal a theta non-rhythmic HD signal whose malleable organization is controlled by visual landmarks.

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