scholarly journals Parallel and convergent processing in grid cell, head-direction cell, boundary cell, and place cell networks

2013 ◽  
Vol 5 (2) ◽  
pp. 207-219 ◽  
Author(s):  
Mark P. Brandon ◽  
Julie Koenig ◽  
Stefan Leutgeb
Keyword(s):  
Grid Cell ◽  
Place Cell ◽  
Cell Boundary ◽  
Head Direction ◽  
Head Direction Cell ◽  
Boundary Cell ◽  
Cell Networks

scholarly journals Hippocampal Place Cell Instability after Lesions of the Head Direction Cell Network

2003 ◽  
Vol 23 (30) ◽  
pp. 9719-9731 ◽  
Author(s):  
Jeffrey L. Calton ◽  
Robert W. Stackman ◽  
Jeremy P. Goodridge ◽  
William B. Archey ◽  
Paul A. Dudchenko ◽  
...  
Keyword(s):  
Place Cell ◽  
Head Direction ◽  
Head Direction Cell ◽  
Cell Network ◽  
Hippocampal Place Cell

scholarly journals On the Organization of Grid and Place Cells: Neural Denoising via Subspace Learning

2019 ◽  
Vol 31 (8) ◽  
pp. 1519-1550
Author(s):  
David M. Schwartz ◽  
O. Ozan Koyluoglu
Keyword(s):  
Hebbian Learning ◽  
Grid Cell ◽  
Subspace Learning ◽  
Place Cell ◽  
Place Cells ◽  
Neural Code ◽  
Neural Representation ◽  
Cell Populations ◽  
Medial Entorhinal Cortex ◽  
Cell Networks

Place cells in the hippocampus (HC) are active when an animal visits a certain location (referred to as a place field) within an environment. Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that form a periodic and hexagonal tiling of the environment. The joint activity of grid and place cell populations, as a function of location, forms a neural code for space. In this article, we develop an understanding of the relationships between coding theoretically relevant properties of the combined activity of these populations and how these properties limit the robustness of this representation to noise-induced interference. These relationships are revisited by measuring the performances of biologically realizable algorithms implemented by networks of place and grid cell populations, as well as constraint neurons, which perform denoising operations. Contributions of this work include the investigation of coding theoretic limitations of the mammalian neural code for location and how communication between grid and place cell networks may improve the accuracy of each population's representation. Simulations demonstrate that denoising mechanisms analyzed here can significantly improve the fidelity of this neural representation of space. Furthermore, patterns observed in connectivity of each population of simulated cells predict that anti-Hebbian learning drives decreases in inter-HC-MEC connectivity along the dorsoventral axis.

scholarly journals Disruption of the head direction cell network impairs the parahippocampal grid cell signal

Science ◽  
2015 ◽  
Vol 347 (6224) ◽  
pp. 870-874 ◽  
Author(s):  
S. S. Winter ◽  
B. J. Clark ◽  
J. S. Taube
Keyword(s):  
Grid Cell ◽  
Head Direction ◽  
Head Direction Cell ◽  
Cell Network ◽  
Cell Signal

scholarly journals A structured scaffold underlies activity in the hippocampus

2021 ◽  
Author(s):  
Dounia Mulders ◽  
Man Yi Yim ◽  
Jae Sung Lee ◽  
Albert K. Lee ◽  
Thibaud Taillefumier ◽  
...  
Keyword(s):  
Random Process ◽  
Grid Cell ◽  
Place Cell ◽  
Place Cells ◽  
Head Direction ◽  
Cell Responses ◽  
Neural Populations ◽  
External Cues ◽  
One Step ◽  
Design Experiments

Place cells are believed to organize memory across space and time, inspiring the idea of the cognitive map. Yet unlike the structured activity in the associated grid and head-direction cells, they remain an enigma: their responses have been difficult to predict and are complex enough to be statistically well-described by a random process. Here we report one step toward the ultimate goal of understanding place cells well enough to predict their fields. Within a theoretical framework in which place fields are derived as a conjunction of external cues with internal grid cell inputs, we predict that even apparently random place cell responses should reflect the structure of their grid inputs and that this structure can be unmasked if probed in sufficiently large neural populations and large environments. To test the theory, we design experiments in long, locally featureless spaces to demonstrate that structured scaffolds undergird place cell responses. Our findings, together with other theoretical and experimental results, suggest that place cells build memories of external inputs by attaching them to a largely prespecified grid scaffold.

Toward Cognitive Navigation: Design and Implementation of a Biologically Inspired Head Direction Cell Network

2021 ◽  
pp. 1-12
Author(s):  
Zhenshan Bing ◽  
Amir EI Sewisy ◽  
Genghang Zhuang ◽  
Florian Walter ◽  
Fabrice O. Morin ◽  
...  
Keyword(s):  
Head Direction ◽  
Biologically Inspired ◽  
Head Direction Cell ◽  
Cell Network ◽  
Design And Implementation

Hippocampal Place-Cell Firing During Movement in Three-Dimensional Space

2001 ◽  
Vol 85 (1) ◽  
pp. 105-116 ◽  
Author(s):  
James J. Knierim ◽  
Bruce L. McNaughton
Keyword(s):  
Hippocampal Neurons ◽  
Horizontal Plane ◽  
Three Dimensional ◽  
Place Cell ◽  
Place Cells ◽  
Limbic Cortex ◽  
Head Direction ◽  
Head Direction Cells ◽  
Recording Apparatus ◽  
Place Fields

“Place” cells of the rat hippocampus are coupled to “head direction” cells of the thalamus and limbic cortex. Head direction cells are sensitive to head direction in the horizontal plane only, which leads to the question of whether place cells similarly encode locations in the horizontal plane only, ignoring the z axis, or whether they encode locations in three dimensions. This question was addressed by recording from ensembles of CA1 pyramidal cells while rats traversed a rectangular track that could be tilted and rotated to different three-dimensional orientations. Cells were analyzed to determine whether their firing was bound to the external, three-dimensional cues of the environment, to the two-dimensional rectangular surface, or to some combination of these cues. Tilting the track 45° generally provoked a partial remapping of the rectangular surface in that some cells maintained their place fields, whereas other cells either gained new place fields, lost existing fields, or changed their firing locations arbitrarily. When the tilted track was rotated relative to the distal landmarks, most place fields remapped, but a number of cells maintained the same place field relative to the x-y coordinate frame of the laboratory, ignoring the z axis. No more cells were bound to the local reference frame of the recording apparatus than would be predicted by chance. The partial remapping demonstrated that the place cell system was sensitive to the three-dimensional manipulations of the recording apparatus. Nonetheless the results were not consistent with an explicit three-dimensional tuning of individual hippocampal neurons nor were they consistent with a model in which different sets of cells are tightly coupled to different sets of environmental cues. The results are most consistent with the statement that hippocampal neurons can change their “tuning functions” in arbitrary ways when features of the sensory input or behavioral context are altered. Understanding the rules that govern the remapping phenomenon holds promise for deciphering the neural circuitry underlying hippocampal function.

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