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 drift in rat pups is consistent with an angular path-integration process

2017 ◽  
Author(s):  
Gilad Tocker ◽  
Eli Borodach ◽  
Tale L. Bjerknes ◽  
May-Britt Moser ◽  
Edvard I. Moser ◽  
...  
Keyword(s):  
Random Walk ◽  
Path Integration ◽  
Open Loop ◽  
Head Direction ◽  
Integration Process ◽  
Neural Basis ◽  
Head Direction Cells ◽  
Rat Pups ◽  
Sense Of Direction ◽  
Eye Opening

SummaryThe sense of direction is a vital computation, whose neural basis is considered to be carried out by head-direction cells. One way to estimate head-direction is by integrating head angular-velocity over time. However, this process results in error accumulation resembling a random walk, proportional to , which constitutes a mark for a path integration process. In the present study we analyzed previously recorded data to quantify the drift in head-direction cells of rat pups before and after eye-opening. We found that in rat pups before eye-opening the drift propagated as a random walk, while in rats after eye-opening the drift was lower. This suggests that a path-integration process underlies the estimation of head-direction, such that before eye-opening the head-direction system runs in an open-loop manner and accumulates error. After eye-opening, visual-input, such as arena shape, helps to correct errors and thus compute the sense of direction accurately.

scholarly journals An Oscillatory Network Model of Head Direction, Spatially Periodic Cells and Place Cells Using Locomotor Inputs

2016 ◽  
Author(s):  
Karthik Soman ◽  
Vignesh Muralidharan ◽  
V. Srinivasa Chakravarthy
Keyword(s):  
Path Integration ◽  
Place Cells ◽  
Border Cells ◽  
Head Direction ◽  
Grid Cells ◽  
Head Direction Cells ◽  
Modeling Approach ◽  
Spatially Periodic ◽  
Locomotor Rhythms ◽  
Oscillatory Network

AbstractWe propose a computational modeling approach that explains the formation of a range of spatial cells like head direction cells, grid cells, border cells and place cells which are believed to play a pivotal role in the spatial navigation of an animal. Most existing models insert special symmetry conditions in the models in order to obtain such symmetries in the outcome; our models do not require such symmetry assumptions. Our modeling approach is embodied in two models: a simple one (Model #1) and a more detailed version (Model #2). In Model #1, velocity input is presented to a layer of Head Direction cells, with no special topology requirements, the outputs of which are presented to a layer of Path Integration neurons. A variety of spatially periodic responses resembling grid cells, are obtained using the Principal Components of Path Integration layer. In Model #2, the input consists of the locomotor rhythms from the four legs of a virtual animal. These rhythms are integrated into the phases of a layer of oscillatory neurons, whose outputs drive a layer of Head Direction cells. The Head Direction cells in turn drive a layer of Path Integration neurons, which in turn project to two successive layers of Lateral Anti Hebbian Networks (LAHN). Cells in the first LAHN resemble grid cells (with both hexagonal and square gridness), and border cells. Cells in the second LAHN exhibit place cell behaviour and a new cell type known as corner cell. Both grid cells and place cells exhibit phase precession in 1D and 2D spaces. The models outline the neural hierarchy necessary to obtain the complete range of spatial cell responses found in the hippocampal system.

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.

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).

Heading-vector navigation based on head-direction cells and path integration

Hippocampus ◽  
2009 ◽  
Vol 19 (5) ◽  
pp. 456-479 ◽  
Author(s):  
John L. Kubie ◽  
André A. Fenton
Keyword(s):  
Path Integration ◽  
Head Direction ◽  
Head Direction Cells ◽  
Vector Navigation
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