scholarly journals Spatial scale and place field stability in a grid-to-place cell model of the dorsoventral axis of the hippocampus

Hippocampus ◽  
2013 ◽  
Vol 23 (8) ◽  
pp. 729-744 ◽  
Author(s):  
David Lyttle ◽  
Brian Gereke ◽  
Kevin K. Lin ◽  
Jean-Marc Fellous
Keyword(s):  
Spatial Scale ◽  
Cell Model ◽  
Place Cell ◽  
Place Field ◽  
Dorsoventral Axis

scholarly journals Hippocampal place cells encode local surface texture boundaries

2019 ◽  
Author(s):  
Chia-Hsuan Wang ◽  
Joseph D. Monaco ◽  
James J. Knierim
Keyword(s):  
Flat Surface ◽  
Cell Activity ◽  
Place Cell ◽  
Cognitive Map ◽  
Neural Representation ◽  
Place Field ◽  
Experimental Conditions ◽  
Inhomogeneous Surface ◽  
Physiological Basis ◽  
Circular Track

SummaryThe cognitive map is often assumed to be a Euclidean map that isometrically represents the real world (i.e. the Euclidean distance between any two locations in the physical world should be preserved on the cognitive map). However, accumulating evidence suggests that environmental boundaries can distort the mental representations of a physical space. For example, the distance between two locations can be remembered as longer than the true physical distance if the locations are separated by a boundary. While this overestimation is observed under different experimental conditions, even when the boundary is formed by flat surface cues, its physiological basis is not well understood. We examined the neural representation of flat surface cue boundaries, and of the space segregated by these boundaries, by recording place cell activity from dorsal CA1 and CA3 while rats foraged on a circular track or square platform with inhomogeneous surface textures. About 40% of the place field edges concentrated near the surface cue boundaries on the circular track (significantly above the chance level 33%). Similarly, the place field edges were more prevalent near the boundaries on the platforms than expected by chance. In both 1-dimensional and 2-dimensional environments, the population vectors of place cell activity changed more abruptly with distance between locations that crossed cue boundaries than between locations within a bounded region. These results show that the locations of surface boundaries were evident as enhanced decorrelations of the neural representations of locations to either side of the boundaries. This enhancement might underlie the cognitive phenomenon of overestimation of distances across boundaries.

scholarly journals Place-cell capacity and volatility with grid-like inputs

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Man Yi Yim ◽  
Lorenzo A Sadun ◽  
Ila R Fiete ◽  
Thibaud Taillefumier
Keyword(s):  
Grid Cell ◽  
Place Cell ◽  
Place Cells ◽  
Place Field ◽  
Cell Capacity ◽  
Spatial Range ◽  
External Cues ◽  
Noise Robust ◽  
Large Response

What factors constrain the arrangement of the multiple fields of a place cell? By modeling place cells as perceptrons that act on multiscale periodic grid-cell inputs, we analytically enumerate a place cell's repertoire - how many field arrangements it can realize without external cues while its grid inputs are unique; and derive its capacity - the spatial range over which it can achieve any field arrangement. We show that the repertoire is very large and relatively noise-robust. However, the repertoire is a vanishing fraction of all arrangements, while capacity scales only as the sum of the grid periods so field arrangements are constrained over larger distances. Thus, grid-driven place field arrangements define a large response scaffold that is strongly constrained by its structured inputs. Finally, we show that altering grid-place weights to generate an arbitrary new place field strongly affects existing arrangements, which could explain the volatility of the place code.

scholarly journals Erratum to: Odour supported place cell model and goal navigation in rodents

2010 ◽  
Vol 28 (3) ◽  
pp. 617-617
Author(s):  
Tomas Kulvicius ◽  
Minija Tamosiunaite ◽  
James Ainge ◽  
Paul Dudchenko ◽  
Florentin Wörgötter
Keyword(s):  
Cell Model ◽  
Place Cell

scholarly journals A boundary vector cell model of place field repetition

2018 ◽  
Vol 18 (3) ◽  
pp. 217-256 ◽  
Author(s):  
Roddy M Grieves ◽  
Éléonore Duvelle ◽  
Paul A Dudchenko
Keyword(s):  
Cell Model ◽  
Place Field ◽  
Boundary Vector

scholarly journals Choice of method of place cell classification determines the population of cells identified

2021 ◽  
Vol 17 (7) ◽  
pp. e1008835
Author(s):  
Dori M. Grijseels ◽  
Kira Shaw ◽  
Caswell Barry ◽  
Catherine N. Hall
Keyword(s):  
Spatial Information ◽  
Real Data ◽  
Place Cell ◽  
Place Cells ◽  
Optical Methods ◽  
Combination Method ◽  
Cell Detection ◽  
Imaging Data ◽  
Place Field ◽  
Implanted Electrodes

Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Here we tested four methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method); the stability of cells’ activity over repeated traversals of an environment (Stability method); a combination of these parameters with the size of the place field (Combination method); and the spatial information held by the cells (Information method). The methods performed differently from each other on both model and real data. In real datasets, vastly different numbers of place cells were identified using the four methods, with little overlap between the populations identified as place cells. Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. Ultimately, we recommend the Peak method be used in future studies to identify place cell populations, as this method is robust to moderate variations in place field within a session, and makes no inherent assumptions about the spatial information in place fields, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties.

scholarly journals The Boundary Vector Cell Model of Place Cell Firing and Spatial Memory

2006 ◽  
Vol 17 (1-2) ◽  
Author(s):  
C. Barry ◽  
C. Lever ◽  
R. Hayman ◽  
T. Hartley ◽  
S. Burton ◽  
...  
Keyword(s):  
Spatial Memory ◽  
Cell Model ◽  
Place Cell ◽  
Boundary Vector ◽  
Cell Firing

scholarly journals Choice of method of place cell classification determines the population of cells identified.

2021 ◽  
Author(s):  
Dori M Grijseels ◽  
Kira Shaw ◽  
Caswell Barry ◽  
Catherine N. Hall
Keyword(s):  
High Sensitivity ◽  
Real Data ◽  
Place Cell ◽  
Place Cells ◽  
Optical Methods ◽  
Combination Method ◽  
Cell Detection ◽  
Imaging Data ◽  
Place Field ◽  
Implanted Electrodes

Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Here we tested three methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method); the stability of cells’ activity over repeated traversals of an environment (Stability method); and a combination of these parameters with the size of the place field (Combination method). The three methods performed differently from each other on both model and real data. The Peak method showed high sensitivity and specificity for detecting model place cells and was the most robust to variations in place field width, reliability and field location. In real datasets, vastly different numbers of place cells were identified using the three methods, with little overlap between the populations identified as place cells. Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. We recommend the Peak method be used in future studies to identify place cell populations, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties.

scholarly journals Where can a place cell put its fields? Let us count the ways

2019 ◽  
Author(s):  
Man Yi Yim ◽  
Lorenzo A Sadun ◽  
Ila R Fiete ◽  
Thibaud Taillefumier
Keyword(s):  
Grid Cell ◽  
Place Cell ◽  
Place Cells ◽  
Small Range ◽  
Place Field ◽  
Structured Grid ◽  
Cell Scaffold ◽  
External Cues ◽  
Relative Robustness ◽  
Hippocampal Place Cell

AbstractA hippocampal place cell exhibits multiple firing fields within and across environments. What factors determine the configuration of these fields, and could they be set down in arbitrary locations? We conceptualize place cells as performing evidence combination across many inputs and selecting a threshold to fire. Thus, mathematically they are perceptrons, except that they act on geometrically organized inputs in the form of multiscale periodic grid-cell drive, and external cues. We analytically count which field arrangements a place cell can realize with structured grid inputs, to show that many more place-field arrangements are realizable with grid-like than one-hot coded inputs. However, the arrangements have a rigid structure, defining an underlying response scaffold. We show that the “separating capacity” or spatial range over which all potential field arrangements are realizable equals the rank of the grid-like input matrix, which in turn equals the sum of distinct grid periods, a small fraction of the unique grid-cell coding range. Learning different grid-to-place weights beyond this small range will alter previous arrangements, which could explain the volatility of the place code. However, compared to random inputs over the same range, grid-structured inputs generate larger margins, conferring relative robustness to place fields when grid input weights are fixed.Significance statementPlace cells encode cognitive maps of the world by combining external cues with an internal coordinate scaffold, but our ability to predict basic properties of the code, including where a place cell will exhibit fields without external cues (the scaffold), remains weak. Here we geometrically characterize the place cell scaffold, assuming it is derived from multiperiodic modular grid cell inputs, and provide exact combinatorial results on the space of permitted field arrangements. We show that the modular inputs permit a large number of place field arrangements, with robust fields, but also strongly constrain their geometry and thus predict a structured place scaffold.

scholarly journals Spatially dispersed synapses yield sharply-tuned place cell responses through dendritic spike initiation

2017 ◽  
Author(s):  
Reshma Basak ◽  
Rishikesh Narayanan
Keyword(s):  
Critical Role ◽  
Place Cell ◽  
Place Field ◽  
Apparent Contradiction ◽  
Cell Responses ◽  
Sharp Feature ◽  
Dendritic Spikes ◽  
Feature Selectivity ◽  
Contradictory Evidence ◽  
Strong Candidate

The literature offers evidence for a critical role of spatially-clustered iso-feature synapses in eliciting dendritic spikes essential for sharp feature selectivity, with apparently contradictory evidence demonstrating spatial dispersion of iso-feature synapses. Here, we reconcile this apparent contradiction by demonstrating that the generation of dendritic spikes, the emergence of an excitatory ramp in somatic voltage responses and sharp tuning of place-cell responses are all attainable even when iso-feature synapses are randomly dispersed across the dendritic arbor. We found this tuning sharpness to be critically reliant on dendritic sodium and transient potassium channels and on N-methyl-D-aspartate receptors. Importantly, we demonstrate that synaptic potentiation targeted to afferents from one specific place field is sufficient to effectuate place-field selectivity even when intrinsically disparate neurons received randomly dispersed afferents from multiple place-field locations. These conclusions proffer dispersed localization of iso-feature synapses as a strong candidate for achieving sharp feature selectivity in neurons across sensory-perceptual systems.

scholarly journals Medial entorhinal cortex lesions induce degradation of CA1 place cell firing stability when self-motion information is used

2020 ◽  
Vol 4 ◽  
pp. 239821282095300
Author(s):  
Pierre-Yves Jacob ◽  
Tiffany Van Cauter ◽  
Bruno Poucet ◽  
Francesca Sargolini ◽  
Etienne Save
Keyword(s):  
Entorhinal Cortex ◽  
Place Cell ◽  
Motion Information ◽  
Baseline Session ◽  
Place Field ◽  
Medial Entorhinal Cortex ◽  
Motion Cues ◽  
Place Fields ◽  
Cell Firing ◽  
Self Motion

The entorhinal–hippocampus network plays a central role in navigation and episodic memory formation. To investigate these interactions, we examined the effect of medial entorhinal cortex lesions on hippocampal place cell activity. Since the medial entorhinal cortex is suggested to play a role in the processing of self-motion information, we hypothesised that such processing would be necessary for maintaining stable place fields in the absence of environmental cues. Place cells were recorded as medial entorhinal cortex–lesioned rats explored a circular arena during five 16-min sessions comprising a baseline session with all sensory inputs available followed by four sessions during which environmental (i.e. visual, olfactory, tactile) cues were progressively reduced to the point that animals could rely exclusively on self-motion cues to maintain stable place fields. We found that place field stability and a number of place cell firing properties were affected by medial entorhinal cortex lesions in the baseline session. When rats were forced to rely exclusively on self-motion cues, within-session place field stability was dramatically decreased in medial entorhinal cortex rats relative to SHAM rats. These results support a major role of the medial entorhinal cortex in processing self-motion cues, with this information being conveyed to the hippocampus to help anchor and maintain a stable spatial representation during movement.

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