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 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 Experience-dependent trends in CA1 theta and slow gamma rhythms in freely behaving mice

2018 ◽  
Vol 119 (2) ◽  
pp. 476-489 ◽  
Author(s):  
Brian J. Gereke ◽  
Alexandra J. Mably ◽  
Laura Lee Colgin
Keyword(s):  
Spatial Information ◽  
Hippocampal Formation ◽  
Cell Activity ◽  
Place Cell ◽  
Place Cells ◽  
Running Speed ◽  
Circular Track ◽  
Gamma Rhythms ◽  
Over Time ◽  
First Session

CA1 place cells become more anticipatory with experience, an effect thought to be caused by NMDA receptor-dependent plasticity in the CA3–CA1 network. Theta (~5–12 Hz), slow gamma (~25–50 Hz), and fast gamma (~50–100 Hz) rhythms are thought to route spatial information in the hippocampal formation and to coordinate place cell ensembles. Yet, it is unknown whether these rhythms exhibit experience-dependent changes concurrent with those observed in place cells. Slow gamma rhythms are thought to indicate inputs from CA3 to CA1, and such inputs are thought to be strengthened with experience. Thus, we hypothesized that slow gamma rhythms would become more evident with experience. We tested this hypothesis using mice freely traversing a familiar circular track for three 10-min sessions per day. We found that slow gamma amplitude was reduced in the early minutes of the first session of each day, even though both theta and fast gamma amplitudes were elevated during this same period. However, in the first minutes of the second and third sessions of each day, all three rhythms were elevated. Interestingly, theta was elevated to a greater degree in the first minutes of the first session than in the first minutes of later sessions. Additionally, all three rhythms were strongly influenced by running speed in dynamic ways, with the influence of running speed on theta and slow gamma changing over time within and across sessions. These results raise the possibility that experience-dependent changes in hippocampal rhythms relate to changes in place cell activity that emerge with experience. NEW & NOTEWORTHY We show that CA1 theta, slow gamma, and fast gamma rhythms exhibit characteristic changes over time within sessions in familiar environments. These effects in familiar environments evolve across repeated sessions.

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 Asymmetry of the temporal code for space by hippocampal place cells

2016 ◽  
Author(s):  
Bryan C. Souza ◽  
Adriano B. L. Tort
Keyword(s):  
Firing Rate ◽  
Spatial Information ◽  
Place Cells ◽  
Spike Timing ◽  
Temporal Coding ◽  
Place Field ◽  
Phase Precession ◽  
Wide Debate ◽  
Rate Coding ◽  
Theta Phase

Hippocampal place cells convey spatial information through spike frequency (“rate coding”) and spike timing relative to the theta phase (“temporal coding”). Whether rate and temporal coding are due to independent or related mechanisms has been the subject of wide debate. Here we show that the spike timing of place cells couples to theta phase before major increases in firing rate, anticipating the animal’s entrance into the classical, rate-based place field. In contrast, spikes rapidly decouple from theta as the animal leaves the place field and firing rate decreases. Therefore, temporal coding has strong asymmetry around the place field center. We further show that the dynamics of temporal coding along space evolves in three stages: phase coupling, phase precession and phase decoupling. These results suggest that place cells represent more future than past locations through their spike timing and that independent mechanisms govern rate and temporal coding.

scholarly journals Changing reward expectation transforms spatial encoding and retrieval in the hippocampus

2020 ◽  
Author(s):  
Seetha Krishnan ◽  
Chery Cherian ◽  
Mark. E. J. Sheffield
Keyword(s):  
Spatial Memory ◽  
Spatial Information ◽  
Place Cell ◽  
Cellular Level ◽  
Place Cells ◽  
Cell Dynamics ◽  
Spatial Encoding ◽  
Internal States ◽  
Spatial Memories ◽  
Encoding And Retrieval

SummaryInternal states of reward expectation play a central role in influencing the strength of spatial memories. At the cellular level, spatial memories are represented through the firing dynamics of hippocampal place cells. However, it remains unclear how internal states of reward expectation influence place cell dynamics and exert their effects on spatial memories. Here we show that when reward expectation is altered, the same environment becomes encoded by a distinct ensemble of place cells at all locations. Further, when reward expectation is high versus low, place cells demonstrate enhanced reliability during navigation and greater stability across days at all locations within the environment. These findings reveal that when rewards are expected, neuromodulatory circuits that represent internal reward expectation support and strengthen the encoding and retrieval of spatial information by place cells at all locations that lead to reward. This enhanced spatial memory can be used to guide future decisions about which locations are most likely to lead to rewards that are crucial for survival.

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 Spatial information transfer in hippocampal place cells depends on trial-to-trial variability, symmetry of place-field firing and biophysical heterogeneities

2020 ◽  
Author(s):  
Ankit Roy ◽  
Rishikesh Narayanan
Keyword(s):  
Information Transfer ◽  
Spatial Information ◽  
Tuning Curve ◽  
Place Cells ◽  
Place Field ◽  
Tuning Curves ◽  
Spatial Tuning ◽  
Model Tuning ◽  
The Impact ◽  
The Relationship

ABSTRACTThe relationship between the feature-tuning curve and information transfer profile of individual neurons provides vital insights about neural encoding. However, the relationship between the spatial tuning curve and spatial information transfer of hippocampal place cells remains unexplored. Here, employing a stochastic search procedure spanning thousands of models, we arrived at 127 conductance-based place-cell models that exhibited signature electrophysiological characteristics and sharp spatial tuning, with parametric values that exhibited neither clustering nor strong pairwise correlations. We introduced trial-to-trial variability in responses and computed model tuning curves and information transfer profiles, using stimulus-specific (SSI) and mutual (MI) information metrics, across locations within the place field. We found spatial information transfer to be heterogeneous across models, but to reduce consistently with increasing degrees of variability. Importantly, whereas reliable low-variability responses implied that maximal information transfer occurred at high-slope regions of the tuning curve, increase in variability resulted in maximal transfer occurring at the peak-firing location in a subset of models. Moreover, experience-dependent asymmetry in place-field firing introduced asymmetries in the information transfer computed through MI, but not SSI, and the impact of activity-dependent variability on information transfer was minimal compared to activity-independent variability. Biophysically, we unveiled a many-to-one relationship between different ion channels and information transfer, and demonstrated critical roles for N-methyl-D-aspartate receptors, transient potassium and dendritic sodium channels in regulating information transfer. Our results emphasize the need to account for trial-to-trial variability, tuning-curve shape and biological heterogeneities while assessing information transfer, and demonstrate ion-channel degeneracy in the regulation of spatial information transfer.

scholarly journals Hippocampal spike-time correlations and place-field overlaps during open field foraging

2019 ◽  
Author(s):  
Mauro M. Monsalve-Mercado ◽  
Yasser Roudi
Keyword(s):  
Open Field ◽  
Spatial Information ◽  
Time Lag ◽  
Place Cells ◽  
Spike Time ◽  
Place Field ◽  
Phase Code ◽  
Place Fields ◽  
Cross Correlations ◽  
The Relationship

AbstractPhase precessing place cells encode spatial information on fine timescales via the timing of their spikes. This phase code has been extensively studied on linear tracks and for short runs in the open field. However, less is known about the phase code on unconstrained trajectories lasting tens of minutes, typical of open field foraging. In previous work (Monsalve-Mercado and Leibold, 2017), an analytic expression was derived for the spike-time cross-correlation between phase precessing place cells during natural foraging in the open field. This expression makes two predictions on how this phase code differs from the linear track case: cross-correlations are symmetric with respect to time, and they represent the distance between pairs of place fields in that the theta-filtered cross-correlations around zero time-lag are positive for cells with nearby fields while they are negative for those with fields further apart. Here we analyze several available open field recordings and show that these predictions hold for pairs of CA1 place cells. We also show that the relationship remains during remapping in CA1, and it is also present in place cells in area CA3. For CA1 place cells of Fmr1-null mice, which exhibit normal place fields but somewhat weaker temporal coordination with respect to theta compared to wild type, the cross-correlations still remain symmetric but the relationship to place field overlap is largely lost. The relationship discussed here describes how spatial information is communicated by place cells to downstream areas in a finer theta-timescale, relevant for learning and memory formation in behavioural tasks lasting tens of minutes in the open field.

scholarly journals On information metrics for spatial coding

2017 ◽  
Author(s):  
Bryan C. Souza ◽  
Rodrigo Pavão ◽  
Hindiael Belchior ◽  
Adriano B.L. Tort
Keyword(s):  
Mutual Information ◽  
Spatial Information ◽  
Hippocampal Formation ◽  
Standard Procedure ◽  
Real Data ◽  
Place Cells ◽  
Spatial Coding ◽  
Neuronal Populations ◽  
Information Metric ◽  
Information Metrics

AbstractThe hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon’s mutual information (Shannon, 1948), and convey information rate in bits/sec or bits/spike (Skaggs et al., 1993; Skaggs et al., 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice.

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