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

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

10.1101/2020.09.17.301747 ◽

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.

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Asymmetry of the temporal code for space by hippocampal place cells

10.1101/060590 ◽

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.

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

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008835 ◽

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.

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Combined administration of levetiracetam and valproic acid attenuates age-related hyperactivity of CA3 place cells, reduces place field area, and increases spatial information content in aged rat hippocampus

Hippocampus ◽

10.1002/hipo.22474 ◽

2015 ◽

Vol 25 (12) ◽

pp. 1541-1555 ◽

Cited By ~ 21

Author(s):

Jonathan Robitsek ◽

Marcia H. Ratner ◽

Tara Stewart ◽

Howard Eichenbaum ◽

David H. Farb

Keyword(s):

Valproic Acid ◽

Information Content ◽

Spatial Information ◽

Place Cells ◽

Rat Hippocampus ◽

Place Field ◽

Aged Rat ◽

Age Related ◽

Combined Administration ◽

Field Area

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

10.1101/801209 ◽

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.

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A Robust Lane Detection Model Using Vertical Spatial Features and Contextual Driving Information

Sensors ◽

10.3390/s21030708 ◽

2021 ◽

Vol 21 (3) ◽

pp. 708

Author(s):

Wenbo Liu ◽

Fei Yan ◽

Jiyong Zhang ◽

Tao Deng

Keyword(s):

Information Exchange ◽

Information Transfer ◽

Spatial Information ◽

Contextual Information ◽

Great Influence ◽

Light Condition ◽

Lane Detection ◽

Detection Model ◽

Spatial Features ◽

Proposed Model

The quality of detected lane lines has a great influence on the driving decisions of unmanned vehicles. However, during the process of unmanned vehicle driving, the changes in the driving scene cause much trouble for lane detection algorithms. The unclear and occluded lane lines cannot be clearly detected by most existing lane detection models in many complex driving scenes, such as crowded scene, poor light condition, etc. In view of this, we propose a robust lane detection model using vertical spatial features and contextual driving information in complex driving scenes. The more effective use of contextual information and vertical spatial features enables the proposed model more robust detect unclear and occluded lane lines by two designed blocks: feature merging block and information exchange block. The feature merging block can provide increased contextual information to pass to the subsequent network, which enables the network to learn more feature details to help detect unclear lane lines. The information exchange block is a novel block that combines the advantages of spatial convolution and dilated convolution to enhance the process of information transfer between pixels. The addition of spatial information allows the network to better detect occluded lane lines. Experimental results show that our proposed model can detect lane lines more robustly and precisely than state-of-the-art models in a variety of complex driving scenarios.

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Place Cells in the Claustrum Remap Under NMDA Receptor Control

10.1101/2021.04.21.440764 ◽

2021 ◽

Author(s):

Emanuela Rizello ◽

Sean Martin ◽

Jennifer Rouine ◽

Charlotte Callaghan ◽

Shane O'Mara

Keyword(s):

Nmda Receptor ◽

Place Cells ◽

Receptor Activity ◽

Oscillatory Activity ◽

Neuronal Responses ◽

Place Field ◽

Visual Inputs ◽

Delta Band ◽

Cortical Inputs ◽

Visual Cortical

Place cells are cells exhibiting location-dependent responses; they have mostly been studied in the hippocampus. Place cells have also been reported in the rat claustrum, an underexplored paracortical region with extensive corto-cortical connectivity. It has been hypothesised that claustral neuronal responses are anchored to cortical visual inputs. We show rat claustral place cells remap when visual inputs are eliminated from the environment and that this remapping is NMDA-receptor-dependent. Eliminating visual input enhances delta-band oscillatory activity in the claustrum, without affecting simultaneously-recorded visual cortical activity. We conclude that, like the hippocampus, claustral place field remapping might be mediated by NMDA receptor activity, and is modulated by visual cortical inputs.

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