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 Position-theta-phase model of hippocampal place cell activity applied to quantification of running speed modulation of firing rate

2019 ◽  
Author(s):  
Kathryn McClain ◽  
David Tingley ◽  
David Heeger ◽  
György Buzsáki
Keyword(s):  
Firing Rate ◽  
Spatial Information ◽  
Cell Activity ◽  
Gain Control ◽  
Place Cell ◽  
Small Subset ◽  
Running Speed ◽  
Speed Modulation ◽  
Place Fields ◽  
Theta Phase

AbstractSpiking activity of place cells in the hippocampus encodes the animal’s position as it moves through an environment. Within a cell’s place field, both the firing rate and the phase of spiking in the local theta oscillation contain spatial information. We propose a position-theta-phase (PTP) model that captures the simultaneous expression of the firing-rate code and theta-phase code in place cell spiking. This model parametrically characterizes place fields to compare across cells, time and condition, generates realistic place cell simulation data, and conceptualizes a framework for principled hypothesis testing to identify additional features of place cell activity. We use the PTP model to assess the effect of running speed in place cell data recorded from rats running on linear tracks. For the majority of place fields we do not find evidence for speed modulation of the firing rate. For a small subset of place fields, we find firing rates significantly increase or decrease with speed. We use the PTP model to compare candidate mechanisms of speed modulation in significantly modulated fields, and determine that speed acts as a gain control on the magnitude of firing rate. Our model provides a tool that connects rigorous analysis with a computational framework for understanding place cell activity.SignificanceThe hippocampus is heavily studied in the context of spatial navigation, and the format of spatial information in hippocampus is multifaceted and complex. Furthermore, the hippocampus is also thought to contain information about other important aspects of behavior such as running speed, though there is not agreement on the nature and magnitude of their effect. To understand how all of these variables are simultaneously represented and used to guide behavior, a theoretical framework is needed that can be directly applied to the data we record. We present a model that captures well-established spatial-encoding features of hippocampal activity and provides the opportunity to identify and incorporate novel features for our collective understanding.

scholarly journals Position–theta-phase model of hippocampal place cell activity applied to quantification of running speed modulation of firing rate

2019 ◽  
Vol 116 (52) ◽  
pp. 27035-27042 ◽  
Author(s):  
Kathryn McClain ◽  
David Tingley ◽  
David J. Heeger ◽  
György Buzsáki
Keyword(s):  
Firing Rate ◽  
Spatial Information ◽  
Cell Activity ◽  
Gain Control ◽  
Place Cell ◽  
Small Subset ◽  
Running Speed ◽  
Speed Modulation ◽  
Place Fields ◽  
Theta Phase

Spiking activity of place cells in the hippocampus encodes the animal’s position as it moves through an environment. Within a cell’s place field, both the firing rate and the phase of spiking in the local theta oscillation contain spatial information. We propose a position–theta-phase (PTP) model that captures the simultaneous expression of the firing-rate code and theta-phase code in place cell spiking. This model parametrically characterizes place fields to compare across cells, time, and conditions; generates realistic place cell simulation data; and conceptualizes a framework for principled hypothesis testing to identify additional features of place cell activity. We use the PTP model to assess the effect of running speed in place cell data recorded from rats running on linear tracks. For the majority of place fields, we do not find evidence for speed modulation of the firing rate. For a small subset of place fields, we find firing rates significantly increase or decrease with speed. We use the PTP model to compare candidate mechanisms of speed modulation in significantly modulated fields and determine that speed acts as a gain control on the magnitude of firing rate. Our model provides a tool that connects rigorous analysis with a computational framework for understanding place cell activity.

scholarly journals Hippocampal place cells use vector computations to navigate

2021 ◽  
Author(s):  
Jake Ormond ◽  
John O'Keefe
Keyword(s):  
Spatial Representation ◽  
Vector Fields ◽  
Cell Activity ◽  
Choice Point ◽  
Place Cell ◽  
Place Cells ◽  
Population Vector ◽  
Goal Location ◽  
Optimal Paths ◽  
Independent Assessment

One function of the Hippocampal Cognitive Map is to provide information about salient locations in familiar environments such as those containing reward or danger, and to support navigation towards or away from those locations. Although much is known about how the hippocampus encodes location in world-centred coordinates, how it supports flexible navigation is less well understood. We recorded from CA1 place cells while rats navigated to a goal or freely foraged on the honeycomb maze. The maze tests the animal's ability to navigate using indirect as well as direct paths to the goal and allows the directionality of place cells to be assessed at each choice point during traversal to the goal. Place fields showed strong directional polarization in the navigation task, and to a lesser extent during random foraging. This polarization was characterized by vector fields which converged to sinks distributed throughout the environment. The distribution of these convergence sinks was centred near the goal location, and the population vector field converged on the goal, providing a strong navigational signal. Changing the goal location led to the movement of ConSinks and vector fields towards the new goal and within-days, the ConSink distance to the goal decreased with continued training. The honeycomb maze allows the independent assessment of spatial representation and spatial action in place cell activity and shows how the latter depends on the former. The results suggest a vector-based model of how the hippocampus supports flexible navigation, allowing animals to select optimal paths to destinations from any location in the environment.

scholarly journals Ripple Band Phase Precession of Place Cell Firing during Replay

2021 ◽  
Author(s):  
Daniel Bush ◽  
Freyja Olafsdottir ◽  
Caswell Barry ◽  
Neil Burgess
Keyword(s):  
Hippocampal Formation ◽  
Receptive Fields ◽  
Negative Relationship ◽  
Place Cell ◽  
Place Cells ◽  
Phase Coding ◽  
Equivalent Rate ◽  
Phase Precession ◽  
Cell Firing ◽  
Ripple Phase

Phase coding offers several theoretical advantages for information transmission compared to an equivalent rate code. Phase coding is shown by place cells in the rodent hippocampal formation, which fire at progressively earlier phases of the movement related 6-12Hz theta rhythm as their spatial receptive fields are traversed. Importantly, however, phase coding is independent of carrier frequency, and so we asked whether it might also be exhibited by place cells during 150-250Hz ripple band activity, when they are thought to replay information to neocortex. We demonstrate that place cells which fire multiple spikes during candidate replay events do so at progressively earlier ripple phases, and that spikes fired across all replay events exhibit a negative relationship between decoded location within the firing field and ripple phase. These results provide insights into the mechanisms underlying phase coding and place cell replay, as well as the neural code propagated to downstream neurons.

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 Representation of Objects in Space by Two Classes of Hippocampal Pyramidal Cells

2004 ◽  
Vol 124 (1) ◽  
pp. 9-25 ◽  
Author(s):  
Bruno Rivard ◽  
Yu Li ◽  
Pierre-Pascal Lenck-Santini ◽  
Bruno Poucet ◽  
Robert U. Muller
Keyword(s):  
Cell Activity ◽  
Pyramidal Cells ◽  
Place Cell ◽  
Place Cells ◽  
Rat Hippocampus ◽  
Ca1 Pyramidal Cells ◽  
New Class ◽  
Familiar Environment ◽  
Current Arrangement ◽  
Number Of Cells

Humans can recognize and navigate in a room when its contents have been rearranged. Rats also adapt rapidly to movements of objects in a familiar environment. We therefore set out to investigate the neural machinery that underlies this capacity by further investigating the place cell–based map of the surroundings found in the rat hippocampus. We recorded from single CA1 pyramidal cells as rats foraged for food in a cylindrical arena (the room) containing a tall barrier (the furniture). Our main finding is a new class of cells that signal proximity to the barrier. If the barrier is fixed in position, these cells appear to be ordinary place cells. When, however, the barrier is moved, their activity moves equally and thereby conveys information about the barrier's position relative to the arena. When the barrier is removed, such cells stop firing, further suggesting they represent the barrier. Finally, if the barrier is put into a different arena where place cell activity is changed beyond recognition (“remapping”), these cells continue to discharge at the barrier. We also saw, in addition to barrier cells and place cells, a small number of cells whose activity seemed to require the barrier to be in a specific place in the environment. We conclude that barrier cells represent the location of the barrier in an environment-specific, place cell framework. The combined place + barrier cell activity thus mimics the current arrangement of the environment in an unexpectedly realistic fashion.

scholarly journals Maintaining Consistency of Spatial Information in the Hippocampal Network: A Combinatorial Geometry Model

2016 ◽  
Vol 28 (6) ◽  
pp. 1051-1071 ◽  
Author(s):  
Y. Dabaghian
Keyword(s):  
Spatial Information ◽  
Synaptic Connection ◽  
Cell Activity ◽  
Internal Representation ◽  
Combinatorial Geometry ◽  
Place Cells ◽  
Geometry Model ◽  
Electrophysiological Recordings ◽  
Hippocampal Network ◽  
Proprioceptive Inputs

Place cells in the rat hippocampus play a key role in creating the animal’s internal representation of the world. During active navigation, these cells spike only in discrete locations, together encoding a map of the environment. Electrophysiological recordings have shown that the animal can revisit this map mentally during both sleep and awake states, reactivating the place cells that fired during its exploration in the same sequence in which they were originally activated. Although consistency of place cell activity during active navigation is arguably enforced by sensory and proprioceptive inputs, it remains unclear how a consistent representation of space can be maintained during spontaneous replay. We propose a model that can account for this phenomenon and suggest that a spatially consistent replay requires a number of constraints on the hippocampal network that affect its synaptic architecture and the statistics of synaptic connection strengths.

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 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 Neural dynamics indicate parallel integration of environmental and self-motion information by place and grid cells

2019 ◽  
Author(s):  
Dmitri Laptev ◽  
Neil Burgess
Keyword(s):  
Path Integration ◽  
Temporal Dynamics ◽  
Hippocampal Formation ◽  
Place Cell ◽  
Place Cells ◽  
Motion Information ◽  
Grid Cells ◽  
Attractor Network ◽  
Cell Firing ◽  
Self Motion

AbstractPlace cells and grid cells in the hippocampal formation are thought to integrate sensory and self-motion information into a representation of estimated spatial location, but the precise mechanism is unknown. We simulated a parallel attractor system in which place cells form an attractor network driven by environmental inputs and grid cells form an attractor network performing path integration driven by self-motion, with inter-connections between them allowing both types of input to influence firing in both ensembles. We show that such a system is needed to explain the spatial patterns and temporal dynamics of place cell firing when rats run on a linear track in which the familiar correspondence between environmental and self-motion inputs is changed (Gothard et al., 1996b; Redish et al., 2000). In contrast, the alternative architecture of a single recurrent network of place cells (performing path integration and receiving environmental inputs) cannot reproduce the place cell firing dynamics. These results support the hypothesis that grid and place cells provide two different but complementary attractor representations (based on self-motion and environmental sensory inputs respectively). Our results also indicate the specific neural mechanism and main predictors of hippocampal map realignment and make predictions for future studies.

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