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 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 Scopolamine Impairs Spatial Information Recorded With “Miniscope” Calcium Imaging in Hippocampal Place Cells

2021 ◽  
Vol 15 ◽  
Author(s):  
Dechuan Sun ◽  
Ranjith Rajasekharan Unnithan ◽  
Chris French
Keyword(s):  
Spatial Memory ◽  
Calcium Imaging ◽  
Memory Retrieval ◽  
Spatial Information ◽  
Place Cells ◽  
Network Activity ◽  
Memory Encoding ◽  
Neural Firing ◽  
Neural Ensemble ◽  
Hippocampal Network

The hippocampus and associated cholinergic inputs have important roles in spatial memory in rodents. Muscarinic acetylcholine receptors (mAChRs) are involved in the communication of cholinergic signals and regulate spatial memory. They have been found to impact the memory encoding process, but the effect on memory retrieval is controversial. Previous studies report that scopolamine (a non-selective antagonist of mAChR) induces cognitive deficits on animals, resulting in impaired memory encoding, but the effect on memory retrieval is less certain. We tested the effects of blocking mAChRs on hippocampal network activity and neural ensembles that had previously encoded spatial information. The activity of hundreds of neurons in mouse hippocampal CA1 was recorded using calcium imaging with a miniaturised fluorescent microscope and properties of place cells and neuronal ensemble behaviour in a linear track environment were observed. We found that the decoding accuracy and the stability of spatial representation revealed by hippocampal neural ensemble were significantly reduced after the administration of scopolamine. Several other parameters, including neural firing rate, total number of active neurons, place cell number and spatial information content were affected. Similar results were also observed in a simulated hippocampal network model. This study enhances the understanding of the function of mAChRs on spatial memory impairment.

scholarly journals Distinct hippocampal network states support theta phase precession and theta sequences in CA1

2021 ◽  
Author(s):  
Matteo Guardamagna ◽  
Federico Stella ◽  
Francesco P. Battaglia
Keyword(s):  
Spatial Information ◽  
Place Cells ◽  
Temporal Coding ◽  
Temporal Code ◽  
Network State ◽  
Phase Precession ◽  
Hippocampal Network ◽  
Theta Phase ◽  
Network States ◽  
Theta Phase Precession

The hippocampus likely uses temporal coding to represent complex memories via mechanisms such as theta phase precession and theta sequences. Theta sequences are rapid sweeps of spikes from multiple place cells, encoding past or planned trajectories or non-spatial information. Phase precession, the correlation between a place cell's theta firing phase and animal position has been suggested to facilitate sequence emergence. We find that CA1 phase precession varies strongly across cells and environmental contingencies. Phase precession depends on the CA1 network state, and is only present when the medium gamma oscillation (60-90 Hz, linked to Entorhinal inputs) dominates. Conversely, theta sequences are most evident for non-precessing cells or with leading slow gamma (20-45 Hz, linked to CA3 inputs). These results challenge the view that phase precession is the mechanism underlying the emergence of theta sequences and point at a 'dual network states' model for hippocampal temporal code, potentially supporting merging of memory and exogenous information in CA1.

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 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 Efficient neural decoding of self-location with a deep recurrent network

2018 ◽  
Author(s):  
Ardi Tampuu ◽  
Tambet Matiisen ◽  
H. Freyja Ólafsdóttir ◽  
Caswell Barry ◽  
Raul Vicente
Keyword(s):  
Hippocampal Neurons ◽  
Cell Activity ◽  
Recurrent Network ◽  
Brain Network ◽  
Place Cells ◽  
Neuronal Firing ◽  
Temporal Context ◽  
Central Component ◽  
Neural Decoding ◽  
Freely Moving

AbstractPlace cells in the mammalian hippocampus signal self-location with sparse spatially stable firing fields. Based on observation of place cell activity it is possible to accurately decode an animal’s location. The precision of this decoding sets a lower bound for the amount of information that the hippocampal population conveys about the location of the animal. In this work we use a novel recurrent neural network (RNN) decoder to infer the location of freely moving rats from single unit hippocampal recordings. RNNs are biologically plausible models of neural circuits that learn to incorporate relevant temporal context without the need to make complicated assumptions about the use of prior information to predict the current state. When decoding animal position from spike counts in 1D and 2D-environments, we show that the RNN consistently outperforms a standard Bayesian model with flat priors. In addition, we also conducted a set of sensitivity analysis on the RNN decoder to determine which neurons and sections of firing fields were the most influential. We found that the application of RNNs to neural data allowed flexible integration of temporal context, yielding improved accuracy relative to a commonly used Bayesian approach and opens new avenues for exploration of the neural code.Author summaryBeing able to accurately self-localize is critical for most motile organisms. In mammals, place cells in the hippocampus appear to be a central component of the brain network responsible for this ability. In this work we recorded the activity of a population of hippocampal neurons from freely moving rodents and carried out neural decoding to determine the animals’ locations. We found that a machine learning approach using recurrent neural networks (RNNs) allowed us to predict the rodents’ true positions more accurately than a standard Bayesian method with flat priors. The RNNs are able to take into account past neural activity without making assumptions about the statistics of neuronal firing. Further, by analyzing the representations learned by the network we were able to determine which neurons, and which aspects of their activity, contributed most strongly to the accurate decoding.

scholarly journals Influence of the Instructions on the Performance and Establishment of Memorization Strategies in Space Judgments

2006 ◽  
Vol 9 (2) ◽  
pp. 312-320 ◽  
Author(s):  
Alessandra Ackel Rodrigues ◽  
Susi Lippi Marques
Keyword(s):  
Graduate Students ◽  
Power Function ◽  
Mental Representation ◽  
Spatial Information ◽  
Internal Representation ◽  
Space Perception ◽  
Physical Space ◽  
Visual Space ◽  
Experimental Conditions ◽  
Experimental Configuration

Studies of visual space perception have been assuming that people have an internal representation of the physical space that surrounds them. A variety of psychophysical procedures has been used in an attempt to measure the properties of visual space. The goal of the present study was to evaluate the accuracy of the mental representation and the strategies adopted to acquire and retain visuo-spatial information of a configuration as a function of two types of instructions. Thirty-eight undergraduate and graduate students participated in the study and were distributed in perceptive and mnemonic experimental conditions. The effect of the instructions (intentional and incidental) on the representation of the distances among the objects of the scene was estimated using exponents of power function, based on the reproduction of the distances among the stimuli of the scene. The results revealed that judgments made under intentional instructions were more frequently based on strategies related to the location of the stimuli, whereas judgments originating from incidental instructions were based on strategies related to the name of the stimuli. It was observed that the intentional instruction facilitated a more accurate mental representation of the observed experimental configuration, enhancing participants' performance.

scholarly journals Persistent trajectory-modulated hippocampal neurons support memory-guided navigation

2019 ◽  
Author(s):  
Nathaniel R. Kinsky ◽  
William Mau ◽  
David W. Sullivan ◽  
Samuel J. Levy ◽  
Evan A. Ruesch ◽  
...  
Keyword(s):  
Calcium Imaging ◽  
Hippocampal Neurons ◽  
Spatial Information ◽  
Single Photon ◽  
Place Cells ◽  
Dependent Activity ◽  
Freely Moving ◽  
Stable Trajectory ◽  
Alternation Task

ABSTRACTTrajectory-dependent splitter neurons in the hippocampus encode information about a rodent’s prior trajectory during performance of a continuous alternation task. As such, they provide valuable information for supporting memory-guided behavior. Here, we employed single-photon calcium imaging in freely moving mice to investigate the emergence and fate of trajectory-dependent activity through learning and mastery of a continuous spatial alternation task. We found that the quality of trajectory-dependent information in hippocampal neurons correlated with task performance. We thus hypothesized that, due to their utility, splitter neurons would exhibit heightened stability. We found that splitter neurons were more likely to remain active and retained more consistent spatial information across multiple days than did place cells. Furthermore, we found that both splitter neurons and place cells emerged rapidly and maintained stable trajectory-dependent/spatial activity thereafter. Our results suggest that neurons with useful functional coding properties exhibit heightened stability to support memory guided behavior.

scholarly journals Place cells in head-fixed mice navigating a floating real-world environment

2020 ◽  
Author(s):  
Mary Ann Go ◽  
Jake Rogers ◽  
Giuseppe P. Gava ◽  
Catherine Davey ◽  
Seigfred Prado ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Real World ◽  
Spatial Information ◽  
Memory Function ◽  
Place Cells ◽  
Neural Population ◽  
Spatial Coding ◽  
Place Fields ◽  
Freely Moving ◽  
World Environment

ABSTRACTThe hippocampal place cell system in rodents has provided a major paradigm for the scientific investigation of memory function and dysfunction. Place cells have been observed in area CA1 of the hippocampus of both freely moving animals, and of head-fixed animals navigating in virtual reality environments. However, spatial coding in virtual reality preparations has been observed to be impaired. Here we show that the use of a real-world environment system for head-fixed mice, consisting of a track floating on air, provides some advantages over virtual reality systems for the study of spatial memory. We imaged the hippocampus of head-fixed mice injected with the genetically encoded calcium indicator GCaMP6s while they navigated circularly constrained or open environments on the floating platform. We observed consistent place tuning in a substantial fraction of cells with place fields remapping when animals entered a different environment. When animals re-entered the same environment, place fields typically remapped over a time period of multiple days, faster than in freely moving preparations, but comparable with virtual reality. Spatial information rates were within the range observed in freely moving mice. Manifold analysis indicated that spatial information could be extracted from a low-dimensional subspace of the neural population dynamics. This is the first demonstration of place cells in head-fixed mice navigating on an air-lifted real-world platform, validating its use for the study of brain circuits involved in memory and affected by neurodegenerative disorders.

Sign in / Sign up

Export Citation Format

Share Document