scholarly journals Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Louis Kang ◽  
Michael R DeWeese
Keyword(s):  
Slow Wave Sleep ◽  
Cell Formation ◽  
Grid Cell ◽  
External Input ◽  
Inhibitory Interneurons ◽  
Grid Cells ◽  
Attractor Network ◽  
Theta Frequency ◽  
Phase Precession ◽  
Underlying Mechanisms

Grid cells fire in sequences that represent rapid trajectories in space. During locomotion, theta sequences encode sweeps in position starting slightly behind the animal and ending ahead of it. During quiescence and slow wave sleep, bouts of synchronized activity represent long trajectories called replays, which are well-established in place cells and have been recently reported in grid cells. Theta sequences and replay are hypothesized to facilitate many cognitive functions, but their underlying mechanisms are unknown. One mechanism proposed for grid cell formation is the continuous attractor network. We demonstrate that this established architecture naturally produces theta sequences and replay as distinct consequences of modulating external input. Driving inhibitory interneurons at the theta frequency causes attractor bumps to oscillate in speed and size, which gives rise to theta sequences and phase precession, respectively. Decreasing input drive to all neurons produces traveling wavefronts of activity that are decoded as replays.

scholarly journals Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network

2019 ◽  
Author(s):  
Louis Kang ◽  
Michael R. DeWeese
Keyword(s):  
Slow Wave Sleep ◽  
Cell Formation ◽  
Grid Cell ◽  
External Input ◽  
Inhibitory Interneurons ◽  
Grid Cells ◽  
Attractor Network ◽  
Theta Frequency ◽  
Phase Precession ◽  
Underlying Mechanisms

Grid cells fire in sequences that represent rapid trajectories in space. During locomotion, theta sequences encode sweeps in position starting slightly behind the animal and ending ahead of it. During quiescence and slow wave sleep, bouts of synchronized activity represent long trajectories called replays, which are well-established in place cells and have been recently reported in grid cells. Theta sequences and replay are hypothesized to facilitate many cognitive functions, but their underlying mechanisms are unknown. A leading mechanism proposed for grid cell formation is the continuous attractor network. We demonstrate that this established architecture naturally produces theta sequences and replay as distinct consequences of modulating external input. Driving inhibitory interneurons at the theta frequency causes attractor bumps to oscillate in speed and size, which gives rise to theta sequences and phase precession, respectively. Decreasing input drive to all neurons produces traveling wavefronts of activity that are decoded as replays.

scholarly journals Network mechanisms of grid cells

2014 ◽  
Vol 369 (1635) ◽  
pp. 20120511 ◽  
Author(s):  
Edvard I. Moser ◽  
May-Britt Moser ◽  
Yasser Roudi
Keyword(s):  
Functional Organization ◽  
Cell Formation ◽  
Grid Cell ◽  
Mammalian Brain ◽  
Grid Cells ◽  
Entire Space ◽  
Competitive Network ◽  
Sensory Cortices ◽  
Firing Properties ◽  
Organizing Principles

One of the major breakthroughs in neuroscience is the emerging understanding of how signals from the external environment are extracted and represented in the primary sensory cortices of the mammalian brain. The operational principles of the rest of the cortex, however, have essentially remained in the dark. The discovery of grid cells, and their functional organization, opens the door to some of the first insights into the workings of the association cortices, at a stage of neural processing where firing properties are shaped not primarily by the nature of incoming sensory signals but rather by internal self-organizing principles. Grid cells are place-modulated neurons whose firing locations define a periodic triangular array overlaid on the entire space available to a moving animal. The unclouded firing pattern of these cells is rare within the association cortices. In this paper, we shall review recent advances in our understanding of the mechanisms of grid-cell formation which suggest that the pattern originates by competitive network interactions, and we shall relate these ideas to new insights regarding the organization of grid cells into functionally segregated modules.

scholarly journals Grid cells show field-to-field variability and this explains the aperiodic response of inhibitory interneurons

2017 ◽  
Author(s):  
Benjamin Dunn ◽  
Daniel Wennberg ◽  
Ziwei Huang ◽  
Yasser Roudi
Keyword(s):  
Experimental Data ◽  
Firing Rate ◽  
Grid Cell ◽  
Network Models ◽  
Theoretical Models ◽  
Inhibitory Neurons ◽  
Inhibitory Interneurons ◽  
Grid Cells ◽  
External Stimuli ◽  
Individual Grid

AbstractResearch on network mechanisms and coding properties of grid cells assume that the firing rate of a grid cell in each of its fields is the same. Furthermore, proposed network models predict spatial regularities in the firing of inhibitory interneurons that are inconsistent with experimental data. In this paper, by analyzing the response of grid cells recorded from rats during free navigation, we first show that there are strong variations in the mean firing rate of the fields of individual grid cells and thus show that the data is inconsistent with the theoretical models that predict similar peak magnitudes. We then build a two population excitatory-inhibitory network model in which sparse spatially selective input to the excitatory cells, presumed to arise from e.g. salient external stimuli, hippocampus or a combination of both, leads to the variability in the firing field amplitudes of grid cells. We show that, when combined with appropriate connectivity between the excitatory and inhibitory neurons, the variability in the firing field amplitudes of grid cells results in inhibitory neurons that do not exhibit regular spatial firing, consistent with experimental data. Finally, we show that even if the spatial positions of the fields are maintained, variations in the firing rates of the fields of grid cells are enough to cause remapping of hippocampal cells.

Oscillator-Interference Models of Path Integration Do Not Require Theta Oscillations

2015 ◽  
Vol 27 (3) ◽  
pp. 548-560 ◽  
Author(s):  
Jeff Orchard
Keyword(s):  
Path Integration ◽  
Activity Patterns ◽  
Field Potential ◽  
Grid Cell ◽  
Place Cells ◽  
Theta Oscillations ◽  
Grid Cells ◽  
Neural Oscillators ◽  
Theta Frequency ◽  
Interference Models

Navigation and path integration in rodents seems to involve place cells, grid cells, and theta oscillations (4–12 Hz) in the local field potential. Two main theories have been proposed to explain the neurological underpinnings of how these phenomena relate to navigation and to each other. Attractor network (AN) models revolve around the idea that local excitation and long-range inhibition connectivity can spontaneously generate grid-cell-like activity patterns. Oscillator interference (OI) models propose that spatial patterns of activity are caused by the interference patterns between neural oscillators. In rats, these oscillators have a frequency close to the theta frequency. Recent studies have shown that bats do not exhibit a theta cycle when they crawl, and yet they still have grid cells. This has been interpreted as a criticism of OI models. However, OI models do not require theta oscillations. We explain why the absence of theta oscillations does not contradict OI models and discuss how the two families of models might be distinguished experimentally.

scholarly journals Bimodal Remapping of Visual Grids

2021 ◽  
Author(s):  
Xiaoyang Long ◽  
Jing Cai ◽  
Bin Deng ◽  
Zhe Sage Chen ◽  
Sheng-Jia Zhang
Keyword(s):  
Grid Cell ◽  
The Novel ◽  
Grid Cells ◽  
Medial Entorhinal Cortex ◽  
Cell Pattern ◽  
Field Patterns ◽  
Regular Class ◽  
Theta Frequency ◽  
Familiar Environment

Spatially modulated neurons from the rat secondary visual cortex (V2) show grid-like firing patterns during freely foraging in open-field enclosures. However, the remapping of the V2 grid cells is not well understood. Here we report two classes of V2 grid cell populations with distinct remapping properties: one regular class with invariant grid field patterns, and the other bimodal class that has remapping induced by environmental manipulations such as changes in enclosure shape, size, orientation and lighting in a familiar environment. The bimodal V2 grid cell pattern remains stable regardless of the follow-up manipulations, but restores to the original firing pattern upon animal's re-entry into the familiar environment on the next day or from the novel environment. The bimodal V2 grid cells are modulated with theta frequency during the course of remapping and stabilize quickly. We also found conjunctive bistable V2 grid cells with invariant head directional tuning. Overall, our results suggest a new grid cell mechanism in V2 that is different from the medial entorhinal cortex (MEC) grid cells.

scholarly journals Description and Analysis of a 20-Year (1960-79) Digital Ice-Concentration Database for the Great Lakes of North America

1983 ◽  
Vol 4 ◽  
pp. 14-18 ◽  
Author(s):  
Raymond A. Assel
Keyword(s):  
North America ◽  
Great Lakes ◽  
Surface Area ◽  
Information Service ◽  
Grid Cell ◽  
Ice Cover ◽  
Unit Surface Area ◽  
Grid Cells ◽  
Data Set ◽  
Ice Concentration

A digital ice-concentration database spanning 20 years (1960 to 1979) was established for the Great Lakes of North America. Data on ice concentration, i.e. the percentage of a unit surface area of the lake that is ice-covered, were abstracted from over 2 800 historic ice charts produced by United States and Canadian government agencies. The database consists of ice concentrations ranging from zero to 100% in 10% increments for individual grid cells of size 5 × 5 km constituting the surface area of each Great Lake. The data set for each of the Great Lakes was divided into half-month periods for statistical analysis. Maxinium, minimum, median, mode, and average ice-concentrations statistics were calculated for each grid cell and half-month period. A lakewide average value was then calculated for each of the half-month ice-concentration statistics for all grid cells for a given lake. Ice-cover variability and the normal extent and progression of the ice cover is discussed within the context of the lakewide averaged value of the minimum and maximum ice concentrations and the lakewide averaged value of the median ice concentrations, respectively. Differences in ice-cover variability among the five Great Lakes are related to mean lake depth and accumulated freezing degree-days. A Great Lakes ice atlas presenting a series of ice charts which depict the maximum, minimum, and median icecover concentrations for each of the Great Lakes for nine half-monthly periods, starting the last half of December and continuing through the last half of April will be published in 1983 by the National Oceanic and Atmospheric Administration (NOAA). The database will be archived at the National Snow and Ice Data Center of the National Environmental Satellite Data and Information Service (NESDIS) in Boulder, Colorado, USA, also in 1983.

scholarly journals A geometric attractor mechanism for self-organization of entorhinal grid modules

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Louis Kang ◽  
Vijay Balasubramanian
Keyword(s):  
Entorhinal Cortex ◽  
Network Models ◽  
Recurrent Inhibition ◽  
Modular Structure ◽  
Self Organization ◽  
Periodic Lattice ◽  
Grid Cells ◽  
Medial Entorhinal Cortex ◽  
Attractor Network ◽  
Discrete Values

Grid cells in the medial entorhinal cortex (MEC) respond when an animal occupies a periodic lattice of ‘grid fields’ in the environment. The grids are organized in modules with spatial periods, or scales, clustered around discrete values separated on average by ratios in the range 1.4–1.7. We propose a mechanism that produces this modular structure through dynamical self-organization in the MEC. In attractor network models of grid formation, the grid scale of a single module is set by the distance of recurrent inhibition between neurons. We show that the MEC forms a hierarchy of discrete modules if a smooth increase in inhibition distance along its dorso-ventral axis is accompanied by excitatory interactions along this axis. Moreover, constant scale ratios between successive modules arise through geometric relationships between triangular grids and have values that fall within the observed range. We discuss how interactions required by our model might be tested experimentally.

scholarly journals A new discrete multiplicative random cascade model for downscaling intermittent rainfall fields

2019 ◽  
Author(s):  
Marc Schleiss
Keyword(s):  
Classical Method ◽  
Mathematical Problem ◽  
Grid Cell ◽  
Cascade Model ◽  
Small Scale ◽  
Grid Cells ◽  
Cascade Generator ◽  
Cascade Models ◽  
First Results ◽  
Original Amount

Abstract. Spatial downscaling of rainfall fields is a challenging mathematical problem for which many different types of methods have been proposed. One popular solution consists in redistributing rainfall amounts over smaller and smaller scales by means of a discrete multiplicative random cascade (DMRC). This works well for slowly varying, homogeneous rainfall fields but often fails in the presence of intermittency (i.e., large amounts of zero rainfall values). The most common workaround in this case is to use two separate cascade models, one for the occurrence and another for the intensity. In this paper, a new and simpler approach based on the notion of equal-volume areas (EVAs) is proposed. Unlike classical cascades where rainfall amounts are redistributed over grid cells of equal size, the EVA cascade splits grid cells into areas of different sizes, each of them containing exactly half of the original amount of water. The relative areas of the sub-grid cells are determined by drawing random values from a logit-normal cascade generator model with scale and intensity dependent standard deviation. The process ends when the amount of water in each sub-grid cell is smaller than a fixed bucket capacity, at which point the output of the cascade can be re-sampled over a regular Cartesian mesh. The present paper describes the implementation of the EVA cascade model and gives some first results for 100 selected events in the Netherlands. Performance is assessed by comparing the outputs of the EVA model to bilinear interpolation and to a classical DMRC model based on fixed grid cell sizes. Results show that on average, the EVA cascade outperforms the classical method, producing fields with more realistic distributions, small-scale extremes and spatial structures. Improvements are mostly credited to the higher robustness of the EVA model to the presence of intermittency and to the lower variance of its generator. However, improvements are not systematic and both approaches have their advantages and weaknesses. For example, while the classical cascade tends to overestimate small-scale extremes and variability, the EVA model tends to produce fields that are slightly too smooth and blocky compared with observations.

scholarly journals Exposure to relaxing words during sleep promotes slow-wave sleep and subjective sleep quality

2020 ◽  
Author(s):  
Jonas Beck ◽  
Erna Loretz ◽  
Björn Rasch
Keyword(s):  
Sleep Quality ◽  
Slow Wave ◽  
Slow Wave Sleep ◽  
Well Being ◽  
Subjective Sleep Quality ◽  
Sleep Depth ◽  
Activity Band ◽  
Underlying Mechanisms ◽  
Healthy Participants ◽  
Subjective Level

AbstractOur thoughts alter our sleep, but the underlying mechanisms are still unknown. We propose that mental processes are active to a greater or lesser extent during sleep and that this degree of activation affects our sleep depth. We examined this notion by activating the concept of “relaxation” during sleep using relaxation-related words in 50 healthy participants. In support of our hypothesis, playing relaxing words during non-rapid eye movement sleep extended the time spent in slow-wave sleep, increased power in the slow-wave activity band after the word cue, and abolished an asymmetrical sleep depth during the word presentation period. On the subjective level, participants reported a higher sleep quality and elevated alertness ratings. Our results support the notion that the activation of mental concepts during sleep can influence sleep depth and provide a basis for interventions using targeted activations to promote sleep depth and sleep quality to foster well-being and health.

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