Hippocampal Spike-Timing Correlations Lead to Hexagonal Grid Fields

Mapping Intimacies ◽

10.1101/153379 ◽

2017 ◽

Author(s):

Mauro M Monsalve-Mercado ◽

Christian Leibold

Keyword(s):

Synaptic Plasticity ◽

Pattern Formation ◽

Entorhinal Cortex ◽

Turing Instability ◽

Place Cells ◽

Spike Timing ◽

Mammalian Brain ◽

Inhibition Mechanism ◽

Temporal Code ◽

Medial Entorhinal Cortex

Space is represented in the mammalian brain by the activity of hippocampal place cells as well as in their spike-timing correlations. Here we propose a theory how this temporal code is transformed to spatial firing rate patterns via spike-timing-dependent synaptic plasticity. The resulting dynamics of synaptic weights resembles well-known pattern formation models in which a lateral inhibition mechanism gives rise to a Turing instability. We identify parameter regimes in which hexagonal firing patterns develop as they have been found in medial entorhinal cortex.

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Redundancy in synaptic connections enables neurons to learn optimally

10.1101/127407 ◽

2017 ◽

Author(s):

Naoki Hiratani ◽

Tomoki Fukai

Keyword(s):

Synaptic Plasticity ◽

Particle Filtering ◽

Neuron Model ◽

Experimental Studies ◽

Dendritic Tree ◽

Spike Timing ◽

Mammalian Brain ◽

Synaptic Connections ◽

Synaptic Organization ◽

Functional Benefit

AbstractRecent experimental studies suggest that, in cortical microcircuits of the mammalian brain, the majority of neuron-to-neuron connections are realized by multiple synapses. However, it is not known whether such redundant synaptic connections provide any functional benefit. Here, we show that redundant synaptic connections enable near-optimal learning in cooperation with synaptic rewiring. By constructing a simple dendritic neuron model, we demonstrate that with multisynaptic connections, synaptic plasticity approximates a sample-based Bayesian filtering algorithm known as particle filtering, and wiring plasticity implements its resampling process. Applying the proposed framework to a detailed single neuron model, we show that the model accounts for many experimental observations, including the dendritic position dependence of spike-timing-dependent plasticity, and the functional synaptic organization on the dendritic tree based on the stimulus selectivity of presynaptic neurons. Our study provides a novel conceptual framework for synaptic plasticity and rewiring.

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A theory of joint attractor dynamics in the hippocampus and the entorhinal cortex accounts for artificial remapping and grid cell field-to-field variability

eLife ◽

10.7554/elife.56894 ◽

2020 ◽

Vol 9 ◽

Author(s):

Haggai Agmon ◽

Yoram Burak

Keyword(s):

Entorhinal Cortex ◽

Activity Patterns ◽

Grid Cell ◽

Mechanistic Explanation ◽

Place Cells ◽

Mammalian Brain ◽

Dimensional Manifold ◽

Grid Cells ◽

Attractor Dynamics ◽

Low Dimensional

The representation of position in the mammalian brain is distributed across multiple neural populations. Grid cell modules in the medial entorhinal cortex (MEC) express activity patterns that span a low-dimensional manifold which remains stable across different environments. In contrast, the activity patterns of hippocampal place cells span distinct low-dimensional manifolds in different environments. It is unknown how these multiple representations of position are coordinated. Here, we develop a theory of joint attractor dynamics in the hippocampus and the MEC. We show that the system exhibits a coordinated, joint representation of position across multiple environments, consistent with global remapping in place cells and grid cells. In addition, our model accounts for recent experimental observations that lack a mechanistic explanation: variability in the firing rate of single grid cells across firing fields, and artificial remapping of place cells under depolarization, but not under hyperpolarization, of layer II stellate cells of the MEC.

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Expression of human Tau40 in the medial entorhinal cortex impairs synaptic plasticity and associated cognitive functions in mice

Biochemical and Biophysical Research Communications ◽

10.1016/j.bbrc.2017.04.153 ◽

2018 ◽

Vol 496 (3) ◽

pp. 1006-1012 ◽

Cited By ~ 1

Author(s):

Yuxue Chen ◽

Lu Liu ◽

Mengzhu Li ◽

Ensheng Yao ◽

Jiahuan Hao ◽

...

Keyword(s):

Synaptic Plasticity ◽

Entorhinal Cortex ◽

Cognitive Functions ◽

Medial Entorhinal Cortex

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Faculty Opinions recommendation of Medial entorhinal cortex lesions only partially disrupt hippocampal place cells and hippocampus-dependent place memory.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725253480.793503570 ◽

2015 ◽

Author(s):

Karl-Peter Giese

Keyword(s):

Entorhinal Cortex ◽

Place Cells ◽

Medial Entorhinal Cortex ◽

Place Memory

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Field repetition and local mapping in the hippocampus and the medial entorhinal cortex

Journal of Neurophysiology ◽

10.1152/jn.00933.2016 ◽

2017 ◽

Vol 118 (4) ◽

pp. 2378-2388 ◽

Cited By ~ 8

Author(s):

Roddy M. Grieves ◽

Éléonore Duvelle ◽

Emma R. Wood ◽

Paul A. Dudchenko

Keyword(s):

Entorhinal Cortex ◽

Local Area ◽

Place Cells ◽

Grid Cells ◽

Medial Entorhinal Cortex ◽

Pattern Completion ◽

Global Space ◽

Local Environments ◽

Neural Substrate ◽

The Relationship

Hippocampal place cells support spatial cognition and are thought to form the neural substrate of a global “cognitive map.” A widely held view is that parts of the hippocampus also underlie the ability to separate patterns or to provide different neural codes for distinct environments. However, a number of studies have shown that in environments composed of multiple, repeating compartments, place cells and other spatially modulated neurons show the same activity in each local area. This repetition of firing fields may reflect pattern completion and may make it difficult for animals to distinguish similar local environments. In this review we 1) highlight some of the navigation difficulties encountered by humans in repetitive environments, 2) summarize literature demonstrating that place and grid cells represent local and not global space, and 3) attempt to explain the origin of these phenomena. We argue that the repetition of firing fields can be a useful tool for understanding the relationship between grid cells in the entorhinal cortex and place cells in the hippocampus, the spatial inputs shared by these cells, and the propagation of spatially related signals through these structures.

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Medial Entorhinal Cortex Lesions Only Partially Disrupt Hippocampal Place Cells and Hippocampus-Dependent Place Memory

Cell Reports ◽

10.1016/j.celrep.2014.10.009 ◽

2014 ◽

Vol 9 (3) ◽

pp. 893-901 ◽

Cited By ~ 100

Author(s):

Jena B. Hales ◽

Magdalene I. Schlesiger ◽

Jill K. Leutgeb ◽

Larry R. Squire ◽

Stefan Leutgeb ◽

...

Keyword(s):

Entorhinal Cortex ◽

Place Cells ◽

Medial Entorhinal Cortex ◽

Place Memory

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A MODEL OF GRID CELLS BASED ON A TWISTED TORUS TOPOLOGY

International Journal of Neural Systems ◽

10.1142/s0129065707001093 ◽

2007 ◽

Vol 17 (04) ◽

pp. 231-240 ◽

Cited By ~ 99

Author(s):

ALEXIS GUANELLA ◽

DANIEL KIPER ◽

PAUL VERSCHURE

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Entorhinal Cortex ◽

Firing Frequency ◽

Place Cells ◽

Grid Cells ◽

Medial Entorhinal Cortex ◽

Triangular Grids ◽

Multiple Regions ◽

Robust To Noise

The grid cells of the rat medial entorhinal cortex (MEC) show an increased firing frequency when the position of the animal correlates with multiple regions of the environment that are arranged in regular triangular grids. Here, we describe an artificial neural network based on a twisted torus topology, which allows for the generation of regular triangular grids. The association of the activity of pre-defined hippocampal place cells with entorhinal grid cells allows for a highly robust-to-noise calibration mechanism, suggesting a role for the hippocampal back-projections to the entorhinal cortex.

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Object and object-memory representations across the proximodistal axis of CA1

10.1101/2020.06.19.160911 ◽

2020 ◽

Author(s):

Brianna Vandrey ◽

James A. Ainge

Keyword(s):

Episodic Memory ◽

Entorhinal Cortex ◽

Place Cells ◽

Spatial Representations ◽

Place Field ◽

Medial Entorhinal Cortex ◽

Object Memory ◽

Place Memory ◽

Object Locations ◽

Memory Representations

AbstractEpisodic memory requires information about objects to be integrated into a spatial framework. Place cells in the hippocampus encode spatial representations of objects that could be generated through signalling from the entorhinal cortex. Projections from lateral and medial entorhinal cortex to the hippocampus terminate in distal and proximal CA1, respectively. We recorded place cells in distal and proximal CA1 as rats explored an environment that contained objects. Place cells in distal CA1 demonstrated higher measures of spatial tuning and expressed place fields closer to objects. Further, remapping to object displacement was modulated by place field proximity to objects in distal, but not proximal CA1. Finally, representations of previous object locations were more precise in distal CA1. Our data suggest that lateral entorhinal cortex inputs to the hippocampus support spatial representations that are more precise and responsive to objects in cue-rich environments. This is consistent with functional segregation in the entorhinal-hippocampal circuits underlying object-place memory.

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Redundancy in synaptic connections enables neurons to learn optimally

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1803274115 ◽

2018 ◽

Vol 115 (29) ◽

pp. E6871-E6879 ◽

Cited By ~ 8

Author(s):

Naoki Hiratani ◽

Tomoki Fukai

Keyword(s):

Synaptic Plasticity ◽

Particle Filtering ◽

Neuron Model ◽

Experimental Studies ◽

Dendritic Tree ◽

Spike Timing ◽

Mammalian Brain ◽

Synaptic Connections ◽

Synaptic Organization ◽

Functional Benefit

Recent experimental studies suggest that, in cortical microcircuits of the mammalian brain, the majority of neuron-to-neuron connections are realized by multiple synapses. However, it is not known whether such redundant synaptic connections provide any functional benefit. Here, we show that redundant synaptic connections enable near-optimal learning in cooperation with synaptic rewiring. By constructing a simple dendritic neuron model, we demonstrate that with multisynaptic connections synaptic plasticity approximates a sample-based Bayesian filtering algorithm known as particle filtering, and wiring plasticity implements its resampling process. Extending the proposed framework to a detailed single-neuron model of perceptual learning in the primary visual cortex, we show that the model accounts for many experimental observations. In particular, the proposed model reproduces the dendritic position dependence of spike-timing-dependent plasticity and the functional synaptic organization on the dendritic tree based on the stimulus selectivity of presynaptic neurons. Our study provides a conceptual framework for synaptic plasticity and rewiring.

Download Full-text