Medial entorhinal cortex lesions induce degradation of CA1 place cell firing stability when self-motion information is used

The entorhinal–hippocampus network plays a central role in navigation and episodic memory formation. To investigate these interactions, we examined the effect of medial entorhinal cortex lesions on hippocampal place cell activity. Since the medial entorhinal cortex is suggested to play a role in the processing of self-motion information, we hypothesised that such processing would be necessary for maintaining stable place fields in the absence of environmental cues. Place cells were recorded as medial entorhinal cortex–lesioned rats explored a circular arena during five 16-min sessions comprising a baseline session with all sensory inputs available followed by four sessions during which environmental (i.e. visual, olfactory, tactile) cues were progressively reduced to the point that animals could rely exclusively on self-motion cues to maintain stable place fields. We found that place field stability and a number of place cell firing properties were affected by medial entorhinal cortex lesions in the baseline session. When rats were forced to rely exclusively on self-motion cues, within-session place field stability was dramatically decreased in medial entorhinal cortex rats relative to SHAM rats. These results support a major role of the medial entorhinal cortex in processing self-motion cues, with this information being conveyed to the hippocampus to help anchor and maintain a stable spatial representation during movement.

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Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local–global reference frames

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2013.0369 ◽

2014 ◽

Vol 369 (1635) ◽

pp. 20130369 ◽

Cited By ~ 187

Author(s):

James J. Knierim ◽

Joshua P. Neunuebel ◽

Sachin S. Deshmukh

Keyword(s):

Entorhinal Cortex ◽

Path Integration ◽

Sensory Input ◽

Reference Frames ◽

External Input ◽

Frame Of Reference ◽

Medial Entorhinal Cortex ◽

Motion Cues ◽

Cortical Input ◽

Self Motion

The hippocampus receives its major cortical input from the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). It is commonly believed that the MEC provides spatial input to the hippocampus, whereas the LEC provides non-spatial input. We review new data which suggest that this simple dichotomy between ‘where’ versus ‘what’ needs revision. We propose a refinement of this model, which is more complex than the simple spatial–non-spatial dichotomy. MEC is proposed to be involved in path integration computations based on a global frame of reference, primarily using internally generated, self-motion cues and external input about environmental boundaries and scenes; it provides the hippocampus with a coordinate system that underlies the spatial context of an experience. LEC is proposed to process information about individual items and locations based on a local frame of reference, primarily using external sensory input; it provides the hippocampus with information about the content of an experience.

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

10.1101/640144 ◽

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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Computing distance information from landmarks and self-motion cues - Differential contributions of anterior-lateral vs. posterior-medial entorhinal cortex in humans

NeuroImage ◽

10.1016/j.neuroimage.2019.116074 ◽

2019 ◽

Vol 202 ◽

pp. 116074 ◽

Cited By ~ 1

Author(s):

Xiaoli Chen ◽

Paula Vieweg ◽

Thomas Wolbers

Keyword(s):

Entorhinal Cortex ◽

Medial Entorhinal Cortex ◽

Distance Information ◽

Motion Cues ◽

Self Motion

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Interplay between somatic and dendritic inhibition promotes the emergence and stabilization of place fields

10.1101/483875 ◽

2018 ◽

Author(s):

Victor Pedrosa ◽

Claudia Clopath

Keyword(s):

Firing Rate ◽

Place Cell ◽

Place Cells ◽

Place Field ◽

Ca1 Neurons ◽

Hippocampal Ca1 ◽

Place Fields ◽

Cell Stability ◽

Cell Firing ◽

Novel Environments

AbstractDuring exploration of novel environments, place fields are rapidly formed in hippocampal CA1 neurons. Place cell firing rate increases in early stages of exploration of novel environments but returns to baseline levels in familiar environments. However, although similar in amplitude and width, place fields in familiar environments are more stable than in novel environments. We propose a computational model of the hippocampal CA1 network, which describes the formation, the dynamics and the stabilization of place fields. We show that although somatic disinhibition is sufficient to form place cells, dendritic inhibition along with synaptic plasticity is necessary for stabilization. Our model suggests that place cell stability is due to large excitatory synaptic weights and large dendritic inhibition. We show that the interplay between somatic and dendritic inhibition balances the increased excitatory weights, so that place cells return to their baseline firing rate after exploration. Our model suggests that different types of interneurons are essential to unravel the mechanisms underlying place field plasticity. Finally, we predict that artificial induced dendritic events can shift place fields even after place field stabilization.

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Mouse entorhinal cortex encodes a diverse repertoire of self-motion signals

Nature Communications ◽

10.1038/s41467-021-20936-8 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Caitlin S. Mallory ◽

Kiah Hardcastle ◽

Malcolm G. Campbell ◽

Alexander Attinger ◽

Isabel I. C. Low ◽

...

Keyword(s):

Entorhinal Cortex ◽

Medial Temporal Lobe ◽

Visual Cues ◽

Neural Circuits ◽

Sensory Cues ◽

Medial Entorhinal Cortex ◽

Representation Of Space ◽

Self Motion ◽

Information Streams ◽

Representations Of Space

AbstractNeural circuits generate representations of the external world from multiple information streams. The navigation system provides an exceptional lens through which we may gain insights about how such computations are implemented. Neural circuits in the medial temporal lobe construct a map-like representation of space that supports navigation. This computation integrates multiple sensory cues, and, in addition, is thought to require cues related to the individual’s movement through the environment. Here, we identify multiple self-motion signals, related to the position and velocity of the head and eyes, encoded by neurons in a key node of the navigation circuitry of mice, the medial entorhinal cortex (MEC). The representation of these signals is highly integrated with other cues in individual neurons. Such information could be used to compute the allocentric location of landmarks from visual cues and to generate internal representations of space.

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Neuronal rebound spiking, resonance frequency and theta cycle skipping may contribute to grid cell firing in medial entorhinal cortex

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2012.0523 ◽

2014 ◽

Vol 369 (1635) ◽

pp. 20120523 ◽

Cited By ~ 28

Author(s):

Michael E. Hasselmo

Keyword(s):

Resonance Frequency ◽

Entorhinal Cortex ◽

Functional Role ◽

Grid Cell ◽

Medial Septum ◽

Medial Entorhinal Cortex ◽

Spatial Periodicity ◽

Cell Firing ◽

Rebound Spiking ◽

Relationship Of

Data show a relationship of cellular resonance and network oscillations in the entorhinal cortex to the spatial periodicity of grid cells. This paper presents a model that simulates the resonance and rebound spiking properties of entorhinal neurons to generate spatial periodicity dependent upon phasic input from medial septum. The model shows that a difference in spatial periodicity can result from a difference in neuronal resonance frequency that replicates data from several experiments. The model also demonstrates a functional role for the phenomenon of theta cycle skipping in the medial entorhinal cortex.

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Systemic administration of two different anxiolytic drugs decreases local field potential theta frequency in the medial entorhinal cortex without affecting grid cell firing fields

Neuroscience ◽

10.1016/j.neuroscience.2017.08.056 ◽

2017 ◽

Vol 364 ◽

pp. 60-70 ◽

Cited By ~ 8

Author(s):

Caitlin K. Monaghan ◽

G. William Chapman ◽

Michael E. Hasselmo

Keyword(s):

Entorhinal Cortex ◽

Local Field ◽

Local Field Potential ◽

Field Potential ◽

Grid Cell ◽

Systemic Administration ◽

Medial Entorhinal Cortex ◽

Theta Frequency ◽

Anxiolytic Drugs ◽

Cell Firing

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How to build a grid cell

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2012.0520 ◽

2014 ◽

Vol 369 (1635) ◽

pp. 20120520 ◽

Cited By ~ 8

Author(s):

Christoph Schmidt-Hieber ◽

Michael Häusser

Keyword(s):

Entorhinal Cortex ◽

Action Potentials ◽

Path Integration ◽

Grid Cell ◽

Medial Entorhinal Cortex ◽

Synaptic Inputs ◽

New Findings ◽

Cell Firing

Neurons in the medial entorhinal cortex fire action potentials at regular spatial intervals, creating a striking grid-like pattern of spike rates spanning the whole environment of a navigating animal. This remarkable spatial code may represent a neural map for path integration. Recent advances using patch-clamp recordings from entorhinal cortex neurons in vitro and in vivo have revealed how the microcircuitry in the medial entorhinal cortex may contribute to grid cell firing patterns, and how grid cells may transform synaptic inputs into spike output during firing field crossings. These new findings provide key insights into the ingredients necessary to build a grid cell.

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Emergent Elasticity in the Neural Code for Space

10.1101/326793 ◽

2018 ◽

Cited By ~ 2

Author(s):

Samuel Ocko ◽

Kiah Hardcastle ◽

Lisa Giocomob ◽

Surya Ganguli

Keyword(s):

Neural Circuit ◽

Topological Defects ◽

Grid Cell ◽

Grid Cells ◽

Motion Cues ◽

Hebbian Plasticity ◽

Attractor Model ◽

Cell Firing ◽

Path Dependent ◽

Self Motion

Upon encountering a novel environment, an animal must construct a consistent environmental map, as well as an internal estimate of its position within that map, by combining information from two distinct sources: self-motion cues and sensory landmark cues. How do known aspects of neural circuit dynamics and synaptic plasticity conspire to accomplish this feat? Here we show analytically how a neural attractor model that combines path integration of self-motion cues with Hebbian plasticity in synaptic weights from landmark cells can self-organize a consistent map of space as the animal explores an environment. Intriguingly, the emergence of this map can be understood as an elastic relaxation process between landmark cells mediated by the attractor network. Moreover, our model makes several experimentally testable predictions, including: (1) systematic path-dependent shifts in the firing field of grid cells towards the most recently encountered landmark, even in a fully learned environment, (2) systematic deformations in the firing fields of grid cells in irregular environments, akin to elastic deformations of solids forced into irregular containers, and (3) the creation of topological defects in grid cell firing patterns through specific environmental manipulations. Taken together, our results conceptually link known aspects of neurons and synapses to an emergent solution of a fundamental computational problem in navigation, while providing a unified account of disparate experimental observations.

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