Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
34,416
result(s) for
"Moser"
Sort by:
Toroidal topology of population activity in grid cells
The medial entorhinal cortex is part of a neural system for mapping the position of an individual within a physical environment
1
. Grid cells, a key component of this system, fire in a characteristic hexagonal pattern of locations
2
, and are organized in modules
3
that collectively form a population code for the animal’s allocentric position
1
. The invariance of the correlation structure of this population code across environments
4
,
5
and behavioural states
6
,
7
, independent of specific sensory inputs, has pointed to intrinsic, recurrently connected continuous attractor networks (CANs) as a possible substrate of the grid pattern
1
,
8
–
11
. However, whether grid cell networks show continuous attractor dynamics, and how they interface with inputs from the environment, has remained unclear owing to the small samples of cells obtained so far. Here, using simultaneous recordings from many hundreds of grid cells and subsequent topological data analysis, we show that the joint activity of grid cells from an individual module resides on a toroidal manifold, as expected in a two-dimensional CAN. Positions on the torus correspond to positions of the moving animal in the environment. Individual cells are preferentially active at singular positions on the torus. Their positions are maintained between environments and from wakefulness to sleep, as predicted by CAN models for grid cells but not by alternative feedforward models
12
. This demonstration of network dynamics on a toroidal manifold provides a population-level visualization of CAN dynamics in grid cells.
Simultaneous recordings from hundreds of grid cells in rats, combined with topological data analysis, show that network activity in grid cells resides on a toroidal manifold that is invariant across environments and brain states.
Journal Article
Spatial representation in the hippocampal formation: a history
Moser, Moser and McNaughton provide a historical overview describing how ideas about integration of self-motion cues have shaped our understanding of spatial representation in hippocampal–entorhinal systems, from the discovery of place cells in the 1970s to contemporary studies of spatial coding in intermingled and interacting cell types within complex circuits.
Since the first place cell was recorded and the cognitive-map theory was subsequently formulated, investigation of spatial representation in the hippocampal formation has evolved in stages. Early studies sought to verify the spatial nature of place cell activity and determine its sensory origin. A new epoch started with the discovery of head direction cells and the realization of the importance of angular and linear movement-integration in generating spatial maps. A third epoch began when investigators turned their attention to the entorhinal cortex, which led to the discovery of grid cells and border cells. This review will show how ideas about integration of self-motion cues have shaped our understanding of spatial representation in hippocampal–entorhinal systems from the 1970s until today. It is now possible to investigate how specialized cell types of these systems work together, and spatial mapping may become one of the first cognitive functions to be understood in mechanistic detail.
Journal Article
Speed cells in the medial entorhinal cortex
Grid cells in the medial entorhinal cortex have spatial firing fields that repeat periodically in a hexagonal pattern. When animals move, activity is translated between grid cells in accordance with the animal’s displacement in the environment. For this translation to occur, grid cells must have continuous access to information about instantaneous running speed. However, a powerful entorhinal speed signal has not been identified. Here we show that running speed is represented in the firing rate of a ubiquitous but functionally dedicated population of entorhinal neurons distinct from other cell populations of the local circuit, such as grid, head-direction and border cells. These ‘speed cells’ are characterized by a context-invariant positive, linear response to running speed, and share with grid cells a prospective bias of ∼50–80 ms. Our observations point to speed cells as a key component of the dynamic representation of self-location in the medial entorhinal cortex.
On the basis of neural firing rates a specific class of neuron is identified in the medial entorhinal cortex that linearly encodes information on running speed in a context-independent manner and that is distinct from other functionally specific entorhinal neurons.
Entorhinal speed cells
It has long been postulated that in the entorhinal cortex, grid cells require information on the running speed of the animal in order to properly encode periodic spatial firing fields as an animal moves through its environment. However, the source of such a signal transmitting speed information has not been previously identified. Here, Edvard Moser and colleagues isolate a specific class of neurons in the medial entorhinal cortex (MEC) that encode information linearly on running speed based on neural firing rates. These 'speed cells' are distinct from other functionally specific MEC neurons and encode speed in a context-independent manner.
Journal Article
Projecting citizenship : photography and belonging in the British Empire
\"Examines the relationship between photography and citizenship, through a comprehensive account of the Colonial Office Visual Instruction Committee's lantern slide lecture scheme: a project initiated by the British government at the beginning of the twentieth century that aimed to photograph the entirety of the empire\"--Provided by publisher.
Book
Integrating time from experience in the lateral entorhinal cortex
The encoding of time and its binding to events are crucial for episodic memory, but how these processes are carried out in hippocampal–entorhinal circuits is unclear. Here we show in freely foraging rats that temporal information is robustly encoded across time scales from seconds to hours within the overall population state of the lateral entorhinal cortex. Similarly pronounced encoding of time was not present in the medial entorhinal cortex or in hippocampal areas CA3–CA1. When animals’ experiences were constrained by behavioural tasks to become similar across repeated trials, the encoding of temporal flow across trials was reduced, whereas the encoding of time relative to the start of trials was improved. The findings suggest that populations of lateral entorhinal cortex neurons represent time inherently through the encoding of experience. This representation of episodic time may be integrated with spatial inputs from the medial entorhinal cortex in the hippocampus, allowing the hippocampus to store a unified representation of what, where and when.
Temporal information that is useful for episodic memory is encoded across a wide range of timescales in the lateral entorhinal cortex, arising inherently from its representation of ongoing experience.
Journal Article
Object-vector coding in the medial entorhinal cortex
The hippocampus and the medial entorhinal cortex are part of a brain system that maps self-location during navigation in the proximal environment
1
,
2
. In this system, correlations between neural firing and an animal’s position or orientation are so evident that cell types have been given simple descriptive names, such as place cells
3
, grid cells
4
, border cells
5
,
6
and head-direction cells
7
. While the number of identified functional cell types is growing at a steady rate, insights remain limited by an almost-exclusive reliance on recordings from rodents foraging in empty enclosures that are different from the richly populated, geometrically irregular environments of the natural world. In environments that contain discrete objects, animals are known to store information about distance and direction to those objects and to use this vector information to guide navigation
8
–
10
. Theoretical studies have proposed that such vector operations are supported by neurons that use distance and direction from discrete objects
11
,
12
or boundaries
13
,
14
to determine the animal’s location, but—although some cells with vector-coding properties may be present in the hippocampus
15
and subiculum
16
,
17
—it remains to be determined whether and how vectorial operations are implemented in the wider neural representation of space. Here we show that a large fraction of medial entorhinal cortex neurons fire specifically when mice are at given distances and directions from spatially confined objects. These ‘object-vector cells’ are tuned equally to a spectrum of discrete objects, irrespective of their location in the test arena, as well as to a broad range of dimensions and shapes, from point-like objects to extended surfaces. Our findings point to vector coding as a predominant form of position coding in the medial entorhinal cortex.
Cells in the mouse medial entorhinal cortex that fire when mice are at a specific distance and direction from a stationary object suggest that vector coding is important for rodent navigation.
Journal Article