↓ Skip to main content

Topological Schemas of Memory Spaces

Overview of attention for article published in Frontiers in Computational Neuroscience, April 2018
Altmetric Badge

Mentioned by

twitter
3 X users

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
46 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Topological Schemas of Memory Spaces
Published in
Frontiers in Computational Neuroscience, April 2018
DOI 10.3389/fncom.2018.00027
Pubmed ID
Authors

Andrey Babichev, Yuri A. Dabaghian

Abstract

Hippocampal cognitive map-a neuronal representation of the spatial environment-is widely discussed in the computational neuroscience literature for decades. However, more recent studies point out that hippocampus plays a major role in producing yet another cognitive framework-the memory space-that incorporates not only spatial, but also non-spatial memories. Unlike the cognitive maps, the memory spaces, broadly understood as "networks of interconnections among the representations of events," have not yet been studied from a theoretical perspective. Here we propose a mathematical approach that allows modeling memory spaces constructively, as epiphenomena of neuronal spiking activity and thus to interlink several important notions of cognitive neurophysiology. First, we suggest that memory spaces have a topological nature-a hypothesis that allows treating both spatial and non-spatial aspects of hippocampal function on equal footing. We then model the hippocampal memory spaces in different environments and demonstrate that the resulting constructions naturally incorporate the corresponding cognitive maps and provide a wider context for interpreting spatial information. Lastly, we propose a formal description of the memory consolidation process that connects memory spaces to the Morris' cognitive schemas-heuristic representations of the acquired memories, used to explain the dynamics of learning and memory consolidation in a given environment. The proposed approach allows evaluating these constructs as the most compact representations of the memory space's structure.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 24%
Researcher 10 22%
Student > Master 6 13%
Student > Postgraduate 5 11%
Student > Bachelor 4 9%
Other 4 9%
Unknown 6 13%
Readers by discipline Count As %
Neuroscience 15 33%
Agricultural and Biological Sciences 5 11%
Physics and Astronomy 4 9%
Psychology 2 4%
Computer Science 2 4%
Other 9 20%
Unknown 9 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 April 2018.
All research outputs
#15,504,780
of 23,041,514 outputs
Outputs from Frontiers in Computational Neuroscience
#874
of 1,355 outputs
Outputs of similar age
#208,014
of 326,474 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#22
of 28 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,355 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,474 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.