Evidence map›Paper›PMID 39678069›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2024

Modeling Grid Cell Distortions with a Grid Cell Calibration Mechanism.

Daniel Strauß, Zhenshan Bing, Genghang Zhuang, Kai Huang, Alois Knoll

Abstract read
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Daniel StraußChair of Robotics, Artificial Intelligence and Real-time Systems, TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0009-0002-9949-2879
Zhenshan BingChair of Robotics, Artificial Intelligence and Real-time Systems, TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-0896-2517
Genghang ZhuangChair of Robotics, Artificial Intelligence and Real-time Systems, TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0003-2478-7912
Kai HuangSchool of Data and Computer Science, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0003-0359-7810
Alois KnollChair of Robotics, Artificial Intelligence and Real-time Systems, TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0003-4840-076X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The medial entorhinal cortex of rodents is known to contain grid cells that exhibit precise periodic firing patterns based on the animal's position, resulting in a distinct hexagonal pattern in space. These cells have been extensively studied due to their potential to unveil the navigational computations that occur within the mammalian brain and interesting phenomena such as so-called grid cell distortions have been observed. Previous neuronal models of grid cells assumed their firing fields were independent of environmental boundaries. However, more recent research has revealed that the grid pattern is, in fact, dependent on the environment's boundaries. When rodents are placed in nonsquare cages, the hexagonal pattern tends to become disrupted and adopts different shapes. We believe that these grid cell distortions can provide insights into the underlying neural circuitry involved in grid cell firing. To this end, a calibration circuit for grid cells is proposed. Our simulations demonstrate that this circuit is capable of reproducing grid distortions observed in several previous studies. Our model also reproduces distortions in place cells and incorporates experimentally observed distortions of speed cells, which present further opportunities for exploration. It generates several experimentally testable predictions, including an alternative behavioral description of boundary vector cells that predicts behaviors in nonsquare environments different from the current model of boundary vector cells. In summary, our study proposes a calibration circuit that reproduces observed grid distortions and generates experimentally testable predictions, aiming to provide insights into the neural mechanisms governing spatial computations in mammals.

Identifiers

PMID39678069
PMCPMC11639139

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.