Evidence map›Paper›PMID 32372936›Full record

ArticleFrontiers in computational neuroscience2020

Intrinsic and Synaptic Properties Shaping Diverse Behaviors of Neural Dynamics.

Lingling An, Yuanhong Tang, Doudou Wang, Shanshan Jia, Qingqi Pei, Quan Wang, Zhaofei Yu, Jian K Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 31% of its field
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

5 citing papers in PubMed, 9 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Lingling AnSchool of Computer Science and Technology, Xidian University, Xi'an, China.
Yuanhong TangSchool of Computer Science and Technology, Xidian University, Xi'an, China.
Doudou WangSchool of Computer Science and Technology, Xidian University, Xi'an, China.
Shanshan JiaNational Engineering Laboratory for Video Technology, Department of Computer Science and Technology, Peking University, Beijing, China.
Qingqi PeiSchool of Computer Science and Technology, Xidian University, Xi'an, China.
Quan WangSchool of Computer Science and Technology, Xidian University, Xi'an, China.
Zhaofei YuNational Engineering Laboratory for Video Technology, Department of Computer Science and Technology, Peking University, Beijing, China.
Jian K LiuCentre for Systems Neuroscience, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, United Kingdom.
Xidian University · CNPeking University · CNUniversity of Leicester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The majority of neurons in the neuronal system of the brain have a complex morphological structure, which diversifies the dynamics of neurons. In the granular layer of the cerebellum, there exists a unique cell type, the unipolar brush cell (UBC), that serves as an important relay cell for transferring information from outside mossy fibers to downstream granule cells. The distinguishing feature of the UBC is that it has a simple morphology, with only one short dendritic brush connected to its soma. Based on experimental evidence showing that UBCs exhibit a variety of dynamic behaviors, here we develop two simple models, one with a few detailed ion channels for simulation and the other one as a two-variable dynamical system for theoretical analysis, to characterize the intrinsic dynamics of UBCs. The reasonable values of the key channel parameters of the models can be determined by analysis of the stability of the resting membrane potential and the rebound firing properties of UBCs. Considered together with a large variety of synaptic dynamics installed on UBCs, we show that the simple-structured UBCs, as relay cells, can extend the range of dynamics and information from input mossy fibers to granule cells with low-frequency resonance and transfer stereotyped inputs to diverse amplitudes and phases of the output for downstream granule cells. These results suggest that neuronal computation, embedded within intrinsic ion channels and the diverse synaptic properties of single neurons without sophisticated morphology, can shape a large variety of dynamic behaviors to enhance the computational ability of local neuronal circuits.

Indexed as

dynamical systemneural dynamic modelingrebound firingstability analysissynaptic dynamics

Identifiers

PMID32372936
PMCPMC7187274
OpenAlexW3018600593

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.