Evidence map›Paper›PMID 38891623›Full record

ArticleAnimals : an open access journal from MDPI2024

Dynamic Nonlinear Spatial Integrations on Encoding Contrasting Stimuli of Tectal Neurons.

Shuman Huang, Pingge Hu, Zhenmeng Zhao, Li Shi

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. CognivueJournal of Alzheimer's disease : JAD · 2025
    Article
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

4 authors.

Shuman HuangKey Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province, College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China.ORCID 0000-0001-5411-743X
Pingge HuDepartment of Automation, Tsinghua University, Beijing 100084, China.ORCID 0000-0002-5250-2788
Zhenmeng ZhaoSchool of Software, Henan Normal University, Xinxiang 453007, China.
Li ShiDepartment of Automation, Tsinghua University, Beijing 100084, China.

Funding

the Key Discipline Construction Project of Zhengzhou University in 2019 XKZDQY201905the Key Scientific Research Projects of Colleges and Universities in Henan province 20A413009
6 · The paper itself

Abstract

Animals detect targets using a variety of visual cues, with the visual salience of these cues determining which environmental features receive priority attention and further processing. Surround modulation plays a crucial role in generating visual saliency, which has been extensively studied in avian tectal neurons. Recent work has reported that the suppression of tectal neurons induced by motion contrasting stimulus is stronger than that by luminance contrasting stimulus. However, the underlying mechanism remains poorly understood. In this study, we built a computational model (called Generalized Linear-Dynamic Modulation) which incorporates independent nonlinear tuning mechanisms for excitatory and inhibitory inputs. This model aims to describe how tectal neurons encode contrasting stimuli. The results showed that: (1) The dynamic nonlinear integration structure substantially improved the accuracy (significant difference (

Indexed as

contrasting stimulidynamic nonlinear spatial integrationsoptic tectumsurround modulation

Identifiers

PMID38891623
PMCPMC11171053

What OpenQuestion holds

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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.