Evidence map›Paper›PMID 17426353›Full record

ArticleNeuroinformatics2007

Voronoi analysis uncovers relationship between mosaics of normally placed and displaced amacrine cells in the thraira retina.

Luciano Da Fontoura Costa, Daniela Maria Oliveira Bonci, Cézar Akiyoshi Saito, Fernando Allan De Farias Rocha, Luiz Carlos De Lima Silveira, Dora Fix Ventura

Abstract read
PubMed Publisher
In one paragraph

Article in Neuroinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.4field-weighted citation impact, top 39% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

6 authors at 3 institutions in 1 country.

Luciano Da Fontoura CostaInstituto de Física de São Carlos, Universidade de São Paulo, Caixa Postal 369, São Carlos, SP, 13560-970 Brazil. luciano@if.sc.usp.br
Daniela Maria Oliveira Bonci
Cézar Akiyoshi Saito
Fernando Allan De Farias Rocha
Luiz Carlos De Lima Silveira
Dora Fix Ventura
Universidade de São Paulo · BRUniversidade Federal do Pará · BRSociedade Brasileira de Neurociências e Comportamento · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although neuronal dynamics is to a high extent a function of synapse strength, the spatial distribution of neurons is also known to play an important role, which is evidenced by the topographical organization of the main stations of the visual system: retina, lateral geniculate nucleus, and cortex. The coexisting systems of normally placed and displaced amacrine cells in the vertebrate retina provide interesting examples of retinotopic spatial organization. However, it is not clear whether these two systems are spatially interrelated or not. The current work applies two mathematical-computational methods-a new method involving Voronoi diagrams for local density quantification and a more traditional approach, the Ripley K function-in order to characterize the mosaics of normally placed and displaced amacrine cells in the retina of Hoplias malabaricus and search for possible spatial relationships between these two types of mosaics. The results obtained by the Voronoi local density analysis suggest that the two systems of amacrine cells are spatially interrelated through nearly constant local density ratios.

Indexed as

Mathematical ComputingSoftwareAmacrine CellsAnimalsCell CommunicationFishesRetinaSynapsesVisual Pathways

Identifiers

PMID17426353
OpenAlexW95603272

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.