Evidence map›Paper›PMID 23756373›Full record

ArticleBioarchitecture

New insights on vertebrate olivo-cerebellar climbing fibers from computerized morphological reconstructions.

Izumi Sugihara, Kerry M Brown, Giorgio A Ascoli

Open access · bronzeAbstract readComment
In one paragraph

Article in Bioarchitecture. 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, top 95% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Izumi SugiharaDepartment of Systems Neurophysiology, Tokyo Medical and Dental University Graduate School and the Center for Brain Integration Research, Tokyo, Japan.
Kerry M Brown
Giorgio A Ascoli
George Mason University · USInstitute for Advanced Study · USTokyo Medical and Dental University · JP

Funding

Generation and Description of Neuronal Morphology and ConnectivityR01NS039600 · NINDS · GEORGE MASON UNIVERSITY · PI ASCOLI, GIORGIO A · 1999 to 2024
$6.9M
NINDS NIH HHS R01 NS039600NINDS NIH HHS R01 NS-39600
6 · The paper itself

Abstract

Characterization of neuronal connectivity is essential to understanding the architecture of the animal nervous system. Specific labeling and imaging techniques can visualize axons and dendrites of single nerve cells. Two-dimensional manual drawing has long been used to describe the morphology of labeled neuronal elements. However, quantitative morphometry, which is essential to understanding functional significance, cannot be readily extracted unless the detailed neuronal geometry is comprehensively reconstructed in three-dimensional space. We have recently applied an accurate and robust digital reconstruction system to cerebellar climbing fibers, which form highly dense and complex terminal arbors as one of the strongest presynaptic endings in the vertebrate nervous system. Resulting statistical analysis has shown how climbing fibers morphology is special in comparison to other axonal terminals. While thick primary branches may convey excitation quickly and faithfully to the far ends, thin tendril branches, which have a larger bouton density, form the majority of presynaptic outputs. This data set, now publicly available from NeuroMorpho.Org for further modeling and analysis, may constitute the first detailed and comprehensive digital reconstruction of the complete axonal terminal field with identified branch types and full accounting of boutons for any neuronal class in the vertebrate brain.

Indexed as

AnimalsCerebellumMaleNerve FibersPresynaptic TerminalsPurkinje Cellsaxonbiotinylated dextran amineboutonbranchescerebellar cortexmolecular layerrattendrilterminal arbor

Identifiers

PMID23756373
PMCPMC3715541
OpenAlexW2053813438

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.