Evidence map›Paper›PMID 31447655›Full record

ArticleFrontiers in neuroanatomy2019

A Derived Positional Mapping of Inhibitory Subtypes in the Somatosensory Cortex.

Daniel Keller, Julie Meystre, Rahul V Veettil, Olivier Burri, Romain Guiet, Felix Schürmann, Henry Markram

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Frontiers in neuroanatomy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 38% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Daniel KellerBlue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
Julie MeystreLaboratory of Neural Microcircuitry, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Rahul V VeettilFaculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Olivier BurriBioimaging and Optics Platform, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Romain GuietBioimaging and Optics Platform, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Felix SchürmannBlue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
Henry MarkramBlue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
École Polytechnique Fédérale de Lausanne · CHBen-Gurion University of the Negev · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obtaining a catalog of cell types is a fundamental building block for understanding the brain. The ideal classification of cell-types is based on the profile of molecules expressed by a cell, in particular, the profile of genes expressed. One strategy is, therefore, to obtain as many single-cell transcriptomes as possible and isolate clusters of neurons with similar gene expression profiles. In this study, we explored an alternative strategy. We explored whether cell-types can be algorithmically derived by combining protein tissue stains with transcript expression profiles. We developed an algorithm that aims to distribute cell-types in the different layers of somatosensory cortex of the developing rat constrained by the tissue- and cellular level data. We found that the spatial distribution of major inhibitory cell types can be approximated using the available data. The result is a depth-wise atlas of inhibitory cell-types of the rat somatosensory cortex. In principle, any data that constrains what can occur in a particular part of the brain can also strongly constrain the derivation of cell-types. This draft inhibitory cell-type mapping is therefore dynamic and can iteratively converge towards the ground truth as further data is integrated.

Indexed as

cell countingcell densitycell typescompositioninhibitory interneuronsneuronal distributionrat brainsomatosensory cortex

Identifiers

PMID31447655
PMCPMC6691028
OpenAlexW2963002378

What OpenQuestion holds

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LicenceCC BY
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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.