ArticleFrontiers in neuroanatomy2019
A Derived Positional Mapping of Inhibitory Subtypes in the Somatosensory Cortex.
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.
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7 citing papers in PubMed, 15 citations in OpenAlex.
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- Cell density quantification of high resolution Nissl images of the juvenile rat brain.Frontiers in neuroanatomy · 2024Article
- Cell-type-specific densities in mouse somatosensory cortex derived from scRNA-seq andFrontiers in neuroanatomy · 2023Article
- Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons.PLoS computational biology · 2023Article
- Injection witheLife · 2021Article
- Operations Research Methods for Estimating the Population Size of Neuron Types.Annals of operations research · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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