Integrating Results across Methodologies Is Essential for Producing Robust Neuronal Taxonomies.

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Neuron. 2017 May 17;94(4):747-751.e1. doi: 10.1016/j.neuron.2017.04.023

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Integrating Results across Methodologies Is Essential for Producing Robust Neuronal Taxonomies. Spruston Lab

Cembrowski MS, Spruston N

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Abstract

Elucidating the diversity and spatial organization of cell types in the brain is an essential goal of neuroscience, with many emerging technologies helping to advance this endeavor. Using a new in situ hybridization method that can measure the expression of hundreds of genes in a given mouse brain section (amplified seqFISH), Shah et al. (2016) describe a spatial organization of hippocampal cell types that differs from previous reports. In seeking to understand this discrepancy, we find that many of the barcoded genes used by seqFISH to characterize this spatial organization, when cross-validated by other sensitive methodologies, exhibit negligible expression in the hippocampus. Additionally, the results of Shah et al. (2016) do not recapitulate canonical cellular hierarchies and improperly classify major neuronal cell types. We suggest that, when describing the spatial organization of brain regions, cross-validation using multiple techniques should be used to yield robust and informative cellular classification. This Matters Arising paper is in response to Shah et al. (2016), published in Neuron. See also the response by Shah et al. (2017), published in this issue.

PMID: 28521129 [PubMed - indexed for MEDLINE]

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Integrating Results across Methodologies Is Essential for Producing Robust Neuronal Taxonomies.

Abstract

PMID: 28521129 [PubMed - indexed for MEDLINE]

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