Parvalbumin-positive interneurons of the prefrontal cortex support working memory and cognitive flexibility

We were supported by the Biotechnology and Biological Sciences Research Council grant BB/H001123/1 (P.W.), the Medical Research Council grants G0601498 and G1100546/2 (P.W.), Tenovus Scotland Grant G09/17 (A.J.M.) and the University of Aberdeen (P.W.). We thank O. Tüscher for discussion, P. Teismann and the microscopy core facility at the University of Aberdeen for the use of microscopy equipment, L. Strachan, A. Plano, S. Deiana for help with behavioral testing.Peer reviewedPublisher PD

A community-based transcriptomics classification and nomenclature of neocortical cell types

© 2020, The Author(s). To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body

Publisher Correction: A community-based transcriptomics classification and nomenclature of neocortical cell types (Nature Neuroscience, (2020), 23, 12, (1456-1468), 10.1038/s41593-020-0685-8)

© 2020, The Author(s). In the version of this article initially published, author Thomas V. Wuttke’s affiliation was shown incorrectly. Dr. Wuttke is affiliated with University of Tübingen, Tübingen, Germany. The error has been corrected in the PDF and HTML versions of this article

Publisher Correction: A community-based transcriptomics classification and nomenclature of neocortical cell types

In the version of this article initially published, author Thomas V. Wuttke’s affiliation was shown incorrectly. Dr. Wuttke is affiliated with University of Tübingen, Tübingen, Germany. The error has been corrected in the PDF and HTML versions of this article

Author Correction: A community-based transcriptomics classification and nomenclature of neocortical cell types

In the version of this article initially published, multiple errors appeared in the author and affiliations lists. The errors have been corrected in the PDF and HTML versions of this article

A community-based transcriptomics classification and nomenclature of neocortical cell types

To understand the function of cortical circuits it is necessary to classify their underlying cellular diversity. Traditional attempts based on comparing anatomical or physiological features of neurons and glia, while productive, have not resulted in a unified taxonomy of neural cell types. The recent development of single-cell transcriptomics has enabled, for the first time, systematic high-throughput profiling of large numbers of cortical cells and the generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data have revealed the existence of clear clusters, many of which correspond to cell types defined by traditional criteria, and which are conserved across cortical areas and species. To capitalize on these innovations and advance the field, we, the Copenhagen Convention Group, propose the community adopts a transcriptome-based taxonomy of the cell types in the adult mammalian neocortex. This core classification should be ontological, hierarchical and use a standardized nomenclature. It should be configured to flexibly incorporate new data from multiple approaches, developmental stages and a growing number of species, enabling improvement and revision of the classification. This community-based strategy could serve as a common foundation for future detailed analysis and reverse engineering of cortical circuits and serve as an example for cell type classification in other parts of the nervous system and other organs