{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T02:55:57Z","timestamp":1787021757101,"version":"build-2736575974"},"reference-count":41,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T00:00:00Z","timestamp":1672876800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001703","name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001703","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020899","name":"ETH Board of the Swiss Federal Institutes of Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100020899","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Knowledge of the cell-type-specific composition of the brain is useful in order to understand the role of each cell type as part of the network. Here, we estimated the composition of the whole cortex in terms of well characterized morphological and electrophysiological inhibitory neuron types (me-types). We derived probabilistic me-type densities from an existing atlas of molecularly defined cell-type densities in the mouse cortex. We used a well-established me-type classification from rat somatosensory cortex to populate the cortex. These me-types were well characterized morphologically and electrophysiologically but they lacked molecular marker identity labels. To extrapolate this missing information, we employed an additional dataset from the Allen Institute for Brain Science containing molecular identity as well as morphological and electrophysiological data for mouse cortical neurons. We first built a latent space based on a number of comparable morphological and electrical features common to both data sources. We then identified 19 morpho-electrical clusters that merged neurons from both datasets while being molecularly homogeneous. The resulting clusters best mirror the molecular identity classification solely using available morpho-electrical features. Finally, we stochastically assigned a molecular identity to a me-type neuron based on the latent space cluster it was assigned to. The resulting mapping was used to derive inhibitory me-types densities in the cortex.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1010058","type":"journal-article","created":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T13:38:44Z","timestamp":1672925924000},"page":"e1010058","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":11,"title":["Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2847-4502","authenticated-orcid":true,"given":"Yann","family":"Roussel","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6295-7148","authenticated-orcid":true,"given":"Csaba","family":"Veraszt\u00f3","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2496-2311","authenticated-orcid":true,"given":"Dimitri","family":"Rodarie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanguy","family":"Damart","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3455-2367","authenticated-orcid":true,"given":"Michael","family":"Reimann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6642-7136","authenticated-orcid":true,"given":"Srikanth","family":"Ramaswamy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henry","family":"Markram","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Keller","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,1,5]]},"reference":[{"key":"pcbi.1010058.ref001","doi-asserted-by":"crossref","first-page":"84","DOI":"10.3389\/fninf.2018.00084","article-title":"A Cell Atlas for the Mouse Brain","volume":"12","author":"C Er\u00f6","year":"2018","journal-title":"Front Neuroinformatics"},{"issue":"7124","key":"pcbi.1010058.ref002","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1038\/nature05453","article-title":"Genome-wide atlas of gene expression in the adult mouse brain","volume":"445","author":"ES Lein","year":"2007","journal-title":"Nature"},{"issue":"9","key":"pcbi.1010058.ref003","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1038\/s41583-019-0195-4","article-title":"The diversity of GABAergic neurons and neural communication elements.","volume":"20","author":"ZJ Huang","year":"2019","journal-title":"Nat Rev Neurosci."},{"issue":"6","key":"pcbi.1010058.ref004","first-page":"1136","article-title":"Communication in Neural Circuits: Tools, Opportunities, and","volume":"164","author":"TN Lerner","year":"2016","journal-title":"Challenges. 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