An in vitro whole-cell electrophysiology dataset of human cortical neurons. (15th November 2022)

• Record Type: Journal Article
• Authors: Howard, Derek; Chameh, Homeira Moradi; Guet-McCreight, Alexandre; Hsiao, Huan Allen; Vuong, Maggie; Seo, Young Seok; Shah, Prajay; Nigam, Anukrati; Chen, Yuxiao; Davie, Melanie; Hay, Etay; Valiante, Taufik A; Tripathy, Shreejoy J
• Is Part Of: GigaScience. Volume 11(2022)
• Publication Date: 2022-11-15
• Subjects: Information storage and retrieval systems -- Research -- Periodicals; Biology -- Research -- Periodicals; Medical sciences -- Research -- Periodicals; Database management -- Periodicals; 570.285
• DOI: 10.1093/gigascience/giac108
• Languages: English
• ISSNs: 2047-217X

Abstract

Abstract: Background: Whole-cell patch-clamp electrophysiology is an essential technique for understanding how single neurons translate their diverse inputs into a functional output. The relative inaccessibility of live human cortical neurons for experimental manipulation has made it difficult to determine the unique features of how human cortical neurons differ from their counterparts in other species. Findings: We present a curated repository of whole-cell patch-clamp recordings from surgically resected human cortical tissue, encompassing 118 neurons from 35 individuals (age range, 21–59 years; 17 male, 18 female). Recorded human cortical neurons derive from layers 2 and 3 (L2&3), deep layer 3 (L3c), or layer 5 (L5) and are annotated with a rich set of subject and experimental metadata. For comparison, we also provide a limited set of comparable recordings from 21-day-old mice (11 cells from 5 mice). All electrophysiological recordings are provided in the Neurodata Without Borders (NWB) format and are available for further analysis via the Distributed Archives for Neurophysiology Data Integration online repository. The associated data conversion code is made publicly available and can help others in converting electrophysiology datasets to the open NWB standard for general reuse. Conclusion: These data can be used for novel analyses of biophysical characteristics of human cortical neurons, including in cross-species or cross-lab comparisons or in building computational models of individual human neurons.