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Supporting data for "An in vitro whole-cell electrophysiology dataset of human cortical neurons"

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DataCite Commons2025-05-26 更新2025-04-15 收录
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http://gigadb.org/dataset/102317
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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.<br>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 old; 17 male, 18 female). Recorded human cortical neurons derive from layers 2&amp;3 (L2&amp;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 (DANDI) 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 re-use. <br>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. <br>This GigaDB dataset includes all the original ABF formatted recordings, including those that failed QC during the conversion to NWB format. The GitHub repository includes the code we used to convert those ABF to NWB format. The resultant NWB files are hosted in the DANDI repository under accessions 000292 and 000293.
提供机构:
GigaScience Database
创建时间:
2022-10-07
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