{"publication_identifier":{"issn":["1553-734X"],"eissn":["1553-7358"]},"citation":{"ista":"Chintaluri C, Bejtka M, Sredniawa W, Czerwinski M, Dzik JM, Jedrzejewska-Szmek J, Wojciki DK. 2024. kCSD-python, reliable current source density estimation with quality control. PLoS Computational Biology. 20(3), e1011941.","ama":"Chintaluri C, Bejtka M, Sredniawa W, et al. kCSD-python, reliable current source density estimation with quality control. <i>PLoS Computational Biology</i>. 2024;20(3). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">10.1371/journal.pcbi.1011941</a>","short":"C. Chintaluri, M. Bejtka, W. Sredniawa, M. Czerwinski, J.M. Dzik, J. Jedrzejewska-Szmek, D.K. Wojciki, PLoS Computational Biology 20 (2024).","chicago":"Chintaluri, Chaitanya, Marta Bejtka, Wladyslaw Sredniawa, Michal Czerwinski, Jakub M. Dzik, Joanna Jedrzejewska-Szmek, and Daniel K. Wojciki. “KCSD-Python, Reliable Current Source Density Estimation with Quality Control.” <i>PLoS Computational Biology</i>. Public Library of Science, 2024. <a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">https://doi.org/10.1371/journal.pcbi.1011941</a>.","apa":"Chintaluri, C., Bejtka, M., Sredniawa, W., Czerwinski, M., Dzik, J. M., Jedrzejewska-Szmek, J., &#38; Wojciki, D. K. (2024). kCSD-python, reliable current source density estimation with quality control. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">https://doi.org/10.1371/journal.pcbi.1011941</a>","ieee":"C. Chintaluri <i>et al.</i>, “kCSD-python, reliable current source density estimation with quality control,” <i>PLoS Computational Biology</i>, vol. 20, no. 3. Public Library of Science, 2024.","mla":"Chintaluri, Chaitanya, et al. “KCSD-Python, Reliable Current Source Density Estimation with Quality Control.” <i>PLoS Computational Biology</i>, vol. 20, no. 3, e1011941, Public Library of Science, 2024, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011941\">10.1371/journal.pcbi.1011941</a>."},"abstract":[{"text":"Interpretation of extracellular recordings can be challenging due to the long range of electric field. This challenge can be mitigated by estimating the current source density (CSD). Here we introduce kCSD-python, an open Python package implementing Kernel Current Source Density (kCSD) method and related tools to facilitate CSD analysis of experimental data and the interpretation of results. We show how to counter the limitations imposed by noise and assumptions in the method itself. kCSD-python allows CSD estimation for an arbitrary distribution of electrodes in 1D, 2D, and 3D, assuming distributions of sources in tissue, a slice, or in a single cell, and includes a range of diagnostic aids. We demonstrate its features in a Jupyter Notebook tutorial which illustrates a typical analytical workflow and main functionalities useful in validating analysis results.","lang":"eng"}],"oa_version":"Published Version","publication":"PLoS Computational Biology","date_created":"2024-03-24T23:00:59Z","publisher":"Public Library of Science","issue":"3","author":[{"id":"E4EDB536-3485-11EA-98D2-20AF3DDC885E","full_name":"Chintaluri, Chaitanya","last_name":"Chintaluri","first_name":"Chaitanya"},{"full_name":"Bejtka, Marta","last_name":"Bejtka","first_name":"Marta"},{"last_name":"Sredniawa","full_name":"Sredniawa, Wladyslaw","first_name":"Wladyslaw"},{"last_name":"Czerwinski","full_name":"Czerwinski, Michal","first_name":"Michal"},{"first_name":"Jakub M.","last_name":"Dzik","full_name":"Dzik, Jakub M."},{"first_name":"Joanna","last_name":"Jedrzejewska-Szmek","full_name":"Jedrzejewska-Szmek, Joanna"},{"full_name":"Wojciki, Daniel K.","last_name":"Wojciki","first_name":"Daniel K."}],"year":"2024","language":[{"iso":"eng"}],"article_type":"original","day":"14","month":"03","department":[{"_id":"TiVo"}],"acknowledgement":"The Python implementation of kCSD was started by Grzegorz Parka during Google Summer of Code project through the International Neuroinformatics Coordinating Facility. Jan Mąka implemented the first Python version of skCSD class. This work was supported by the Polish National Science Centre (2013/08/W/NZ4/00691 to DKW; 2015/17/B/ST7/04123 to DKW). ","quality_controlled":"1","title":"kCSD-python, reliable current source density estimation with quality control","date_published":"2024-03-14T00:00:00Z","article_processing_charge":"Yes","type":"journal_article","volume":20,"_id":"15169","doi":"10.1371/journal.pcbi.1011941","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","related_material":{"link":[{"relation":"software","url":"https://github.com/Neuroinflab/kCSD-python"}]},"scopus_import":"1","intvolume":"        20","publication_status":"published","article_number":"e1011941","date_updated":"2024-03-25T07:54:23Z","status":"public"}