{"issue":"5","month":"05","title":"What we can and what we cannot see with extracellular multielectrodes","publication_identifier":{"issn":["1553-7358"]},"doi":"10.1371/journal.pcbi.1008615","_id":"17132","type":"journal_article","citation":{"short":"C. Chintaluri, M. Bejtka, W. Średniawa, M. Czerwiński, J.M. Dzik, J. Jędrzejewska-Szmek, K. Kondrakiewicz, E. Kublik, D.K. Wójcik, PLOS Computational Biology 17 (2021).","apa":"Chintaluri, C., Bejtka, M., Średniawa, W., Czerwiński, M., Dzik, J. M., Jędrzejewska-Szmek, J., … Wójcik, D. K. (2021). What we can and what we cannot see with extracellular multielectrodes. <i>PLOS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1008615\">https://doi.org/10.1371/journal.pcbi.1008615</a>","ama":"Chintaluri C, Bejtka M, Średniawa W, et al. What we can and what we cannot see with extracellular multielectrodes. <i>PLOS Computational Biology</i>. 2021;17(5). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008615\">10.1371/journal.pcbi.1008615</a>","ista":"Chintaluri C, Bejtka M, Średniawa W, Czerwiński M, Dzik JM, Jędrzejewska-Szmek J, Kondrakiewicz K, Kublik E, Wójcik DK. 2021. What we can and what we cannot see with extracellular multielectrodes. PLOS Computational Biology. 17(5), e1008615.","mla":"Chintaluri, Chaitanya, et al. “What We Can and What We Cannot See with Extracellular Multielectrodes.” <i>PLOS Computational Biology</i>, vol. 17, no. 5, e1008615, Public Library of Science, 2021, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008615\">10.1371/journal.pcbi.1008615</a>.","ieee":"C. Chintaluri <i>et al.</i>, “What we can and what we cannot see with extracellular multielectrodes,” <i>PLOS Computational Biology</i>, vol. 17, no. 5. Public Library of Science, 2021.","chicago":"Chintaluri, Chaitanya, Marta Bejtka, Władysław Średniawa, Michał Czerwiński, Jakub M. Dzik, Joanna Jędrzejewska-Szmek, Kacper Kondrakiewicz, Ewa Kublik, and Daniel K. Wójcik. “What We Can and What We Cannot See with Extracellular Multielectrodes.” <i>PLOS Computational Biology</i>. Public Library of Science, 2021. <a href=\"https://doi.org/10.1371/journal.pcbi.1008615\">https://doi.org/10.1371/journal.pcbi.1008615</a>."},"oa_version":"Published Version","oa":1,"publisher":"Public Library of Science","publication_status":"published","author":[{"id":"BA06AFEE-A4BA-11EA-AE5C-14673DDC885E","last_name":"Chintaluri","full_name":"Chintaluri, Chaitanya","first_name":"Chaitanya","orcid":"0000-0003-4252-1608"},{"full_name":"Bejtka, Marta","first_name":"Marta","last_name":"Bejtka"},{"full_name":"Średniawa, Władysław","first_name":"Władysław","last_name":"Średniawa"},{"last_name":"Czerwiński","first_name":"Michał","full_name":"Czerwiński, Michał"},{"last_name":"Dzik","first_name":"Jakub M.","full_name":"Dzik, Jakub M."},{"last_name":"Jędrzejewska-Szmek","full_name":"Jędrzejewska-Szmek, Joanna","first_name":"Joanna"},{"full_name":"Kondrakiewicz, Kacper","first_name":"Kacper","last_name":"Kondrakiewicz"},{"last_name":"Kublik","full_name":"Kublik, Ewa","first_name":"Ewa"},{"last_name":"Wójcik","first_name":"Daniel K.","full_name":"Wójcik, Daniel K."}],"language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2024-06-11T14:43:37Z","article_number":"e1008615","publication":"PLOS Computational Biology","date_published":"2021-05-14T00:00:00Z","article_processing_charge":"No","year":"2021","has_accepted_license":"1","article_type":"original","volume":17,"extern":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1371/journal.pcbi.1008615"}],"status":"public","abstract":[{"lang":"eng","text":"<jats:p>Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable. We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data. We show that with conceptual separation of the estimation space from experimental setup one can recover sources not accessible to standard methods.</jats:p>"}],"date_updated":"2024-06-17T10:48:15Z","intvolume":"        17","quality_controlled":"1","day":"14"}