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Because of their high computational demand, analyses of source-projected hdEEG data are typically performed offline. Here, we present a real-time noninvasive electrophysiology toolbox, RT-NET, which has been specifically developed for online reconstruction of neural activity using hdEEG. RT-NET relies on the Lab Streaming Layer for acquiring raw data from a large number of EEG amplifiers and for streaming the processed data to external applications. RT-NET estimates a spatial filter for artifact removal and source activity reconstruction using a calibration dataset. This spatial filter is then applied to the hdEEG data as they are acquired, thereby ensuring low latencies and computation times. Overall, our analyses show that RT-NET can estimate real-time neural activity with performance comparable to offline analysis methods. It may therefore enable the development of novel brain\u2013computer interface applications such as source-based neurofeedback.<\/jats:p>","DOI":"10.1007\/s12021-020-09479-3","type":"journal-article","created":{"date-parts":[[2020,7,28]],"date-time":"2020-07-28T00:02:31Z","timestamp":1595894551000},"page":"251-266","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["RT-NET: real-time reconstruction of neural activity using high-density electroencephalography"],"prefix":"10.1007","volume":"19","author":[{"given":"Roberto","family":"Guarnieri","sequence":"first","affiliation":[]},{"given":"Mingqi","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Gaia Amaranta","family":"Taberna","sequence":"additional","affiliation":[]},{"given":"Marco","family":"Ganzetti","sequence":"additional","affiliation":[]},{"given":"Stephan P.","family":"Swinnen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6485-5559","authenticated-orcid":false,"given":"Dante","family":"Mantini","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,7,28]]},"reference":[{"key":"9479_CR1","doi-asserted-by":"publisher","unstructured":"Adde, G., Clerc, M., Faugeras, O., Keriven, R., Kybic, J., & Papadopoulo, T. 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