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BCILAB is a MATLAB toolbox for Brain-Computer Interface (BCI) research. It facilitates the design and development of new methods for cognitive state estimation and their use in both offline data analysis and real-time applications. BCILAB includes an easily extensible collection of currently over 100 methods from the literature (covering signal processing, machine learning and BCI-specific methods). Aside from supporting advanced BCI research, a special aim of BCILAB is to facilitate the adoption of machine learning and advanced statistical modeling for functional neuroimaging purposes in tandem with the EEGLAB platform. | BCILAB is a MATLAB toolbox for Brain-Computer Interface (BCI) research. It facilitates the design and development of new methods for cognitive state estimation and their use in both offline data analysis and real-time applications. BCILAB includes an easily extensible collection of currently over 100 methods from the literature (covering signal processing, machine learning and BCI-specific methods). Aside from supporting advanced BCI research, a special aim of BCILAB is to facilitate the adoption of machine learning and advanced statistical modeling for functional neuroimaging purposes in tandem with the EEGLAB platform. | ||
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| + | ==Organizations== | ||
| + | *[[Neuroimaging_Informatics_Tools_and_Resources_Clearinghouse|Neuroimaging Informatics Tools and Resources Clearinghouse]] | ||
| + | *[[NITRC|NITRC]] | ||
==Links== | ==Links== | ||
[http://www.nitrc.org/projects/bcilab/ Website] | [http://www.nitrc.org/projects/bcilab/ Website] | ||
[https://github.com/sccn/BCILAB GitHub] | [https://github.com/sccn/BCILAB GitHub] | ||
Latest revision as of 22:07, 11 April 2022
BCILAB is a MATLAB toolbox for Brain-Computer Interface (BCI) research. It facilitates the design and development of new methods for cognitive state estimation and their use in both offline data analysis and real-time applications. BCILAB includes an easily extensible collection of currently over 100 methods from the literature (covering signal processing, machine learning and BCI-specific methods). Aside from supporting advanced BCI research, a special aim of BCILAB is to facilitate the adoption of machine learning and advanced statistical modeling for functional neuroimaging purposes in tandem with the EEGLAB platform.