Publications

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2013
Lu J, McFarland DJ, Wolpaw J. Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfaces. Journal of neural engineering [Internet]. 2013;10:016002. http://www.ncbi.nlm.nih.gov/pubmed/23220879PDF icon Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfaces.pdf (1.77 MB)
Brunner, Clemens, Andreoni G, Bianchi L, Blankertz B, Breitwieser C, Kanoh S, Lecuyer A, et al.. BCI Software Platforms. In Towards Practical Brain-Computer Interfaces [Internet]. Biological and Medical Physics; 2013. http://link.springer.com/chapter/10.1007/978-3-642-29746-5_16PDF icon BCI Software Platforms.pdf (0 bytes)
Morales-Flores E, Ramirez-Cortes J, Gomez-Gil P, Alarcon-Aquino V. Brain Computer Interface Development Based on Recurrent Neural Networks and ANFIS Systems. Soft Computing Applications in Optimization, Control and Recognition [Internet]. 2013;294. https://link.springer.com/chapter/10.1007/978-3-642-35323-9_9
Wolpaw J. Brain-computer interfaces. Handbook of clinical neurology [Internet]. 2013;110:67–74. http://www.ncbi.nlm.nih.gov/pubmed/23312631PDF icon Brain-computer interfaces. .pdf (1.61 MB)
Schalk G. Brain-Computer Interfaces Yesterday, Today, and Tomorrow: A Status Report of Bioengineering Research Partnership EB0085. 2013.
Schalk G. Brain-Computer Interfacing Using P300 Evoked Potentials. 2013.
Schalk G. Brain-Computer Interfacing Using P300 Evoked Potentials. 2013.
McFarland DJ. Characterizing multivariate decoding models based on correlated EEG spectral features. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology [Internet]. 2013;124:1297–1302. http://www.ncbi.nlm.nih.gov/pubmed/23466267PDF icon Characterizing multivariate decoding models based on correlated EEG spectral features.pdf (1.49 MB)
Schalk G. Communicating Directly With the Brain. 2013.
Prueckl R, Kapeller C, Potes C, Korostenskaja M, Schalk G, Lee KH, et al.. CortiQ - clinical software for electrocorticographic real-time functional mapping of the eloquent cortex. Conf Proc IEEE Eng Med Biol Soc [Internet]. 2013;2013:6365-8. http://www.ncbi.nlm.nih.gov/pubmed/24111197PDF icon CortiQ - clinical software for electrocorticographic real-time functional mapping of the eloquent cortex. .pdf (477.47 KB)
Prueckl R, Kapeller C, Potes C, Korostenskaja M, Schalk G, Lee KH, et al.. cortiQ – Clinical Software for Electrocorticographic Real-Time Functional Mapping of the Eloquent Cortex. 35th Annual International IEEE EMBS Conference (EMBC). 2013.
Schalk G. ECoG-Based Neuroscience and Neuroengineering. 2013.
Schalk G. Exciting Opportunities for Neuroengineering. 2013.
Schalk G. The Exciting World of Brain-Computer Interfaces. 2013.
Cacace AT, McFarland DJ. Factors Influencing Tests of Auditory Processing: A Perspective on Current Issues and Relevant Concerns. Journal of the American Academy of Audiology [Internet]. 2013;24:572–589. http://www.ncbi.nlm.nih.gov/pubmed/24047945PDF icon Factors Influencing Tests of Auditory Processing- A Perspective on Current Issues and Relevant Concerns. .pdf (19.34 MB)
Ramirez-Cortes J, -Carballido M, Alarcon-Aquino V, Gomez-Gil P, Morales-Flores E. FPGA-based educational platform for real-time image processing experiments. Computer Applications in Engineering Education [Internet]. 2013;21. http://www.researchgate.net/publication/227651194_FPGAbased_educational_platform_for_realtime_image_processing_experimentsPDF icon FPGA-based educational platform for real-time image processing experiments.pdf (1 MB)
Farquhar J, Jeremy Jeremy Hill. Interactions Between Pre-Processing and Classification Methods for Event-Related-Potential Classification : Best-Practice Guidelines for Brain-Computer Interfacing. Neuroinformatics [Internet]. 2013;. http://www.ncbi.nlm.nih.gov/pubmed/23250668PDF icon Interactions between pre-processing and classification methods for event-related-potential classification best-practice guidelines for brain-computer interfacing.pdf (391.32 KB)
Schalk G. Long-term Cortical Neuroprostheses: Prospects and Challenges. 2013.
Kubanek J, Snyder LH, Brunton BW, Brody CD, Schalk G. A low-frequency oscillatory neural signal in humans encodes a developing decision variable. NeuroImage [Internet]. 2013;83:795–808. http://www.ncbi.nlm.nih.gov/pubmed/23872495PDF icon A low-frequency oscillatory neural signal in humans encodes a developing decision variable.pdf (1.53 MB)

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