NEUROPSYCHOLOGY

Brain-Computer Interfaces translate parameters of brain activity into signals to control external devices, such as computers or prostheses. Recent developments have demonstrated that Brain Computer Interfaces can be used successfully to control the motion of wheel chairs, a computer program such as Google Earth, and to aid writing and communicating. We aim at providing the basics for BCI applications, by exploring the feasibility of real time analysis of data from brain imaging methods such as EEG and NIRS, as well as comparing the usefulness of different mental tasks for control purposes. Our real-time data analysis methods are further employed for the research into training effects by neurofeedback. This research is conducted in labs at the University Graz as well as at the Technical University Graz.

Selected Publications:

Brunner C., Allison B.Z., Krusienski D.J., Kaiser V., Müller-Putz G.R., Pfurtscheller G., Neuper C. (2010). Improved signal processing approaches in an offline simulation of a hybrid brain–computer interface. Journal of Neuroscience Methods, 188, 165-173. [PDF]

Friedrich E.V.C., Scherer R., Sonnleitner K., Neuper C. (2011). Impact of auditory distraction on user performance in a brain–computer interface driven by different mental tasks. Clinical Neurophysiology, in press. [PDF]

Kübler A, Neuper C (2008). Gehirn-Computer-Schnittstellen (Brain-Computer Interfaces): Anwendungen und Perspektiven. Neuroforum, 3, 204-210. [PDF]

Pfurtscheller G., Bauernfeind G., Wriessnegger S.C., Neuper C. (2010). Focal frontal (de)oxyhemoglobin responses during simple arithmetic. International Journal of Psychophysiology, 76, 186-192. [PDF]

	Neuropsychology / Research Areas / Brain-Computer Interface


	Brain-Computer Interface (BCI)


	Brain-Computer Interfaces translate parameters of brain activity into signals to control external devices, such as computers or prostheses. Recent developments have demonstrated that Brain Computer Interfaces can be used successfully to control the motion of wheel chairs, a computer program such as Google Earth, and to aid writing and communicating. We aim at providing the basics for BCI applications, by exploring the feasibility of real time analysis of data from brain imaging methods such as EEG and NIRS, as well as comparing the usefulness of different mental tasks for control purposes. Our real-time data analysis methods are further employed for the research into training effects by neurofeedback. This research is conducted in labs at the University Graz as well as at the Technical University Graz. Selected Publications: Brunner C., Allison B.Z., Krusienski D.J., Kaiser V., Müller-Putz G.R., Pfurtscheller G., Neuper C. (2010). Improved signal processing approaches in an offline simulation of a hybrid brain–computer interface. Journal of Neuroscience Methods, 188, 165-173. [PDF] Friedrich E.V.C., Scherer R., Sonnleitner K., Neuper C. (2011). Impact of auditory distraction on user performance in a brain–computer interface driven by different mental tasks. Clinical Neurophysiology, in press. [PDF] Kübler A, Neuper C (2008). Gehirn-Computer-Schnittstellen (Brain-Computer Interfaces): Anwendungen und Perspektiven. Neuroforum, 3, 204-210. [PDF] Pfurtscheller G., Bauernfeind G., Wriessnegger S.C., Neuper C. (2010). Focal frontal (de)oxyhemoglobin responses during simple arithmetic. International Journal of Psychophysiology, 76, 186-192. [PDF]