Teresa Sollfrank

• Neural oscillations can be measured by electroencephalography (EEG) and these oscillations can be characterized by their frequency, amplitude and phase. The mechanistic properties of neural oscillations and their synchronization are able to explain various aspects of many cognitive functions such as motor control, memory, attention, information transfer across brain regions, segmentation of the sensory input and perception (Arnal and Giraud, 2012). The alpha band frequency is the dominant oscillation in the human brain. This oscillatoryNeural oscillations can be measured by electroencephalography (EEG) and these oscillations can be characterized by their frequency, amplitude and phase. The mechanistic properties of neural oscillations and their synchronization are able to explain various aspects of many cognitive functions such as motor control, memory, attention, information transfer across brain regions, segmentation of the sensory input and perception (Arnal and Giraud, 2012). The alpha band frequency is the dominant oscillation in the human brain. This oscillatory activity is found in the scalp EEG at frequencies around 8-13 Hz in all healthy adults (Makeig et al., 2002) and considerable interest has been generated in exploring EEG alpha oscillations with regard to their role in cognitive (Klimesch et al., 1993; Hanselmayr et al., 2005), sensorimotor (Birbaumer, 2006; Sauseng et al., 2009) and physiological (Lehmann, 1971; Niedermeyer, 1997; Kiyatkin, 2010) aspects of human life. The ability to voluntarily regulate the alpha amplitude can be learned with neurofeedback training and offers the possibility to control a brain-computer interface (BCI), a muscle independent interaction channel. BCI research is predominantly focused on the signal processing, the classification and the algorithms necessary to translate brain signals into control commands than on the person interacting with the technical system. The end-user must be properly trained to be able to successfully use the BCI and factors such as task instructions, training, and especially feedback can therefore play an important role in learning to control a BCI (Neumann and Kübler, 2003; Pfurtscheller et al., 2006, 2007; Allison and Neuper, 2010; Friedrich et al., 2012; Kaufmann et al., 2013; Lotte et al., 2013). The main purpose of this thesis was to investigate how end-users can efficiently be trained to perform alpha band modulation recorded over their sensorimotor cortex. The herein presented work comprises three studies with healthy participants and participants with schizophrenia focusing on the effects of feedback and training time on cortical activation patterns and performance. In the first study, the application of a realistic visual feedback to support end-users in developing a concrete feeling of kinesthetic motor imagery was tested in 2D and 3D visualization modality during a single training session. Participants were able to elicit the typical event-related desynchronisation responses over sensorimotor cortex in both conditions but the most significant decrease in the alpha band power was obtained following the three-dimensional realistic visualization. The second study strengthen the hypothesis that an enriched visual feedback with information about the quality of the input signal supports an easier approach for motor imagery based BCI control and can help to enhance performance. Significantly better performance levels were measurable during five online training sessions in the groups with enriched feedback as compared to a conventional simple visual feedback group, without significant differences in performance between the unimodal (visual) and multimodal (auditory–visual) feedback modality. Furthermore, the last study, in which people with schizophrenia participated in multiple sessions with simple feedback, demonstrated that these patients can learn to voluntarily regulate their alpha band. Compared to the healthy group they required longer training times and could not achieve performance levels as high as the control group. Nonetheless, alpha neurofeedback training lead to a constant increase of the alpha resting power across all 20 training session. To date only little is known about the effects of feedback and training time on BCI performance and cortical activation patterns. The presented work contributes to the evidence that healthy individuals can benefit from enriched feedback: A realistic presentation can support participants in getting a concrete feeling of motor imagery and enriched feedback, which instructs participants about the quality of their input signal can give support while learning to control the BCI. This thesis demonstrates that people with schizophrenia can learn to gain control of their alpha oscillations recorded over the sensorimotor cortex when participating in sufficient training sessions. In conclusion, this thesis improved current motor imagery BCI feedback protocols and enhanced our understanding of the interplay between feedback and BCI performance.…
• Die Wirksamkeit von Feedback und Trainingseffekten während der Alphaband Modulation über dem menschlichen sensomotorischen Cortex