A Brain-Computer Interface (BCI) provides a completely new output pathway and so an additional possible way a person can express himself if he/she suffers disorders like amyotrophic lateral sclerosis (ALS), brainstem stroke, brain or spinal cord injury or other diseases which impair the function of the common output pathways which are responsible for the control of muscles or impair the muscles. BCIs are used to control external devices such as virtual environments, orthotic, prosthetic, or spelling devices just to mention some of them. Therefore different EEG signals can be used for BCI control, for example slow cortical potentials, event related (de)synchronization, steady-state visual potentials, or the P300 event related potentials.
In this section an overall introduction into BCI research will be given. The four aforementioned signals for BCI control will be explained in detail. Furthermore their (dis)-advantages and potential use will be discussed. At the end a live demonstration of a BCI will be given.

From simple displacement of a cursor on a screen to fine-grained control of neuroprosthetic limbs, moving toward natural control with brain computer interfaces (BCI) will require providing physiologically relevant multisensory feedback to the brain. BCI users must also have the feeling that the output device is a natural extension of their own body in order to avoid biological rejection and to curb control frustration. Interestingly, in the cognitive neurosciences there exist several multisensory-driven bodily illusions that can experimentally manipulate bodily ownership of virtual or prosthetic limbs. These illusions serve as an ideal research platform to investigate how the brain integrates and interacts with BCIs.
In this talk I will discuss a series of experiments performed to investigate the electrophysiological mechanisms associated with illusory body parts ownership and their relationship to motor imagery. To unveil the neural mechanisms of illusory ownership of two virtual arms, we recorded high-density electroencephalography while participants experienced visuo-tactile stimulation on a 3D virtual body, receiving somatosensory stimulation via automated haptics. I will propose a promising application of our findings to the control of BCIs by demonstrating that physiologically relevant multisensory feedback can affect BCI performance. Finally, I will present preliminary results of studies that shed light on the limits of self-attribution of control while interacting with BCIs. These findings help isolate the conditions under which BCIs optimally function. Throughout the talk, emphasis will be on the manner in which we are applying cognitive and neuroscientific research to enhance non-invasive BCIs.

In this part we want to address the practical usage of Brain-Computer Interfaces. A BCI transforms the electrical brain activity into control signals, but what do we want to control with it? Especially since BCIs are no longer only used by healthy subjects under control conditions in laboratory environments, but by patients controlling applications at their homes, without the BCI experts around. Four major application areas can be identified where disabled individuals could greatly benefit from advancements in BCI technology, namely, "Communication and Control", "Motor Substitution", "Entertainment", and "Motor Recovery".
In this talk will focus on applications to mentally write a text via a virtual keyboard, to browse the Internet, to control a small mobile robot designed for telepresence applications or to control its own wheelchair. Since the BCI is not a perfect control channel techniques like shared control are used to enhance the interaction. Results of healthy subjects and patients will be presented and the outcomes will be compared. Furthermore future trends will be addressed.