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The neurophysiological studies covered by the subject of Brain-Computer Interfaces (BCIs) (del R. Millan et al., 2004; Lebedev & Nicolelis, 2006; Wolpaw et al., 2002) represent a promising, but so far rather undiscovered, area of research. What is perhaps the most interesting part of BCI research is the idea of understanding the information coding in the brain and its use when performing different predefined actions or commands. Recent reports have proposed various techniques for the development of BCIs, based either on the electroencephalographic (EEG) non-invasive (Birbaumer et al., 1999; Wolpaw & McFarland, 2004), invasive (Taylor et al., 2002; Wessberg et al., 2000), magnetoencephalographic (MEG) (Georgopoulos et al., 2005; Mellinger et al., 2007) or other (fMRI, PET, optical imaging) measurements. Since all of these, except EEG, still represent technically demanding and expensive methods, the EEG-based BCIs tend to prevail. Modern BCIs are often classified into several groups based on the electrophysiological signals used, i.e., the different brain potentials (evoked visual, slow cortical, P300 evoked), the mu and beta rhythms, the activities of single cortical neurons, etc. (Wolpaw et al., 2002). The human brain can be considered as a system of highly interconnected groups of neurons, where each neuron or group acts as an oscillator. When the brain is in a certain mode or state, different groups of these neurons synchronize themselves to a certain physiological frequency. In order to achieve a large-scale neuronal synchronization that is detectable, for instance, when using an EEG, several tens of thousands of neurons need to fire at approximately the same time with respect to a neuronal population that has approximately the same spatial orientation. It is believed that the theory of oscillations represents one of the essential mechanisms of brain operation, as studies have shown that every single process in the brain is probably within the neuronal system mediated by means of the electric oscillations of the neuronal populations (Engel et al., 2001). These oscillations or oscillatory activity can be classified into different frequency bands and are referred to as the brain rhythms ([0.5 − 3Hz] – delta, [4 − 7HZ] – theta, [8 − 12Hz] – alpha, [13 − 30Hz] – beta, [30 − 50Hz] – gamma). It is suggested that the synchronization of the oscillatory activity carries out the brain’s functionality, cognition and behavior, which are based on distributed, parallel information processing and exchange between anatomically not necessarily connected neuronal populations (Ivanitsky et al., 2001; Manganotti et al., 1998; Pfurtscheller & Andrew, 1999). When a collaboration of neuronal populations is necessary to 7

Visuo-Motor Tasks in a Brain-Computer Interface Analysis