Reduce peripheral noise of a VEP-based Brain-Computer Interface using different colors
A Brain-Computer Interface (BCI) is an interface between the human brain and a computer. BCIs enable physically paralyzed patients, for example, to control a computer via pure brain activity. The currently best performing BCIs are based on the idea of Sutter, who stated that “the electrical scalp response to a modulated target is largest if the target is located within the central 1° of the visual field” and that “this makes it possible to construct a gaze-controlled keyboard”. However, although the response to visual stimuli within the central 1° of the visual field is largest, Sutter has also shown that responses can be measured in the peripheral parts of the visual field. This means that neighbored targets (letters) to the gazed target are also in the visual field and causes unwanted responses, which act as additional noise. Considering the structure of the human eye, there two types of photoreceptor cells: cones and rods, which are differently distributed over the retina. Cones are mainly located and densely packed in the central field and are responsible for color vision, whereas rods are mainly located at the outer parts of the retina and are used for peripheral vision. This lead to the assumption that visual stimuli, excluding the wavelengths to which the rods respond, should lead to less peripheral perception and therefore to less noise.
The aim of this work is to test the effect of different chromatic stimuli to the BCI performance. In order to evaluate this, it is necessary to test the system on itself as well as with other test persons. In this respect there will be an introduction on how to prepare an EEG.
- Interest in neuroscience
- Experience in MATLAB is beneficial (for EEG data analysis)