fMRI analysis on the GPU-Possibilities and challenges
Computer Methods and Programs in Biomedicine
Online semi-supervised ensemble updates for fMRI data
PSL'11 Proceedings of the First IAPR TC3 conference on Partially Supervised Learning
Semi-supervised ensemble update strategies for on-line classification of fMRI data
Pattern Recognition Letters
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We present the first step towards a brain computer interface (BCI) for communication using real-time functional magnetic resonance imaging (fMRI). The subject in the MR scanner sees a virtual keyboard and steers a cursor to select different letters that can be combined to create words. The cursor is moved to the left by activating the left hand, to the right by activating the right hand, down by activating the left toes and up by activating the right toes. To select a letter, the subject simply rests for a number of seconds. We can thus communicate with the subject in the scanner by for example showing questions that the subject can answer. Similar BCI for communication have been made with electroencephalography (EEG). In these implementations the subject for example focuses on a letter while different rows and columns of the virtual keyboard are flashing. The system then tries to detect if the correct letter is flashing or not. In our setup we instead classify the brain activity. Our system is not limited to a communication interface, but can be used for any interface where five degrees of freedom is necessary.