Alex Brandmeyer: Auditory perceptual learning using decoded-EEG neurofeedback
This talk reports on the results of a study that applied a series of multivariate pattern classification analyses to an EEG dataset collected from native and non-native speakers of English to investigate these analyses’ ability to track ongoing passive auditory perception at the single-trial level. The research also includes a series of pilot studies in which a similar classification approach was used to realize a novel form of neurofeedback based on single-trial measurements of evoked responses to simple auditory tone stimuli.
I'm a PhD student in the Cognitive Artificial Intelligence department at the Donders Centre for Cognition, working in the Brain Computer Interface (BCI) research group. My main interests lie in multi-modal perception, music cognition, music and digital audio technologies, artificial intelligence, and cognitive neuroscience. Previously, I have participated in research on the perception of speech in noisy environments (Cocktail Party Effect), and the accompanying perceptual changes that occur with aging. I also did my Master's thesis and 3 years of technical work on the Practice Space project here in Nijmegen, developing real-time visual feedback technology for music education purposes.