Investigating cortical encoding of auditory space & motion in humans using EEG - BEDNAR, ADAM (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2020)
This work uses a novel linear regression-based framework together with scalp recorded electroencephalography (EEG) to study various aspects of spatial hearing in humans. In our first study, we showed that in an acoustic scene with one sound source, auditory cortex tracks the time-varying location of a continuously moving sound. Specifically, we identified two distinct frequency components, namely, delta (0-2Hz) and the alpha power (8-12Hz) of EEG that track the sound location. The delta and the power of alpha EEG encoding had different spatio-temporal characteristics, which suggested that they potentially reflect different aspects of auditory motion processing. Importantly, we also showed that the trajectory tracking is not specific to a particular type of spatial acoustic cue and is independent from the well-known sound envelope tracking of the cortex. In our second study we created an experiment where subjects listened to two concurrent sound stimuli that were moving independently within the horizontal plane and were tasked with paying attention to one of them. We showed that the attended sound source trajectory can be reliably reconstructed from EEG, even in the presence of other competing sources and demonstrated that the trajectory tracking works for noise as well as more complex speech stimuli. We also observed weak tracking of the unattended source location for the speech stimuli, however, this applied only to delta but not to the alpha power EEG component. This further suggests that location tracking by delta and alpha power EEG possibly represent different neural mechanisms. Finally, with more practical applications in mind, we demonstrated that the trajectory reconstruction approach can be used to decode selective attention. In our third study we investigated cortical sensitivity to sound position, velocity, speed and acceleration. We found that sound speed but not velocity can be reconstructed from EEG independently from sound position. Surprisingly, our results also indicated that sound acceleration might be independently represented at the cortical level, which has not been reported before. In the last study, we deployed our reconstruction method in a naturalistic scenario where subjects were allowed to move their heads and received visual input over a virtual reality headset. We were primarily interested in whether sound location is cortically encoded using cranio- or allo-centric coordinates. Although our initial analysis indicated a cranio-centric representation of sound location, we were not able to reconstruct the trajectory from EEG after we removed the head motion-related artefacts. Therefore, we were unable to find strong evidence for cortical encoding in either frame of reference. Our secondary goal was to test the feasibility of using the Oculus Rift headset together with EEG recording. Although we found it is possible to use this setup, we have encountered several practical issues, such as subject discomfort during longer recordings that need to be addressed.
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Keywords: sound; localization; cocktail party; motion; attention; electroencephalography