The perception of self-motion draws on inputs from the visual, vestibular and proprioceptive systems. Decades of behavioural research has shed light on constructs such as multisensory weighting, heading perception, and sensory thresholds, that are involved in self-motion perception. Despite the abundance of knowledge generated by behavioural studies, there is a clear lack of research exploring the neural processes associated with full-body, multisensory self-motion perception in humans. Much of what is known about the neural correlates of self-motion perception comes from either the animal literature, or from human neuroimaging studies only administering visual self-motion stimuli. The goal of this thesis was to bridge the gap between understanding the behavioural correlates of full-body self-motion perception, and the underlying neural processes of the human brain. We used a high-fidelity motion simulator to manipulate the interaction of the visual and vestibular systems to gain insights into cognitive processes related to self-motion perception. The present line of research demonstrated that theta, alpha and beta oscillations are the underlying electrophysiological oscillations associated with self-motion perception. Specifically, the three empirical chapters combine to contribute two main findings to our understanding of self-motion perception. First, the beta band is an index of visual-vestibular weighting. We demonstrated that beta event-related synchronization power is associated with visual weighting bias, and beta event-related desynchronization power is associated with vestibular weighting bias. Second, the theta band is associated with direction processing, regardless of whether direction information is provided through the visual or vestibular system. This research is the first of its kind and has opened the door for future research to further develop our understanding of biomarkers related to self-motion perception. / Dissertation / Doctor of Philosophy (PhD) / As we move through the environment, either by walking, or operating a vehicle, our senses collect many different kinds of information that allow us to perceive factors such as, how fast we are moving, which direction we are headed in, or how other objects are moving around us. Many of our senses take in very different information, for example, the vestibular system processes information about our head movements, while our visual system processes information about incoming light waves. Despite how different all of this self-motion information can be, we still manage to have one smooth perception of our bodies moving through the environment. This smooth perception of self-motion is due to our senses sharing information with one another, which is called multisensory integration. Two of the most important senses for collecting information about self-motion are the visual and vestibular systems. To this point, very little is known about the biological processes in the brain while the visual and vestibular systems integrate information about self-motion. Understanding this process is limited because until recently, we have not had the technology or the methodology to adequately record the brain while physically moving people in a virtual environment. Our team developed a ground-breaking set of methodologies to solve this issue, and discovered key insights into brainwave patterns that take place in order for us to perceive ourselves in motion. There were two critical insights from our line of research. First, we identified a specific brainwave frequency (beta oscillations) that indexes integration between the visual and vestibular systems. Second, we demonstrated another brainwave frequency (theta oscillation) that is associated with perceiving which direction we are headed in, regardless of which sense this direction information is coming from. Our research lays the foundation for our understanding of biological processes of self-motion perception and can be applied to diagnosing vestibular disorders or improving pilot simulator training.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/28043 |
| Date | January 2022 |
| Creators | Townsend, Peter |
| Contributors | Shedden, Judith, Psychology |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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