- Title
- An exploration of how variability affects auditory mismatch negativity
- Creator
- Yeark, Mattsen
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2023
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Different states of the world create a range of sensory signals, some of which are essential to human survival and others that are irrelevant. The purpose of the brain is to determine meaningful states of the environment, based on the sensory input those states elicit from sensory systems. An example of a neurological response to changes in the environment is the Mismatch Negativity (MMN) component. This auditory event related potential is elicited when a regular pattern of sounds is interrupted. MMN is sensitive to a variety of different factors, ranging from mental disorders to stimulus probabilities, making it a prime candidate to test underlying differences in sensory learning. Although actively under development, there is yet to be a complete understanding of the factors that affect MMN and what underlying processes it represents. A popular theory is that the MMN is a neural correlate of a precision-weighted prediction error that reflects the difference between the stimulus input and the prediction made by the brain. What is under-explored is how these prediction errors function to update sensory predictions when there is different amounts of noise in the sensory system. The thesis introduction provides a review of the factors that have been shown to influence the MMN and an outline of each of the prevailing theories that explain it. Following this, three experimental papers are presented that each individually explore how different forms of stimulus variability can affect the way the brain detects changes in the auditory environment. The first paper explored whether alternate types of variability differentially modulate MMN amplitude. The results of this study suggested that relevant variability, that in the same domain as the deviant feature, may be more impactful. The second paper examined whether variability implemented across longer timescales affected MMN amplitude. This was done by adding a frequency change to each block of a longer sound sequence. No significant effect of variability was found, with the MMN continuing to show strong first learning patterns (Primacy Bias) in both the variability and no variability groups. The final paper examined whether the results of the first study were generalisable to a sound sequence consisting of different features and regularities. It was found that when spatial variability was added to a sound sequence with a duration deviant there was no significant effect of the variability. Combined, results of the three studies suggest that the MMN is sensitive to the type of deviating feature, the level at which it is implemented, and the type of noise introduced.
- Subject
- mismatch negativity; precision; predictive coding; variability
- Identifier
- http://hdl.handle.net/1959.13/1509723
- Identifier
- uon:56286
- Rights
- Copyright 2023 Mattsen Yeark
- Language
- eng
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 8 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 403 KB | Adobe Acrobat PDF | View Details Download |