Motor and Context Information in the Attenuation of Auditory ERP Amplitudes
Year: 2024
Type: dissertation
Abstract: The attenuation of neuronal responses to sounds that are produced by our own actions compared to sounds that we perceive in the environment has been suspected to result from sensory predictions that are matched to the actual sensory input we receive. The classic explanation is that of cerebellar forward models, which use information about planned motor activity to generated predictions, and attenuate sensory processing for correctly predicted stimuli. However, self- and externally generated sounds also differ in their temporally predictability, and temporally predictable externally generated sounds indeed display an attenuation of the N1 ERP component in EEG studies that is similar to that for self-generated sounds. The studies in this dissertation have added evidence for separate systems of sensory predictions based on temporal predictability, and motor-information. Study 2 showed that the N1 attenuation for observed motor acts developed slower over time when viewed from a first- instead of a third-person perspective, possibly as an effect of familiarity with third-person action observation. In Study 3, we reported an N1 attenuation for pro-, but not anti-saccade generated sounds, which are likely suffering from a disturbance of the forward model system. Crucially, the effects in both studies were found despite equal temporal predictability between motor related conditions, suggesting an independent influence of motor information based predictive processing. In study 1 we confirmed that assumptions about the context sounds are produced in impact not the N1, but the P2 component, which might reflect an aspect of the sense of agency. These studies also demonstrated the value of the analysis of ERP amplitude time courses as an important tool to uncover differing temporal patterns that would be hidden in aggregated datasets.
Author: Seidel, Alexander
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7002181980