Is that clear? Robust electrophysiological measures of the effects of prior knowledge on degraded speech perception.
Synigal, S. R.; Li, W.; Serody, M. R.; Thompson, J. L.; Lalor, E. C.
Show abstract
Perception and sensation are not synonymous. Rather, perception is a process whereby sensory input is organized and interpreted in a behaviorally relevant way based on memory, experience, and context. One specific framework that is commonly invoked to explain perception is that of Bayesian inference. This framework casts perception as a probabilistic process whereby imprecise sensory data are combined with prior knowledge (prior) to determine what is consciously perceived (the posterior probability), which reflects the brains best guess as to the cause(s) of the sensory data. A striking behavioral example of how prior information can influence perception is seen in studies in which degraded speech is rendered intelligible by presenting information about the speech content in advance. Neurophysiological studies of this phenomenon have primarily focused on how it affects neural indices of low-level sensory encoding. The size of any reported effects on these indices tends to be much smaller - and much less consistent - than the notably large effects on perception that come with prior information. In the present study, we recorded EEG from 27 healthy adult participants (16 female) as they listened to degraded speech clips that were preceded by matching or mismatching text. Prior knowledge in the form of matching text led to a large perceptual pop-out effect when listening to degraded speech. Analyses of the resulting EEG revealed: 1) significant but relatively weak effects of prior information on EEG measures of the linguistic encoding of speech; and 2) a very large effect of prior information on an EEG signal that resembles a well-established neural index of perceptual evidence accumulation and that was strongly related to speech intelligibility ratings across participants. These EEG signals likely relate to separate components of a Bayesian inferential process during the predictive perception of degraded speech. As such, they have implications for understanding predictive perception more broadly and for future research on perceptual disturbances in clinical populations.
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