Behavioural and neural correlates of auditory expectation and their implications for understanding auditory hallucinations

Normal perception relies on predictive coding, in which neural networks establish associations among stimuli and form predictions of expected input. When the actual stimulus does not match the prediction (i.e. it is unexpected) a signal called prediction error is generated. Prediction error modifies expectation and allows correct perception of external sounds. The work presented here investigated the mechanisms of auditory predictive coding in healthy individuals that might relate to abnormal auditory predictions in auditory hallucinations. A task with pairs of associated stimuli was developed in order to induce learning of relationships between visual cues and auditory outcomes. Whilst the majority of the auditory stimuli were presented within the learnt associations (i.e. they were expected), the minority appeared in mismatched pairs (i.e. they were unexpected). It was hypothesised that auditory outcomes that violate the expectation would evoke increased response time and neural activity compared with those that match expectation. Auditory expectation as induced in the task employed in this work had only a trend-level effect on response time. Functional MRI studies revealed that unexpected, compared with expected, sounds and silences evoked increased activation in the left middle temporal gyrus. Unexpected sounds, but not unexpected silence, versus those expected, evoked greater activation in the left superior temporal gyrus. The increased response to unexpected, compared with expected, sounds and silences, suggests that left superior and middle temporal gyri are involved in processing auditory stimuli that do not match expectation, i.e. generating auditory prediction error. These findings suggest that the superior and middle temporal gyrus perform different functions in integrating sensory information with predictive signals during auditory perception. The results are discussed in terms of a model of auditory predictive coding in normal perception, and suggest how this model may help explain the occurrence of auditory hallucinations in clinical populations.EThOS - Electronic Theses Online ServiceGBUnited Kingdo