Attention or prediction? Characterizing the top-down influence of predictive context on speech encoding

Theories of predictive coding propose that perception is the process of inferring the causes of our sensory input by comparing that input with predictions derived from our internal models of the world. Such predictive processes are thought to play a central role in language comprehension, however, robust neurophysiological evidence for such processes, particularly during natural speech perception, remains limited. Previous work has suggested that the early auditory encoding of words in natural speech is influenced by their preceding linguistic context. However, it remains unclear whether this effect is driven by prediction per se or dynamic modulations of attention based on contextual uncertainty. To distinguish between these alternatives, we recorded electroencephalography from 17 healthy adults while they listened to slightly changed audiobook. Specifically, we identified and replaced several unsurprising content words with more surprising words. We quantified the early auditory encoding of words using speech-envelope reconstruction accuracy within 100-ms time window after word onset and examined its relationship to word surprisal and contextual uncertainty. We found that more surprising words showed enhanced early auditory encoding despite matched contextual constraint. Moreover, the temporal profile of this enhancement depended on when the incoming speech signal diverged from the predicted phonological sequence, consistent with the emergence of prediction-error responses. Linear mixed-effects modeling further revealed that word surprisal had a substantially stronger influence on early auditory encoding than contextual uncertainty. Together, these findings indicate that the early auditory encoding of words during naturalistic speech perception is more strongly associated with predictive computations than with uncertainty-driven attentional gain.