High-level prediction of continuous speech during mind-wandering
Abstract
Abundant evidence shows that when listening to speech or reading text, we continuously make high-level predictions about upcoming words – their content, meaning, and relationship to the overall narrative. Does this process stop when our mind wanders away and conscious experience becomes decoupled from the content of the speech? Conversely, is word prediction sufficient for conscious experience, or can these processes dissociate? We conducted an EEG study where participants (N = 25) listened to audiobooks (>12,000 words) while occasionally providing self-reports of mind-wandering. In line with current accounts, mind-wandering was associated with spectral changes in the signal, compared to subjectively attentive listening, as well as decreased early response to word onset. However, neural markers of word-level contextual surprise (indexed by the contextual surprise of large language models) remained intact during mind-wandering, alongside significant encoding of semantic content. Last, we measured the neural encoding of predictive context, reflected by the correlation between brain activity and the vector embeddings that language models use to predict each word given prior context. This encoding also persisted during mind-wandering with a weak decline compared to on-task periods, pointing towards a decreased ability to integrate information from multiple words. Our findings show that the brain predicts and monitors relevant inputs even when the subjective experience of the external environment is dimmed during mind-wandering. It carries implications for theoretical accounts of both mind-wandering and conscious awareness. This study examines how spontaneous drifts in listening relate to EEG responses to continuous speech, using encoding models of semantic and contextual representations. It finds that neural markers of prediction, surprisal, and word meaning persist when the mind wanders away from speech contents, even as perceptual responses weaken.
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Authors: Gal Refael Chen, R. S. Finkelstein, Ariel Goldstein, Ran R. Hassin, Leon Y. Deouell
Institutions: Hebrew University of Jerusalem