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RTs in conversation, with average gaps of 200 msec and often less, beat standard RTs, despite the complexity of response and the lag in speech production (600 msec or more). This can only be achieved by anticipation of timing and content of turns in conversation, about which little is known. Using EEG and an experimental task with conversational stimuli, we show that estimation of turn durations are based on anticipating the way the turn would be completed. We found a neuronal correlate of turn-end anticipation localized in ACC and inferior parietal lobule, namely a beta-frequency desynchronization as early as 1250 msec, before the end of the turn. We suggest that anticipation of the other's utterance leads to accurately timed transitions in everyday conversations.

Oscillatory neuronal dynamics, observed in the human electroencephalogram (EEG) during language processing, have been related to the dynamic formation of functionally coherent networks that serve the role of integrating the different sources of information needed for understanding the linguistic input. To further explore the functional role of oscillatory synchrony during language processing, we quantified event-related EEG power changes induced by the presentation of open-class (OC) words and closed-class (CC) words in a wide range of frequencies (from 1 to 30 Hz), while subjects read a short story. Word presentation induced three oscillatory components: a theta power increase (4-7 Hz), an alpha power decrease (10-12 Hz), and a beta power decrease (16-21 Hz). Whereas the alpha and beta responses showed mainly quantitative differences between the two word classes, the theta responses showed qualitative differences between OC words and CC words: A theta power increase was found over left temporal areas for OC words, but not for CC words. The left temporal theta increase may index the activation of a network involved in retrieving the lexical-semantic properties of the OC items.