TY - JOUR T1 - In spoken word recognition the future predicts the past JF - bioRxiv DO - 10.1101/150151 SP - 150151 AU - Laura Gwilliams AU - Tal Linzen AU - David Poeppel AU - Alec Marantz Y1 - 2018/01/01 UR - http://biorxiv.org/content/early/2018/01/11/150151.abstract N2 - Speech is an inherently noisy and ambiguous signal. In order to fluently derive meaning, a listener must integrate contextual information to guide interpretations of the sensory input. While many studies have demonstrated the influence of prior context on speech perception, the neural mechanisms supporting the integration of subsequent context remain unknown. Using magnetoencephalography, we analysed responses to spoken words with a varyingly ambiguous onset phoneme, the identity of which is later disambiguated at the lexical uniqueness point1. Our findings suggest that primmary auditory cortex is sensitive to phonological ambiguity very early during processing — at just 50 ms after onset. Subphonemic detail is preserved in auditory cortex over long timescales, and re-evoked at subsequent phoneme positions. Commitments to phonological categories occur in parallel, resolving on the shorter time-scale of ~450 ms. These findings provide evidence that future input determines the perception of earlier speech sounds by maintaining sensory features until they can be integrated with top down lexical information.Significance statement The perception of a speech sound is determined by its surrounding context, in the form of words, sentences, and other speech sounds. Often, such contextual information becomes available later than the sensory input. The present study is the first to unveil how the brain uses this subsequent information to aid speech comprehension. Concretely, we find that the auditory system supports prolonged access to the transient acoustic signal, while concurrently making guesses about the identity of the words being said. Such a processing strategy allows the content of the message to be accessed quickly, while also permitting re-analysis of the acoustic signal to minimise parsing mistakes. ER -