Abstract
ABSTRACTAuditory speech comprehension is a multi-faceted process in which attention, prediction, and sensorimotor integration (via active sensing) interact with or complement each other. Although different conceptual models that focus on one of these aspects exist, we still lack a unified understanding of their role in speech processing. Here, we replicated and extended two recently published studies from our lab to investigate the influence of prediction tendency on ocular and neural tracking of attended speech. We propose that selective attention guides ocular speech tracking, which in turn mediates neural encoding of speech. In contrast, individual prediction tendency and its relation to neural speech tracking seem to be largely independent of attention. Importantly, prediction tendency and ocular speech tracking seem to be unrelated. With the current work, we propose a framework that aims to bridge the gaps between attention, prediction, and active (ocular) sensing in order to contribute to a holistic understanding of neural speech processing.
Publisher
Cold Spring Harbor Laboratory
Reference39 articles.
1. The Psychophysics Toolbox
2. Brodbeck, C. , Das, P. , Kulasingham, J. P. , Bhattasali, S. , Gaston, P. , Resnik, P. , & Simon, J. Z . (2021). Eelbrain: A Python toolkit for time-continuous analysis with temporal response functions. BioRxiv, 2021.08.01.454687. https://doi.org/10.1101/2021.08.01.454687
3. Continuous speech processing;Current Opinion in Physiology,2020
4. Semantic Context Enhances the Early Auditory Encoding of Natural Speech
5. Bambi: A simple interface for fitting Bayesian linear models in Python;ArXiv Preprint ArXiv,2020
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献