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Lee M. Miller
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Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2021) 33 (4): 574–593.
Published: 01 April 2021
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In recent years, a growing number of studies have used cortical tracking methods to investigate auditory language processing. Although most studies that employ cortical tracking stem from the field of auditory signal processing, this approach should also be of interest to psycholinguistics—particularly the subfield of sentence processing—given its potential to provide insight into dynamic language comprehension processes. However, there has been limited collaboration between these fields, which we suggest is partly because of differences in theoretical background and methodological constraints, some mutually exclusive. In this paper, we first review the theories and methodological constraints that have historically been prioritized in each field and provide concrete examples of how some of these constraints may be reconciled. We then elaborate on how further collaboration between the two fields could be mutually beneficial. Specifically, we argue that the use of cortical tracking methods may help resolve long-standing debates in the field of sentence processing that commonly used behavioral and neural measures (e.g., ERPs) have failed to adjudicate. Similarly, signal processing researchers who use cortical tracking may be able to reduce noise in the neural data and broaden the impact of their results by controlling for linguistic features of their stimuli and by using simple comprehension tasks. Overall, we argue that a balance between the methodological constraints of the two fields will lead to an overall improved understanding of language processing as well as greater clarity on what mechanisms cortical tracking of speech reflects. Increased collaboration will help resolve debates in both fields and will lead to new and exciting avenues for research.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2009) 21 (9): 1790–1804.
Published: 01 September 2009
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In noisy environments, listeners tend to hear a speaker's voice yet struggle to understand what is said. The most effective way to improve intelligibility in such conditions is to watch the speaker's mouth movements. Here we identify the neural networks that distinguish understanding from merely hearing speech, and determine how the brain applies visual information to improve intelligibility. Using functional magnetic resonance imaging, we show that understanding speech-in-noise is supported by a network of brain areas including the left superior parietal lobule, the motor/premotor cortex, and the left anterior superior temporal sulcus (STS), a likely apex of the acoustic processing hierarchy. Multisensory integration likely improves comprehension through improved communication between the left temporal–occipital boundary, the left medial-temporal lobe, and the left STS. This demonstrates how the brain uses information from multiple modalities to improve speech comprehension in naturalistic, acoustically adverse conditions.