The goal of this project is to use multimodal (functional magnetic resonance imaging (fMRI) and electroencephalography (EEG)) neuroimaging methods to examine the nature of linguistic and non-linguistic influences on brainstem encoding of speech signals in adults. In direct conflict with the concept of auditory brainstem nuclei as passive relay stations for behaviorally-relevant signals, recent studies have demonstrated active transformation of the signal, as represented in the auditory midbrain and brainstem. However, the mechanisms underlying such early sensory plasticity are unclear. In this proposal, an integrative model of subcortical auditory plasticity is posited (predictive tunin), which argues for a continuous, online modulation of bottom-up signals via corticofugal pathways, based on an algorithm that constantly anticipates incoming stimulus regularities, thereby transforming representation in the auditory pathway. This proposal utilizes cross-language and case-control designs and innovative EEG methods to directly address the role of brainstem circuitry in dynamic encoding of speech and test competing neural models (local modulation vs. predictive tuning). Causal influences (top-down vs. bottom-up) during speech processing will be tested using fMRI effective connectivity analyses. The proposed experiments will provide a comprehensive examination of mechanisms underlying brainstem plasticity and expand the understanding of the neurobiology of speech perception beyond the current corticocentric focus. Recent studies show that a number of clinical populations exhibit speech-encoding deficits at the level of the brainstem. The design and analysis methods developed in this proposal can be used to evaluate the locus (bottom-up versus top-down) of such encoding deficits.

Public Health Relevance

The goal of this project is to study top-down influences on human brainstem function as it relates to the dynamics of speech processing. Understanding mechanistic aspects of human brainstem function the role of will provide critical insights into developing biomarkers that can evaluate the locus of speech processing deficits (bottom-up versus top-down) in clinical populations and monitor the effects of auditory and linguistic training.

National Institute of Health (NIH)
National Institute on Deafness and Other Communication Disorders (NIDCD)
Research Project (R01)
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Language and Communication Study Section (LCOM)
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Platt, Christopher
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University of Texas Austin
Other Health Professions
Schools of Arts and Sciences
United States
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Yi, Han-Gyol; Maddox, W Todd; Mumford, Jeanette A et al. (2016) The Role of Corticostriatal Systems in Speech Category Learning. Cereb Cortex 26:1409-20
Lau, Joseph Cy; Wong, Patrick Cm; Chandrasekaran, Bharath (2016) Context-dependent plasticity in the subcortical encoding of linguistic pitch patterns. J Neurophysiol :jn.00656.2016
Smayda, Kirsten E; Van Engen, Kristin J; Maddox, W Todd et al. (2016) Audio-Visual and Meaningful Semantic Context Enhancements in Older and Younger Adults. PLoS One 11:e0152773
Zhang, Fengqing; Jiang, Wenxin; Wong, Patrick et al. (2016) A Bayesian probit model with spatially varying coefficients for brain decoding using fMRI data. Stat Med :
Ettlinger, Marc; Morgan-Short, Kara; Faretta-Stutenberg, Mandy et al. (2016) The Relationship Between Artificial and Second Language Learning. Cogn Sci 40:822-47
Antoniou, Mark; Wong, Patrick C M (2016) Varying irrelevant phonetic features hinders learning of the feature being trained. J Acoust Soc Am 139:271-8
Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping et al. (2016) Resting-state low-frequency fluctuations reflect individual differences in spoken language learning. Cortex 76:63-78
Reetzke, Rachel; Maddox, W Todd; Chandrasekaran, Bharath (2016) The role of age and executive function in auditory category learning. J Exp Child Psychol 142:48-65
Chandrasekaran, Bharath; Yi, Han-Gyol; Smayda, Kirsten E et al. (2016) Effect of explicit dimensional instruction on speech category learning. Atten Percept Psychophys 78:566-82
Van Engen, Kristin J; Xie, Zilong; Chandrasekaran, Bharath (2016) Audiovisual sentence recognition not predicted by susceptibility to the McGurk effect. Atten Percept Psychophys :

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