期刊
JOURNAL OF NEUROSCIENCE
卷 37, 期 27, 页码 6539-6557出版社
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.3267-16.2017
关键词
fMRI; natural stimuli; regression; speech
资金
- National Science Foundation [1151208203]
- National Eye Institute [EY019684]
- National Institute on Deafness and Other Communication Disorders [NIDCD 007293]
- Center for Science of Information, a National Science Foundation Science and Technology Center [CCF-0939370]
- William Orr Dingwall Neurolinguistics Fellowship
- Career Award at the Scientific Interface from the Burroughs-Wellcome Fund
- Direct For Computer & Info Scie & Enginr [1208203] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems [1208203] Funding Source: National Science Foundation
Speech comprehension requires that the brain extract semantic meaning from the spectral features represented at the cochlea. To investigate this process, we performed an fMRI experiment in which five men and two women passively listened to several hours of natural narrative speech. We then used voxelwise modeling to predict BOLD responses based on three different feature spaces that represent the spectral, articulatory, and semantic properties of speech. The amount of variance explained by each feature space was then assessed using a separate validation dataset. Because some responses might be explained equally well by more than one feature space, we used a variance partitioning analysis to determine the fraction of the variance that was uniquely explained by each feature space. Consistent with previous studies, we found that speech comprehension involves hierarchical representations starting in primary auditory areas and moving laterally on the temporal lobe: spectral features are found in the core of A1, mixtures of spectral and articulatory in STG, mixtures of articulatory and semantic in STS, and semantic in STS and beyond. Our data also show that both hemispheres are equally and actively involved in speech perception and interpretation. Further, responses as early in the auditory hierarchy as in STS are more correlated with semantic than spectral representations. These results illustrate the importance of using natural speech in neuro-linguistic research. Our methodology also provides an efficient way to simultaneously test multiple specific hypotheses about the representations of speech without using block designs and segmented or synthetic speech.
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