title: Deciphering phonemes from syllables in blood oxygenation level-dependent signals in human superior temporal gyrus.
abstract: Linguistic units such as phonemes and syllables are important for speech perception. How the brain encodes these units is not well understood. Many neuroimaging studies have found distinct representations of consonant-vowel syllables that shared one phoneme and differed in the other phoneme (e.g. /ba/ and /da/), but it is unclear whether this discrimination ability is due to the neural coding of phonemes or syllables. We combined functional magnetic resonance imaging with multivariate pattern analysis to explore this question. Subjects listened to nine Mandarin syllables in a consonant-vowel form. We successfully decoded phonemes from the syllables based on the blood oxygenation level-dependent signals in the superior temporal gyrus (STG). Specifically, a classifier trained on the cortical patterns elicited by a set of syllables, which contained two phonemes, could distinguish the cortical patterns elicited by other syllables that contained the two phonemes. The results indicated that phonemes have unique representations in the STG. In addition, there was a categorical effect, i.e. the cortical patterns of consonants were similar, and so were the cortical patterns of vowels. Further analysis showed that phonemes exhibited stronger encoding specificity in the mid-STG than in the anterior STG.
authors.affiliation: Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and Technology, Tsinghua University, Room 4-504, FIT Building, Beijing, 100084, China.
authors.forename: Qingtian
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and Technology, Tsinghua University, Room 4-504, FIT Building, Beijing, 100084, China.|Center for Brain-Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Hu
authors.affiliation: Department of Psychology, Peking University, Beijing, China.|IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
authors.forename: Huan
authors.initials: H
authors.lastname: Luo
authors.affiliation: Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and Technology, Tsinghua University, Room 4-504, FIT Building, Beijing, 100084, China.
authors.forename: Jianmin
authors.initials: J
authors.lastname: Li
authors.affiliation: Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and Technology, Tsinghua University, Room 4-504, FIT Building, Beijing, 100084, China.
authors.forename: Xiaolu
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and Technology, Tsinghua University, Room 4-504, FIT Building, Beijing, 100084, China.|Center for Brain-Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Bo
authors.initials: B
authors.lastname: Zhang
mesh_terms: D000328:Adult; D001303:Auditory Cortex / Q000098:blood supply / Q000502:physiology*; D001931:Brain Mapping; D006801:Humans; D008037:Linguistics; D008297:Male; D010100:Oxygen / Q000097:blood*; D013067:Speech Perception
chemical_list: D010100:Oxygen
keywords: auditory processing; functional magnetic resonance imaging; multivariate analysis; pattern classification; speech perception