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人类颞上回神经元的语音特异性调谐

Speech-specific tuning of neurons in human superior temporal gyrus.

作者信息

Chan Alexander M, Dykstra Andrew R, Jayaram Vinay, Leonard Matthew K, Travis Katherine E, Gygi Brian, Baker Janet M, Eskandar Emad, Hochberg Leigh R, Halgren Eric, Cash Sydney S

机构信息

Medical Engineering and Medical Physics, Department of Neurology.

Program in Speech and Hearing Bioscience and Technology, Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA, Department of Neurology.

出版信息

Cereb Cortex. 2014 Oct;24(10):2679-93. doi: 10.1093/cercor/bht127. Epub 2013 May 16.

Abstract

How the brain extracts words from auditory signals is an unanswered question. We recorded approximately 150 single and multi-units from the left anterior superior temporal gyrus of a patient during multiple auditory experiments. Against low background activity, 45% of units robustly fired to particular spoken words with little or no response to pure tones, noise-vocoded speech, or environmental sounds. Many units were tuned to complex but specific sets of phonemes, which were influenced by local context but invariant to speaker, and suppressed during self-produced speech. The firing of several units to specific visual letters was correlated with their response to the corresponding auditory phonemes, providing the first direct neural evidence for phonological recoding during reading. Maximal decoding of individual phonemes and words identities was attained using firing rates from approximately 5 neurons within 200 ms after word onset. Thus, neurons in human superior temporal gyrus use sparse spatially organized population encoding of complex acoustic-phonetic features to help recognize auditory and visual words.

摘要

大脑如何从听觉信号中提取单词仍是一个未解之谜。在多次听觉实验中,我们从一名患者的左侧前颞上回记录了约150个单神经元和多神经元活动。在低背景活动下,45%的神经元对特定的口语单词有强烈反应,而对纯音、噪声编码语音或环境声音几乎没有反应。许多神经元被调整到复杂但特定的音素集,这些音素集会受到局部语境的影响,但对说话者不变,并且在自我产生的语音过程中受到抑制。几个神经元对特定视觉字母的放电与它们对相应听觉音素的反应相关,这为阅读过程中的语音重新编码提供了首个直接神经证据。使用单词开始后200毫秒内约5个神经元的放电率,可实现对单个音素和单词身份的最大解码。因此,人类颞上回中的神经元使用稀疏的空间组织群体编码来处理复杂的声学语音特征,以帮助识别听觉和视觉单词。

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