Auditory skills and brain morphology predict individual differences in adaptation to degraded speech
Auditory skills and brain morphology predict individual differences in adaptation to degraded speech
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DOI：
10.1016/j.neuropsychologia.2012.05.013
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发表时间：
2012-07-01
期刊：
影响因子：
2.6
通讯作者：
Obleser, Jonas
中科院分区：
文献类型：
--
作者：
Erb, Julia;Henry, Molly J.;Obleser, Jonas
噪声声码语音是一种频谱高度退化的信号，但它保留了语音的时间包络。听众在适应这种退化的语音信号的能力上有很大的差异。在这里，我们假设，个体差异的适应声码语音应该是可预测的非语音听觉，认知和神经解剖因素。我们测试了18名听力正常的参与者在短期语音编码的语音学习范式（听100个4波段语音编码的句子）。非言语听觉技能进行了评估，使用幅度调制（AM）率歧视，其中调制率集中在4赫兹的语音相关率。工作记忆能力进行了评估（数字广度和非字重复），和结构MRI扫描进行了检查的声编码语音学习的解剖预测使用基于体素的形态测量。在AM辨别任务中，学会更快理解退化语音的听众也表现出更小的阈值。这种适应退化语言的能力在解剖学上进一步反映在左丘脑（枕）区域的灰质体积增加上，该区域与听觉和前额叶皮质密切相关。因此，个人非言语听觉技能和左丘脑灰质体积可以预测听众适应退化语音的速度。(C)2012爱思唯尔有限公司保留所有权利。
Noise-vocoded speech is a spectrally highly degraded signal, but it preserves the temporal envelope of speech. Listeners vary considerably in their ability to adapt to this degraded speech signal. Here, we hypothesised that individual differences in adaptation to vocoded speech should be predictable by non-speech auditory, cognitive, and neuroanatomical factors. We tested 18 normal-hearing participants in a short-term vocoded speech-learning paradigm (listening to 100 4-band-vocoded sentences). Non-speech auditory skills were assessed using amplitude modulation (AM) rate discrimination, where modulation rates were centred on the speech-relevant rate of 4 Hz. Working memory capacities were evaluated (digit span and nonword repetition), and structural MRI scans were examined for anatomical predictors of vocoded speech learning using voxel-based morphometry. Listeners who learned faster to understand degraded speech also showed smaller thresholds in the AM discrimination task. This ability to adjust to degraded speech is furthermore reflected anatomically in increased grey matter volume in an area of the left thalamus (pulvinar) that is strongly connected to the auditory and prefrontal cortices. Thus, individual non-speech auditory skills and left thalamus grey matter volume can predict how quickly a listener adapts to degraded speech. (C) 2012 Elsevier Ltd. All rights reserved.