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Neural mechanisms of auditory feedback during speech

Neural mechanisms of auditory feedback during speech
言语过程中听觉反馈的神经机制
批准号:
6920704
负责人:
SRIKANTAN S. NAGARAJAN
金额:
$45.21万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-07-15 至 2009-06-30

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中文摘要
翻译
描述(由申请人提供):了解在说话过程中听觉反馈是如何处理的,可以深入了解语音产生和感知的基本机制。这种知识也可能最终有助于早期发现,并导致治疗策略的一些流行的临床条件下,在异常处理听觉反馈的损害已被报告(例如口吃,帕金森氏病,精神分裂症)。虽然许多行为研究已经研究了听觉感知如何影响语音产生,但直到最近才开始研究功能性神经影像学研究如何影响语音产生的神经过程。最近的研究表明,在听觉皮层和上级颞平面的其他区域,说话引起“说话诱导抑制”(SIS):与来自外部来源的相同语音相比,对自我产生的语音的反应受到抑制。在我们最近的工作中,我们已经表明,SIS在听觉皮层并不导致在说话过程中,这方面的全面抑制。相反,SIS似乎是反馈预测误差(FPE)的神经相关-实际听觉输入和该听觉输入的内部“说话诱导预测”(SIP)之间的比较。SIS在听觉皮层的表达导致了这样的假设,即SIS反映了自我产生的听觉辨别来自外部产生的刺激(自我-非自我假说)。然而,在我们的理解的听觉反馈在言语运动控制,这是由行为研究和我们的初步数据支持的改进,表明SIS也可能反映反馈处理的言语运动控制(言语运动控制假说)。我们已经开发了一个统一的概念模型,体现了这两个假设,我们提出的实验使用SIS来测试神经相关性和这个模型的有效性。具体的目的是确定SIS是如何调制1)改变反馈,2)言语目标动态和3)言语运动适应。这些操作不仅帮助我们解开SIS的功能意义,但也帮助我们确定是否有SIS的功能分化的上级颞平面。此外,我们的实验操作如何影响大脑其他部位的活动,将使我们能够确定产生SIS的机制的神经相关性。我们的方法利用独特的实时语音反馈改变方法与功能磁共振成像(fMRI)和磁源成像(MSI)。功能磁共振成像良好的空间分辨率将使重建的空间位置的活动有关的SIS和SIP,而MSI的良好的时间分辨率将使我们能够重建的序列激活在这些领域。
英文摘要
DESCRIPTION (provided by applicant): Understanding how auditory feedback is processed during speaking provides insights into fundamental mechanisms underlying speech production and perception. This knowledge might also ultimately contribute to the early detection and lead to treatment strategies for a number of prevalent clinical conditions where impairments in abnormal processing of auditory feedback have been reported (e.g. stuttering, Parkinson's disease, schizophrenia). While many behavioral studies have examined how auditory perception affects speech production, only recently have functional neuroimaging studies begun examining how producing speech affects the neural processes serving auditory perception. Recent studies have shown that in auditory cortex and other areas in the superior temporal plane, speaking causes "speaking-induced suppression" (SIS): response to self-produced speech is suppressed when compared to identical speech from an external source. In our recent work, we have shown that SIS in auditory cortex does not result from overall inhibition of this area during speaking. Rather, SIS appears to be a neural correlate of a feedback prediction error (FPE) - a comparison between actual auditory input and an internal "speaking-induced prediction" (SIP) of that auditory input. SIS expression in auditory cortex has led to the hypothesis that SIS reflects auditory discrimination of self-produced from externally produced stimuli (Self-non-Self Hypothesis). However, refinements in our understanding of auditory feedback in speech motor control, that are supported by behavioral studies and our preliminary data, suggest that SIS may also reflect feedback processing for speech motor control (Speech Motor Control Hypothesis). We have developed a unifying conceptual model that embodies both hypotheses, and our proposed experiments use SIS to test the neural correlates and the validity of this model. The specific aims are to determine how SIS is modulated by 1) altered feedback, 2) speech target dynamics and 3) speech motor adaptation. These manipulations not only help us to unravel the functional significance of SIS but also help us determine if there is a differentiation of the function of SIS across the superior temporal plane. Furthermore, how activity in other parts of the brain is affected by our experimental manipulations will allow us to determine the neural correlates of the mechanisms that generate SIS. Our approach capitalizes on unique real-time speech feedback alteration methods used with functional magnetic resonance imaging (fMRI) and magnetic source imaging (MSI). The excellent spatial resolution of fMRI will enable reconstruction of spatial locations of activity related to SIS and SIP while the excellent temporal resolution of MSI will enable us to reconstruct the sequence of activation in these areas.
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Multimodal modeling framework for fusing structural and functional connectome data
  • 批准号:
    9360098
  • 项目类别:
  • 资助金额:
    $18.48万
  • 财政年份:
    2016
  • 负责人:
    SRIKANTAN S. NAGARAJAN
  • 依托单位:
Multimodal modeling framework for fusing structural and functional connectome data
Multimodal modeling framework for fusing structural and functional connectome data
Fusion of Electromagnetic Brain Imaging and fMRI
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