神经振荡影响快速言语识别的时间瓶颈-365bet在线客服-365bet在线客服-365体育官网客户端-365heart

1 问题提出

在日常生活中, 大脑需要在短时间内快速处理大量信息, 如驾驶汽车在车流中穿梭, 如快速浏览音视频并实时获取信息。这种快速信息处理的能力让我们能够适应不断变化的环境。大脑如何快速地处理信息?其速率瓶颈来自于何处?这是心理学与神经科学的前沿热点问题, 至今尚未被完全破解。

快速言语的识别是快速信息处理的一个典型例子。人类的自然语速大约为每秒2~5个音节(Reynolds & Givens, 2001; Greenberg et al., 2003; Hyafil et al., 2015; Ding et al., 2017; Molinaro et al., 2021)。即使将语速提高到原来的3倍, 即每秒8~12个音节左右, 人们仍然可以理解言语含义。但如果语速提高到原来的3倍以上, 对言语的识别将显著下降(Dupoux & Green, 1997; Peelle et al., 2004; Nourski et al., 2009)。这一时间瓶颈与神经振荡alpha振荡速率相一致。那么, 快速言语识别的时间瓶颈与大脑的alpha振荡频率有何关联?这一关联如何解释了大脑实时加工的基本机制?

本研究拟使用脑电图、脑磁图和经颅电刺激, 考察快速言语识别的时间瓶颈是否取决于大脑的alpha振荡频率, 并进一步揭示大脑处理信息的时间分辨率及其背后的神经机制。本研究将从三个方面考察alpha振荡影响快速言语识别的机制: (1) Alpha振荡的速率是否与快速言语识别的时间瓶颈相一致?(2) Alpha振荡的速率如何调控快速言语的识别行为?(3) Alpha振荡的速率如何影响快速言语的神经加工过程?

2 国内外研究现状

2.1 Alpha振荡调控大脑的时间分辨率

近年来的研究表明, alpha振荡的速率影响大脑处理过程的时间分辨率(Mathewson et al., 2009; Dugué et al., 2011; Cecere et al., 2015; Keitel et al., 2019; Grabot & Kayser, 2020)。例如, 前人研究表明, 两个相邻的视觉光点有时会被感知为分隔的两个光点, 有时则会被感知为连续的一个光点。这种双光点知觉融合的临界间隔约为90~130 ms左右, 换算到频域约为8~12 Hz, 与alpha频率范围一致。并且, 对于每个被试来说, 其知觉融合的临界间隔与自身alpha振荡的频率一致。即被试自身alpha振荡频率越高, 或者说一个alpha振荡周期时间越短, 双光点知觉融合的临界间隔就越小; 反之, 若被试自身alpha振荡频率越低, 即一个alpha振荡周期时间越长, 则双光点知觉融合的临界间隔就越大(Samaha & Postle, 2015; Ronconi & Melcher, 2017)。同时, 通过经颅电刺激调整alpha振荡的速率, 也可以改变知觉融合的临界间隔。对于两个相同时间间隔的刺激, 当alpha振荡较快时, 两个相邻刺激的间隔会超过一个alpha周期, 则被试可以分辨其为两个刺激; 反之, 如果alpha振荡较慢, 两个刺激都落在同一个alpha周期内, 被试便难以分辨这两个刺激。

此外, alpha振荡的频率同样影响了其他瞬时知觉的时间分辨率。例如, 时间相近的视觉和听觉信号可能会被知觉为前后独立或同时发生的信号, 这取决于视觉和听觉两信号呈现的间隔时间。研究表明这一间隔时间的阈限也与alpha振荡的速率有关, 即间隔短于一个alpha周期的视觉和听觉信号, 得以在同一周期内被加工, 更容易被知觉为同时发生(Cecere et al., 2015)。又例如两点的闪烁可能被知觉为不同的运动模式, 也取决于闪烁前后帧的间隔时间是否长于一个alpha周期, 从而导致前后两帧是否在同周期内被整合(Shen et al., 2019)。这意味着, alpha振荡的频率会影响大脑如何处理时间相近的信息, 即落在一个alpha周期内的多个刺激难以被分辨。

特别要说明的是, alpha振荡速率对时间分辨率的影响不仅限于视觉过程。如上所述, 视听整合的阈限时间也与alpha振荡的周期时间有关(Cecere et al., 2015)。这意味着, alpha振荡的影响可能不仅限于知觉过程, 而是涉及到更高级的识别整合过程。那么, 各感觉通道, 包括听觉通道, 其时间分辨率都会受到alpha振荡的调控。此外, 已有研究也表明, 听觉通道的识别过程也会受到alpha振荡的影响。比如, alpha振荡的相位会影响听者在噪音下的声音识别(Neuling et al., 2012), 或影响听者对不同声音信号的差异辨别(Hansen et al., 2019)。又比如, alpha振荡会帮助连续言语信号的分割过程(Shahin & Pitt, 2012), 从而为言语识别打好基础。因此, 言语识别的时间瓶颈很可能也取决于alpha 振荡的速率。

2.2 Alpha振荡影响快速言语识别的机制

Alpha振荡影响快速言语识别的机制是一个复杂过程。上述研究已经表明, alpha振荡影响大脑时间分辨率的关键在于不同刺激是否落在同一个alpha振荡周期内。也就是说, 大脑可以充分加工间隔超过一个alpha周期的相邻两刺激, 而难以同时加工落在一个alpha周期的两个刺激。这意味着大脑知觉识别的时间瓶颈与alpha振荡的频率有关(Samaha & Postle, 2015; Ronconi & Melcher, 2017)。因此, 在快速言语识别领域, 相邻音节是否落在同一个alpha振荡周期内, 很可能是识别行为的关键。

此外, 另一个需要解决的重要问题是, alpha振荡主要调控快速言语识别的哪个过程, 是初级的感觉过程, 还是更高级的知觉组织过程。现有的研究证据大多支持alpha振荡的调控并不基于初级感觉过程。原因有如下两点。其一, 有研究发现, 在言语加速到难以理解的4倍速情形下, 听皮层的神经振荡与言语包络仍然有很高的相关性。换言之, 即使言语速度加快到不可理解的程度, 初级听皮层仍可以很好地追随语音包络。这说明初级感觉皮层可以很好地追随快速言语信号的波动(Nourski et al., 2009; Mukamel et al., 2011)。这种简单的言语-神经追随不受语速的影响, 并不是快速言语识别的时间瓶颈。因此, alpha振荡对快速言语识别的调控更可能是一种高层的、后期的调控, 会影响信息的后期整合。其二, 根据认知神经方向的现有研究, 并不只有初级感觉皮层能够表征言语信号的时间信息。在其他皮层, 例如听觉皮层和运动皮层都能捕捉到对言语包络的追随(Wilson et al., 2004; Du et al., 2014; Cheung et al., 2016; Assaneo & Poeppel, 2018; Park et al., 2018)。而左侧额下回广泛参与言语加工过程, 也可能是快速言语处理的关键脑区之一(Adank & Devlin, 2010; Peelle et al., 2010; Vagharchakian et al., 2012)。这些研究结果都说明alpha振荡影响快速言语识别的调控机制应当是涉及高级认知脑区的复杂过程。

最后要说明的是, 当前对alpha振荡调控刺激分辨的神经机制的研究中存在一定不足。由于现有研究其刺激都是光点或短音, 持续时间过短, 因此无法得知alpha振荡如何影响对刺激本身的神经表征(Cecere et al., 2015; Samaha & Postle, 2015; Ronconi & Melcher, 2017; Shen et al., 2019; Grabot & Kayser, 2020)。即是说, 在研究过程中首先需要描绘刺激本身的神经表征, 之后才能探究alpha振荡怎样对此神经表征产生影响。那么, 对于言语这种长时程信号, 可以很方便地记录并解码其相应的神经表征。此外, 已有研究表明, 言语的神经表征可受调节并体现言语可懂度(Ding & Simon, 2012; Mesgarani & Chang, 2012; Brodbeck et al., 2018; Zou et al., 2019)。因此, 后续研究应当利用长时程言语信号及其神经表征, 可以进一步阐释alpha振荡如何调控刺激自身的神经表达, 从而影响知觉过程的时间分辨率。

3 研究构想

为了深入研究alpha振荡影响快速言语识别的神经机制, 我们提出了以下三个相互关联且层层深入的研究内容: (1)研究1验证大脑alpha振荡是否影响快速言语识别的时间瓶颈, 即两者是否一致。(2)若研究1已经证实alpha振荡影响了言语识别的时间瓶颈, 研究2将详细阐述alpha振荡如何调控快速语言识别的行为表现, 并重点考察这种调控是否基于高级认知过程。(3)在研究1、研究2的基础上, 研究3将进一步在脑活动层面上考察, alpha振荡的调控作用如何反映在言语的神经表征中。

3.1 研究1: 快速言语识别的时间瓶颈与alpha振荡频率的一致性

已有研究表明, 自然语速约2~5字/秒, 而大脑最快可以识别约3倍语速的快速言语(Dupoux & Green, 1997; Ghitza & Greenberg, 2009; Vagharchakian et al., 2012; Borges et al., 2018)。即是说, 言语识别的时间瓶颈约为每秒8~12个音节(字), 恰好与alpha振荡的频率区间相重合。如果个体快速言语识别的时间瓶颈与其固有的alpha振荡的频率相一致, 则这一结论能够为alpha振荡是否可以调控言语识别行为提供核心证据。因此, 研究1设计了两个实验来验证快速言语识别的时间瓶颈是否与alpha振荡的频率相一致。

研究1的子实验1假设快速言语识别的时间瓶颈与大脑alpha振荡的频率相一致, 且具有相关关系。研究1预计招募较大规模被试, 分别测量被试对快速言语识别行为的时间瓶颈(即言语识别的阈限速率)和被试自身固有的alpha振荡频率, 并考察这两个变量是否具有相关性。即个体固有的alpha振荡频率越快, 是否其言语识别的阈限速率就越快。研究1使用不同语速(8~12 Hz)的言语材料, 记录被试在不同语速下的识别率, 并计算50%识别率对应的阈限语速。同时, 将使用脑电图记录并提取每个被试的alpha振荡峰值频率。将行为与电生理数据相结合, 子实验1考察被试的行为阈限与alpha振荡频率是否相一致。

研究1的子实验2考察大脑alpha振荡的频率是否能实时预测言语识别的时间瓶颈。即是说, 在每个被试内, 试次前的alpha振荡频率应可以预测该试次的行为结果。对于每个被试, 使用10Hz的快速言语进行多次实验, 并记录其言语识别正确率。根据行为结果, 不同试次分为不同正确率的几组, 分别计算并比较各组试次前的alpha振荡频率。子实验2想考察, 是否行为成绩越好的试次, 其alpha振荡的频率就越快。研究1的两个实验都希望证实alpha振荡的速率与被试快速言语识别的时间瓶颈一致。

3.2 研究2: Alpha振荡调控快速言语识别的行为表现

研究2旨在具体考察alpha振荡如何调控快速言语识别的行为表现。具体而言, 研究2将使用较慢(8 Hz)和较快(12 Hz)的alpha振荡频率, 记录快速言语识别的行为成绩, 考察更快的alpha振荡是否带来更好的快速言语识别表现。同时, 研究2也将考察alpha振荡对时间瓶颈的调控是否基于高层认知过程。如前所述, alpha振荡对快速言语识别的影响, 更可能是一种不基于感觉皮层的、高层的、后期的调控。为了验证这种高层调控的假设, 研究2设计了两个实验来考察alpha振荡是否不需要基于听皮层就可以调控快速言语的识别过程。

研究2的子实验1想探究, 操控被试的alpha振荡频率, 是否可以调控快速言语识别的行为表现。具体来讲, 子实验1在10 Hz的快速言语前, 使用听觉纯音操控被试的alpha振荡频率, 呈现更快(12 Hz)或更慢(8 Hz)频率的纯音, 并测试被试对快速言语的识别成绩。子实验1想考察更快的alpha振荡(12 Hz)是否帮助言语识别, 使其行为表现更好?子实验1希望证实, 改变alpha振荡频率的确可以调控快速言语识别的行为表现。

在子实验1的基础上, 研究2的子实验2进一步考察alpha振荡频率如何从高层级调控快速言语识别的行为表现。子实验2使用经颅电刺激来诱发alpha振荡, 考察不同脑区, 即听皮层与非听皮层, 其alpha振荡调控言语识别的效果。具体而言, 在10 Hz的快速语音前, 使用更快(12 Hz)或更慢(8 Hz)的alpha振荡来电刺激被试。刺激脑区选择4个脑区, 中心电极根据脑电系统放置于左听皮层(T7)、右听皮层(T8)、中央运动区(Cz)、前额叶(FPz) 4个位置。子实验2想探索: 1)同子实验1, 更快的alpha振荡(12 Hz)是否带来更好的言语识别成绩?2)不同脑区的alpha振荡是否都可以达到此调控效果, 如前额叶的alpha振荡是否也可以调控言语识别行为?子实验2希望证明alpha振荡的速度调控了大脑快速言语识别的行为表现, 且这种调控基于高级的认知过程。

3.3 研究3: Alpha振荡调控大脑对言语加工的神经过程

前两个研究证实alpha振荡调控快速言语识别的行为表现, 接下来, 研究3将在神经层面讨论alpha振荡如何影响大脑对快速言语的加工过程。如前所述, 即使加快到不可理解的言语, 初级听皮层仍可以很好地追随其语音包络(Nourski et al., 2009; Mukamel et al., 2011)。因此, alpha 振荡对言语神经表征的调控应基于高级认知过程而影响信息的后期整合, 更可能体现在言语神经表征上。解码言语的神经表征, 可以体现言语可懂度、言语理解等高级过程(Zion Golumbic et al., 2013; Leonard et al., 2016; Brodbeck et al., 2018; Zou et al., 2019)。在此基础上, 研究3将从两方面进行分别考察: 1)对于快速言语识别的神经过程, alpha振荡是影响对语音信号的简单时间追随, 还是影响更高级的认知过程, 以更复杂的方式体现在言语神经表征上?2)Alpha振荡对快速言语神经表征的调控在初级听觉皮层, 还是在更高级功能的脑区如运动皮层和前额叶皮层?

研究3将在神经层面探讨alpha振荡如何影响大脑对快速言语的加工过程。同之前的研究, 研究3同样使用10 Hz的快速言语刺激, 记录被试对言语的识别成绩。同时, 研究3使用脑磁图记录被试对言语信号的神经响应, 并使用时间响应函数解码言语信号的神经表征。将所有试次随机分为两集合, 作为训练集和测试集。对于训练集的各试次, 根据试次前alpha振荡的快慢, 分为高频组和低频组, 并训练分类器对不同组别的神经表征进行分类。接下来, 用训练好的分类器将测试集试次根据其神经表征进行再分组, 考察两组的言语识别成绩是否有差异。研究3想探寻: 1)神经表征过程如何受alpha振荡调控, 即alpha振荡频率分类的神经表征在波形、峰值、潜伏期等指标上有哪些差异。2)这种调控是否与快速言语识别相关, 即高频alpha组对应的神经表征特征, 是否可以预测更好的识别成绩。3)考察这种alpha振荡对言语神经表征的调控, 在不同脑区是否有所差别。研究3希望说明, alpha振荡如何影响言语信号的神经编码方式, 从而帮助快速言语的识别。

4 理论建构

本研究提出alpha振荡影响快速言语识别时间瓶颈的模型假设(图1)。在一个alpha振荡周期内, 大脑难以同时加工两个刺激(Samaha & Postle, 2015; Ronconi & Melcher, 2017)。因此, 当语速慢于alpha振荡频率时, 多个alpha振荡周期加工一个字/音节, 则言语可以被充分加工并识别。然而, 当语速逐渐加快, 直至快于alpha振荡频率时, 则在一个alpha振荡周期内同时存在多个字/音节, 此时多个字/音节互相抢占认知资源, 从而均无法被充分加工, 言语难以被大脑识别。

图1

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图1

Alpha振荡调控快速言语识别的模型假设。当alpha振荡频率较快时(上), 不同字/音节落在不同alpha振荡周期, 言语可以被充分加工识别, 并未到时间瓶颈。当alpha振荡频率较慢时(下), 多个字/音节争夺一个alpha振荡周期内的认知资源, 言语无法被识别, 存在时间瓶颈。

本研究有三点创新之处。第一, 本研究以大脑alpha振荡为切入点考察快速言语识别的时间瓶颈。对于快速言语识别的时间瓶颈, 已有研究更多地集中于快速言语识别的行为成绩曲线(Dupoux & Green, 1997; Vagharchakian et al., 2012; Pefkou et al., 2017), 或线索等外界条件对快速言语识别的影响(Borges et al., 2018)。本研究明确了快速言语识别的本质属于知觉加工的时间分辨率问题。因此, 本研究突破性地以大脑alpha振荡为切入点, 提出“alpha振荡是快速言语识别的关键”的理论假设。本研究考察alpha振荡如何调控快速言语识别的时间瓶颈, 为快速言语的识别行为相关研究提供了新的视角。

本研究以alpha振荡为例考察了神经振荡如何作用于认知过程。以往考察alpha振荡对行为表现的影响(Samaha & Postle, 2015; Ronconi & Melcher, 2017; Ho et al., 2019; Grabot & Kayser, 2020), 但对于这种调控的具体机制并不清楚。本研究创新性地考察alpha振荡调控言语识别的机制是否基于高级过程, 即高级脑区如额叶的alpha振荡能否也调节快速言语识别。本研究可以更好地理解大脑神经振荡如何调控知觉的时间分辨率, 验证神经振荡的调控是否基于高级认知过程。

第三, 本研究可以观测神经振荡如何调控刺激自身的神经表征。虽然以往研究已经探索了alpha振荡调控时间分辨率的机制, 但这些研究中刺激都是简单的光点或似动现象(Samaha & Postle, 2015; Ronconi & Melcher, 2017; Shen et al., 2019)。这类刺激持续时间很短, 难以观测到刺激自身的神经表征, 因此无法推测alpha振荡如何调控刺激自身的神经表征。本研究创新性地在材料上使用了言语这种长时程的复杂信号作为研究对象。由于言语信号持续时间长且复杂, 其神经表征可以被观测及解码。因此本研究可以更深入地了解alpha振荡影响瞬时加工的神经机制。

综上, 本研究使用快速言语序列, 考察alpha振荡如何调控其识别的时间瓶颈, 验证alpha振荡的作用是否基于高级认知过程, 并探究这种alpha振荡的作用如何体现于大脑对刺激的神经表征。本研究旨在更好地理解神经振荡如何调控知觉的时间分辨率, 进而探索神经振荡影响快速加工的通用机制。

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[1]

Adank, P., & Devlin, J. T. (2010). On-line plasticity in spoken sentence comprehension: Adapting to time-compressed speech

Neuroimage, 49(1), 1124-1132.

DOI:10.1016/j.neuroimage.2009.07.032

PMID:19632341

[本文引用: 1]

Listeners show remarkable flexibility in processing variation in speech signal. One striking example is the ease with which they adapt to novel speech distortions such as listening to someone with a foreign accent. Behavioural studies suggest that significant improvements in comprehension occur rapidly--often within 10-20 sentences. In the present experiment, we investigate the neural changes underlying on-line adaptation to distorted speech using time-compressed speech. Listeners performed a sentence verification task on normal-speed and time-compressed sentences while their neural responses were recorded using fMRI. The results showed that rapid learning of the time-compressed speech occurred during presentation of the first block of 16 sentences and was associated with increased activation in left and right auditory association cortices and in left ventral premotor cortex. These findings suggest that the ability to adapt to a distorted speech signal may, in part, rely on mapping novel acoustic patterns onto existing articulatory motor plans, consistent with the idea that speech perception involves integrating multi-modal information including auditory and motoric cues.

[2]

Assaneo, M. F., & Poeppel, D. (2018). The coupling between auditory and motor cortices is rate-restricted: Evidence for an intrinsic speech-motor rhythm

Science Advance, 4(2), Article eaao3842. https://doi.org/10.1126/sciadv.aao3842

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[本文引用: 1]

[3]

Borges, A. F. T., Giraud, A. L., Mansvelder, H. D., & Linkenkaer-Hansen, K. (2018). Scale-free amplitude modulation of neuronal oscillations tracks comprehension of accelerated speech

Journal of Neuroscience, 38(3), 710-722.

DOI:10.1523/JNEUROSCI.1515-17.2017

PMID:29217685

[本文引用: 2]

Speech comprehension is preserved up to a threefold acceleration, but deteriorates rapidly at higher speeds. Current models posit that perceptual resilience to accelerated speech is limited by the brain's ability to parse speech into syllabic units using δ/θ oscillations. Here, we investigated whether the involvement of neuronal oscillations in processing accelerated speech also relates to their scale-free amplitude modulation as indexed by the strength of long-range temporal correlations (LRTC). We recorded MEG while 24 human subjects (12 females) listened to radio news uttered at different comprehensible rates, at a mostly unintelligible rate and at this same speed interleaved with silence gaps. δ, θ, and low-γ oscillations followed the nonlinear variation of comprehension, with LRTC rising only at the highest speed. In contrast, increasing the rate was associated with a monotonic increase in LRTC in high-γ activity. When intelligibility was restored with the insertion of silence gaps, LRTC in the δ, θ, and low-γ oscillations resumed the low levels observed for intelligible speech. Remarkably, the lower the individual subject scaling exponents of δ/θ oscillations, the greater the comprehension of the fastest speech rate. Moreover, the strength of LRTC of the speech envelope decreased at the maximal rate, suggesting an inverse relationship with the LRTC of brain dynamics when comprehension halts. Our findings show that scale-free amplitude modulation of cortical oscillations and speech signals are tightly coupled to speech uptake capacity. One may read this statement in 20-30 s, but reading it in less than five leaves us clueless. Our minds limit how much information we grasp in an instant. Understanding the neural constraints on our capacity for sensory uptake is a fundamental question in neuroscience. Here, MEG was used to investigate neuronal activity while subjects listened to radio news played faster and faster until becoming unintelligible. We found that speech comprehension is related to the scale-free dynamics of δ and θ bands, whereas this property in high-γ fluctuations mirrors speech rate. We propose that successful speech processing imposes constraints on the self-organization of synchronous cell assemblies and their scale-free dynamics adjusts to the temporal properties of spoken language.Copyright © 2018 the authors 0270-6474/18/380710-13$15.00/0.

[4]

Brodbeck, C., Hong, L. E., & Simon, J. Z. (2018). Rapid transformation from auditory to linguistic representations of continuous speech

Current Biology, 28(24), 3976-3983.

DOI:S0960-9822(18)31409-X

PMID:30503620

[本文引用: 2]

During speech perception, a central task of the auditory cortex is to analyze complex acoustic patterns to allow detection of the words that encode a linguistic message [1]. It is generally thought that this process includes at least one intermediate, phonetic, level of representations [2-6], localized bilaterally in the superior temporal lobe [7-9]. Phonetic representations reflect a transition from acoustic to linguistic information, classifying acoustic patterns into linguistically meaningful units, which can serve as input to mechanisms that access abstract word representations [10, 11]. While recent research has identified neural signals arising from successful recognition of individual words in continuous speech [12-15], no explicit neurophysiological signal has been found demonstrating the transition from acoustic and/or phonetic to symbolic, lexical representations. Here, we report a response reflecting the incremental integration of phonetic information for word identification, dominantly localized to the left temporal lobe. The short response latency, approximately 114 ms relative to phoneme onset, suggests that phonetic information is used for lexical processing as soon as it becomes available. Responses also tracked word boundaries, confirming previous reports of immediate lexical segmentation [16, 17]. These new results were further investigated using a cocktail-party paradigm [18, 19] in which participants listened to a mix of two talkers, attending to one and ignoring the other. Analysis indicates neural lexical processing of only the attended, but not the unattended, speech stream. Thus, while responses to acoustic features reflect attention through selective amplification of attended speech, responses consistent with a lexical processing model reveal categorically selective processing.Copyright © 2018 Elsevier Ltd. All rights reserved.

[5]

Cecere, R., Rees, G., & Romei, V. (2015). Individual differences in alpha frequency drive crossmodal illusory perception

Current Biology, 25(2), 231-235.

DOI:S0960-9822(14)01495-X

PMID:25544613

[本文引用: 4]

Perception routinely integrates inputs from different senses. Stimulus temporal proximity critically determines whether or not these inputs are bound together. Despite the temporal window of integration being a widely accepted notion, its neurophysiological substrate remains unclear. Many types of common audio-visual interactions occur within a time window of ∼100 ms. For example, in the sound-induced double-flash illusion, when two beeps are presented within ∼100 ms together with one flash, a second illusory flash is often perceived. Due to their intrinsic rhythmic nature, brain oscillations are one candidate mechanism for gating the temporal window of integration. Interestingly, occipital alpha band oscillations cycle on average every ∼100 ms, with peak frequencies ranging between 8 and 14 Hz (i.e., 120-60 ms cycle). Moreover, presenting a brief tone can phase-reset such oscillations in visual cortex. Based on these observations, we hypothesized that the duration of each alpha cycle might provide the temporal unit to bind audio-visual events. Here, we first recorded EEG while participants performed the sound-induced double-flash illusion task and found positive correlation between individual alpha frequency (IAF) peak and the size of the temporal window of the illusion. Participants then performed the same task while receiving occipital transcranial alternating current stimulation (tACS), to modulate oscillatory activity either at their IAF or at off-peak alpha frequencies (IAF±2 Hz). Compared to IAF tACS, IAF-2 Hz and IAF+2 Hz tACS, respectively, enlarged and shrunk the temporal window of illusion, suggesting that alpha oscillations might represent the temporal unit of visual processing that cyclically gates perception and the neurophysiological substrate promoting audio-visual interactions.Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

[6]

Cheung, C., Hamiton, L. S., Johnson, K., & Chang, E. F. (2016). The auditory representation of speech sounds in human motor cortex

Elife, 5, Article e12577. https://doi.org/10.7554/eLife.12577

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[本文引用: 1]

[7]

Ding, N., Patel, A. D., Chen, L., Butler, H., Luo, C., & Poeppel, D. (2017). Temporal modulations in speech and music

Neuroscience and Biobehavioral Reviews, 81(Pt B),181-187.

DOI:S0149-7634(16)30566-8

PMID:28212857

[本文引用: 1]

Speech and music have structured rhythms. Here we discuss a major acoustic correlate of spoken and musical rhythms, the slow (0.25-32Hz) temporal modulations in sound intensity and compare the modulation properties of speech and music. We analyze these modulations using over 25h of speech and over 39h of recordings of Western music. We show that the speech modulation spectrum is highly consistent across 9 languages (including languages with typologically different rhythmic characteristics). A different, but similarly consistent modulation spectrum is observed for music, including classical music played by single instruments of different types, symphonic, jazz, and rock. The temporal modulations of speech and music show broad but well-separated peaks around 5 and 2Hz, respectively. These acoustically dominant time scales may be intrinsic features of speech and music, a possibility which should be investigated using more culturally diverse samples in each domain. Distinct modulation timescales for speech and music could facilitate their perceptual analysis and its neural processing.Copyright © 2017 Elsevier Ltd. All rights reserved.

[8]

Ding, N., & Simon, J. Z. (2012). Emergence of neural encoding of auditory objects while listening to competing speakers

Proceedings of the National Academy of Sciences of the United States of America, 109(29), 11854-11859.

[本文引用: 1]

[9]

Du, Y., Buchsbaum, B. R., Grady, C. L., & Alain, C. (2014). Noise Differentially impacts phoneme representations in the auditory and speech motor systems

Proceedings of the National Academy of Sciences of the United States of America, 111(19), 7126-7131.

[本文引用: 1]

[10]

Dugué, L., Marque, P., & VanRullen, R. (2011). The phase of ongoing oscillations mediates the causal relation between brain excitation and visual perception

Journal of Neuroscience, 31(33), 11889-11893.

DOI:10.1523/JNEUROSCI.1161-11.2011

PMID:21849549

[本文引用: 1]

Why does neuronal activity in sensory brain areas sometimes give rise to perception, and sometimes not? Although neuronal noise is often invoked as the key factor, a portion of this variability could also be due to the history and current state of the brain affecting cortical excitability. Here we directly test this idea by examining whether the phase of prestimulus oscillatory activity is causally linked with modulations of cortical excitability and with visual perception. Transcranial magnetic stimulation (TMS) was applied over human visual cortex to induce illusory perceptions (phosphenes) while electroencephalograms (EEGs) were simultaneously recorded. Subjects reported the presence or absence of an induced phosphene following a single pulse of TMS at perceptual threshold. The phase of ongoing alpha (∼10 Hz) oscillations within 400 ms before the pulse significantly covaried with the perceptual outcome. This effect was observed in occipital regions around the site of TMS, as well as in a distant frontocentral region. In both regions, we found a systematic relationship between prepulse EEG phase and perceptual performance: phosphene probability changed by ∼15% between opposite phases. In summary, we provide direct evidence for a chain of causal relations between the phase of ongoing oscillations, neuronal excitability, and visual perception: ongoing oscillations create periodic "windows of excitability," with sensory perception being more likely to occur at specific phases.

[11]

Dupoux, E., & Green, K. (1997). Perceptual adjustment to highly compressed speech: Effects of talker and rate changes

Journal of Experimental Psychology: Human Perception and Performance, 23(3), 914-927.

DOI:10.1037/0096-1523.23.3.914

URL

[本文引用: 3]

[12]

Ghitza, O., & Greenberg, S. (2009). On the possible role of brain rhythms in speech perception: Intelligibility of time-compressed speech with periodic and aperiodic insertions of silence

Phonetica, 66(1-2), 113-126.

DOI:10.1159/000208934

PMID:19390234

[本文引用: 1]

This study was motivated by the prospective role played by brain rhythms in speech perception. The intelligibility - in terms of word error rate - of natural-sounding, synthetically generated sentences was measured using a paradigm that alters speech-energy rhythm over a range of frequencies. The material comprised 96 semantically unpredictable sentences, each approximately 2 s long (6-8 words per sentence), generated by a high-quality text-to-speech (TTS) synthesis engine. The TTS waveform was time-compressed by a factor of 3, creating a signal with a syllable rhythm three times faster than the original, and whose intelligibility is poor (<50% words correct). A waveform with an artificial rhythm was produced by automatically segmenting the time-compressed waveform into consecutive 40-ms fragments, each followed by a silent interval. The parameters varied were the length of the silent interval (0-160 ms) and whether the lengths of silence were equal ('periodic') or not ('aperiodic'). The performance curve (word error rate as a function of mean duration of silence) was U-shaped. The lowest word error rate (i.e., highest intelligibility) occurred when the silence was 80 ms long and inserted periodically. This is also the condition for which word error rate increased when the silence was inserted aperiodically. These data are consistent with a model (TEMPO) in which low-frequency brain rhythms affect the ability to decode the speech signal. In TEMPO, optimum intelligibility is achieved when the syllable rhythm is within the range of the high theta-frequency brain rhythms (6-12 Hz), comparable to the rate at which segments and syllables are articulated in conversational speech.(c) 2009 S. Karger AG, Basel.

[13]

Grabot, L., & Kayser, C. (2020). Alpha activity reflects the magnitude of an individual bias in human perception

Journal of Neuroscience, 40(17), 3443-3454.

DOI:10.1523/JNEUROSCI.2359-19.2020

PMID:32179571

[本文引用: 3]

Biases in sensory perception can arise from both experimental manipulations and personal trait-like features. These idiosyncratic biases and their neural underpinnings are often overlooked in studies on the physiology underlying perception. A potential candidate mechanism reflecting such idiosyncratic biases could be spontaneous alpha band activity, a prominent brain rhythm known to influence perceptual reports in general. Using a temporal order judgment task, we here tested the hypothesis that alpha power reflects the overcoming of an idiosyncratic bias. Importantly, to understand the interplay between idiosyncratic biases and contextual (temporary) biases induced by experimental manipulations, we quantified this relation before and after temporal recalibration. Using EEG recordings in human participants (male and female), we find that prestimulus frontal alpha power correlates with the tendency to respond relative to an own idiosyncratic bias, with stronger α leading to responses matching the bias. In contrast, alpha power does not predict response correctness. These results also hold after temporal recalibration and are specific to the alpha band, suggesting that alpha band activity reflects, directly or indirectly, processes that help to overcome an individual's momentary bias in perception. We propose that combined with established roles of parietal α in the encoding of sensory information frontal α reflects complementary mechanisms influencing perceptual decisions. The brain is a biased organ, frequently generating systematically distorted percepts of the world, leading each of us to evolve in our own subjective reality. However, such biases are often overlooked or considered noise when studying the neural mechanisms underlying perception. We show that spontaneous alpha band activity predicts the degree of biasedness of human choices in a time perception task, suggesting that alpha activity indexes processes needed to overcome an individual's idiosyncratic bias. This result provides a window onto the neural underpinnings of subjective perception, and offers the possibility to quantify or manipulate such priors in future studies.Copyright © 2020 the authors.

[14]

Greenberg, S., Carvey, H., Hitchcock, L., & Chang, S. Y. (2003). Temporal properties of spontaneous speech-a syllable-centric perspective

Journal of Phonetics, 31(3-4), 465-485.

DOI:10.1016/j.wocn.2003.09.005

URL

[本文引用: 1]

[15]

Hansen, N. E., Harel, A., Iyer, N., Simpson, B. D., & Wisniewski, M. G. (2019). Pre-stimulus brain state predicts auditory pattern identification accuracy

Neuroimage, 199, 512-520.

DOI:S1053-8119(19)30446-X

PMID:31129305

[本文引用: 1]

Recent studies show that pre-stimulus band-specific power and phase in the electroencephalogram (EEG) can predict accuracy on tasks involving the detection of near-threshold stimuli. However, results in the auditory modality have been mixed, and few works have examined pre-stimulus features when more complex decisions are made (e.g. identifying supra-threshold sounds). Further, most auditory studies have used background sounds known to induce oscillatory EEG states, leaving it unclear whether phase predicts accuracy without such background sounds. To address this gap in knowledge, the present study examined pre-stimulus EEG as it relates to accuracy in a tone pattern identification task. On each trial, participants heard a triad of 40-ms sinusoidal tones (separated by 40-ms intervals), one of which was at a different frequency than the other two. Participants' task was to indicate the tone pattern (low-low-high, low-high-low, etc.). No background sounds were employed. Using a phase opposition measure based on inter-trial phase consistencies, pre-stimulus 7-10 Hz phase was found to differ between correct and incorrect trials ∼200 to 100 ms prior to tone-pattern onset. After sorting trials into bins based on phase, accuracy was found to be lowest at around π-+ relative to individuals' most accurate phase bin. No significant effects were found for pre-stimulus power. In the context of the literature, findings suggest an important relationship between the complexity of task demands and pre-stimulus activity within the auditory domain. Results also raise interesting questions about the role of induced oscillatory states or rhythmic processing modes in obtaining pre-stimulus effects of phase in auditory tasks.Copyright © 2019 Elsevier Inc. All rights reserved.

[16]

Ho, H. T., Burr, D. C., Alais, D., & Morrone, M. C. (2019). Auditory perceptual history is propagated through alpha oscillations

Current Biology, 29(24), 4208-4217.

DOI:S0960-9822(19)31381-8

PMID:31761705

[本文引用: 1]

Perception is a proactive, "predictive" process, in which the brain relies, at least in part, on accumulated experience to make best guesses about the world to test against sensory data, updating the guesses as new experience is acquired. Using novel behavioral methods, the present study demonstrates the role of alpha rhythms in communicating past perceptual experience. Participants were required to discriminate the ear of origin of brief sinusoidal tones that were presented monaurally at random times within a burst of uncorrelated dichotic white noise masks. Performance was not constant but varied with delay after noise onset in an oscillatory manner at about 9 Hz (alpha rhythm). Importantly, oscillations occurred only for trials preceded by a target tone to the same ear, either on the previous trial or two trials back. These results suggest that communication of perceptual history generates neural oscillations within specific perceptual circuits, strongly implicating behavioral oscillations in predictive perception and with formation of working memory.Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

[17]

Hyafil, A., Fontolan, L., Kabdebon, C., Gutkin, B., & Giraud, A. L. (2015). Speech encoding by coupled cortical theta and gamma oscillations

Elife, 4, Article e06213. https://doi.org/10.7554/eLife.06213

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[本文引用: 1]

[18]

Keitel, C., Keitel, A., Benwell, C. S. Y., Daube, C., Thut, G., & Gross, J. (2019). Stimulus-driven brain rhythms within the alpha band: The attentional-modulation conundrum

Journal of Neuroscience, 39(16), 3119-3129.

DOI:10.1523/JNEUROSCI.1633-18.2019

PMID:30770401

[本文引用: 1]

Two largely independent research lines use rhythmic sensory stimulation to study visual processing. Despite the use of strikingly similar experimental paradigms, they differ crucially in their notion of the stimulus-driven periodic brain responses: one regards them mostly as synchronized (entrained) intrinsic brain rhythms; the other assumes they are predominantly evoked responses [classically termed steady-state responses (SSRs)] that add to the ongoing brain activity. This conceptual difference can produce contradictory predictions about, and interpretations of, experimental outcomes. The effect of spatial attention on brain rhythms in the alpha band (8-13 Hz) is one such instance: alpha-range SSRs have typically been found to increase in power when participants focus their spatial attention on laterally presented stimuli, in line with a gain control of the visual evoked response. In nearly identical experiments, retinotopic decreases in entrained alpha-band power have been reported, in line with the inhibitory function of intrinsic alpha. Here we reconcile these contradictory findings by showing that they result from a small but far-reaching difference between two common approaches to EEG spectral decomposition. In a new analysis of previously published human EEG data, recorded during bilateral rhythmic visual stimulation, we find the typical SSR gain effect when emphasizing stimulus-locked neural activity and the typical retinotopic alpha suppression when focusing on ongoing rhythms. These opposite but parallel effects suggest that spatial attention may bias the neural processing of dynamic visual stimulation via two complementary neural mechanisms. Attending to a visual stimulus strengthens its representation in visual cortex and leads to a retinotopic suppression of spontaneous alpha rhythms. To further investigate this process, researchers often attempt to phase lock, or entrain, alpha through rhythmic visual stimulation under the assumption that this entrained alpha retains the characteristics of spontaneous alpha. Instead, we show that the part of the brain response that is phase locked to the visual stimulation increased with attention (as do steady-state evoked potentials), while the typical suppression was only present in non-stimulus-locked alpha activity. The opposite signs of these effects suggest that attentional modulation of dynamic visual stimulation relies on two parallel cortical mechanisms-retinotopic alpha suppression and increased temporal tracking.Copyright © 2019 Keitel et al.

[19]

Leonard, M. K., Baud, M. O., Sjerps, M. J., & Chang, E. F. (2016). Perceptual restoration of masked speech in human cortex

Nature Communications, 7, Article 13619. https://doi.org/10.1038/ncomms13619

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Mathewson, K. E., Beck, D. M., Ro, T., Fabiani, M., & Gratton, G. (2009). Illuminating awareness: Investigating the temporal and spatial neural dynamics of metacontrast masking using the event-related optical signal

Journal of Vision, 9(8), 765.

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Mesgarani, N., & Chang, E. F. (2012). Selective cortical representation of attended speaker in multi-talker speech perception

Nature, 485(7397), 233-236.

DOI:10.1038/nature11020

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Molinaro, N., Lizarazu, M., Baldin, V., Pérez-Navarro, J., Lallier, M., & Ríos-López, P. (2021). Speech-brain phase coupling is enhanced in low contextual semantic predictability conditions

Neuropsychologia, 156, 107830.

DOI:10.1016/j.neuropsychologia.2021.107830

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Mukamel, R., Nir, Y., Harel, M., Arieli, A., Malach, R., & Fried, I. (2011). Invariance of firing rate and field potential dynamics to stimulus modulation rate in human auditory cortex

Human Brain Mapping, 32(8), 1181-1193.

DOI:10.1002/hbm.21100

PMID:20665720

[本文引用: 2]

The effect of stimulus modulation rate on the underlying neural activity in human auditory cortex is not clear. Human studies (using both invasive and noninvasive techniques) have demonstrated that at the population level, auditory cortex follows stimulus envelope. Here we examined the effect of stimulus modulation rate by using a rare opportunity to record both spiking activity and local field potentials (LFP) in auditory cortex of patients during repeated presentations of an audio-visual movie clip presented at normal, double, and quadruple speeds. Mean firing rate during evoked activity remained the same across speeds and the temporal response profile of firing rate modulations at increased stimulus speeds was a linearly scaled version of the response during slower speeds. Additionally, stimulus induced power modulation of local field potentials in the high gamma band (64-128 Hz) exhibited similar temporal scaling as the neuronal firing rate modulations. Our data confirm and extend previous studies in humans and anesthetized animals, supporting a model in which both firing rate, and high-gamma LFP power modulations in auditory cortex follow the temporal envelope of the stimulus across different modulation rates.Copyright © 2010 Wiley-Liss, Inc.

[24]

Neuling, T., Rach, S., Wagner, S., Wolters, C. H., & Herrmann, C. S. (2012). Good vibrations: Oscillatory phase shapes perception

Neuroimage, 63(2), 771-778.

DOI:10.1016/j.neuroimage.2012.07.024

PMID:22836177

[本文引用: 1]

In the current study, we provide compelling evidence to answer the long-standing question whether perception is continuous or periodic. Spontaneous brain oscillations are assumed to be the underlying mechanism of periodic perception. Depending on the phase angle of the oscillations, an identical stimulus results in different perceptual outcomes. Past results, however, can only account for a correlation of perception with the phase of the ongoing brain oscillations. Therefore, it is desirable to demonstrate a causal relation between phase and perception. One way to address this question is to entrain spontaneous brain oscillations by applying an external oscillation and then demonstrate behavioral consequences of this oscillation. We conducted an auditory detection experiment with humans, recorded the electroencephalogram (EEG) concurrently and simultaneously applied oscillating transcranial direct current stimulation at 10Hz (α-tDCS). Our approach revealed that detection thresholds were dependent on the phase of the oscillation that was entrained by α-tDCS. This behavioral effect was accompanied by an electrophysiological effect: α-power was enhanced after α-tDCS as compared to a pre-stimulation period. By showing a causal relation between phase and perception, our results extend findings of previous studies that were only able to demonstrate a correlation. We found that manipulation of the phase resulted in different detection thresholds, which supports the notion that perception can be periodically modulated by oscillatory processes. This demonstrates that tDCS can serve as a tool in neuroscience to extend the knowledge of the functional significance of brain oscillations.Copyright © 2012 Elsevier Inc. All rights reserved.

[25]

Nourski, K. V., Reale, R. A., Oya, H., Kawasaki, H., Kovach, C. K., Chen, H.,... Brugge, J. F. (2009). Temporal envelope of time-compressed speech represented in the human auditory cortex

Journal of Neuroscience, 29(49), 15564-15574.

DOI:10.1523/JNEUROSCI.3065-09.2009

PMID:20007480

[本文引用: 3]

Speech comprehension relies on temporal cues contained in the speech envelope, and the auditory cortex has been implicated as playing a critical role in encoding this temporal information. We investigated auditory cortical responses to speech stimuli in subjects undergoing invasive electrophysiological monitoring for pharmacologically refractory epilepsy. Recordings were made from multicontact electrodes implanted in Heschl's gyrus (HG). Speech sentences, time compressed from 0.75 to 0.20 of natural speaking rate, elicited average evoked potentials (AEPs) and increases in event-related band power (ERBP) of cortical high-frequency (70-250 Hz) activity. Cortex of posteromedial HG, the presumed core of human auditory cortex, represented the envelope of speech stimuli in the AEP and ERBP. Envelope following in ERBP, but not in AEP, was evident in both language-dominant and -nondominant hemispheres for relatively high degrees of compression where speech was not comprehensible. Compared to posteromedial HG, responses from anterolateral HG-an auditory belt field-exhibited longer latencies, lower amplitudes, and little or no time locking to the speech envelope. The ability of the core auditory cortex to follow the temporal speech envelope over a wide range of speaking rates leads us to conclude that such capacity in itself is not a limiting factor for speech comprehension.

[26]

Park, H., Ince, R. A. A., Schyns, P. G., Thut, G., & Gross, J. (2018). Representational interactions during audiovisual speech entrainment: Redundancy in left posterior superior temporal gyrus and synergy in left motor cortex

PLoS Biology, 16(8), Article e2006558. https://doi.org/10.1371/journal.pbio.2006558

URL

[本文引用: 1]

[27]

Peelle, J. E., McMillan, C., Moore, P., Grossman, M., & Wingfield, A. (2004). Dissociable patterns of brain activity during comprehension of rapid and syntactically complex speech: Evidence from fMRI

Brain and Language, 91(3), 315-325.

PMID:15533557

[本文引用: 1]

Sentence comprehension is a complex task that involves both language-specific processing components and general cognitive resources. Comprehension can be made more difficult by increasing the syntactic complexity or the presentation rate of a sentence, but it is unclear whether the same neural mechanism underlies both of these effects. In the current study, we used event-related functional magnetic resonance imaging (fMRI) to monitor neural activity while participants heard sentences containing a subject-relative or object-relative center-embedded clause presented at three different speech rates. Syntactically complex object-relative sentences activated left inferior frontal cortex across presentation rates, whereas sentences presented at a rapid rate recruited frontal brain regions such as anterior cingulate and premotor cortex, regardless of syntactic complexity. These results suggest that dissociable components of a large-scale neural network support the processing of syntactic complexity and speech presented at a rapid rate during auditory sentence processing.

[28]

Peelle, J. E., Troiani, V., Wingfield, A., & Grossman, M. (2010). Neural processing during older adults' comprehension of spoken sentences: Age differences in resource allocation and connectivity

Cerebral Cortex, 20(4), 773-782.

DOI:10.1093/cercor/bhp142

URL

[本文引用: 1]

[29]

Pefkou, M., Arnal, L. H., Fontolan, L., & Giraud, A. L. (2017). θ-band and β-band neural activity reflects independent syllable tracking and comprehension of time-compressed speech

Journal of Neuroscience, 37(33), 7930-7938.

DOI:10.1523/JNEUROSCI.2882-16.2017

PMID:28729443

[本文引用: 1]

Recent psychophysics data suggest that speech perception is not limited by the capacity of the auditory system to encode fast acoustic variations through neural γ activity, but rather by the time given to the brain to decode them. Whether the decoding process is bounded by the capacity of θ rhythm to follow syllabic rhythms in speech, or constrained by a more endogenous top-down mechanism, e.g., involving β activity, is unknown. We addressed the dynamics of auditory decoding in speech comprehension by challenging syllable tracking and speech decoding using comprehensible and incomprehensible time-compressed auditory sentences. We recorded EEGs in human participants and found that neural activity in both θ and γ ranges was sensitive to syllabic rate. Phase patterns of slow neural activity consistently followed the syllabic rate (4-14 Hz), even when this rate went beyond the classical θ range (4-8 Hz). The power of θ activity increased linearly with syllabic rate but showed no sensitivity to comprehension. Conversely, the power of β (14-21 Hz) activity was insensitive to the syllabic rate, yet reflected comprehension on a single-trial basis. We found different long-range dynamics for θ and β activity, with β activity building up in time while more contextual information becomes available. This is consistent with the roles of θ and β activity in stimulus-driven versus endogenous mechanisms. These data show that speech comprehension is constrained by concurrent stimulus-driven θ and low-γ activity, and by endogenous β activity, but not primarily by the capacity of θ activity to track the syllabic rhythm. Speech comprehension partly depends on the ability of the auditory cortex to track syllable boundaries with θ-range neural oscillations. The reason comprehension drops when speech is accelerated could hence be because θ oscillations can no longer follow the syllabic rate. Here, we presented subjects with comprehensible and incomprehensible accelerated speech, and show that neural phase patterns in the θ band consistently reflect the syllabic rate, even when speech becomes too fast to be intelligible. The drop in comprehension, however, is signaled by a significant decrease in the power of low-β oscillations (14-21 Hz). These data suggest that speech comprehension is not limited by the capacity of θ oscillations to adapt to syllabic rate, but by an endogenous decoding process.Copyright © 2017 the authors 0270-6474/17/377930-09$15.00/0.

[30]

Reynolds, M. E., & Givens, J. (2001). Presentation rate in comprehension of natural and synthesized speech

Perceptual and Motor Skills, 92(3 Pt 2), 958-968.

PMID:11565939

[本文引用: 1]

This study examined the effect of four presentation rates (approximately 130, 150, 170, and 190 words per minute) on the comprehension of natural and synthesized speech by having 96 subjects [1 man, 95 women ranging in age from 18 to 40 years (M=21.0)] perform a sentence-verification task. Analysis showed that, while their response latencies were significantly faster to natural than to synthesized speech, presentation rate did not have a significant effect on response latencies when sentences were presented at rates within the average speaking range (approximately 130 to 190 words per minute). Implications these findings may have for the use of synthesized speech in human factors applications are discussed.

[31]

Ronconi, L., & Melcher, D. (2017). The role of oscillatory phase in determining the temporal organization of perception: Evidence from sensory entrainment

Journal of Neuroscience, 37(44), 10636-10644.

DOI:10.1523/JNEUROSCI.1704-17.2017

PMID:28972130

[本文引用: 6]

Recent behavioral, neuroimaging, and neurophysiological studies have renewed the idea that the information processing within different temporal windows is linked to the phase and/or frequency of the ongoing oscillations, predominantly in the theta/alpha band (∼4-7 and 8-12 Hz, respectively). However, being correlational in nature, this evidence might reflect a nonfunctional byproduct rather than having a causal role. A more direct link can be shown with methods that manipulate oscillatory activity. Here, we used audiovisual entrainment at different frequencies in the prestimulus period of a temporal integration/segregation task. We hypothesized that entrainment would align ongoing oscillations and drive them toward the stimulation frequency. To reveal behavioral oscillations in temporal perception after the entrainment, we sampled the segregation/integration performance densely in time. In Experiment 1, two groups of human participants (both males and females) received stimulation either at the lower or the upper boundary of the alpha band (∼8.5 vs 11.5 Hz). For both entrainment frequencies, we found a phase alignment of the perceptual oscillation across subjects, but with two different power spectra that peaked near the entrainment frequency. These results were confirmed when perceptual oscillations were characterized in the time domain with sinusoidal fittings. In Experiment 2, we replicated the findings in a within-subject design, extending the results for frequencies in the theta (∼6.5 Hz), but not in the beta (∼15 Hz), range. Overall, these findings show that temporal segregation can be modified by sensory entrainment, providing evidence for a critical role of ongoing oscillations in the temporal organization of perception. The continuous flow of sensory input is not processed in an analog fashion, but rather is grouped by the perceptual system over time. Recent studies pinpointed the phase and/or frequency of the neural oscillations in the theta/alpha band (∼4-12 Hz) as possible mechanisms underlying temporal windows in perception. Here, we combined two innovative methodologies to provide more direct support for this evidence. We used sensory entrainment to align neural oscillations to different frequencies and then characterized the resultant perceptual oscillation with a temporal dense sampling of the integration/segregation performance. Our results provide the first evidence that the frequency of temporal segregation can be modified by sensory entrainment, supporting a critical role of ongoing oscillations in the integration/segregation of information over time.Copyright © 2017 Ronconi and Melcher.

[32]

Samaha, J., & Postle, B. R. (2015). The speed of alpha-band oscillations predicts the temporal resolution of visual perception

Current Biology, 25(22), 2985-2990.

DOI:10.1016/j.cub.2015.10.007

PMID:26526370

[本文引用: 6]

Evidence suggests that scalp-recorded occipital alpha-band (8-13 Hz) oscillations reflect phasic information transfer in thalamocortical neurons projecting from lateral geniculate nucleus to visual cortex. In animals, the phase of ongoing alpha oscillations has been shown to modulate stimulus discrimination and neuronal spiking. Human research has shown that alpha phase predicts visual perception of near-threshold stimuli and subsequent neural activity and that the frequency of these oscillations predicts reaction times, as well as the maximum temporal interval necessary for perceived simultaneity. These phasic effects have led to the hypothesis that conscious perception occurs in discrete temporal windows, clocked by the frequency of alpha oscillations. Under this hypothesis, variation in the frequency of occipital alpha oscillations should predict variation in the temporal resolution of visual perception. Specifically, when two stimuli fall within the same alpha cycle, they may be perceived as a single stimulus, resulting in perception with lower temporal resolution when alpha frequency is lower. We tested this by assessing the relationship between two-flash fusion thresholds (a measure of the temporal resolution of visual perception) and the frequency of eyes-closed and task-related alpha rhythms. We found, both between and within subjects, that faster alpha frequencies predicted more accurate flash discrimination, providing novel evidence linking alpha frequency to the temporal resolution of perception.Copyright © 2015 Elsevier Ltd. All rights reserved.

[33]

Shahin, A. J., & Pitt, M. A. (2012). Alpha activity marking word boundaries mediates speech segmentation

European Journal of Neuroscience, 36(12), 3740-3748.

DOI:10.1111/ejn.12008

PMID:23020238

[本文引用: 1]

This study examined the neurophysiological mechanisms of speech segmentation, the process of parsing the continuous speech signal into isolated words. Individuals listened to sequences of two monosyllabic words (e.g. gas source) and non-words (e.g. nas sorf). When these phrases are spoken, talkers usually produce one continuous s-sound, not two distinct s-sounds, making it unclear where one word ends and the next one begins. This ambiguity in the signal can also result in perceptual ambiguity, causing the sequence to be heard as one word (failed to segment) or two words (segmented). We compared listeners' electroencephalogram activity when they reported hearing one word or two words, and found that bursts of fronto-central alpha activity (9-14 Hz), following the onset of the physical /s/ and end of phrase, indexed speech segmentation. Left-lateralized beta activity (14-18 Hz) following the end of phrase distinguished word from non-word segmentation. A hallmark of enhanced alpha activity is that it reflects inhibition of task-irrelevant neural populations. Thus, the current results suggest that disengagement of neural processes that become irrelevant as the words unfold marks word boundaries in continuous speech, leading to segmentation. Beta activity is likely associated with unifying word representations into coherent phrases.© 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

[34]

Shen, L., Han, B., Chen, L., & Chen, Q. (2019). Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity

PLoS Biology, 17(3), Article e3000025. https://doi.org/10.1371/journal.pbio.3000025

URL

[本文引用: 3]

[35]

Vagharchakian, L., Dehaene-Lambertz, G., Pallier, C., & Dehaene, S. (2012). A temporal bottleneck in the language comprehension network

Journal of Neuroscience, 32(26), 9089-9102.

DOI:10.1523/JNEUROSCI.5685-11.2012

PMID:22745508

[本文引用: 3]

Humans can understand spoken or written sentences presented at extremely fast rates of ∼400 wpm, far exceeding the normal speech rate (∼150 wpm). How does the brain cope with speeded language? And what processing bottlenecks eventually make language incomprehensible above a certain presentation rate? We used time-resolved fMRI to probe the brain responses to spoken and written sentences presented at five compression rates, ranging from intelligible (60-100% of the natural duration) to challenging (40%) and unintelligible (20%). The results show that cortical areas differ sharply in their activation speed and amplitude. In modality-specific sensory areas, activation varies linearly with stimulus duration. However, a large modality-independent left-hemispheric language network, including the inferior frontal gyrus (pars orbitalis and triangularis) and the superior temporal sulcus, shows a remarkably time-invariant response, followed by a sudden collapse for unintelligible stimuli. Finally, linear and nonlinear responses, reflecting a greater effort as compression increases, are seen at various prefrontal and parietal sites. We show that these profiles fit with a simple model according to which the higher stages of language processing operate at a fixed speed and thus impose a temporal bottleneck on sentence comprehension. At presentation rates faster than this internal processing speed, incoming words must be buffered, and intelligibility vanishes when buffer storage and retrieval operations are saturated. Based on their temporal and amplitude profiles, buffer regions can be identified with the left inferior frontal/anterior insula, precentral cortex, and mesial frontal cortex.

[36]

Wilson, S. M., Saygin, A. P., Sereno, M. I., & Iacoboni, M. (2004). Listening to speech activates motor areas involved in speech production

Nature Neuroscience, 7(7), 701-702.

DOI:10.1038/nn1263

PMID:15184903

[本文引用: 1]

To examine the role of motor areas in speech perception, we carried out a functional magnetic resonance imaging (fMRI) study in which subjects listened passively to monosyllables and produced the same speech sounds. Listening to speech activated bilaterally a superior portion of ventral premotor cortex that largely overlapped a speech production motor area centered just posteriorly on the border of Brodmann areas 4a and 6, which we distinguished from a more ventral speech production area centered in area 4p. Our findings support the view that the motor system is recruited in mapping acoustic inputs to a phonetic code.

[37]

Zion Golumbic, E. M., Ding, N., Bickel, S., Lakatos, P., Schevon, C. A., McKhann, G. M.,... Schroeder, C. E. (2013). Mechanisms underlying selective neuronal tracking of attended speech at a "cocktail party"

Neuron, 77(5), 980-991.

DOI:10.1016/j.neuron.2012.12.037

PMID:23473326

[本文引用: 1]

The ability to focus on and understand one talker in a noisy social environment is a critical social-cognitive capacity, whose underlying neuronal mechanisms are unclear. We investigated the manner in which speech streams are represented in brain activity and the way that selective attention governs the brain's representation of speech using a "Cocktail Party" paradigm, coupled with direct recordings from the cortical surface in surgical epilepsy patients. We find that brain activity dynamically tracks speech streams using both low-frequency phase and high-frequency amplitude fluctuations and that optimal encoding likely combines the two. In and near low-level auditory cortices, attention "modulates" the representation by enhancing cortical tracking of attended speech streams, but ignored speech remains represented. In higher-order regions, the representation appears to become more "selective," in that there is no detectable tracking of ignored speech. This selectivity itself seems to sharpen as a sentence unfolds.Copyright © 2013 Elsevier Inc. All rights reserved.

[38]

Zou, J., Feng, J., Xu, T., Jin, P., Luo, C., Zhang, J.,... Ding, N. (2019). Auditory and language contributions to neural encoding of speech features in noisy environments

Neuroimage, 192, 66-75.

DOI:S1053-8119(19)30143-0

PMID:30822469

[本文引用: 2]

Recognizing speech in noisy environments is a challenging task that involves both auditory and language mechanisms. Previous studies have demonstrated human auditory cortex can reliably track the temporal envelope of speech in noisy environments, which provides a plausible neural basis for noise-robust speech recognition. The current study aimed at teasing apart auditory and language contributions to noise-robust envelope tracking by comparing the neural responses of 2 groups of listeners, i.e., native listeners and foreign listeners who did not understand the testing language. In the experiment, speech signals were mixed with spectrally matched stationary noise at 4 intensity levels and listeners' neural responses were recorded using electroencephalography (EEG). When the noise intensity increased, the neural response gain increased in both groups of listeners, demonstrating auditory gain control. Language comprehension generally reduced the response gain and envelope-tracking precision, and modulated the spatial and temporal profile of envelope-tracking activity. Based on the spatio-temporal dynamics of envelope-tracking activity, a linear classifier can jointly decode the 2 listener groups and 4 levels of noise intensity. Altogether, the results showed that without feedback from language processing, auditory mechanisms such as gain control can lead to a noise-robust speech representation. High-level language processing modulated the spatio-temporal profile of the neural representation of speech envelope, instead of generally enhancing the envelope representation.Copyright © 2019 Elsevier Inc. All rights reserved.

On-line plasticity in spoken sentence comprehension: Adapting to time-compressed speech

2010

... 此外, 另一个需要解决的重要问题是, alpha振荡主要调控快速言语识别的哪个过程, 是初级的感觉过程, 还是更高级的知觉组织过程.现有的研究证据大多支持alpha振荡的调控并不基于初级感觉过程.原因有如下两点.其一, 有研究发现, 在言语加速到难以理解的4倍速情形下, 听皮层的神经振荡与言语包络仍然有很高的相关性.换言之, 即使言语速度加快到不可理解的程度, 初级听皮层仍可以很好地追随语音包络.这说明初级感觉皮层可以很好地追随快速言语信号的波动(Nourski et al., 2009; Mukamel et al., 2011).这种简单的言语-神经追随不受语速的影响, 并不是快速言语识别的时间瓶颈.因此, alpha振荡对快速言语识别的调控更可能是一种高层的、后期的调控, 会影响信息的后期整合.其二, 根据认知神经方向的现有研究, 并不只有初级感觉皮层能够表征言语信号的时间信息.在其他皮层, 例如听觉皮层和运动皮层都能捕捉到对言语包络的追随(Wilson et al., 2004; Du et al., 2014; Cheung et al., 2016; Assaneo & Poeppel, 2018; Park et al., 2018).而左侧额下回广泛参与言语加工过程, 也可能是快速言语处理的关键脑区之一(Adank & Devlin, 2010; Peelle et al., 2010; Vagharchakian et al., 2012).这些研究结果都说明alpha振荡影响快速言语识别的调控机制应当是涉及高级认知脑区的复杂过程. ...

The coupling between auditory and motor cortices is rate-restricted: Evidence for an intrinsic speech-motor rhythm

2018

Scale-free amplitude modulation of neuronal oscillations tracks comprehension of accelerated speech

2018

... 已有研究表明, 自然语速约2~5字/秒, 而大脑最快可以识别约3倍语速的快速言语(Dupoux & Green, 1997; Ghitza & Greenberg, 2009; Vagharchakian et al., 2012; Borges et al., 2018).即是说, 言语识别的时间瓶颈约为每秒8~12个音节(字), 恰好与alpha振荡的频率区间相重合.如果个体快速言语识别的时间瓶颈与其固有的alpha振荡的频率相一致, 则这一结论能够为alpha振荡是否可以调控言语识别行为提供核心证据.因此, 研究1设计了两个实验来验证快速言语识别的时间瓶颈是否与alpha振荡的频率相一致. ...

... 本研究有三点创新之处.第一, 本研究以大脑alpha振荡为切入点考察快速言语识别的时间瓶颈.对于快速言语识别的时间瓶颈, 已有研究更多地集中于快速言语识别的行为成绩曲线(Dupoux & Green, 1997; Vagharchakian et al., 2012; Pefkou et al., 2017), 或线索等外界条件对快速言语识别的影响(Borges et al., 2018).本研究明确了快速言语识别的本质属于知觉加工的时间分辨率问题.因此, 本研究突破性地以大脑alpha振荡为切入点, 提出“alpha振荡是快速言语识别的关键”的理论假设.本研究考察alpha振荡如何调控快速言语识别的时间瓶颈, 为快速言语的识别行为相关研究提供了新的视角. ...

Rapid transformation from auditory to linguistic representations of continuous speech

2018

... 最后要说明的是, 当前对alpha振荡调控刺激分辨的神经机制的研究中存在一定不足.由于现有研究其刺激都是光点或短音, 持续时间过短, 因此无法得知alpha振荡如何影响对刺激本身的神经表征(Cecere et al., 2015; Samaha & Postle, 2015; Ronconi & Melcher, 2017; Shen et al., 2019; Grabot & Kayser, 2020).即是说, 在研究过程中首先需要描绘刺激本身的神经表征, 之后才能探究alpha振荡怎样对此神经表征产生影响.那么, 对于言语这种长时程信号, 可以很方便地记录并解码其相应的神经表征.此外, 已有研究表明, 言语的神经表征可受调节并体现言语可懂度(Ding & Simon, 2012; Mesgarani & Chang, 2012; Brodbeck et al., 2018; Zou et al., 2019).因此, 后续研究应当利用长时程言语信号及其神经表征, 可以进一步阐释alpha振荡如何调控刺激自身的神经表达, 从而影响知觉过程的时间分辨率. ...

... 前两个研究证实alpha振荡调控快速言语识别的行为表现, 接下来, 研究3将在神经层面讨论alpha振荡如何影响大脑对快速言语的加工过程.如前所述, 即使加快到不可理解的言语, 初级听皮层仍可以很好地追随其语音包络(Nourski et al., 2009; Mukamel et al., 2011).因此, alpha 振荡对言语神经表征的调控应基于高级认知过程而影响信息的后期整合, 更可能体现在言语神经表征上.解码言语的神经表征, 可以体现言语可懂度、言语理解等高级过程(Zion Golumbic et al., 2013; Leonard et al., 2016; Brodbeck et al., 2018; Zou et al., 2019).在此基础上, 研究3将从两方面进行分别考察: 1)对于快速言语识别的神经过程, alpha振荡是影响对语音信号的简单时间追随, 还是影响更高级的认知过程, 以更复杂的方式体现在言语神经表征上?2)Alpha振荡对快速言语神经表征的调控在初级听觉皮层, 还是在更高级功能的脑区如运动皮层和前额叶皮层? ...

Individual differences in alpha frequency drive crossmodal illusory perception

2015

... 近年来的研究表明, alpha振荡的速率影响大脑处理过程的时间分辨率(Mathewson et al., 2009; Dugué et al., 2011; Cecere et al., 2015; Keitel et al., 2019; Grabot & Kayser, 2020).例如, 前人研究表明, 两个相邻的视觉光点有时会被感知为分隔的两个光点, 有时则会被感知为连续的一个光点.这种双光点知觉融合的临界间隔约为90~130 ms左右, 换算到频域约为8~12 Hz, 与alpha频率范围一致.并且, 对于每个被试来说, 其知觉融合的临界间隔与自身alpha振荡的频率一致.即被试自身alpha振荡频率越高, 或者说一个alpha振荡周期时间越短, 双光点知觉融合的临界间隔就越小; 反之, 若被试自身alpha振荡频率越低, 即一个alpha振荡周期时间越长, 则双光点知觉融合的临界间隔就越大(Samaha & Postle, 2015; Ronconi & Melcher, 2017).同时, 通过经颅电刺激调整alpha振荡的速率, 也可以改变知觉融合的临界间隔.对于两个相同时间间隔的刺激, 当alpha振荡较快时, 两个相邻刺激的间隔会超过一个alpha周期, 则被试可以分辨其为两个刺激; 反之, 如果alpha振荡较慢, 两个刺激都落在同一个alpha周期内, 被试便难以分辨这两个刺激. ...

... 此外, alpha振荡的频率同样影响了其他瞬时知觉的时间分辨率.例如, 时间相近的视觉和听觉信号可能会被知觉为前后独立或同时发生的信号, 这取决于视觉和听觉两信号呈现的间隔时间.研究表明这一间隔时间的阈限也与alpha振荡的速率有关, 即间隔短于一个alpha周期的视觉和听觉信号, 得以在同一周期内被加工, 更容易被知觉为同时发生(Cecere et al., 2015).又例如两点的闪烁可能被知觉为不同的运动模式, 也取决于闪烁前后帧的间隔时间是否长于一个alpha周期, 从而导致前后两帧是否在同周期内被整合(Shen et al., 2019).这意味着, alpha振荡的频率会影响大脑如何处理时间相近的信息, 即落在一个alpha周期内的多个刺激难以被分辨. ...

... 特别要说明的是, alpha振荡速率对时间分辨率的影响不仅限于视觉过程.如上所述, 视听整合的阈限时间也与alpha振荡的周期时间有关(Cecere et al., 2015).这意味着, alpha振荡的影响可能不仅限于知觉过程, 而是涉及到更高级的识别整合过程.那么, 各感觉通道, 包括听觉通道, 其时间分辨率都会受到alpha振荡的调控.此外, 已有研究也表明, 听觉通道的识别过程也会受到alpha振荡的影响.比如, alpha振荡的相位会影响听者在噪音下的声音识别(Neuling et al., 2012), 或影响听者对不同声音信号的差异辨别(Hansen et al., 2019).又比如, alpha振荡会帮助连续言语信号的分割过程(Shahin & Pitt, 2012), 从而为言语识别打好基础.因此, 言语识别的时间瓶颈很可能也取决于alpha 振荡的速率. ...

The auditory representation of speech sounds in human motor cortex

2016

Temporal modulations in speech and music

2017

... 快速言语的识别是快速信息处理的一个典型例子.人类的自然语速大约为每秒2~5个音节(Reynolds & Givens, 2001; Greenberg et al., 2003; Hyafil et al., 2015; Ding et al., 2017; Molinaro et al., 2021).即使将语速提高到原来的3倍, 即每秒8~12个音节左右, 人们仍然可以理解言语含义.但如果语速提高到原来的3倍以上, 对言语的识别将显著下降(Dupoux & Green, 1997; Peelle et al., 2004; Nourski et al., 2009).这一时间瓶颈与神经振荡alpha振荡速率相一致.那么, 快速言语识别的时间瓶颈与大脑的alpha振荡频率有何关联?这一关联如何解释了大脑实时加工的基本机制? ...

Emergence of neural encoding of auditory objects while listening to competing speakers

2012

Noise Differentially impacts phoneme representations in the auditory and speech motor systems

2014

The phase of ongoing oscillations mediates the causal relation between brain excitation and visual perception

2011

Perceptual adjustment to highly compressed speech: Effects of talker and rate changes

1997

On the possible role of brain rhythms in speech perception: Intelligibility of time-compressed speech with periodic and aperiodic insertions of silence

2009

Alpha activity reflects the magnitude of an individual bias in human perception

2020

... 本研究以alpha振荡为例考察了神经振荡如何作用于认知过程.以往考察alpha振荡对行为表现的影响(Samaha & Postle, 2015; Ronconi & Melcher, 2017; Ho et al., 2019; Grabot & Kayser, 2020), 但对于这种调控的具体机制并不清楚.本研究创新性地考察alpha振荡调控言语识别的机制是否基于高级过程, 即高级脑区如额叶的alpha振荡能否也调节快速言语识别.本研究可以更好地理解大脑神经振荡如何调控知觉的时间分辨率, 验证神经振荡的调控是否基于高级认知过程. ...

Temporal properties of spontaneous speech-a syllable-centric perspective

2003

Pre-stimulus brain state predicts auditory pattern identification accuracy

2019

Auditory perceptual history is propagated through alpha oscillations

2019

Speech encoding by coupled cortical theta and gamma oscillations

2015

Stimulus-driven brain rhythms within the alpha band: The attentional-modulation conundrum

2019

Perceptual restoration of masked speech in human cortex

2016

Illuminating awareness: Investigating the temporal and spatial neural dynamics of metacontrast masking using the event-related optical signal

2009

Selective cortical representation of attended speaker in multi-talker speech perception

2012

Speech-brain phase coupling is enhanced in low contextual semantic predictability conditions

2021

Invariance of firing rate and field potential dynamics to stimulus modulation rate in human auditory cortex

2011

Good vibrations: Oscillatory phase shapes perception

2012

Temporal envelope of time-compressed speech represented in the human auditory cortex

2009

Representational interactions during audiovisual speech entrainment: Redundancy in left posterior superior temporal gyrus and synergy in left motor cortex

2018

Dissociable patterns of brain activity during comprehension of rapid and syntactically complex speech: Evidence from fMRI

2004

Neural processing during older adults' comprehension of spoken sentences: Age differences in resource allocation and connectivity

2010

θ-band and β-band neural activity reflects independent syllable tracking and comprehension of time-compressed speech

2017

Presentation rate in comprehension of natural and synthesized speech

2001

The role of oscillatory phase in determining the temporal organization of perception: Evidence from sensory entrainment

2017

... Alpha振荡影响快速言语识别的机制是一个复杂过程.上述研究已经表明, alpha振荡影响大脑时间分辨率的关键在于不同刺激是否落在同一个alpha振荡周期内.也就是说, 大脑可以充分加工间隔超过一个alpha周期的相邻两刺激, 而难以同时加工落在一个alpha周期的两个刺激.这意味着大脑知觉识别的时间瓶颈与alpha振荡的频率有关(Samaha & Postle, 2015; Ronconi & Melcher, 2017).因此, 在快速言语识别领域, 相邻音节是否落在同一个alpha振荡周期内, 很可能是识别行为的关键. ...

... 本研究提出alpha振荡影响快速言语识别时间瓶颈的模型假设(图1).在一个alpha振荡周期内, 大脑难以同时加工两个刺激(Samaha & Postle, 2015; Ronconi & Melcher, 2017).因此, 当语速慢于alpha振荡频率时, 多个alpha振荡周期加工一个字/音节, 则言语可以被充分加工并识别.然而, 当语速逐渐加快, 直至快于alpha振荡频率时, 则在一个alpha振荡周期内同时存在多个字/音节, 此时多个字/音节互相抢占认知资源, 从而均无法被充分加工, 言语难以被大脑识别. ...

... 第三, 本研究可以观测神经振荡如何调控刺激自身的神经表征.虽然以往研究已经探索了alpha振荡调控时间分辨率的机制, 但这些研究中刺激都是简单的光点或似动现象(Samaha & Postle, 2015; Ronconi & Melcher, 2017; Shen et al., 2019).这类刺激持续时间很短, 难以观测到刺激自身的神经表征, 因此无法推测alpha振荡如何调控刺激自身的神经表征.本研究创新性地在材料上使用了言语这种长时程的复杂信号作为研究对象.由于言语信号持续时间长且复杂, 其神经表征可以被观测及解码.因此本研究可以更深入地了解alpha振荡影响瞬时加工的神经机制. ...

The speed of alpha-band oscillations predicts the temporal resolution of visual perception

2015

Alpha activity marking word boundaries mediates speech segmentation

2012

Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity

2019

A temporal bottleneck in the language comprehension network

2012

Listening to speech activates motor areas involved in speech production

2004

Mechanisms underlying selective neuronal tracking of attended speech at a "cocktail party"

2013

Auditory and language contributions to neural encoding of speech features in noisy environments

2019

神经振荡影响快速言语识别的时间瓶颈

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