Language production involves a complex set of computations, from conceptualization to articulation, which are thought to engage cascading neural events in the language network. However, recent neuromagnetic evidence suggests simultaneous meaning-to-speech mapping in picture naming tasks, as indexed by early parallel activation of frontotemporal regions to lexical semantic, phonological, and articulatory information. Here we investigate the time course of word production, asking to what extent such "earliness" is a distinctive property of the associated spatiotemporal dynamics. Using MEG, we recorded the neural signals of 34 human subjects (26 males) overtly naming 134 images from four semantic object categories (animals, foods, tools, clothes). Within each category, we covaried word length, as quantified by the number of syllables contained in a word, and phonological neighborhood density to target lexical and post-lexical phonological/phonetic processes. Multivariate pattern analyses searchlights in sensor space distinguished the stimulus-locked spatiotemporal responses to object categories early on, from 150 to 250 ms after picture onset, whereas word length was decoded in left frontotemporal sensors at 250-350 ms, followed by the latency of phonological neighborhood density (350-450 ms). Our results suggest a progression of neural activity from posterior to anterior language regions for the semantic and phonological/phonetic computations preparing overt speech, thus supporting serial cascading models of word production.

SIGNIFICANCE STATEMENT Current psycholinguistic models make divergent predictions on how a preverbal message is mapped onto articulatory output during the language planning. Serial models predict a cascading sequence of hierarchically organized neural computations from conceptualization to articulation. In contrast, parallel models posit early simultaneous activation of multiple conceptual, phonological, and articulatory information in the language system. Here we asked whether such earliness is a distinctive property of the neural dynamics of word production. The combination of the millisecond precision of MEG with multivariate pattern analyses revealed subsequent onset times for the neural events supporting semantic and phonological/phonetic operations, progressing from posterior occipitotemporal to frontal sensor areas. The findings bring new insights for refining current theories of language production.

语言生产涉及一组复杂的计算，从概念化到发音，这些计算被认为涉及语言网络中的级联神经事件。然而，最近的神经磁学证据表明，图片命名任务中同时存在意义到语音的映射，这可以通过额颞区域的早期并行激活与词汇语义、语音和发音信息进行索引。在这里，我们调查了单词产生的时间过程，询问这种“早期”在多大程度上是相关时空动态的独特属性。使用 MEG，我们记录了 34 名人类受试者（26 名男性）的神经信号，公开命名了来自四个语义对象类别（动物、食物、工具、衣服）的 134 张图像。在每个类别中，我们协变字长，通过单词中包含的音节数量和语音邻域密度来量化，以针对词汇和词汇后语音/语音过程。多变量模式分析传感器空间中的探照灯在图片开始后 150 到 250 毫秒的早期区分了对对象类别的刺激锁定时空响应，而左额颞叶传感器在 250-350 毫秒时解码了字长，然后是语音的延迟邻域密度（350-450 ms）。我们的研究结果表明，神经活动从后部语言区域发展到前部语言区域，用于准备公开语音的语义和语音/语音计算，从而支持单词生成的串行级联模型。和语音邻域密度，以针对词汇和词汇后语音/语音过程。多变量模式分析传感器空间中的探照灯在图片开始后 150 到 250 毫秒的早期区分了对对象类别的刺激锁定时空响应，而左额颞叶传感器在 250-350 毫秒时解码了字长，然后是语音的延迟邻域密度（350-450 ms）。我们的研究结果表明，神经活动从后部语言区域发展到前部语言区域，用于准备公开语音的语义和语音/语音计算，从而支持单词生成的串行级联模型。和语音邻域密度，以针对词汇和词汇后语音/语音过程。多变量模式分析传感器空间中的探照灯在图片开始后 150 到 250 毫秒的早期区分了对对象类别的刺激锁定时空响应，而左额颞叶传感器在 250-350 毫秒时解码了字长，然后是语音的延迟邻域密度（350-450 ms）。我们的研究结果表明，神经活动从后部语言区域发展到前部语言区域，用于准备公开语音的语义和语音/语音计算，从而支持单词生成的串行级联模型。图片开始后 150 到 250 毫秒，而左额颞叶传感器在 250-350 毫秒时解码字长，然后是语音邻域密度的延迟（350-450 毫秒）。我们的研究结果表明，神经活动从后部语言区域发展到前部语言区域，用于准备公开语音的语义和语音/语音计算，从而支持单词生成的串行级联模型。图片开始后 150 到 250 毫秒，而左额颞叶传感器在 250-350 毫秒时解码字长，然后是语音邻域密度的延迟（350-450 毫秒）。我们的研究结果表明，神经活动从后部语言区域发展到前部语言区域，用于准备公开语音的语义和语音/语音计算，从而支持单词生成的串行级联模型。

重要性声明当前的心理语言学模型对语言规划期间如何将语前信息映射到发音输出做出不同的预测。串行模型预测从概念化到表达的层次结构神经计算的级联序列。相比之下，并行模型假设语言系统中多个概念、语音和发音信息的早期同时激活。在这里，我们询问这种提前是否是单词产生的神经动力学的一个独特属性。MEG 的毫秒精度与多变量模式分析的结合揭示了支持语义和语音/语音操作的神经事件的后续发作时间，从枕颞后部到额叶传感器区域进展。