Department of Psychology, New York University, New York, NY 10003;
Department of Psychology, New York University, New York, NY 10003.
Proc Natl Acad Sci U S A. 2019 May 14;116(20):10113-10121. doi: 10.1073/pnas.1816414116. Epub 2019 Apr 24.
A body of research demonstrates convincingly a role for synchronization of auditory cortex to rhythmic structure in sounds including speech and music. Some studies hypothesize that an oscillator in auditory cortex could underlie important temporal processes such as segmentation and prediction. An important critique of these findings raises the plausible concern that what is measured is perhaps not an oscillator but is instead a sequence of evoked responses. The two distinct mechanisms could look very similar in the case of rhythmic input, but an oscillator might better provide the computational roles mentioned above (i.e., segmentation and prediction). We advance an approach to adjudicate between the two models: analyzing the phase lag between stimulus and neural signal across different stimulation rates. We ran numerical simulations of evoked and oscillatory computational models, showing that in the evoked case,phase lag is heavily rate-dependent, while the oscillatory model displays marked phase concentration across stimulation rates. Next, we compared these model predictions with magnetoencephalography data recorded while participants listened to music of varying note rates. Our results show that the phase concentration of the experimental data is more in line with the oscillatory model than with the evoked model. This finding supports an auditory cortical signal that () contains components of both bottom-up evoked responses and internal oscillatory synchronization whose strengths are weighted by their appropriateness for particular stimulus types and () cannot be explained by evoked responses alone.
大量研究有力地证明了听觉皮层与包括语音和音乐在内的声音的节奏结构同步在其中发挥了作用。一些研究假设，听觉皮层中的振荡器可能是分割和预测等重要时间进程的基础。这些发现的一个重要批评提出了一个合理的担忧，即所测量的可能不是振荡器，而是诱发反应的序列。在节奏输入的情况下，这两种截然不同的机制可能看起来非常相似，但振荡器可能更能提供上述计算作用（即分割和预测）。我们提出了一种方法来判断这两种模型：分析在不同刺激率下刺激和神经信号之间的相位滞后。我们对诱发和振荡计算模型进行了数值模拟，结果表明在诱发情况下，相位滞后严重依赖于速率，而振荡模型在刺激率下表现出明显的相位集中。接下来，我们将这些模型预测与参与者听不同音符率音乐时记录的脑磁图数据进行了比较。我们的结果表明，实验数据的相位集中更符合振荡模型，而不符合诱发模型。这一发现支持了一种听觉皮层信号，该信号 () 包含由其对特定刺激类型的适宜性加权的自上而下诱发反应和内部振荡同步的成分，并且 () 不能仅用诱发反应来解释。
