Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540.
Proc Natl Acad Sci U S A. 2022 Dec 20;119(51):e2209307119. doi: 10.1073/pnas.2209307119. Epub 2022 Dec 12.
When listening to spoken narratives, we must integrate information over multiple, concurrent timescales, building up from words to sentences to paragraphs to a coherent narrative. Recent evidence suggests that the brain relies on a chain of hierarchically organized areas with increasing temporal receptive windows to process naturalistic narratives. We hypothesized that the structure of this cortical processing hierarchy should result in an observable sequence of response lags between networks comprising the hierarchy during narrative comprehension. This study uses functional MRI to estimate the response lags between functional networks during narrative comprehension. We use intersubject cross-correlation analysis to capture network connectivity driven by the shared stimulus. We found a fixed temporal sequence of response lags-on the scale of several seconds-starting in early auditory areas, followed by language areas, the attention network, and lastly the default mode network. This gradient is consistent across eight distinct stories but absent in data acquired during rest or using a scrambled story stimulus, supporting our hypothesis that narrative construction gives rise to internetwork lags. Finally, we build a simple computational model for the neural dynamics underlying the construction of nested narrative features. Our simulations illustrate how the gradual accumulation of information within the boundaries of nested linguistic events, accompanied by increased activity at each level of the processing hierarchy, can give rise to the observed lag gradient.
在聆听口语叙述时，我们必须在多个并发时间尺度上整合信息，从单词、句子、段落到连贯的叙述。最近的证据表明，大脑依赖于一系列层次化组织的区域，这些区域的时间接收窗口逐渐增大，以处理自然叙事。我们假设，这种皮质处理层次结构的结构应该导致在叙述理解过程中，构成层次结构的网络之间存在可观察到的响应延迟序列。本研究使用功能磁共振成像来估计叙述理解过程中功能网络之间的响应延迟。我们使用主体间互相关分析来捕获由共享刺激驱动的网络连通性。我们发现，在听觉区域早期，接着是语言区域、注意力网络，最后是默认模式网络，存在一个固定的响应延迟时间序列——跨越几个秒的尺度。这种梯度在八个不同的故事中是一致的，但在休息时或使用打乱的故事刺激时的数据中不存在，支持了我们的假设，即叙述构建会产生网络间的延迟。最后，我们为嵌套叙述特征构建的神经动力学构建了一个简单的计算模型。我们的模拟说明了如何在嵌套语言事件的边界内逐渐积累信息，同时在处理层次结构的每个级别增加活动，从而产生观察到的延迟梯度。
