Department of Media, Aalto University School of Arts, Design and Architecture, Helsinki, Finland.
Baltic Film, Media, Arts and Communication School, Tallinn University, Tallinn, Estonia.
PLoS One. 2018 Jul 3;13(7):e0200134. doi: 10.1371/journal.pone.0200134. eCollection 2018.
Narratives surround us in our everyday life in different forms. In the sensory brain areas, the processing of narratives is dependent on the media of presentation, be that in audiovisual or written form. However, little is known of the brain areas that process complex narrative content mediated by various forms. To isolate these regions, we looked for the functional networks reacting in a similar manner to the same narrative content despite different media of presentation. We collected 3-T fMRI whole brain data from 31 healthy human adults during two separate runs when they were either viewing a movie or reading its screenplay text. The independent component analysis (ICA) was used to separate 40 components. By correlating the components' time-courses between the two different media conditions, we could isolate 5 functional networks that particularly related to the same narrative content. These TOP-5 components with the highest correlation covered fronto-temporal, parietal, and occipital areas with no major involvement of primary visual or auditory cortices. Interestingly, the top-ranked network with highest modality-invariance also correlated negatively with the dialogue predictor, thus pinpointing that narrative comprehension entails processes that are not language-reliant. In summary, our novel experiment design provided new insight into narrative comprehension networks across modalities.
叙事在我们的日常生活中以不同的形式围绕着我们。在感觉大脑区域中,叙事的处理依赖于呈现的媒介,无论是视听形式还是书面形式。然而,对于通过各种形式传递的复杂叙事内容所涉及的大脑区域知之甚少。为了分离这些区域,我们寻找在观看电影或阅读其剧本文本时,对相同叙事内容以相似方式反应的功能网络。我们在两次独立的运行中从 31 名健康成年人那里收集了 3-T fMRI 全脑数据,当时他们要么观看电影,要么阅读其剧本。独立成分分析(ICA)用于分离 40 个组件。通过比较两种不同媒体条件下的组件时间历程,我们可以分离出与相同叙事内容特别相关的 5 个功能网络。这 5 个具有最高相关性的 TOP-5 组件涵盖了额颞叶、顶叶和枕叶区域,而主要视觉或听觉皮质没有明显参与。有趣的是,模式不变性最高的网络与对话预测器呈负相关,这表明叙事理解需要不依赖语言的过程。总之,我们新颖的实验设计为跨模态的叙事理解网络提供了新的见解。