发表机构
ELTE Eötvös Loránd University; Budapest University of Technology; HUN-REN Wigner Research Centre for Physics; Semmelweis University; University of Miskolc; University of Szeged; The University of Texas at Austin（埃尔特大学; 布达佩斯技术大学; HUN-REN威金物理研究所; 塞梅尔维斯大学; 米什科尔茨大学; 塞格德大学; 德克萨斯大学奥斯汀分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究利用连续脑电图探索叙事理解，提取与电影转换对齐的电位，发现转换相关电位受叙事背景影响，可用深度神经网络从连续记录中恢复，为分析观众理解电影叙事提供半自动框架，还可用于其他连续刺激。
AI 中文摘要
利用脑电图（EEG）进行脑研究的潜力，从根本上受到内在噪声和脑活动在头皮上扩散投影的限制。标准事件相关电位（ERP）范式虽通过重复独立试验解决了这一限制，但偏离了自然主义实验条件。作为更自然主义的替代方案，我们在参与者观看短片时收集连续脑电图，并提取与电影急剧转换（剪辑）对齐的电位。我们证明，这种转换相关电位（TRP）表现出与显著信息处理相关的典型ERP样时间结构。通过比较连贯电影与包含匹配剪辑后感官输入的场景打乱版本，我们发现这些反应受叙事背景系统影响。然后我们表明，与剪辑相关的脑电图特征可以用紧凑的深度神经网络（DNN）直接从群体平均连续记录中恢复。该探测器在电影和受试者群体中具有通用性，所得的TRP再现了手动标注剪辑所观察到的主要上下文依赖效应。这些结果表明，叙事背景在脑电图反应中留下了可测量的特征，该特征可以在连续记录中直接检测到，并且这种检测为分析观众如何处理和理解电影叙事提供了一个半自动框架。我们提出，这里概述的方法可以适用于解析对其他形式连续刺激的脑电图反应，为探索更接近人类自然体验的实验条件提供一个通用工具。
英文摘要
Harnessing the potential of electroencephalography (EEG) for brain research is fundamentally limited by intrinsic noise and the diffuse projection of brain-generated activity over the scalp. The standard event-related potential (ERP) paradigm addresses this limitation by relying on repeated independent trials, albeit at the cost of moving away from naturalistic experimental conditions. As a more naturalistic alternative, we collected continuous EEG while participants watched short films and extracted potentials aligned to sharp cinematic transitions (cuts). We demonstrate that such transition-related potentials (TRPs) exhibit canonical ERP-like temporal structure associated with significant information processing. By comparing coherent films with scene-scrambled versions containing matched post-cut sensory input, we find that these responses are systematically shaped by narrative context. We then show that the cut-related EEG signature can be recovered directly from group-averaged continuous recordings with a compact deep neural network (DNN). The detector generalized across films and subject groups, and the resulting TRPs reproduced the main context-dependent effects observed for manually annotated cuts. These results indicate that narrative context leaves a measurable signature in EEG responses, that this signature can be detected directly in continuous recordings, and that such detections provide a semi-automated framework for analyzing how viewers process and understand film narratives. We propose that the method outlined here can be adapted to parse EEG responses to other forms of continuous stimulation, providing a general tool for probing experimental conditions that are closer to natural human experience.
Comments40 pages, 14 figures
