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Distinct Mechanism of Audiovisual Integration With Informative and Uninformative Sound in a Visual Detection Task: A DCM Study

机译:视觉检测任务中视听集成与信息性和非信息性声音的区别机制:DCM研究

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摘要

Previous studies have shown that task-irrelevant auditory information can provide temporal clues for the detection of visual targets and improve visual perception; such sounds are called informative sounds. The neural mechanism of the integration of informative sound and visual stimulus has been investigated extensively, using behavioral measurement or neuroimaging methods such as functional magnetic resonance imaging (fMRI) and event-related potential (ERP), but the dynamic processes of audiovisual integration cannot be characterized formally in terms of directed neuronal coupling. The present study adopts dynamic causal modeling (DCM) of fMRI data to identify changes in effective connectivity in the hierarchical brain networks that underwrite audiovisual integration and memory. This allows us to characterize context-sensitive changes in neuronal coupling and show how visual processing is contextualized by the processing of informative and uninformative sounds. Our results show that audiovisual integration with informative and uninformative sounds conforms to different optimal models in the two conditions, indicating distinct neural mechanisms of audiovisual integration. The findings also reveal that a sound is uninformative owing to low-level automatic audiovisual integration and informative owing to integration in high-level cognitive processes.
机译:先前的研究表明,与任务无关的听觉信息可以为视觉目标的检测提供时间线索,并改善视觉感知。这种声音称为信息性声音。使用行为测量或神经影像学方法(例如功能磁共振成像(fMRI)和事件相关电位(ERP)),已经广泛研究了信息性声音和视觉刺激整合的神经机制,但视听整合的动态过程无法在定向神经元耦合方面正式表征。本研究采用fMRI数据的动态因果模型(DCM)来识别承保视听整合和记忆的分层大脑网络中有效连接的变化。这使我们能够表征神经元耦合中上下文相关的变化,并显示视觉处理如何通过信息性和非信息性声音的处理来实现上下文化。我们的结果表明,在两种情况下,具有信息性和非信息性声音的视听整合符合不同的最佳模型,表明了视听整合的独特神经机制。研究结果还表明,由于低级别的自动视听集成,声音没有信息性,而由于高级认知过程的集成,声音没有信息性。

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