Mapping perception and emotion in the human brain with functional magnetic resonance imaging and diffusion tensor imaging using naturalistic stimuli

使用自然刺激的功能磁共振成像和扩散张量成像来绘制人脑中的感知和情绪

• 批准号: RGPIN-2021-03568
• 负责人: Ekstrand, Chelsea
• 金额: $ 2.4万
• 依托单位: University of Lethbridge
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742617
• 关键词: Mapping; perception; emotion; human; brain

Creating cognitive maps of how the brain processes the real-world around us is a central goal of neuroscience. This is no simple task, however, as human cognition is vastly complex, nuanced, and involves processing information in a multimodal and dynamic world. Because of its complexity, previous research has relied on proxies of stimuli in the real-world that may not adequately represent the stimulus (and thus the cognitive process) they are attempting to investigate. Increasingly, research in cognitive neuroscience is shifting away from strictly controlled experimental paradigms in favour of more naturalistic tasks to probe the multiscale dynamics of real-world processing. Naturalistic stimuli (such as audiovisual movies) may be better suited to help map complex human brain responses by providing a more valid proxy of natural viewing and listening. With the shift from strict control to naturalistic cognition, however, comes the computational challenge of analyzing, interpreting, and disentangling complex brain responses in a meaningful way. To overcome these challenges, my research combines behavioural, neuroimaging, and computational techniques to study the brain under dynamic and naturalistic conditions. The long-term objective of this program of research is to map the structural and functional architecture of naturalistic cognition in the human brain. To achieve this, this program of research has three specific short-term objectives: 1) to build a database of emotional, perceptual, and physiological responses of individuals to a wide range of movie stimuli that will be an essential and valuable resource for expanding the field of naturalistic neuroscience; 2) to use advanced data-driven analysis approaches that identify events in movie stimuli using brain activity patterns and integrate brain response patterns with perceptual and emotional attributes of the stimulus; and 3) to use state-of-the-art computational modeling techniques to identify structure/function relationships between white matter connectivity and naturalistic brain responses. This highly innovative program of research will take a systems approach to the study of naturalistic cognition by incorporating behavioural characteristics, functional neuroimaging, and structural connectivity to identify the underlying network architecture of naturalistic cognition. Thus, it will facilitate ground-breaking advancements in the field of naturalistic neuroscience in Canada and will provide the first step to mapping the structural and functional architecture of real-world cognition in the human brain. This research will be at the forefront of an exciting and timely data-driven approach to cognitive neuroscience aimed at bridging the gap between research and the real-world. Further, it will provide a critical benefit to society by elucidating the ways in which the brain is able to process the complex, multimodal world around us.

创建有关大脑如何处理我们周围的现实世界的认知图是神经科学的核心目标。但是，这并不是一个简单的任务，因为人类认知非常复杂，细微差别，并且涉及在多模式和动态世界中处理信息。由于其复杂性，以前的研究依赖于现实世界中可能无法充分代表刺激的刺激的代理（因此是认知过程）。认知神经科学的研究越来越多地从严格控制的实验范式转移到了更自然的任务，以探究现实世界加工的多尺度动力学。自然主义的刺激（例如视听电影）可能更适合通过提供自然观看和聆听的更有效的代理来帮助绘制复杂的人脑反应。 然而，随着从严格控制向自然主义认知的转变，以有意义的方式分析，解释和解释复杂的大脑反应的计算挑战。为了克服这些挑战，我的研究结合了行为，神经影像学和计算技术，以在动态和自然主义条件下研究大脑。该研究计划的长期目标是绘制人脑自然认知的结构和功能结构。为了实现这一目标，该研究计划具有三个特定的短期目标：1）建立个人对广泛的电影刺激的情感，感知和生理反应数据库，这将是扩大自然主义神经科学领域的重要资源； 2）使用先进的数据驱动分析方法，使用大脑活动模式识别电影刺激中的事件，并将大脑反应模式与刺激的感知和情感属性相结合； 3）使用最先进的计算建模技术来识别白质连通性和自然主义大脑反应之间的结构/功能关系。这项高度创新的研究计划将通过结合行为特征，功能性神经影像和结构连接性来采用系统方法来研究自然主义认知，以识别自然主义认知的潜在网络结构。因此，它将促进加拿大自然主义神经科学领域的突破性进步，并将提供第一步，以绘制人脑中现实世界认知的结构和功能性结构。这项研究将是一种令人兴奋的及时数据驱动方法的认知神经科学方法的最前沿，旨在弥合研究与现实世界之间的差距。此外，它将通过阐明大脑能够处理我们周围复杂的多模式世界的方式来为社会带来关键的好处。