The Neural Basis of Internal Attention

我们的大脑是如何让我们关注自己的想法的？当你审阅一份手稿时，你可能会偶尔发现自己在回忆去年的暑假。这种内部注意状态是我们日常认知的一个突出方面，涉及到内部参与认知过程，如记忆回忆。它与适应性结果（如创造力）和适应性不良后果（如表现缺陷）有关。虽然它占据了我们清醒时间的一半，但内部注意力的神经基础在很大程度上仍然是未知的。总的来说，我的NSERC研究项目旨在阐明支持这一基本认知现象的神经机制和结构。特别是，我将与我的HQP团队一起努力实现三个主要目标。首先，我将阐明特定类型的内部注意背后的神经机制。虽然我之前的研究建立了内部注意的时空动态，但它的异质性并没有被考虑。因此，目前的建议将是第一个揭示支持不同类型的内部注意的神经机制。其次，我将建立默认网络子系统在内部的关键作用。我最近的工作表明，额顶叶控制网络的组成部分是因果关系；然而，默认网络子系统的因果作用仍然未知。第三，我将在生态有效范式中使用带有EEG测量的机器学习实时预测内部注意力状态。这将是第一个使用自然刺激和电生理测量来实时检测内部注意力的研究。为了实现这些目标，我将采用几种方法方法。提出的研究主要依赖于脑电图（EEG）记录和先进的信号处理技术。它们还涉及神经心理学方法，以确定内部注意所需的神经基质的因果关系，以及使用颅内脑电图的神经外科方法。这是认知神经科学中的一种新兴方法，其特点是具有出色的空间和时间分辨率，对于阐明内部注意力的神经动力学非常重要。此外，拟议的研究需要先进的统计技术，包括线性混合效应模型分析和基于聚类的排列检验。这种独特的方法组合将为我的hqp提供绝佳的机会，让他们掌握关键技能，帮助他们在未来的岗位上脱颖而出。我提出的研究将是发展一个理论模型的关键，解释内部注意的神经生理学基础，从而巩固加拿大作为注意力神经科学研究的主要贡献者。该项目最终将推动优化注意力控制工具的开发，这将使加拿大人在教育和职业环境中受益。

How does our brain enable us to pay attention to our thoughts? As you review a manuscript, you may occasionally find yourself reminiscing your last summer vacation. This internal attention state is a prominent aspect of our everyday cognition that involves attending internally to cognitive processes such as memory recall. It is associated with adaptive outcomes such as creativity and maladaptive consequences such as performance deficits. Although it occupies up to half of our awake time, the neural basis of internal attention remains largely unknown. Broadly, my NSERC research program aims to elucidate the neural mechanisms and structures supporting this fundamental cognitive phenomenon. In particular, I will work with my team of HQP to pursue three main objectives. First, I will clarify the neural mechanisms underlying specific types of internal attention. Although my previous research established the spatiotemporal dynamics of internal attention, its heterogeneous nature was not considered. Therefore the current proposal will be the first to reveal the neural mechanism supporting different types of internal attention. Second, I will establish the critical role of default network subsystems in internal attention. My recent work indicated components of the fronto-parietal control network are causally involved; however, the causal role of default network subsystems remains unknown. Third, I will predict internal attention states in real time using machine learning with EEG measures in ecologically valid paradigms. This will be the first study to use naturalistic stimuli with electrophysiological measures for real time detection of internal attention. To address these objectives, I will employ several methodological approaches. The proposed studies primarily rely on electroencephalogram (EEG) recordings, and advanced signal processing techniques. They also involve the neuropsychological approach to determine the causal relevance of neural substrates necessary for internal attention, as well as the neurosurgical approach using intracranial EEG. This is an emerging methodology in cognitive neuroscience that is characterized by excellent spatial and temporal resolution important for elucidating the neural dynamics of internal attention. In addition, the proposed research requires advanced statistical techniques, including linear mixed effects model analyses and cluster based permutation tests. This unique combination of approaches will provide outstanding opportunities for my HQPs to master crucial skills that will help them excel in future positions. My proposed research will be pivotal for developing a theoretical model that explains the neurophysiological basis of internal attention, thereby solidifying Canada as a leading contributor to attentional neuroscience research. This program will ultimately drive the development of tools that optimize attentional control, which will benefit Canadians in educational and occupational settings.