Predicting attention fluctuations and their consequences for memory from functional brain connectivity

持续的注意力对于安全和成功地完成日常任务至关重要，比如开车或听演讲。然而，当我们经历走神、分心、无聊或疲惫时，我们保持专注的能力会随着时间的推移而波动（即，当我们试图保持注意力时，感觉我们“没油了”）。由此产生的注意力缺失会对正在进行的行为产生有害的后果，例如注意力的缺失会导致我们在高速公路上错过出口。这种失败也可能影响后来的记忆，例如，导致我们在疏忽时遇到的材料测试表现不佳。虽然注意力的波动是普遍存在的，但研究人员缺乏一种方法来跟踪注意力随时间的变化，预测注意力的丧失，并描述注意力波动对各种情况下随后记忆的影响，例如观看讲座或执行注意力任务（例如，要求人监视图像流并检测稀有目标画面的任务）。该项目将使用功能性磁共振成像（fMRI）数据来预测心理和“自然主义”任务（如看电影和听故事）中的注意力波动，并询问注意力状态的fMRI活动特征是否会影响人们以后的记忆。这项工作可以帮助我们更好地跟踪注意力的变化，并预测在实验室和现实世界中的注意力失败，并将导致更好地了解我们如何参加影响我们记住的方式。最近的工作表明，功能性大脑连接模式预测一个人保持注意力的整体能力。功能性连接是用功能性磁共振成像（fMRI）测量的，反映了两个不同脑区的fMRI信号时间过程之间的统计依赖性。当区域被认为是强功能连接时，这些区域的活动往往同步增加和减少，而功能连接较弱的区域的活动则不同步。拟议中的项目询问功能连接从一个时刻到下一个时刻的变化，即功能连接动态，是否反映了一个人参与手头任务的程度的变化。该项目还将描述这些波动的注意力状态如何影响正在进行的行为和后来的记忆。具体来说，研究人员将在三种不同类型的扫描中收集fMRI数据。在每次扫描过程中，志愿者将被要求要么执行注意力任务，在这个任务中，他们按下一个按钮来回应屏幕上出现在图像流中的某些图片，安静地休息，要么看电影或听故事，后者更接近于反映我们通常经历注意力波动的真实情况。研究人员将提出三个主要问题。首先，功能连接动态（通过计算功能磁共振成像扫描期间短时间窗口内的功能连接强度来测量）如何与任务、休息期和叙述期间的注意力动态相关？其次，大脑网络的重叠或不同程度如何，其中活动的强度预测了不同背景下的整体持续注意力和注意力波动（即，任务表现，休息，视觉和听觉叙事感知）？最后，在信息编码过程中，注意状态的大脑特征如何与后来的记忆表现相关，包括在注意力任务中遇到的图像的识别以及电影和故事叙述的口头回忆？这项工作可能会提高我们跟踪焦点随时间变化的能力，并在实验和自然环境中预测注意力失败。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Sustained attention is critical for safely and successfully completing everyday tasks, like driving a car or listening to a presentation. Our ability to maintain focus, however, fluctuates over time when we experience mind wandering, distraction, boredom, or depletion (i.e., feeling like we’re “out of gas” when we try to sustain attention). Resulting attention failures can have deleterious consequences for ongoing behavior, such as a lapse in attention causing us to miss our exit on the highway. Such failures may also impact later memory, for example, leading to poor performance on tests of material we encountered while being inattentive. Although fluctuations in attention are pervasive, researchers lack a way to track changes in attention over time, predict attention lapses, and characterize the consequences of attention fluctuations for subsequent memory in a variety of situations, such as watching a lecture or performing an attention task (e.g., a task that requires a person to monitor a stream of images and detect a rare target picture). This project will use functional magnetic resonance imaging (fMRI) data to predict attention fluctuations during psychological and “naturalistic” tasks—like watching movies and listening to stories—and ask whether fMRI activity signatures of attentional states impact what people go on to remember at a later time. This work may help us better track attention changes and predict attention failures in lab-based and real-world contexts and will lead to a better understanding of the manner in which how we attend affects what we remember.Recent work suggests that patterns of functional brain connectivity predict a person’s overall ability to sustain attention. Functional connectivity is measured with functional magnetic resonance imaging (fMRI) and reflects statistical dependence between the fMRI signal time-courses in two different brain regions. When regions are said to be strongly functionally connected, activity in those regions tends to increase and decrease in sync, whereas activity in regions that are weakly functionally connected varies out of sync. The proposed project asks whether changes in functional connectivity from one moment to the next—that is, functional connectivity dynamics—reflect changes in the degree to which a person is attending to the task at hand. The project will also characterize how these fluctuating attentional states affect ongoing behavior and later memory. Specifically, the investigators will collect fMRI data during three different types of scans. During each scan, volunteers will be asked to either perform attention tasks in which they press a button in response to certain pictures that appear in a stream of images on a screen, rest quietly, or watch movies or listen to stories—the latter of which more closely mirror real-world situations in which we commonly experience attention fluctuations. The researchers will ask three primary questions. First, how do functional connectivity dynamics (measured by calculating functional connectivity strength in short time windows during fMRI scans) relate to attention dynamics during the tasks, rest period, and narratives? Second, how overlapping or distinct are brain networks in which the strength of activity predicts overall sustained attention and attention fluctuations in different contexts (i.e., task performance, rest, and visual and auditory narrative perception)? Finally, how are brain signatures of attentional states during encoding of information related to later memory performance, including recognition of the images encountered during the attention tasks and verbal recall of the movie and story narratives? This work may improve our ability to track changes in focus over time and predict attention failures in experimental and naturalistic contexts. It will provide insights into the functional architecture of sustained attention itself and inform us about the relationships between sustained attention and memory.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.