CAREER: Neural Dynamics of Sleep-Mediated Learning in Brain Computer Interface (BCI) Applications

职业：脑机接口 (BCI) 应用中睡眠介导学习的神经动力学

• 批准号: 2047529
• 负责人: Sujith Vijayan
• 金额: $ 69.64万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2047529&HistoricalAwards=false
• 关键词: CAREER; Neural; Dynamics; Sleep; Mediated

Brain Computer Interfaces (BCIs) allow an individual’s brain activity to control an external device or application (e.g., a prosthetic arm, wheelchair, or cursor on a computer screen), but learning to use BCIs proficiently often takes significant time and effort, which can be frustrating to the user. A better understanding of the role of sleep in BCI learning may allow for interventions that speed up learning in BCI applications. Sleep is known to boost learning and memory consolidation for a variety of tasks and sleep can be manipulated to enhance and speed up learning (e.g., by playing task-related auditory cues during sleep). However, the importance of sleep for BCI learning remains unknown. This research will examine whether sleep plays a role in learning BCI tasks and whether sleep can be manipulated using covert auditory sounds to speed up BCI learning. This work will provide the basic science knowledge needed for a safe, non-invasive, sleep-based intervention that will allow individuals to master the use of an assistive BCI device more quickly by engaging learning pathways that are active during sleep. An enhanced understanding of the fundamental relationship between sleep and learning will also lead to better treatment for diseases in which cognitive and memory deficits are tied to abnormal sleep (e.g., schizophrenia). This project also offers research opportunities that will enhance undergraduate and K-12 education through curriculum development and outreach initiatives that incorporate aspects of sleep and learning, BCIs, and brain activity.This project will employ computational and experimental methods to investigate the role of sleep in BCI learning. Subjects will move a cursor by modulating their brain activity before and after sleep. Simultaneously, neural data will be collected: either EEG data from healthy subjects (to probe large-scale neural dynamics) or human intracranial depth electrode data from patients undergoing invasive monitoring (to probe circuit-level and single neuron dynamics). In additional studies using the same basic design, task-related or carefully chosen non-task-related auditory cues will be played covertly during sleep. These studies will identify the neural dynamics crucial to sleep-mediated learning of BCI applications and the ways in which to optimally engage these processes and manipulate sleep to speed up learning. The generalization of the adaptive stimulation paradigm developed for this work could be applied in broad contexts in which stimuli are presented to manipulate, probe, and characterize brain dynamics; to facilitate such investigations, the software will be made freely available. The proposed work will lay the foundation for a large-scale and potentially transformative research program to investigate sleep and learning, as the experimenter’s ability to choose and perturb the mappings that control BCI tasks may facilitate the identification of the neural features critical for sleep-mediated learning and potentially reveal novel mechanisms related to sleep-mediated learning.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.

脑机接口（BCI）允许个体的大脑活动控制外部设备或应用程序（例如，假肢、轮椅或计算机屏幕上的光标），但是学习熟练地使用BCI通常需要大量的时间和精力，这可能会使用户感到沮丧。更好地理解睡眠在BCI学习中的作用可能会允许在BCI应用中加速学习的干预措施。众所周知，睡眠可以促进学习和记忆巩固各种任务，睡眠可以被操纵来增强和加速学习（例如，通过在睡眠期间播放与任务相关的听觉线索）。然而，睡眠对于BCI学习的重要性仍然未知。这项研究将研究睡眠是否在学习BCI任务中发挥作用，以及睡眠是否可以使用隐蔽的听觉声音来加速BCI学习。这项工作将提供安全，非侵入性，基于睡眠的干预所需的基本科学知识，使个人能够通过参与睡眠期间活跃的学习途径更快地掌握辅助BCI设备的使用。对睡眠和学习之间基本关系的进一步理解也将有助于更好地治疗认知和记忆缺陷与异常睡眠有关的疾病（例如，精神分裂症）。该项目还提供了研究机会，将通过课程开发和推广活动，包括睡眠和学习，脑机接口和大脑活动方面，提高本科生和K-12教育。该项目将采用计算和实验方法来调查睡眠在脑机接口学习中的作用。受试者将通过调节睡眠前后的大脑活动来移动光标。同时，将收集神经数据：来自健康受试者的EEG数据（以探测大规模神经动力学）或来自接受侵入性监测的患者的人类颅内深部电极数据（以探测电路水平和单个神经元动力学）。在使用相同基本设计的其他研究中，任务相关或精心选择的非任务相关听觉线索将在睡眠期间秘密播放。这些研究将确定对BCI应用的睡眠介导学习至关重要的神经动力学，以及最佳参与这些过程和操纵睡眠以加速学习的方式。为这项工作开发的自适应刺激范式的推广可以应用于广泛的背景下，其中刺激被提出来操纵，探测和表征大脑动力学;为了促进这种调查，该软件将免费提供。这项拟议中的工作将为一项大规模的、具有潜在变革性的研究计划奠定基础，该计划将调查睡眠和学习，因为实验者选择和干扰控制BCI任务的映射的能力可能有助于识别对睡眠介导学习至关重要的神经特征，并可能揭示与睡眠相关的新机制。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。

项目成果

Emotional Memory Processing during REM Sleep with Implications for Post-Traumatic Stress Disorder

• DOI: 10.1523/jneurosci.1020-22.2022
• 发表时间: 2023-01-18
• 期刊: JOURNAL OF NEUROSCIENCE
• 影响因子: 5.3
• 作者: Young-Ah，Rho;Sherfey，Jason;Vijayan，Sujith
• 通讯作者: Vijayan，Sujith