Precisely quantifying the dynamic impact of sleep quality on cognitive fluctuations

项目总结 在越来越多的经验性行为治疗中，临床医生面临的主要挑战 确定特定治疗何时对谁有效(1-4)。现有的证据表明， 睡眠干预改善被诊断为多种精神障碍的成年人的认知功能 (5-7)。认知的改善反过来又预示着心理社会和适应能力的改善(8-10)。然而，鉴于 睡眠和认知功能之间的联系的强度因个体而异 时间(11-13)，所有认知受损的人都不太可能平等地从睡眠中受益 认知干预。这项工作的长期目标是开发和测试全面的、基于证据的 指导方针，将有助于优化有不良精神后果风险的成年人的认知功能。 这项F32提案的直接目标是量化睡眠对认知变化的动态影响 人与人之间和人内主持人的背景(例如，精神病学特征和状态)，使临床医生能够 评估患者的睡眠习惯如何影响认知表现，并相应地调整睡眠建议。 直到最近，由于技术限制，还无法评估睡眠和睡眠之间的动态联系 认知力。到目前为止，大多数关于这一主题的研究都招募了非临床样本，强加了非自然主义的睡眠 操作，和/或评估与单一认知结果有关的睡眠(最常见的是警觉)(14)。 为了克服临床翻译中的这些障碍，本研究将分析被动感知和生态学 来自大型多站点U01(Aurora；n=2626)和R01(TOTAL n=600)研究的瞬时评估(EMA)数据。 这些研究密集地抽样了睡眠(源于动作图)、认知功能(处理速度、记忆力和 警觉性)和心理状态(自我报告)变量在不同的临床和社区样本中，提供 史无前例的力量来开发一个可概括的模型来描述睡眠对认知波动的影响， 考虑到个体间和个体内的变异性，到目前为止，这种变异性混淆了精确的方法 干预。具体的目标有三个：(1)明确睡眠对认知变化的强烈影响 创伤后暴露的背景；(2)量化个体间和个体内的心理病理因素， 影响睡眠和认知之间关系的强度；以及(3)检验睡眠和认知之间的概括性 在独立的临床和社区样本中生成的模型。这一贡献意义重大，因为它将 促进个性化心理治疗干预，使临床医生能够定制睡眠指南 最大限度地有利于认知。这一提议具有创新性，因为它需要分析来自智能手机的数据- 参与者在典型条件下完成的基于认知的测量，增强生态有效性。 最后，这项提议具有启发性，因为它带来了精准精神病学、数字化的高级培训。 来自麦克莱恩精神病学技术研究所著名领导者的表型和重复性， 提供关键的知识和技能，以帮助候选人开始独立的研究生涯。

PROJECT SUMMARY Amid the ever-growing number of empirically-supported behavioral treatments, a principal challenge for clinicians is identifying when and for whom a given treatment will be effective (1–4). Extant evidence suggests the utility of sleep interventions to improve cognitive functioning in adults diagnosed with a variety of psychiatric disorders (5–7). Cognitive improvements, in turn, predict psychosocial and adaptive improvements (8–10). However, given that the strength of the association between sleep and cognitive functioning varies across individuals and over time (11–13), it is unlikely that all individuals with impaired cognition will benefit equally from sleep-based cognitive interventions. The long-term goal of this work is to develop and test comprehensive, evidence-based guidelines that will be useful in optimizing cognitive functioning in adults at risk for adverse psychiatric outcomes. The immediate objective of this F32 proposal is to quantify the dynamic impact of sleep on cognitive variation in the context of between- and within-person moderators (e.g., psychiatric traits and states), enabling clinicians to evaluate how patient sleep habits impact cognitive performance and tailor sleep recommendations accordingly. Until recently, technological limitations precluded assessment of the dynamic association between sleep and cognition. To date, most research on the topic has recruited non-clinical samples, imposed non-naturalistic sleep manipulations, and/or evaluated sleep in relation to a single cognitive outcome (most commonly, vigilance) (14). To overcome these barriers to clinical translation, the present study will analyze passive sensing and ecological momentary assessment (EMA) data from large, multisite U01 (AURORA; n=2626) and R01 (total n=600) studies. These studies densely sample sleep (actigraphy-derived), cognitive functioning (processing speed, memory, and vigilance), and psychological state (self-reported) variables in diverse clinical and community samples, affording unprecedented power to develop a generalizable model describing the impact of sleep on cognitive fluctuations, accounting for inter- and intra-individual variability that has heretofore confounded precision approaches to intervention. Specific aims are threefold: (1) to specify the robust impact of sleep on cognitive variation in the context of posttraumatic exposure; (2) to quantify inter- and intra-individual psychopathological factors that influence the strength of the relationship between sleep and cognition; and (3) to examine the generalizability of resultant models in independent clinical and community samples. This contribution is significant because it will facilitate individualized psychotherapeutic interventions, empowering clinicians to customize sleep guidelines to maximally benefit cognition. This proposal is innovative because it entails analysis of data from smartphone- based cognitive measures that participants complete under typical conditions, enhancing ecological validity. Finally, this proposal is instructive because it occasions advanced trainings in precision psychiatry, digital phenotyping, and reproducibility from renowned leaders at McLean’s Institute for Technology in Psychiatry, providing critical knowledge and skills to assist the candidate as she launches an independent research career.