Understanding the emotional dynamics of everyday life: modeling brain state changes and their implications for mental health

了解日常生活的情绪动态：模拟大脑状态变化及其对心理健康的影响

• 批准号: 10572732
• 负责人: Matthew E. Sachs
• 金额: --
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2023-01-02
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10572732
• 关键词: Address; Adult; Affect; Affective; Affective Symptoms; Attenuated; Basic Science; Behavioral Paradigm; Biometry; Brain; Brain region; Clinical; Clinical Research; Clinical Trials Design; Communication; Complex; Computer Models; Data; Data Analyses; Data Set; Diagnosis; Ecological momentary assessment; Emotional; Emotions; Environment; Experimental Designs; Faculty; Film; Functional Magnetic Resonance Imaging; Funding; Future; Goals; Individual; Individual Differences; Insula of Reil; Intervention; Knowledge; Learning; Life; Link; Magnetic Resonance Imaging; Major Depressive Disorder; Measures; Medial; Mental Depression; Mental Health; Methodology; Modeling; Mood Disorders; Moods; Music; Nature; Negative Valence; Neurobiology; Participant; Pattern; Persons; Positive Valence; Prediction of Response to Therapy; Prefrontal Cortex; Psychiatry; Research; Research Domain Criteria; Resources; Rest; Risk; Risk Assessment; Sampling; Severities; Signal Transduction; Specific qualifier value; Stimulus; Structure; Symptoms; System; Testing; Time; Training; United States National Institutes of Health; Universities; Variant; Work; analytical method; biotypes; brain based; career development; clinically significant; computational neuroscience; depressive symptoms; disabling symptom; emotional behavior; emotional experience; emotional stimulus; emotional symptom; environmental change; experience; flexibility; imaging study; improved; individual variation; member; movie; multimodality; neural; neurobehavioral; neurofeedback; neuroimaging; neuromechanism; non-verbal; novel; physical conditioning; positive emotional state; programs; public health relevance; response; self-reported depression; skills; spatiotemporal; theories; tool; trait

PROJECT SUMMARY / ABSTRACT Research has shown that individuals with, or at risk for developing, mood disorders have abnormalities in temporal aspects of their emotions in everyday life. Particularly relevant for major depressive disorder (MDD) is emotional inertia, which indicates an emotional system that is rigid and cannot flexibly respond to changing environmental demands. Lab studies have confirmed attenuated responses to both positive and negative stimuli in MDD, leading to the Emotion Context Insensitivity theory. Despite the relevance of affect dynamics for MDD, few studies have assessed the neural mechanisms that underly changing emotional states in an ecologically-valid manner. Resting-state fMRI studies have shown that time-varying patterns within and between fronto-insular and cortical midline brain regions have implications for both affect in daily life and MDD severity, but with an unstructured task like rest, it is difficult to assess how these patterns reflect emotional experiences. This project addresses these limitations through 3 specific aims that use naturalistic, emotional stimuli: (1) Determine time-varying brain patterns associated with dynamics of emotional experience in response to films; (2) Assess the time-varying brain patterns associated with emotions dynamics in response to a novel experimentally-designed musical stimuli; (3) Relate individual differences in time-varying brain patterns with individual differences in a) emotional dynamics in everyday life and b) affective traits related to depression. The hypothesis is that time-varying activation patterns in fronto-insular, subcortical, and cortical- midline regions will reflect changing emotions induced by movies and music and that variation in these patterns will predict variation in positive and negative emotion dynamics in daily life (over the course of weeks) and depression severity. Such results will specify the neural mechanisms underlying the association between emotional inertia and depression, lending neurobehavioral support for one of several emotion theories of mood disorders. The PI’s long-term goal is to become an NIH-funded faculty member of an R1 university, with a research program focused on modelling brain systems involved in complex, socioemotional behaviors and leveraging results to test new tools for characterizing, assessing risk for, and treating mood disorders. The training objectives are to (1) acquire practical knowledge needed to apply dynamic computational models to BOLD signal in response to naturalistic stimuli; (2) learn how clinicians conceptualize and measure affective symptoms of mood disorders; (3) further skills in experience sampling data analysis to model affect dynamics and predict individual differences in brain patterns; (4) enhance academic/professional skills to successfully transition to independence. Career development will take place at Columbia University, a vibrant research environment with outstanding resources to support the proposal, including relevant courses/ seminars, state- of-the-art MRI facilities, and expert faculty in Computational Neuroscience, Biostatistics, and Psychiatry.

项目摘要 /摘要 研究表明，患有或有发展的情绪障碍的人在 他们日常生活中情绪的临时方面。与重度抑郁症（MDD）特别相关的是 情绪惯性，这表明情绪系统是僵化的，无法灵活地响应变化 环境需求。实验室研究已证实对正面和负面的反应减弱 MDD中的刺激，导致情绪环境不敏感理论。尽管情感动态有相关性 对于MDD，很少有研究评估了神经机制，这些神经机制是在不断变化的情绪状态下的神经机制 生态播种方式。静止状态的fMRI研究表明，内部和时间变化的模式 在额 - 和皮质中线大脑区域之间对日常生活和MDD的影响都有影响 严重程度，但是有了像休息这样的非结构化任务，很难评估这些模式如何反映情感 经验。该项目通过使用自然主义，情感的3个特定目标来解决这些限制 刺激：（1）确定与情感体验动态相关的时变大脑模式 对电影的回应； （2）评估与情绪动态有关的随时间变化的大脑模式 进行实验设计的新颖的音乐刺激； （3）随时间变化的大脑的相关个体差异 a）日常生活中情感动态的模式和b）与 沮丧。假设是，前单键，皮质和皮质 - 皮质上的时变激活模式 中线区域将反映电影和音乐引起的不断变化的情绪以及这些模式的变化 将预测日常生活中积极和负面情绪动态的差异（在几周的过程中）和 抑郁严重程度。这样的结果将指定与 情绪惯性和抑郁，借用对情绪情绪理论之一的神经行为支持 疾病。 PI的长期目标是成为R1大学的NIH资助的教职员工， 研究计划的重点是建模涉及复杂，社会情感行为的大脑系统和 利用结果测试新工具以表征，评估和治疗情绪障碍的风险。 培训目标是（1）获取将动态计算模型应用于 响应自然主义刺激的大胆信号； （2）了解临床医生如何概念化和衡量情感 情绪障碍的症状； （3）进一步的经验抽样数据分析以模型影响动态的技能 并预测大脑模式的个体差异； （4）提高学术/专业技能 过渡到独立。职业发展将在哥伦比亚大学进行，这是一项充满活力的研究 具有支持该提案的杰出资源的环境，包括相关课程/半货人，州 - ART MRI设施以及计算神经科学，生物统计学和精神病学专家教师。