A Computerized Intervention Targeting Cognitive Control Network Deficits in Depression

针对抑郁症认知控制网络缺陷的计算机干预

• 批准号: 10005461
• 负责人: JOAQUIN A ANGUERA
• 金额: $ 64.16万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-19 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10005461
• 关键词: 3-Dimensional; Adherence; Adult; Aftercare; Algorithms; Anisotropy; Anterior; Antidepressive Agents; Attention; Behavior; Behavioral; Caring; Clinical; Cognitive; Cognitive remediation; Control Groups; Data; Depressed mood; Development; Disease; Disease remission; Dorsal; Elderly; Expectancy; Functional Magnetic Resonance Imaging; Funding; Goals; Hamilton Rating Scale for Depression; Home environment; Individual; Intervention; Major Depressive Disorder; Measures; Mechanics; Medical; Mental Depression; Methods; Middle frontal gyrus structure; Moods; Nature; Negative Valence; Neurosciences; Outcome; Outcome Measure; Participant; Patient Self-Report; Peer Review; Performance; Phase; Pilot Projects; Predisposition; Protocols documentation; Psychotherapy; Randomized Clinical Trials; Research Design; Research Domain Criteria; Research Methodology; Sampling; Short-Term Memory; Signal Transduction; Site; Specific qualifier value; Stimulus; Symptoms; System; Task Performances; Testing; Thinking; Training; Treatment Efficacy; Video Games; World Health Organization Disability Assessment Schedule; base; cingulate cortex; clinical efficacy; cognitive control; cognitive function; cognitive training; computerized; depressed patient; depressive symptoms; disability; emotion regulation; evidence base; experience; functional improvement; geriatric depression; improved; improved functioning; interest; middle age; mood symptom; problem solving therapy; randomized trial; recruit; response; sustained attention; therapy design; tool; trait; treatment adherence; white matter

Project: EVO (or “EVO”) is a mobile 3D video game that has been shown to reduce older adults' susceptibility to interference by augmenting sustained attention and working memory abilities (e.g. cognitive control) through targeted adaptive algorithms. The combination of peer-reviewed validity, adaptivity, and fun video game mechanics elevates the EVO platform beyond other at-home training tools while reducing burden associated with tedious task replication. We propose to study EVO as a potential intervention for the treatment of depression, a disorder that worsens medical outcomes, promotes disability, increases expense, and complicates medical care by clouding the clinical picture and undermining treatment adherence. R61 Phase: We will first conduct a 2-year proof of concept study to determine if EVO can engage the cognitive control network (CCN) in 30 middle-aged and older adults with major depression. Primary aims for this phase of the proposed project are to determine if EVO will result in greater CCN engagement using three levels of analysis (circuitry, performance, self-report). At the circuitry level, we will measure CCN engagement by probing the system using task-based fMRI. We hypothesize that activation and functional connectivity (FC) of anterior aspects of the CCN will increase from baseline to 4-weeks after treatment initiation. Our decision to move to the next phase of the planned study is that 66% of our sample will show significant increases in CCN functions at the circuitry level of analysis (CCN activation and FC) and at either the performance level or self- report level of analysis. R33 Phase: Should our proof of concept phase pass the Go/No-go rule, we will then conduct a 3-year pilot study to compare EVO to an expectancy-matched control game in terms of CCN target engagement at the circuitry (task-based fMRI) and behavioral levels (task performance, self-report) in 60 middle-aged and older adults with major depression. In addition, we well determine if changes in target engagement are associated with changes in mood and mood-induced disability. The decision to move onto development of a proposal to study the clinical efficacy of EVO in a larger randomized clinical trial will be based on whether we find (1) that EVO out-performs our control condition in terms of the engagement of CCN at the circuitry and behavioral levels (2) significant associations between changes in engagement of the CCN and changes in mood and (3) that the study methods are feasible to complete (sampling rate, retention, intervention adherence, intervention acceptability and expectancy-match for our control condition).

项目：EVO(或“EVO”)是一款移动3D视频游戏，已被证明可以降低老年人的易感性 通过增强持续的注意力和工作记忆能力(如认知控制)来进行干预 有针对性的自适应算法。结合同行评议的有效性、适应性和趣味性的视频游戏 机械师将EVO平台提升为超越其他家庭培训工具，同时减少相关负担 单调乏味的任务复制。我们建议研究EVO作为一种潜在的干预措施来治疗 抑郁症是一种疾病，会恶化医疗结果，促进残疾，增加费用，以及 使医疗护理复杂化，使临床情况变得模糊，并破坏了治疗的一致性。 R61阶段：我们将首先进行为期两年的概念验证研究，以确定EVO是否可以参与认知 30例中老年抑郁症患者的控制网络(CCN)检测这一阶段的主要目标 拟议项目的一部分是确定EVO是否将使用三个级别的 分析(电路、性能、自我报告)。在电路级别，我们将通过以下方式衡量CCN参与度 使用基于任务的功能磁共振检查系统。我们假设，激活和功能连接性(FC) 治疗开始后，CCN的前部将从基线增加到4周。我们决定 进入计划研究的下一阶段是，我们的样本中66%的人的CCN将显著增加 在电路分析级别(CCN激活和FC)以及在性能级别或自 报告分析级别。 R33阶段：如果我们的概念验证阶段通过了通过/不通过规则，我们将进行为期3年的试验 将EVO与预期匹配的控制游戏在CCN目标参与度方面进行比较的研究 60名中老年人的电路(基于任务的功能磁共振成像)和行为水平(任务表现、自我报告) 患有严重抑郁症的成年人。此外，我们很好地确定目标参与度的变化是否与 情绪的变化和情绪导致的残疾。决定制定一项提案，以 在更大规模的随机临床试验中研究EVO的临床疗效将基于我们是否发现(1) 就CCN在电路和行为上的接合而言，EVO的表现优于我们的控制条件 水平(2)CCN参与度的变化与情绪变化之间的显著关联和(3) 研究方法是可行的(抽样率、保留率、干预依从性、干预措施 可接受性和预期-与我们的控制条件匹配)。