Neuroimaging and Neurocognitive Computerized Adaptive Testing in Schizophrenia

精神分裂症的神经影像学和神经认知计算机自适应测试

• 批准号: 8766955
• 负责人: Michael L Thomas
• 金额: $ 14.85万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8766955
• 关键词: Address; Area; Award; Base of the Brain; Behavior; Behavioral; Brain; Clinical; Clinical Research; Cognitive; Cognitive deficits; Complement; Consultations; Control Groups; Data; Development; Diagnosis; Disease; Functional Magnetic Resonance Imaging; Goals; Grant; Image; Knowledge; Link; Maps; Measurement; Memory impairment; Methodology; Modeling; National Institute of Mental Health; Neurocognitive; Neurocognitive Deficit; Participant; Patients; Pattern; Performance; Physiology; Plague; Prefrontal Cortex; Psychiatric therapeutic procedure; Psychometrics; Psychopathology; Psychotic Disorders; Public Health; Recording of previous events; Reporting; Research; Research Design; Research Personnel; Research Training; Scanning; Schizophrenia; Science; Shapes; Short-Term Memory; Space Models; Stimulus; Technology; Testing; Training; blood oxygen level dependent; brain behavior; career development; computerized; improved; innovation; mathematical model; neural recruitment; neuroimaging; novel; public health relevance; relating to nervous system; response; skills; spatiotemporal; stem; theories

DESCRIPTION (provided by applicant): Although schizophrenia researchers have a rich history of identifying psychometric confounds in clinical studies, problems continue to plague some areas of the field because these confounds have been addressed using measurement technologies developed in the early 20th century. In functional magnetic resonance imaging (fMRI), for instance, links between brain activation and behavior elicited through working memory (WM) tasks used during scanning can be obscured by confounds stemming from traditional measurement technology. The central premise of this grant is that applying modern measurement theory to task development is critical for using fMRI to test advanced brain-behavior models of cognitive psychopathology. Accordingly, this project will focus on training and research in psychometric imaging. The award will provide the candidate with support to pursue career development objectives that complement his expertise in advanced measurement theory and technology with training in fMRI with an applied focus on schizophrenia. The first training objective is for the candidate to obtain knowledge and skills needed to conduct schizophrenia research. In Specific Aim 1 he will use this training to show that matching item difficulty to WM ability through neurocognitive computerized adaptive testing minimizes and equates standard errors of ability estimates between patients and controls. This aim will establish an innovative methodology for eliminating the differential reliability confound in schizophrenia research. The second training objective is for the candidate to obtain knowledge and skills needed to conduct fMRI research. In Specific Aim 2 he will use this training to compare blood oxygen level-dependent response in dorsolateral prefrontal cortex between schizophrenia and control participants in order to test inverted-"U" and neural inefficiency brain activation models of WM deficits in schizophrenia. This aim will formally test two widely assumed but unconfirmed theories of cognitive psychopathology in the disorder. The third training objective is for the candidate to develop analytical skills needed to study functional bran networks. In Specific Aim 3 he will use this training to map spatiotemporal activation patterns in fMRI data using state-space modeling in order to explore the theory that patients show more disorganized neural recruitment than controls. This aim will robustly test the brain-behavior theory positing that WM deficits in schizophrenia are associated with poorly organized patterns of neural recruitment-as manifested by an increased number of brain-states and by activation that is uncoupled from performance-using a well-defined and modern psychometric testing approach. The candidate's long-term goals are to provide psychometric imaging consultation to researchers studying schizophrenia and other brain-based disorders and to develop an R01 plan to study advanced neuroimaging and mathematical modeling of cognitive psychopathology in psychotic disorders. This line of research will contribute to public health by identifying potential neural targets for psychiatric treatments aimed at reducing neurocognitive deficits in psychosis.

描述（由申请人提供）：尽管精神分裂症研究人员在临床研究中识别心理测量混淆方面有着丰富的历史，但由于使用世纪早期开发的测量技术已经解决了这些混淆问题，因此该领域的某些领域仍存在问题。例如，在功能性磁共振成像（fMRI）中，大脑激活与扫描过程中使用的工作记忆（WM）任务引发的行为之间的联系可能会被传统测量技术造成的混淆所掩盖。这项资助的中心前提是，将现代测量理论应用于任务开发，对于使用功能磁共振成像来测试认知精神病理学的高级大脑行为模型至关重要。因此，该项目将侧重于心理测量成像的培训和研究。该奖项将为候选人提供支持，以追求职业发展目标，以补充他在先进测量理论和技术方面的专业知识，并在功能磁共振成像方面进行培训，重点是精神分裂症。第一个培训目标是让候选人获得进行精神分裂症研究所需的知识和技能。在具体目标1中，他将使用这种训练来证明，通过神经认知计算机化自适应测试将项目难度与WM能力相匹配，最大限度地减少并等同于患者和对照组之间能力估计的标准误差。这一目标将建立一个创新的方法，以消除差异的信度混淆精神分裂症的研究。第二个培训目标是让候选人获得进行fMRI研究所需的知识和技能。在具体目标2中，他将使用这种训练来比较精神分裂症和对照受试者之间背外侧前额叶皮层的血氧水平依赖性反应，以测试精神分裂症WM缺陷的倒“U”型和神经低效脑激活模型。这一目标将正式测试两个广泛假设，但未经证实的理论认知精神病理学的障碍。第三个培训目标是培养候选人研究功能性麸皮网络所需的分析技能。在Specific Aim 3中，他将使用这种训练来使用状态空间建模来映射fMRI数据中的时空激活模式，以探索患者比对照组表现出更多无组织神经募集的理论。这一目标将有力地测试大脑行为理论，该理论认为精神分裂症中的WM缺陷与神经募集的组织不良模式相关，表现为大脑状态数量的增加和与表现脱钩的激活，使用定义明确的现代心理测量测试方法。候选人的长期目标是为研究精神分裂症和其他基于大脑的疾病的研究人员提供心理测量成像咨询，并制定R01计划，以研究精神障碍中认知精神病理学的高级神经成像和数学建模。这一系列的研究将有助于公共卫生，通过确定潜在的神经目标，精神病治疗，旨在减少精神病的神经认知缺陷。