REAL-TIME LOCALIZED NEUROMODULATION IN MAJOR DEPRESSION

重度抑郁症的实时局部神经调节

• 批准号: 7722872
• 负责人: Paul Lawrence Hamilton
• 金额: $ 0.56万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7722872
• 关键词: Brain; Computer Retrieval of Information on Scientific Projects Database; Computer software; Data; Disease; Disease model; Effectiveness; Functional Magnetic Resonance Imaging; Funding; Grant; Institution; Learning; Localized; Major Depressive Disorder; Maps; Mental Depression; Methods; Modeling; Participant; Quality of life; Research; Research Personnel; Resources; Signal Transduction; Source; System; Techniques; Therapeutic procedure; Time; Training; United States National Institutes of Health; Update; blood oxygen level dependent; depressive symptoms; design; interest; neuroimaging; novel therapeutics; relating to nervous system

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Background: The application of functional neuroimaging techniques to the study of major depressive disorder has been critical in helping to identifying its neural correlates as well as in informing neuroaffective models of the disorder. Two shortcomings of this approach have emerged, however. First, investigators have not distinguished neural correlates of depression from neural factors that are involved more critically in producing and sustaining depressive symptomatology. This distinction is essential in creating informative and useful neuroaffective models of depression. Second, functional neuroimaging studies of depression have had limited impact on the quality of life among those suffering from the disorder. This study was designed both to examine the use of real-time localized neurofeedback training to isolate crucial neural factors in depression, and to assess the potential effectiveness of real-time neurofeedback as a novel therapeutic procedure in the treatment of depression. Methods and preliminary data: We have developed a software and hardware configuration capable of extracting and analyzing blood oxygen level dependent (BOLD) fMRI data in real time. Currently, this system can extract and display continuously updated BOLD signal both from a region of interest and from the whole brain. This information can be presented to participants who can then, through iterative trial and error, learn to modulate activity within a given region of interest. In addition, statistical maps reflecting contrasts of interest can be generated and displayed in real time.

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