Learned regulation of the limbic network via combined EEG and fMRI

描述(申请人提供)：该项目旨在开发一种新的治疗常见神经精神障碍的潜在方法，特别是慢性疼痛综合症和情感障碍，包括抑郁、焦虑和创伤后应激障碍(PTSD)。我们之前已经证明，实时功能磁共振成像(RT-fMRI)可以提供反馈信号(神经反馈)，允许人们获得对嘴前扣带核(RACC)激活的学习自愿控制，这反过来又改变了痛觉。这里, 我们的目标是开发一种大脑验证的脑电(EEG)神经反馈方法，包括同时进行EEG和fMRI记录。然后，这个系统将被用来确定反映rACC和杏仁核调控的脑电信号。多种精神状态(如抑郁、焦虑)与无法调节情绪有关，表现为包括ACC和杏仁核在内的边缘环路功能障碍。然而，目前的精神病治疗方法通常缺乏关于大脑网络和机制的特异性。基于研究表明，个人可以通过在线反馈来训练自己调节自己的心理和生理反应，这项拟议的研究旨在开发一种新的工具，通过使用大脑信号作为反馈的基础，通过心理训练来增强生理弹性。因此，神经反馈可以为治疗神经精神障碍提供一种潜在的、互补的/替代的方法。同时采集的高空间分辨率fMRI数据和高时间分辨率EEG数据与先进的统计学习方法相结合，提供了一种合理的方法来推断和生成稳健而有效的EEG神经反馈信号，该信号甚至可以针对rACC或杏仁核等大脑深层结构作为反馈来源。鉴于精神病理学的高流行率和当前治疗的非特异性靶向，开发一种强大的方法来学习调节特定的边缘区域是重要的。具体地说，新的脑电神经反馈工具可能是一种新颖的、合理的、基于神经科学的治疗干预措施，可能成为一种便携式、易于使用和低成本的临床工具，用于改善对大脑工作的自我控制。从长远来看，这种技术可能有助于缓解慢性疼痛，调节抑郁症和焦虑症患者的情绪不稳定和痛苦。

DESCRIPTION (provided by applicant): This project aims to develop a novel potential treatment for common neuropsychiatric disorders, specifically chronic pain syndrome and affective disorders including depression, anxiety, and post-traumatic stress disorder (PTSD). We have previously shown that real-time functional magnetic resonance imaging (rt-fMRI) can provide a feedback signal (neurofeedback) that allows people to gain learned voluntary control of activation in the rostral anterior cingulate (rACC), which in turn alters pain perception. Here, we aim to develop a brain-validated electroencephalography (EEG) neurofeedback method that involves simultaneous EEG and fMRI recordings. This system will then be used to determine EEG signatures reflective of regulation of rACC and of the amygdala. Multiple psychiatric states (e.g., depressive, anxious) are associated with an inability to regulate emotion and appear to be characterized by dysfunction of the limbic circuit including the ACC and amygdala. However, current psychiatric treatment approaches typically lack specificity regarding brain networks and mechanisms. Based on research studies indicating that individuals can be trained to regulate their own mental and physiological responses through online feedback, the proposed study aims to develop a novel tool for enhancing physiological resilience through psychological training using brain signals as the basis for such feedback. Thus, neurofeedback can provide a potential, complementary/alternate approach for treatment of neuropsychiatric disturbances. The combination of simultaneously acquired high spatial-resolution fMRI data and high temporal-resolution EEG data together with advanced statistical learning approaches provide a plausible way to infer and generate a robust and effective EEG neurofeedback signals that can target even deep brain structures such as the rACC or amygdala as the source of feedback. Given the high prevalence of psychopathology and the non-specific targeting of current treatments, the development of a robust method for learned regulation of specific limbic regions is important. Specifically, the new EEG-neurofeedback tool could be a novel, rational, neuroscience-based therapeutic intervention that could become a portable, easy-to-use, and low-cost clinical tool for improving self-control over brain working. In the long-term such a technique could be useful in alleviating chronic pain and regulating emotional instability and agony in cases of depression and anxiety syndromes.