基于临床观察和量子化世界中脑波解码成果提出抑郁症"多神经递质脑空间振荡失衡"病机假说，推测中医辨证论治能双向调节失衡的递质拮抗对回归常态、改善脑区互联系数、提高脑区能级等微观机制。利用"脑讯息搜索"技术和分子流行病学设计探索抑郁症大脑及分区多神经递质拮抗对激活状况，并探索脑波量子化世界其余量子位指标，如脑全球化参数、脑量子化联接图、脑能级图、大脑全息图、量子意识模型的特征，寻找特征性生物标志。解析抑郁症脑波量子化异常指标（微观指标）与自制调查因素、五态人格、证候要素、QOL、EEG等宏观指标的相关性。同时探索抑郁症证候的宏观和微观病机，丰富抑郁症病机内涵。再通过队列研究和随机对照试验探索中医辨证论治抑郁症的脑波量子化指标转归规律，以验证病机假说和解析辨证论治机制。本研究方法对其它精神疾病的病机研究有借鉴作用，有希望成为一种研究范式。本研究模式亦可为中医个体化诊治评价研究开辟新思路。

From the proposed pathogenesis hypothesis of depression, i.e. imbalance of multiple neurotransmitter oscillation in brain spaces, based on clinical observations and fruits of the study of decoding the brain waves in a hidden quantum world，we speculated that the micro-mechanisms of traditional Chinese medicine(TCM) syndrome differential therapy can be of a two-directional adjustment on the neurotransmitters antagonizing pairs' imbalance status to a normal state, or improve the quantal inter-net quatient(QIQ) of brain regions, or increase the energy level of brain regions, et al. We plan to explore the activation status of multi-antagonizing pairs of neurotransmitters in both the whole brain and each brain region in depression population, and further the characters of other qubits' indexes of brain waves' quanta world such as brain global parameters(GPS), Qnet association(Qnet A), energy level graph, holograph(HOLO), quantum conscious mode with the technology of Search of Encephalo-Telex (SET) and the design of molecular epidemiology, so as to find the diagnostic bio-markers of depression. We also respectively explore the relativity of these abnormal indexes expression of brain waves' quanta world (namely micro-indexes) with self-designed investigated factors, five-state characters, essential elements of syndrome, quality of life (QOL) and EEG of these macro-indexes. Simultaneously, we also explore both the macro-pathogenesis and micro-pathogenesis of syndrome of TCM in depression, and thereupon, could enrich the connotation of depression pathogenesis. Finally, we will further study the evolutional mechanisms of the brain waves quantal indexes after Syndrome Differentiation and Treatment in TCM, by both cohort-study and randomized controlled trials, in order to illustrate the above pathogenesis hypothesis and therapeutic mechanism of TCM. This research method could use reference for pathogenesis study of other psychosis illness, and might become a research paradigm of this field. In addition, This research mode could also open up a new ideals for individualized evaluation study of diagnosis and treatment in TCM.

基于临床观察和量子化世界中脑波解码成果提出抑郁症“多神经递质脑空间振荡失衡”病机假说，利用“脑讯息搜索”技术和临床流行病学量表调查设计，探索抑郁症大脑及各分区多神经递质激活状况，揭示抑郁症人群脑波背后的分子生物标志－大脑各脑区多种神经递质变化规律，丰富抑郁症病机内涵；同时初步探索抑郁症各证候的大脑各脑区多种神经递质变化规律，初探抑郁症证候可能潜存的生物标志。结果：1建立了300余例抑郁症及对照组的关系型数据库，包括五态人格、五五体质、抑郁、焦虑、失眠、SCL-90等量表原始数据与结果、脑神经递质的定量和定性结果等。2抑郁症表现为多脑区多神经递质的振荡失衡，而非单一的神经递质变化为主。抑郁症各脑区表现为ACH激活值降低，INH升高和EXC降低，DA下降和5-HT升高为主要优势。但不排除还有少部分患者恰好是完全相反的变化规律。各递质对间（EXC和INH，DA和5-HT，ACH和NE）有明显的拮抗关系，而各脑区间的相同递质亦有明显的正相关。3进一步，针对抑郁症典型人格即太阴伴阴阳和平低人格，及抑郁阳虚体质和抑郁阴虚体质三组人群的大脑各脑区多种神经递质变化规律进行初步探索，用因子分析 (Factor analysis)方法分别提取了25、24和24个公因子（Principal Component）,因子累计方差贡献率(Cumulative Variance %)分别达到78.38%，81.67%和79.03%。4在抑郁证候研究中，就抑郁肝郁证和抑郁阴虚证两大主证进行大脑各脑区多种神经递质变化规律分析，用因子分析 (Factor analysis)方法分别提取了24和22个公因子（Principal Component）,因子累计方差贡献率(Cumulative Variance %)分别达到76.76%，和80.11%。5 综合各组研究提示：各脑区多种神经递质的指标变化灵敏性高，特异性强，适合做抑郁症的生物标志。3个递质拮抗对的组合应能解释所有可能的递质活动状态，再结合脑区定位分析，可解释临床的复杂现象。但是各脑区多种神经递质的变化规律呈现的是较为复杂的递质指纹图谱，适合在复杂系统下进行深入分析，其全脑递质指纹图谱有待进一挖掘和分析。6本研究为抑郁症诊治的客观评价开启新思路，同时亦为其它心身疾病的个体化诊治评价研究开辟新思路。