如何对功能性胃肠病进行有效治疗，减轻患者临床症状，一直困扰着患者和临床工作者，症状重叠和互相转换现象的存在是对功能性胃肠病进行有效治疗的重要制约因素。为满足功能性胃肠病患者有针对性治疗的需求，本课题采用症状分类和病情分级的实验设计，借助多模态神经影像技术，研究不同类型、不同病情程度下患者大脑感知、记忆、情感网络模式的改变，试图探索不同类患者的中枢特异性和相似性以及病情发展与中枢异常改变的对应关系；借助多变量模式分析算法，采用脑网络特征进行疾病症状和病情预测，探寻各类病患的中枢发展轨迹，优化功能性胃肠病诊断和病情发展的影像学标记；基于功能性胃肠病患者大脑网络异常的中枢特性，结合脑-肠肽水平分析，从内分泌水平上揭示病患大脑机制与内环境因素之间的关系，为检测功能性胃肠病的发病原因、病情进展和疗效评价提供新的途径，具有重要的社会意义和临床价值。

How to treat functional gastrointestinal disorders (FGID) and relieve the patients’ symptoms effectively has bothers clinicians and sufferers for long time. The existence of symptom overlap and transformation is major hindrance in treating FGID. In the study, we aim to explore the specificity and similarity between different FGID patients concerning the brain networks related to sensory, memory and affection according to the need of patients who requires targeted treatment. By multi-model neuroimaging techniques, we observe the brain functional-strucutral network changes and corresponding relation between the brain alterations and development of FGID with different subtypes. Based on multi-variate pattern analysis, the observed brain network features are used to detect the type and grade in order to probe the central markers of disease progression. Next, the level of brain-gut peptide is assessed for investigating the relationship between central mechanisms and human body environment, which validates the central markers of FGID patients by the level of neural-endocrine. The study will provide a new method for detecting pathogenesis, progression and therapeutic evaluation of FGID and bring significant value to society and clinic.