Abstract：
Brain neuromodulation effectively treats neurological diseases and psychiatric disorders such as Depression. However, due to patient heterogeneity, neuromodulation treatment outcomes are often highly variable, requiring patient-specific stimulation protocols throughout the recovery stages to optimize treatment outcomes. Therefore, it is critical to personalize neuromodulation protocol to optimize the patient-specific stimulation targets and parameters by accommodating inherent interpatient variability and intersession alteration during treatments. The study aims to develop a personalized repetitive transcranial magnetic stimulation (rTMS) protocol and evaluate its feasibility in optimizing the treatment efficiency using an existing dataset from an antidepressant experimental imaging study in depression. The personalization of the rTMS treatment protocol was achieved by personalizing both stimulation targets and parameters via a novel approach integrating the functional brain network controllability analysis and optimal control analysis. First, the functional brain network controllability analysis was performed to identify the optimal rTMS stimulation target from the effective connectivity network constructed from patient-specific resting-state functional magnetic resonance imaging data. The optimal control algorithm was then applied to optimize the rTMS stimulation parameters based on the optimized target. The performance of the proposed personalized rTMS technique was evaluated using datasets collected from a longitudinal antidepressant experimental imaging study in depression (n = 20). Simulation models demonstrated that the proposed personalized rTMS protocol outperformed the standard rTMS treatment by efficiently steering a depressive resting brain state to a healthy resting brain state, indicated by the significantly less control energy needed and higher model fitting accuracy achieved. The node with the maximum average controllability of each patient was designated as the optimal target region for the personalized rTMS protocol. Our results also demonstrated the theoretical feasibility of achieving comparable neuromodulation efficacy by stimulating a single node compared to stimulating multiple driver nodes. The findings support the feasibility of developing personalized neuromodulation protocols to more efficiently treat depression and other neurological diseases.
摘要：
脑神经调节有效治疗神经系统疾病和精神疾病，如抑郁症。然而,由于患者的异质性，神经调节治疗结果通常是高度可变的，在整个恢复阶段都需要患者特定的刺激方案，以优化治疗结果。因此,通过适应治疗期间固有的患者间变异性和疗程间改变,个性化神经调节方案以优化患者特异性刺激目标和参数是至关重要的.该研究旨在开发个性化的重复经颅磁刺激（rTMS）方案，并使用抑郁症抗抑郁药实验成像研究的现有数据集评估其优化治疗效率的可行性。rTMS治疗方案的个性化是通过集成功能脑网络可控性分析和最优控制分析的新颖方法对刺激目标和参数进行个性化来实现的。首先,我们进行了功能性脑网络可控性分析,以从根据患者特异性静息态功能磁共振成像数据构建的有效连接网络中识别最佳rTMS刺激目标.然后应用最优控制算法以基于优化的目标优化rTMS刺激参数。使用从抑郁症的纵向抗抑郁实验成像研究中收集的数据集评估了所提出的个性化rTMS技术的性能（n=20）。仿真模型表明，提出的个性化rTMS协议通过有效地将抑郁的静息大脑状态转向健康的静息大脑状态，优于标准的rTMS治疗。所需的控制能量明显减少，模型拟合精度更高。每个患者具有最大平均可控性的节点被指定为个性化rTMS协议的最佳目标区域。我们的结果还证明了与刺激多个驱动节点相比，通过刺激单个节点实现可比的神经调节功效的理论可行性。研究结果支持开发个性化神经调节方案以更有效地治疗抑郁症和其他神经系统疾病的可行性。
