PDF(Pubmed)
Abstract：
Mental disorders are among the top most demanding challenges in world-wide health. A large number of mental disorders exhibit pathological rhythms, which serve as the disorders characteristic biomarkers. These rhythms are the targets for neurostimulation techniques. Open-loop neurostimulation employs stimulation protocols, which are rather independent of the patients health and brain state in the moment of treatment. Most alternative closed-loop stimulation protocols consider real-time brain activity observations but appear as adaptive open-loop protocols, where e.g., pre-defined stimulation sets in if observations fulfil pre-defined criteria. The present theoretical work proposes a fully-adaptive closed-loop neurostimulation setup, that tunes the brain activities power spectral density (PSD) according to a user-defined PSD. The utilized brain model is non-parametric and estimated from the observations via magnitude fitting in a pre-stimulus setup phase. Moreover, the algorithm takes into account possible conduction delays in the feedback connection between observation and stimulation electrode. All involved features are illustrated on pathological α- and γ-rhythms known from psychosis. To this end, we simulate numerically a linear neural population brain model and a non-linear cortico-thalamic feedback loop model recently derived to explain brain activity in psychosis.
摘要：
精神障碍是世界范围内最严峻的挑战之一。大量的精神障碍表现出病理节律,作为疾病特征性生物标志物。这些节律是神经刺激技术的目标。开环神经刺激采用刺激协议，这与患者在治疗时的健康状况和大脑状态无关。大多数替代闭环刺激协议考虑实时大脑活动观察，但表现为自适应开环协议，其中，例如，如果观察结果符合预定义的标准，则设置预定义的刺激。本理论工作提出了一种完全自适应的闭环神经刺激设置，根据用户定义的PSD调整大脑活动功率谱密度(PSD)。所利用的脑模型是非参数的,并且在预刺激设置阶段中经由幅度拟合从观察来估计。此外，该算法考虑了观察电极和刺激电极之间的反馈连接中可能的传导延迟。所有涉及的特征均在精神病中已知的病理性α和γ节律上进行了说明。为此,我们用数值模拟了一个线性神经群体大脑模型和一个非线性皮质-丘脑反馈回路模型，该模型最近被用来解释精神病患者的大脑活动。
