A translational platform for prototyping closed-loop neuromodulation systems
A translational platform for prototyping closed-loop neuromodulation systems
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DOI：
10.3389/fncir.2012.00117
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发表时间：
2013-01-22
影响因子：
3.5
通讯作者：
Denison, Tim
中科院分区：
文献类型：
--
作者：
Afshar, Pedram;Khambhati, Ankit;Denison, Tim
虽然通过刺激调节神经活动是对神经系统疾病（例如帕金森病和原发性震颤）的有效治疗，但是改进神经调节治疗的机会仍然在于自动调整治疗以持续优化患者结果。与实现这一点相关的实际问题包括缺乏与疾病状态相关的人类数据，患者状态的验证不佳的估计值，以及基于估计状态的最佳刺激参数的未知动态映射。为了克服这些挑战，我们提出了一个研究平台，包括：一个植入的传感和刺激设备，收集数据和运行自动闭环算法;一个外部工具，原型分类器和控制策略算法;和实时遥测更新植入设备固件和监测其状态。在研究海马动力学的慢性大型动物模型中证明了原型系统。我们使用该平台来寻找观察到的状态的生物标志物和不同刺激幅度的传递函数。数据显示，中等水平的刺激抑制海马β活动，而高水平的刺激产生类似于海马的后放电活动。将生物标志物和传递函数观察结果映射到分类器和控制策略算法中，将其下载到植入设备中，以连续滴定刺激幅度，以获得所需的网络效果。该平台被设计为一个灵活的原型工具，可用于开发各种神经系统疾病的改进机制模型和自动闭环系统。
While modulating neural activity through stimulation is an effective treatment for neurological diseases such as Parkinson's disease and essential tremor, an opportunity for improving neuromodulation therapy remains in automatically adjusting therapy to continuously optimize patient outcomes. Practical issues associated with achieving this include the paucity of human data related to disease states, poorly validated estimators of patient state, and unknown dynamic mappings of optimal stimulation parameters based on estimated states. To overcome these challenges, we present an investigational platform including: an implanted sensing and stimulation device to collect data and run automated closed-loop algorithms; an external tool to prototype classifier and control-policy algorithms; and real-time telemetry to update the implanted device firmware and monitor its state. The prototyping system was demonstrated in a chronic large animal model studying hippocampal dynamics. We used the platform to find biomarkers of the observed states and transfer functions of different stimulation amplitudes. Data showed that moderate levels of stimulation suppress hippocampal beta activity, while high levels of stimulation produce seizure-like after-discharge activity. The biomarker and transfer function observations were mapped into classifier and control-policy algorithms, which were downloaded to the implanted device to continuously titrate stimulation amplitude for the desired network effect. The platform is designed to be a flexible prototyping tool and could be used to develop improved mechanistic models and automated closed-loop systems for a variety of neurological disorders.