Optimized temporal pattern of brain stimulation designed by computational evolution

Received: 7 December 2015; Accepted: 18 November 2016

DAVID T. BROCKER, Brandon D. Swan, Rosa Q. So, Dennis A. Turner, Robert E. Gross, WARREN M. GRILL

Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.

Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA.

Departments of Neurosurgery and Neurology, Emory University, Atlanta, GA 30322, USA.

Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.

Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA.

在脑深部刺激（DBS）中，通过插入患者大脑深处的电极提供电脉冲可以缓解帕金森病或震颤的症状，甚至可以缓解强迫症等疾病。然而，这些刺激模式通常是固定的，具有统一的频率和振幅。为了设计更好的刺激模式，Brocker等人建立了一个帕金森病的模型，并使用进化算法来寻找新的时间刺激模式。在动物模型和帕金森病患者中应用这种进化得出的刺激模式验证了它与标准刺激模式一样有效，但所需的总能量明显减少。由于DBS的一个缺点是需要经常进行有风险的手术来更换电源，而新的刺激模式对电池的消耗更少，意味着病人更少接受更换手术，维持健康时间更久。

原文：Optimized temporal pattern of brain stimulation designed by computational evolution

译文：通过进化算法设计优化脑深部电刺激时间模式