首页> 外国专利> STOCHASTIC-SWITCHED NOISE STIMULATION FOR IDENTIFICATION OF INPUT-OUTPUT BRAIN NETWORK DYNAMICS AND CLOSED LOOP CONTROL

STOCHASTIC-SWITCHED NOISE STIMULATION FOR IDENTIFICATION OF INPUT-OUTPUT BRAIN NETWORK DYNAMICS AND CLOSED LOOP CONTROL

机译:随机开关噪声仿真,用于确定输入/输出网络的动力学特性和闭环控制

摘要

Time-efficient identification of a brain network input-output (IO) dynamics model for brain stimulation includes generating an input stochastic-switched noise-modulated waveform characterized by at least one parameter modulated according to a stochastic-switched noise sequence, inputting the input stochastic-switched noise-modulated waveform to a clinical brain-response system, recording one or more time-correlated outputs of the clinical brain-response system responsive to the input stochastic-switched noise-modulated waveform, and identifying a brain network IO dynamics model that optimally correlates the input stochastic-switched noise-modulated waveform to the one or more time-delimited outputs of the clinical brain-response system. A desired brain response to an input electrical signal may be obtained using the model, such as by modulating the input electrical signal using a closed-loop control algorithm based on the brain network IO dynamics model.
机译:用于大脑刺激的脑网络输入输出(IO)动力学模型的时效识别包括生成输入随机切换的噪声调制波形,该波形的特征在于至少一个根据随机切换的噪声序列调制的参数,输入该输入随机信号-将噪声调制波形切换到临床脑响应系统,记录输入响应随机切换噪声调制波形后临床大脑响应系统的一个或多个与时间相关的输出,并确定一个脑网络IO动力学模型最佳地将输入的随机切换噪声调制波形与临床脑反应系统的一个或多个时间限定的输出相关。可以使用该模型来获得对输入电信号的期望的大脑响应,例如通过使用基于大脑网络IO动力学模型的闭环控制算法对输入电信号进行调制。

著录项

  • 公开/公告号US2019200934A1

    专利类型

  • 公开/公告日2019-07-04

    原文格式PDF

  • 申请/专利权人 UNIVERSITY OF SOUTHERN CALIFORNIA;

    申请/专利号US201716325297

  • 发明设计人 MARYAM SHANECHI;

    申请日2017-08-14

  • 分类号A61B5;G06F17/50;A61N1/05;

  • 国家 US

  • 入库时间 2022-08-21 12:07:10

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