Hsiao Min-Chi, Song Dong, Berger Theodore W
Department of Biomedical Engineering at University of Southern California (USC), Los Angeles, CA 90089, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:5535-8. doi: 10.1109/IEMBS.2008.4650468.
We are developing a biomimetic electronic neural prosthesis to replace regions of the hippocampal brain area that have been damaged by disease or insult. Our previous study has shown that the VLSI implementation of a CA3 nonlinear dynamic model can functionally replace the CA3 subregion of the hippocampal slice. As a result, the propagation of temporal patterns of activity from DG-->VLSI-->CA1 reproduces the activity observed experimentally in the biological DG-->CA3-->CA1 circuit. In this project, we incorporate an open-loop controller to optimize the output (CA1) response. Specifically, we seek to optimize the stimulation signal to CA1 using a predictive dentate gyrus (DG)-CA1 nonlinear model (i.e., DG-CA1 trajectory model) and a CA1 input-output model (i.e., CA1 plant model), such that the ultimate CA1 response (i.e., desired output) can be first predicted by the DG-CA1 trajectory model and then transformed to the desired stimulation through the inversed CA1 plant model. Lastly, the desired CA1 output is evoked by the estimated optimal stimulation. This study will be the first stage of formulating an integrated modeling-control strategy for the hippocampal neural prosthetic system.
我们正在研发一种仿生电子神经假体,以替代因疾病或损伤而受损的海马脑区。我们之前的研究表明,CA3非线性动态模型的超大规模集成电路实现能够在功能上替代海马切片的CA3子区域。因此,从齿状回(DG)到超大规模集成电路再到CA1的时间活动模式的传播,再现了在生物DG→CA3→CA1回路中实验观察到的活动。在这个项目中,我们加入了一个开环控制器来优化输出(CA1)响应。具体来说,我们试图使用预测性齿状回(DG)-CA1非线性模型(即DG-CA1轨迹模型)和CA1输入-输出模型(即CA1对象模型)来优化对CA1的刺激信号,以便最终的CA1响应(即期望输出)能够首先由DG-CA1轨迹模型预测,然后通过CA1对象模型的逆模型转换为期望的刺激。最后,通过估计的最优刺激来诱发期望的CA1输出。这项研究将是为海马神经假体系统制定综合建模-控制策略的第一阶段。