Exploring Vestibulo-Ocular Adaptation in a Closed-Loop Neuro-Robotic Experiment Using STDP. A Simulation Study

Francisco Naveros, J. Garrido, A. Arleo, E. Ros, N. Luque
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引用次数: 2

Abstract

Studying and understanding the computational primitives of our neural system requires for a diverse and complementary set of techniques. In this work, we use the Neuro-robotic Platform (NRP)to evaluate the vestibulo ocular cerebellar adaptatIon (Vestibulo-ocular reflex, VOR)mediated by two STDP mechanisms located at the cerebellar molecular layer and the vestibular nuclei respectively. This simulation study adopts an experimental setup (rotatory VOR)widely used by neuroscientists to better understand the contribution of certain specific cerebellar properties (i.e. distributed STDP, neural properties, coding cerebellar topology, etc.)to r-VOR adaptation. The work proposes and describes an embodiment solution for which we endow a simulated humanoid robot (iCub)with a spiking cerebellar model by means of the NRP, and we face the humanoid to an r-VOR task. The results validate the adaptive capabilities of the spiking cerebellar model (with STDP)in a perception-action closed-loop (r- VOR)causing the simulated iCub robot to mimic a human behavior.
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利用STDP在闭环神经机器人实验中探索前庭-眼适应。模拟研究
研究和理解我们神经系统的计算原语需要一套多样化和互补的技术。在这项工作中,我们使用神经机器人平台(NRP)来评估分别位于小脑分子层和前庭核的两种STDP机制介导的前庭眼小脑适应(vestibulo -ocular reflex, VOR)。本仿真研究采用神经科学家广泛使用的实验设置(旋转VOR),以更好地了解某些特定的小脑特性(如分布式STDP、神经特性、编码小脑拓扑等)对r-VOR适应的贡献。本文提出并描述了一种实施方案,通过NRP赋予仿真人形机器人(iCub)尖峰小脑模型,并使其面对r-VOR任务。结果验证了尖峰小脑模型(带有STDP)在感知-行动闭环(r- VOR)中的自适应能力,使模拟的iCub机器人能够模仿人类的行为。
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