An Integrated Neurorobotics Model of the Cerebellar-Basal Ganglia Circuitry.

International journal of neural systems Pub Date : 2023-11-01 Epub Date: 2023-10-04 DOI:10.1142/S0129065723500594
Jhielson M Pimentel, Renan C Moioli, Mariana F P De Araujo, Patricia A Vargas
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Abstract

This work presents a neurorobotics model of the brain that integrates the cerebellum and the basal ganglia regions to coordinate movements in a humanoid robot. This cerebellar-basal ganglia circuitry is well known for its relevance to the motor control used by most mammals. Other computational models have been designed for similar applications in the robotics field. However, most of them completely ignore the interplay between neurons from the basal ganglia and cerebellum. Recently, neuroscientists indicated that neurons from both regions communicate not only at the level of the cerebral cortex but also at the subcortical level. In this work, we built an integrated neurorobotics model to assess the capacity of the network to predict and adjust the motion of the hands of a robot in real time. Our model was capable of performing different movements in a humanoid robot by respecting the sensorimotor loop of the robot and the biophysical features of the neuronal circuitry. The experiments were executed in simulation and the real world. We believe that our proposed neurorobotics model can be an important tool for new studies on the brain and a reference toward new robot motor controllers.

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小脑基底神经节回路的集成神经机器人模型。
这项工作提出了一个大脑神经机器人模型,该模型集成了小脑和基底神经节区域,以协调人形机器人的运动。众所周知,这种小脑基底神经节回路与大多数哺乳动物使用的运动控制有关。已经为机器人领域的类似应用设计了其他计算模型。然而,它们中的大多数完全忽略了基底神经节和小脑神经元之间的相互作用。最近,神经科学家指出,这两个区域的神经元不仅在大脑皮层水平上交流,而且在皮层下水平上交流。在这项工作中,我们建立了一个集成的神经机器人模型,以评估网络实时预测和调整机器人手部运动的能力。我们的模型能够通过尊重机器人的感觉运动回路和神经元回路的生物物理特征,在人形机器人中进行不同的运动。实验是在模拟和现实世界中进行的。我们相信,我们提出的神经机器人模型可以成为对大脑进行新研究的重要工具,并为新的机器人运动控制器提供参考。
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