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A model for the transfer of control from the brain to the spinal cord through synaptic learning
Journal of Computational Neuroscience ( IF 1.2 ) Pub Date : 2020-10-02 , DOI: 10.1007/s10827-020-00767-0
Preeti Sar 1 , Hartmut Geyer 2
Affiliation  

The spinal cord is essential to the control of locomotion in legged animals and humans. However, the actual circuitry of the spinal controller remains only vaguely understood. Here we approach this problem from the viewpoint of learning. More precisely, we assume the circuitry evolves through the transfer of control from the brain to the spinal cord, propose a specific learning mechanism for this transfer based on the error between the cord and brain contributions to muscle control, and study the resulting structure of the spinal controller in a simplified neuromuscular model of human locomotion. The model focuses on the leg rebound behavior in stance and represents the spinal circuitry with 150 muscle reflexes. We find that after learning a spinal controller has evolved that produces leg rebound motions in the absence of a central brain input with only three structural reflex groups. These groups contain individual reflexes well known from physiological experiments but thought to serve separate purposes in the control of human locomotion. Our results suggest a more holistic interpretation of the role of individual sensory projections in spinal networks than is common. In addition, we discuss potential neural correlates for the proposed learning mechanism that may be probed in experiments. Together with such experiments, neuromuscular models of spinal learning likely will become effective tools for uncovering the structure and development of the spinal control circuitry.



中文翻译:

通过突触学习将控制权从大脑转移到脊髓的模型

脊髓对于控制有腿动物和人类的运动至关重要。然而,脊柱控制器的实际电路仍然只是模糊的理解。在这里,我们从学习的角度来解决这个问题。更准确地说,我们假设电路是通过从大脑到脊髓的控制转移而进化的,基于脊髓和大脑对肌肉控制的贡献之间的误差提出了这种转移的特定学习机制,并研究了由此产生的结构人类运动的简化神经肌肉模型中的脊柱控制器。该模型侧重于站立时的腿部反弹行为,并代表具有 150 种肌肉反射的脊柱回路。我们发现,在学习了一个脊柱控制器后,它已经进化出在没有中央大脑输入的情况下产生腿部反弹运动,只有三个结构性反射群。这些群体包含生理实验中众所周知的个体反射,但被认为在控制人类运动方面有不同的用途。我们的结果表明,对个体感觉投射在脊柱网络中的作用的解释比常见的更全面。此外,我们讨论了可能在实验中探索的拟议学习机制的潜在神经相关性。与这些实验一起,脊柱学习的神经肌肉模型可能会成为揭示脊柱控制电路结构和发展的有效工具。这些群体包含生理实验中众所周知的个体反射,但被认为在控制人类运动方面有不同的用途。我们的结果表明,对个体感觉投射在脊柱网络中的作用的解释比常见的更全面。此外,我们讨论了可能在实验中探索的拟议学习机制的潜在神经相关性。与这些实验一起,脊柱学习的神经肌肉模型可能会成为揭示脊柱控制电路结构和发展的有效工具。这些群体包含生理实验中众所周知的个体反射,但被认为在控制人类运动方面有不同的用途。我们的结果表明,对个体感觉投射在脊柱网络中的作用的解释比常见的更全面。此外,我们讨论了可能在实验中探索的拟议学习机制的潜在神经相关性。与这些实验一起,脊柱学习的神经肌肉模型可能会成为揭示脊柱控制电路结构和发展的有效工具。我们讨论了可能在实验中探索的拟议学习机制的潜在神经相关性。与这些实验一起,脊柱学习的神经肌肉模型可能会成为揭示脊柱控制电路结构和发展的有效工具。我们讨论了可能在实验中探索的拟议学习机制的潜在神经相关性。与这些实验一起,脊柱学习的神经肌肉模型可能会成为揭示脊柱控制电路结构和发展的有效工具。

更新日期:2020-10-04
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