The Bcm rule allows a spinal cord model to learn rhythmic movements.

IF 1.7 4区 工程技术 Q3 COMPUTER SCIENCE, CYBERNETICS
Biological Cybernetics Pub Date : 2023-10-01 Epub Date: 2023-08-18 DOI:10.1007/s00422-023-00970-z
Matthias Kohler, Florian Röhrbein, Alois Knoll, Alin Albu-Schäffer, Henrik Jörntell
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引用次数: 0

Abstract

Currently, it is accepted that animal locomotion is controlled by a central pattern generator in the spinal cord. Experiments and models show that rhythm generating neurons and genetically determined network properties could sustain oscillatory output activity suitable for locomotion. However, current central pattern generator models do not explain how a spinal cord circuitry, which has the same basic genetic plan across species, can adapt to control the different biomechanical properties and locomotion patterns existing in these species. Here we demonstrate that rhythmic and alternating movements in pendulum models can be learned by a monolayer spinal cord circuitry model using the Bienenstock-Cooper-Munro learning rule, which has been previously proposed to explain learning in the visual cortex. These results provide an alternative theory to central pattern generator models, because rhythm generating neurons and genetically defined connectivity are not required in our model. Though our results are not in contradiction to current models, as existing neural mechanism and structures, not used in our model, can be expected to facilitate the kind of learning demonstrated here. Therefore, our model could be used to augment existing models.

Abstract Image

Bcm规则允许脊髓模型学习有节奏的运动。
目前,人们普遍认为动物的运动是由脊髓中的中央模式发生器控制的。实验和模型表明,产生节律的神经元和遗传决定的网络特性可以维持适合运动的振荡输出活动。然而,目前的中央模式生成器模型并不能解释跨物种具有相同基本遗传计划的脊髓回路如何适应控制这些物种中存在的不同生物力学特性和运动模式。在这里,我们证明了单摆模型中的节奏和交替运动可以通过单层脊髓回路模型使用Bienenstock-Cooper-Muno学习规则来学习,该规则以前曾被提出用于解释视觉皮层的学习。这些结果为中心模式生成器模型提供了一种替代理论,因为在我们的模型中不需要产生节律的神经元和遗传定义的连接。尽管我们的结果与当前的模型并不矛盾,但现有的神经机制和结构(未在我们的模型中使用)有望促进这里演示的学习。因此,我们的模型可以用来扩充现有的模型。
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来源期刊
Biological Cybernetics
Biological Cybernetics 工程技术-计算机:控制论
CiteScore
3.50
自引率
5.30%
发文量
38
审稿时长
6-12 weeks
期刊介绍: Biological Cybernetics is an interdisciplinary medium for theoretical and application-oriented aspects of information processing in organisms, including sensory, motor, cognitive, and ecological phenomena. Topics covered include: mathematical modeling of biological systems; computational, theoretical or engineering studies with relevance for understanding biological information processing; and artificial implementation of biological information processing and self-organizing principles. Under the main aspects of performance and function of systems, emphasis is laid on communication between life sciences and technical/theoretical disciplines.
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