Brainstem neural mechanisms controlling locomotion with special reference to basal vertebrates.

IF 3.4 3区 医学 Q2 NEUROSCIENCES
Philippe Lacroix-Ouellette, Réjean Dubuc
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Abstract

Over the last 60 years, the basic neural circuitry responsible for the supraspinal control of locomotion has progressively been uncovered. Initially, significant progress was made in identifying the different supraspinal structures controlling locomotion in mammals as well as some of the underlying mechanisms. It became clear, however, that the complexity of the mammalian central nervous system (CNS) prevented researchers from characterizing the detailed cellular mechanisms involved and that animal models with a simpler nervous system were needed. Basal vertebrate species such as lampreys, xenopus embryos, and zebrafish became models of choice. More recently, optogenetic approaches have considerably revived interest in mammalian models. The mesencephalic locomotor region (MLR) is an important brainstem region known to control locomotion in all vertebrate species examined to date. It controls locomotion through intermediary cells in the hindbrain, the reticulospinal neurons (RSNs). The MLR comprises populations of cholinergic and glutamatergic neurons and their specific contribution to the control of locomotion is not fully resolved yet. Moreover, the downward projections from the MLR to RSNs is still not fully understood. Reporting on discoveries made in different animal models, this review article focuses on the MLR, its projections to RSNs, and the contribution of these neural elements to the control of locomotion. Excellent and detailed reviews on the brainstem control of locomotion have been recently published with emphasis on mammalian species. The present review article focuses on findings made in basal vertebrates such as the lamprey, to help direct new research in mammals, including humans.

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控制运动的脑干神经机制,特别涉及基础脊椎动物。
在过去的60年里,负责脊柱上运动控制的基本神经回路逐渐被发现。最初,在确定控制哺乳动物运动的不同棘上结构以及一些潜在机制方面取得了重大进展。然而,很明显,哺乳动物中枢神经系统(CNS)的复杂性使研究人员无法描述所涉及的详细细胞机制,因此需要具有更简单神经系统的动物模型。基底脊椎动物物种,如七鳃鳗、爪蟾胚胎和斑马鱼,成为了首选的模型。最近,光遗传学方法极大地恢复了对哺乳动物模型的兴趣。中脑运动区(MLR)是迄今为止已知的控制所有脊椎动物运动的重要脑干区域。它通过后脑的中间细胞,网状脊髓神经元(rsn)来控制运动。MLR由胆碱能和谷氨酸能神经元群组成,它们对运动控制的具体贡献尚未完全确定。此外,从最大回归比到最小回归比的向下预测仍未完全了解。本文报道了在不同动物模型中所取得的发现,重点介绍了MLR及其对rsn的预测,以及这些神经元素对运动控制的贡献。最近发表了关于脑干控制运动的优秀和详细的综述,重点是哺乳动物物种。本文主要综述了在基础脊椎动物(如七鳃鳗)中的发现,以帮助指导包括人类在内的哺乳动物的新研究。
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来源期刊
CiteScore
6.00
自引率
5.70%
发文量
135
审稿时长
4-8 weeks
期刊介绍: Frontiers in Neural Circuits publishes rigorously peer-reviewed research on the emergent properties of neural circuits - the elementary modules of the brain. Specialty Chief Editors Takao K. Hensch and Edward Ruthazer at Harvard University and McGill University respectively, are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Frontiers in Neural Circuits launched in 2011 with great success and remains a "central watering hole" for research in neural circuits, serving the community worldwide to share data, ideas and inspiration. Articles revealing the anatomy, physiology, development or function of any neural circuitry in any species (from sponges to humans) are welcome. Our common thread seeks the computational strategies used by different circuits to link their structure with function (perceptual, motor, or internal), the general rules by which they operate, and how their particular designs lead to the emergence of complex properties and behaviors. Submissions focused on synaptic, cellular and connectivity principles in neural microcircuits using multidisciplinary approaches, especially newer molecular, developmental and genetic tools, are encouraged. Studies with an evolutionary perspective to better understand how circuit design and capabilities evolved to produce progressively more complex properties and behaviors are especially welcome. The journal is further interested in research revealing how plasticity shapes the structural and functional architecture of neural circuits.
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