Intersegmental coordination of the central pattern generator via interleaved electrical and chemical synapses in zebrafish spinal cord.

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Lae Un Kim, Hermann Riecke
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引用次数: 1

Abstract

A significant component of the repetitive dynamics during locomotion in vertebrates is generated within the spinal cord. The legged locomotion of mammals is most likely controled by a hierarchical, multi-layer spinal network structure, while the axial circuitry generating the undulatory swimming motion of animals like lamprey is thought to have only a single layer in each segment. Recent experiments have suggested a hybrid network structure in zebrafish larvae in which two types of excitatory interneurons (V2a-I and V2a-II) both make first-order connections to the brain and last-order connections to the motor pool. These neurons are connected by electrical and chemical synapses across segments. Through computational modeling and an asymptotic perturbation approach we show that this interleaved interaction between the two neuron populations allows the spinal network to quickly establish the correct activation sequence of the segments when starting from random initial conditions, as needed for a swimming spurt, and to reduce the dependence of the intersegmental phase difference (ISPD) of the oscillations on the swimming frequency. The latter reduces the frequency dependence of the waveform of the swimming motion. In the model the reduced frequency dependence is largely due to the different impact of chemical and electrical synapses on the ISPD and to the significant spike-frequency adaptation that has been observed experimentally in V2a-II neurons, but not in V2a-I neurons. Our model makes experimentally testable predictions and points to a benefit of the hybrid structure for undulatory locomotion that may not be relevant for legged locomotion.

Abstract Image

斑马鱼脊髓中通过交错的电突触和化学突触的中央模式发生器的节间协调。
在脊椎动物运动过程中,重复动力学的一个重要组成部分是在脊髓内产生的。哺乳动物的腿部运动很可能是由一个分层的、多层的脊柱网络结构控制的,而产生像七鳃鳗这样的动物的波动游泳运动的轴向电路被认为在每个部分只有一个层。最近的实验表明,斑马鱼幼体中存在一种混合网络结构,其中两种类型的兴奋性中间神经元(V2a-I和V2a-II)都与大脑建立一阶连接,并与运动池建立最后一阶连接。这些神经元通过电突触和化学突触连接在一起。通过计算建模和渐近摄动方法,我们表明,两个神经元群之间的交错相互作用允许脊髓网络在从随机初始条件开始时快速建立正确的片段激活序列,如游泳爆发所需,并减少振荡的段间相位差(ISPD)对游泳频率的依赖。后者降低了游泳运动波形的频率依赖性。在该模型中,频率依赖性的降低主要是由于化学突触和电突触对ISPD的不同影响,以及在V2a-II神经元中观察到的显著的尖峰频率适应,而在V2a-I神经元中则没有。我们的模型进行了实验可测试的预测,并指出了混合结构对波动运动的好处,这可能与腿运动无关。
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来源期刊
CiteScore
2.00
自引率
8.30%
发文量
32
审稿时长
3 months
期刊介绍: The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.
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