均匀抑制对于CA1区中定位细胞的相位进动是最佳的。

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Journal of Computational Neuroscience Pub Date : 2022-08-01 Epub Date: 2023-07-05 DOI:10.1007/s10827-023-00855-x
Georgy Vandyshev, Ivan Mysin
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引用次数: 0

摘要

位置细胞是海马神经元,编码动物在太空中的位置。对位置细胞的研究对于理解大脑神经网络对信息的处理至关重要。位置细胞尖峰序列的一个重要特征是相位进动。当动物在场地中奔跑时,场地细胞的放电从θ节律的上升期通过最小值转移到下降期。对沿Schaffer络和穿孔通路的锥体神经元的兴奋性输入在相位进动中的作用进行了描述,但对局部中间神经元的作用知之甚少。我们的目标是使用数学方法估计场CA1中间神经元对位置细胞相位进动的贡献。之所以选择CA1字段,是因为它提供了构建和验证模型所需的最大实验数据集。我们的模拟发现了锥体神经元兴奋性和抑制性输入的最佳参数,从而使其产生具有相位进动影响的尖峰序列。锥体神经元的均匀抑制最好地解释了相位进动的影响。在中间神经元中,轴突神经元对锥体细胞的抑制作用最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Homogeneous inhibition is optimal for the phase precession of place cells in the CA1 field.

Homogeneous inhibition is optimal for the phase precession of place cells in the CA1 field.

Place cells are hippocampal neurons encoding the position of an animal in space. Studies of place cells are essential to understanding the processing of information by neural networks of the brain. An important characteristic of place cell spike trains is phase precession. When an animal is running through the place field, the discharges of the place cells shift from the ascending phase of the theta rhythm through the minimum to the descending phase. The role of excitatory inputs to pyramidal neurons along the Schaffer collaterals and the perforant pathway in phase precession is described, but the role of local interneurons is poorly understood. Our goal is estimating of the contribution of field CA1 interneurons to the phase precession of place cells using mathematical methods. The CA1 field is chosen because it provides the largest set of experimental data required to build and verify the model. Our simulations discover optimal parameters of the excitatory and inhibitory inputs to the pyramidal neuron so that it generates a spike train with the effect of phase precession. The uniform inhibition of pyramidal neurons best explains the effect of phase precession. Among interneurons, axo-axonal neurons make the greatest contribution to the inhibition of pyramidal cells.

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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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