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
{"title":"均匀抑制对于CA1区中定位细胞的相位进动是最佳的。","authors":"Georgy Vandyshev,&nbsp;Ivan Mysin","doi":"10.1007/s10827-023-00855-x","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":"51 3","pages":"389-403"},"PeriodicalIF":1.5000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Homogeneous inhibition is optimal for the phase precession of place cells in the CA1 field.\",\"authors\":\"Georgy Vandyshev,&nbsp;Ivan Mysin\",\"doi\":\"10.1007/s10827-023-00855-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":54857,\"journal\":{\"name\":\"Journal of Computational Neuroscience\",\"volume\":\"51 3\",\"pages\":\"389-403\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10827-023-00855-x\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/7/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10827-023-00855-x","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/7/5 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
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。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
期刊最新文献
Effect of burst spikes on linear and nonlinear signal transmission in spiking neurons. Mean-field analysis of synaptic alterations underlying deficient cortical gamma oscillations in schizophrenia. Firing rate models for gamma oscillations in I-I and E-I networks. JCNS goes multiscale. A cortical field theory - dynamics and symmetries.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1