• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

成人齿状核大神经元的形态学和分类:二维图像的定性和定量分析。

Morphology and classification of large neurons in the adult human dentate nucleus: a qualitative and quantitative analysis of 2D images.

机构信息

Department of Biophysics, School of Medicine, University of Belgrade, Visegradska 26, 11000 Belgrade, Serbia.

出版信息

Neurosci Res. 2010 May;67(1):1-7. doi: 10.1016/j.neures.2010.01.002. Epub 2010 Jan 15.

DOI:10.1016/j.neures.2010.01.002
PMID:20079774
Abstract

The dentate nucleus represents the most lateral of the four cerebellar nuclei that serve as major relay centres for fibres coming from the cerebellar cortex. Although many relevant findings regarding to the structure, neuronal morphology and cytoarchitectural development of the dentate nucleus have been presented so far, very little quantitative information has been collected on the types of large neurons in the human dentate nucleus. In the present study we qualitatively analyze our sample of large neurons according to their morphology and topology, and classify these cells into four types. Then, we quantify the morphology of such cell types taking into account seven morphometric parameters which describe the main properties of the cell soma, dendritic field and dendrite arborization. By performing appropriate statistics we prove out our classification of the large dentate neurons in the adult human. To the best of our knowledge, this study represents the first attempt of quantitative analysis of morphology and classification of the large neurons in the adult human dentate nucleus.

摘要

齿状核是四个小脑核中最外侧的一个,作为来自小脑皮层纤维的主要中继中心。尽管目前已经提出了许多关于齿状核的结构、神经元形态和细胞构筑发育的相关发现,但关于人类齿状核中大型神经元的类型,很少有定量信息被收集。在本研究中,我们根据形态和拓扑结构对我们的大型神经元样本进行定性分析,并将这些细胞分为四种类型。然后,我们考虑七个形态计量参数来量化这些细胞类型的形态,这些参数描述了细胞体、树突场和树突分支的主要特性。通过进行适当的统计学分析,我们证明了我们对成人齿状核中大型神经元的分类。据我们所知,这项研究代表了对成人齿状核中大型神经元的形态定量分析和分类的首次尝试。

相似文献

1
Morphology and classification of large neurons in the adult human dentate nucleus: a qualitative and quantitative analysis of 2D images.成人齿状核大神经元的形态学和分类:二维图像的定性和定量分析。
Neurosci Res. 2010 May;67(1):1-7. doi: 10.1016/j.neures.2010.01.002. Epub 2010 Jan 15.
2
Morphology and cell classification of large neurons in the adult human dentate nucleus: a quantitative study.成人齿状核内大神经元的形态和细胞分类:一项定量研究。
Neurosci Lett. 2010 Jan 1;468(1):59-63. doi: 10.1016/j.neulet.2009.10.063. Epub 2009 Oct 24.
3
On the classification of normally distributed neurons: an application to human dentate nucleus.关于正态分布神经元的分类:在人类齿状核中的应用。
Biol Cybern. 2011 Mar;104(3):175-83. doi: 10.1007/s00422-011-0426-x. Epub 2011 Feb 22.
4
Application of fractal analysis to neuronal dendritic arborisation patterns of the monkey dentate nucleus.分形分析在猴齿状核神经元树突分支模式中的应用。
Neurosci Lett. 2007 Sep 20;425(1):23-7. doi: 10.1016/j.neulet.2007.08.009. Epub 2007 Aug 11.
5
Classification of adult human dentate nucleus border neurons: Artificial neural networks and multidimensional approach.成人人类齿状核边界神经元的分类:人工神经网络与多维方法。
J Theor Biol. 2016 Sep 7;404:273-284. doi: 10.1016/j.jtbi.2016.06.011. Epub 2016 Jun 15.
6
Cell image area as a tool for neuronal classification.细胞图像面积作为神经元分类的一种工具。
J Neurosci Methods. 2009 Sep 15;182(2):272-8. doi: 10.1016/j.jneumeth.2009.06.004. Epub 2009 Jun 12.
7
Quantitative morphological analysis of the cerebellar nuclei in normal and lurcher mutant mice. I. Morphology and cell number.正常和蹒跚突变小鼠小脑核的定量形态学分析。I. 形态学和细胞数量。
J Comp Neurol. 1994 May 1;343(1):173-82. doi: 10.1002/cne.903430113.
8
Dentate nucleus of Ateles ater. Cytomorphometric analysis.蛛猴齿状核。细胞形态计量分析。
Acta Anat (Basel). 1975;93(2):228-39.
9
No change in neuron numbers in the dentate nucleus of patients with schizophrenia estimated with a new stereological method--the smooth fractionator.采用一种新的体视学方法——平滑分离法估计,精神分裂症患者齿状核中的神经元数量没有变化。
J Anat. 2004 Oct;205(4):313-21. doi: 10.1111/j.0021-8782.2004.00337.x.
10
[Quantitative analysis of dendritic branching pattern of large neurons in human cerebellum].[人类小脑大型神经元树突分支模式的定量分析]
Vojnosanit Pregl. 2010 Sep;67(9):712-6. doi: 10.2298/vsp1009712m.

引用本文的文献

1
Dentate nucleus: a review and implications for dentatotomy.齿状核:综述及对齿状核切开术的影响。
Acta Neurochir (Wien). 2024 May 17;166(1):219. doi: 10.1007/s00701-024-06104-z.
2
The Morphology of Brain Neurons: The Box-Counting Method in the Quantitative Analysis of 2D Images.脑神经元形态学:二维图像定量分析中的方块计数法。
Adv Neurobiol. 2024;36:173-189. doi: 10.1007/978-3-031-47606-8_8.
3
The Cerebellar Dopaminergic System.小脑多巴胺能系统
Front Syst Neurosci. 2021 Aug 5;15:650614. doi: 10.3389/fnsys.2021.650614. eCollection 2021.
4
The Anatomical and Functional Heterogeneity of the Mediodorsal Thalamus.丘脑背内侧核的解剖学和功能异质性
Brain Sci. 2020 Sep 9;10(9):624. doi: 10.3390/brainsci10090624.
5
Dissociation between Cerebellar and Cerebral Neural Activities in Humans with Long-Term Bilateral Sensorineural Hearing Loss.长期双侧感音神经性听力损失患者小脑和大脑神经活动的分离。
Neural Plast. 2019 Mar 27;2019:8354849. doi: 10.1155/2019/8354849. eCollection 2019.
6
Mining Big Neuron Morphological Data.挖掘大型神经元形态数据。
Comput Intell Neurosci. 2018 Jun 24;2018:8234734. doi: 10.1155/2018/8234734. eCollection 2018.
7
The posterior cerebellum, a new organ at risk?小脑后部,一个新的风险器官?
Clin Transl Radiat Oncol. 2017 Nov 23;8:22-26. doi: 10.1016/j.ctro.2017.11.010. eCollection 2018 Jan.
8
Basal ganglia and cerebellar interconnectivity within the human thalamus.人类丘脑内基底神经节与小脑的相互连接
Brain Struct Funct. 2017 Jan;222(1):381-392. doi: 10.1007/s00429-016-1223-z. Epub 2016 Apr 18.
9
Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns.人类大脑小脑核在立体定向空间中的细胞构筑图谱及其共激活模式的描绘。
Front Neuroanat. 2015 May 13;9:54. doi: 10.3389/fnana.2015.00054. eCollection 2015.
10
Binary matrix shuffling filter for feature selection in neuronal morphology classification.用于神经元形态分类中特征选择的二元矩阵重排滤波器
Comput Math Methods Med. 2015;2015:626975. doi: 10.1155/2015/626975. Epub 2015 Mar 29.