形态计量分析中心提出的人类结构-大脑连接矩阵哈佛-牛津图谱框架:用一种新的神经解剖学类型学提高人类结构连接精度的历史视角和未来方向。

IF 2.3 4区 医学 Q2 DEVELOPMENTAL BIOLOGY
Developmental Neuroscience Pub Date : 2023-01-01 Epub Date: 2023-03-28 DOI:10.1159/000530358
Nikos Makris, Richard Rushmore, Jonathan Kaiser, Matthew Albaugh, Marek Kubicki, Yogesh Rathi, Fan Zhang, Lauren J O'Donnell, Edward Yeterian, Verne S Caviness, David N Kennedy
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引用次数: 0

摘要

人类神经系统的完整结构定义必须包括其接线图的描绘(例如,Swanson LW.大脑结构:理解基本计划,2012)。人脑电路图(BCD[Front Neuronanat.2020;14:18])的完整公式由于无法确定其整体连接(即,不仅是通路干,还有起源和终止)而受到阻碍。从结构的角度来看,BCD的神经解剖学公式应该包括每个纤维束的起源和终止,以及纤维束的三维地形过程。经典的神经解剖学研究为通路干及其推测的起源和终止提供了轨迹信息[Dejine J和Dejerine Klumpke A.Anatomie des Centres Nerveux,1901;Dejerin J和Dejerine Klumpke A.Anatomie de Centres Neerveux:Mémethodes générales d’étude embryologie histogénèse et histologie.Anatomie du cerveau,1895;Ludwig E和Klingler J。人类大脑图谱,1956年;Makris N.使用组织学和磁共振方法对人类关联纤维通路的描绘;1999年;神经影像学。1999年1月;9(1):18-45]。我们之前已经总结了这些研究[Neuroimage.1999 Jan;9(1):18-45],并将其呈现在宏观水平的人类大脑结构连接矩阵中。当前上下文中的矩阵是一种组织结构,它体现了关于皮层区域及其连接的解剖学知识。根据马萨诸塞州总医院形态计量分析中心在21世纪初建立的哈佛-牛津图谱神经解剖学框架,这与分割单位有关,该框架基于Verne Caviness博士及其同事的MRI体积测量范式[Brain Dev.1999 Jul;21(5):289-95]。这是一个经典的连接矩阵,主要基于DTI束描记术出现之前的数据,我们称之为“前DTI时代”的人类结构连接矩阵。此外,我们还提供了代表性的例子,其中包括来自非人类灵长类动物的经验证的结构连接信息,以及DTI纤维束成像研究中出现的关于人类结构连接的最新信息。我们称之为“DTI时代”的人类结构连接矩阵。这个更新的矩阵代表了一项正在进行的工作,由于缺乏关于起源和终止以及路径干的经验证的人类连接发现,因此必然是不完整的。重要的是,我们使用神经解剖学类型来表征人脑中不同类型的连接,这对于组织矩阵和前瞻性数据库至关重要。尽管在细节上是实质性的,目前的矩阵可以被认为只是部分完整的,因为与人类纤维系统组织有关的数据来源在很大程度上局限于从解剖标本的大体解剖中推断或从非人灵长类动物实验中推断路径追踪信息[Front Neuronanat.2020;14:18,Front Neuronanat.2022;16:1035420,and Brain Imaging Behav.2021;15(3):1589-1621]。这些矩阵体现了对大脑连接的系统描述,可用于神经科学的认知和临床研究,重要的是,可指导进一步阐明、验证和完成人类BCD的研究工作[Front Neuronanat.2020;14:18]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology.

A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology.

A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology.

A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology.

A complete structural definition of the human nervous system must include delineation of its wiring diagram (e.g., Swanson LW. Brain architecture: understanding the basic plan, 2012). The complete formulation of the human brain circuit diagram (BCD [Front Neuroanat. 2020;14:18]) has been hampered by an inability to determine connections in their entirety (i.e., not only pathway stems but also origins and terminations). From a structural point of view, a neuroanatomic formulation of the BCD should include the origins and terminations of each fiber tract as well as the topographic course of the fiber tract in three dimensions. Classic neuroanatomical studies have provided trajectory information for pathway stems and their speculative origins and terminations [Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux, 1901; Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux: Méthodes générales d'étude-embryologie-histogénèse et histologie. Anatomie du cerveau, 1895; Ludwig E and Klingler J. Atlas cerebri humani, 1956; Makris N. Delineation of human association fiber pathways using histologic and magnetic resonance methodologies; 1999; Neuroimage. 1999 Jan;9(1):18-45]. We have summarized these studies previously [Neuroimage. 1999 Jan;9(1):18-45] and present them here in a macroscale-level human cerebral structural connectivity matrix. A matrix in the present context is an organizational construct that embodies anatomical knowledge about cortical areas and their connections. This is represented in relation to parcellation units according to the Harvard-Oxford Atlas neuroanatomical framework established by the Center for Morphometric Analysis at Massachusetts General Hospital in the early 2000s, which is based on the MRI volumetrics paradigm of Dr. Verne Caviness and colleagues [Brain Dev. 1999 Jul;21(5):289-95]. This is a classic connectional matrix based mainly on data predating the advent of DTI tractography, which we refer to as the "pre-DTI era" human structural connectivity matrix. In addition, we present representative examples that incorporate validated structural connectivity information from nonhuman primates and more recent information on human structural connectivity emerging from DTI tractography studies. We refer to this as the "DTI era" human structural connectivity matrix. This newer matrix represents a work in progress and is necessarily incomplete due to the lack of validated human connectivity findings on origins and terminations as well as pathway stems. Importantly, we use a neuroanatomical typology to characterize different types of connections in the human brain, which is critical for organizing the matrices and the prospective database. Although substantial in detail, the present matrices may be assumed to be only partially complete because the sources of data relating to human fiber system organization are limited largely to inferences from gross dissections of anatomic specimens or extrapolations of pathway tracing information from nonhuman primate experiments [Front Neuroanat. 2020;14:18, Front Neuroanat. 2022;16:1035420, and Brain Imaging Behav. 2021;15(3):1589-1621]. These matrices, which embody a systematic description of cerebral connectivity, can be used in cognitive and clinical studies in neuroscience and, importantly, to guide research efforts for further elucidating, validating, and completing the human BCD [Front Neuroanat. 2020;14:18].

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来源期刊
Developmental Neuroscience
Developmental Neuroscience 医学-发育生物学
CiteScore
4.00
自引率
3.40%
发文量
49
审稿时长
>12 weeks
期刊介绍: ''Developmental Neuroscience'' is a multidisciplinary journal publishing papers covering all stages of invertebrate, vertebrate and human brain development. Emphasis is placed on publishing fundamental as well as translational studies that contribute to our understanding of mechanisms of normal development as well as genetic and environmental causes of abnormal brain development. The journal thus provides valuable information for both physicians and biologists. To meet the rapidly expanding information needs of its readers, the journal combines original papers that report on progress and advances in developmental neuroscience with concise mini-reviews that provide a timely overview of key topics, new insights and ongoing controversies. The editorial standards of ''Developmental Neuroscience'' are high. We are committed to publishing only high quality, complete papers that make significant contributions to the field.
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