What does this part of the brain do?

大脑的这一部分有什么作用?

基本信息

项目摘要

Despite decades of neuroimaging work striving to relate the topological organization of the brain to the available taxonomy of human behavior, the relationship between behavioral functions and the nervous system has remained elusive. Many studies have used fMRI to examine which brain region was activated for a particular behavioral task. In a lesser extent and systematic fashion, other studies have examined how behavioral variability across subjects or pathology relate to grey matter volume (GM) assuming that if a given brain region is engaged in a particular behavioral function, GM in that region should covary with performance or scores measured with a specific task or (clinical) questionnaire targeting this function. Moreover, it has to be acknowledged, that most likely no brain region may support a particular behavioral function on its own. Hence, identifying those phenotypes that may be predicted from structural and functional connectivity patterns of a region may provide another alternative to its functional characterization. However, these different concepts towards functional characterization have never been compared in order to examine how they converge or complement each other. Filling this gap by a systematic evaluation thus represents the key aim of this work. Implementing a large array of different approaches towards functional inference, applying them to a heterogeneous set of regions and comparing the ensuing characterizations will represent an important foundation for future brain mapping endeavors by providing an objective reference for how to answer the key question in systems neuroscience 'What does this part of the brain do?'
尽管几十年来神经影像学工作一直在努力将大脑的拓扑组织与人类行为的现有分类联系起来,但行为功能和神经系统之间的关系仍然难以捉摸。许多研究使用功能性磁共振成像来检查大脑的哪个区域被激活以执行特定的行为任务。在较小程度上和系统的方式,其他研究已经检查了受试者或病理学之间的行为变异性如何与灰质体积(GM)相关,假设如果给定的大脑区域参与特定的行为功能,则该区域的GM应该与特定任务或针对该功能的(临床)问卷测量的表现或分数协变。此外,必须承认,很可能没有大脑区域可以独立支持特定的行为功能。因此,鉴定可以从区域的结构和功能连接模式预测的那些表型可以为其功能表征提供另一种替代。然而,这些不同的概念对功能特性从来没有比较,以检查它们如何收敛或相互补充。因此,通过系统评价填补这一空白是这项工作的主要目标。实施一系列不同的方法来进行功能推理,将它们应用于一组异质的区域,并比较随后的表征,这将为未来的大脑映射工作提供一个重要的基础,为如何回答系统神经科学中的关键问题提供客观的参考。'

项目成果

期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Anosognosia and default mode subnetwork dysfunction in Alzheimer's disease
  • DOI:
    10.1002/hbm.24775
  • 发表时间:
    2019-08-24
  • 期刊:
  • 影响因子:
    4.8
  • 作者:
    Antoine, Nicolas;Bahri, Mohamed A.;Salmon, Eric
  • 通讯作者:
    Salmon, Eric
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Professor Dr. Simon Eickhoff其他文献

Professor Dr. Simon Eickhoff的其他文献

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{{ truncateString('Professor Dr. Simon Eickhoff', 18)}}的其他基金

Automated brain-age prediction and its interpretation
自动脑年龄预测及其解释
  • 批准号:
    432015680
  • 财政年份:
    2019
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Multi-modal Mapping of the human dorsal premotor cortex based on function and connectivity
基于功能和连接性的人类背侧前运动皮层的多模态映射
  • 批准号:
    241883002
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Machine-learning on brain connectomics: Individual prediction of cognitive functioning in health and cerebral small vessel disease
脑连接组学的机器学习:健康和脑小血管疾病中认知功能的个体预测
  • 批准号:
    454012190
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes
Prediction of treatment success of dialectic behavioral therapy in borderline personality disorder
边缘性人格障碍辩证行为疗法治疗成功的预测
  • 批准号:
    499083365
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Connectivity-Optimized Individualized Localization (COIL)
连接优化的个性化定位 (COIL)
  • 批准号:
    519094028
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants

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