• 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

全脑建模:过去、现在与未来。

Whole-Brain Modelling: Past, Present, and Future.

机构信息

Department of Psychiatry and Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.

Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.

出版信息

Adv Exp Med Biol. 2022;1359:313-355. doi: 10.1007/978-3-030-89439-9_13.

DOI:10.1007/978-3-030-89439-9_13
PMID:35471545
Abstract

Whole-Brain Modelling is a scientific field with a short history and a long past. Its various disciplinary roots and conceptual ingredients extend back to as early as the 1940s. It was not until the late 2000s, however, that a nascent paradigm emerged in roughly its current form-concurrently, and in many ways joined at the hip, with its sister field of macro-connectomics. This period saw a handful of seminal papers authored by a certain motley crew of notable theoretical and cognitive neuroscientists, which have served to define much of the landscape of whole-brain modelling as it stands at the start of the 2020s. At the same time, the field has over the past decade expanded in a dozen or more fascinating new methodological, theoretical, and clinical directions. In this chapter we offer a potted Past, Present, and Future of whole-brain modelling, noting what we take to be some of its greatest successes, hardest challenges, and most exciting opportunities.

摘要

全脑建模是一个历史短暂但渊源流长的科学领域。它的各种学科根源和概念成分可以追溯到 20 世纪 40 年代早期。直到 2000 年代后期,一种新兴的范式才以大致目前的形式出现——与宏观连接组学领域同时出现,并在许多方面紧密结合。这一时期出现了少数几篇由一群著名的理论和认知神经科学家撰写的开创性论文,这些论文定义了 21 世纪 20 年代初全脑建模的大部分领域。与此同时,该领域在过去十年中以十多个迷人的新方法学、理论和临床方向扩展。在本章中,我们提供了全脑建模的简史、现状和未来,指出了我们认为它最成功、最具挑战性和最令人兴奋的一些机会。

相似文献

1
Whole-Brain Modelling: Past, Present, and Future.全脑建模:过去、现在与未来。
Adv Exp Med Biol. 2022;1359:313-355. doi: 10.1007/978-3-030-89439-9_13.
2
Meta-connectomics: human brain network and connectivity meta-analyses.元连接组学:人类脑网络与连接性荟萃分析
Psychol Med. 2016 Apr;46(5):897-907. doi: 10.1017/S0033291715002895. Epub 2016 Jan 26.
3
Depression, neuroimaging and connectomics: a selective overview.抑郁、神经影像学与连接组学:选择性综述。
Biol Psychiatry. 2015 Feb 1;77(3):223-235. doi: 10.1016/j.biopsych.2014.08.009. Epub 2014 Aug 23.
4
Small-world human brain networks: Perspectives and challenges.小世界人类大脑网络:观点与挑战。
Neurosci Biobehav Rev. 2017 Jun;77:286-300. doi: 10.1016/j.neubiorev.2017.03.018. Epub 2017 Apr 5.
5
Functional connectomics from a "big data" perspective.从“大数据”角度看功能连接组学
Neuroimage. 2017 Oct 15;160:152-167. doi: 10.1016/j.neuroimage.2017.02.031. Epub 2017 Feb 14.
6
Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy.连接组学与图论分析:癫痫网络异常的新见解。
Epilepsia. 2015 Nov;56(11):1660-8. doi: 10.1111/epi.13133. Epub 2015 Sep 22.
7
Structural MRI connectome in development: challenges of the changing brain.发育中的结构磁共振成像连接组:变化中的大脑所面临的挑战
Br J Radiol. 2014 Jul;87(1039):20140086. doi: 10.1259/bjr.20140086. Epub 2014 May 14.
8
Small-World Brain Networks Revisited.再次探讨小世界脑网络。
Neuroscientist. 2017 Oct;23(5):499-516. doi: 10.1177/1073858416667720. Epub 2016 Sep 21.
9
Connectomics: comprehensive approaches for whole-brain mapping.连接组学:全脑图谱绘制的综合方法。
Microscopy (Oxf). 2015 Feb;64(1):57-67. doi: 10.1093/jmicro/dfu103. Epub 2014 Dec 18.
10
Great expectations: using whole-brain computational connectomics for understanding neuropsychiatric disorders.巨大的期望:利用全脑计算连接组学理解神经精神障碍。
Neuron. 2014 Dec 3;84(5):892-905. doi: 10.1016/j.neuron.2014.08.034.

引用本文的文献

1
A comprehensive investigation of intracortical and corticothalamic models of the alpha rhythm.对阿尔法节律的皮质内及皮质丘脑模型的全面研究。
PLoS Comput Biol. 2025 Apr 10;21(4):e1012926. doi: 10.1371/journal.pcbi.1012926. eCollection 2025 Apr.
2
Stimulation mapping and whole-brain modeling reveal gradients of excitability and recurrence in cortical networks.刺激映射和全脑建模揭示了皮质网络中兴奋性和循环性的梯度。
Nat Commun. 2025 Apr 4;16(1):3222. doi: 10.1038/s41467-025-58187-6.
3
Dialogue mechanisms between astrocytic and neuronal networks: A whole-brain modelling approach.

本文引用的文献

1
Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy.静息态 fMRI 的全脑建模可区分 ADHD 亚型,并有助于分层神经刺激治疗。
Neuroimage. 2021 May 1;231:117844. doi: 10.1016/j.neuroimage.2021.117844. Epub 2021 Feb 10.
2
Dynamic coupling of whole-brain neuronal and neurotransmitter systems.全脑神经元和神经递质系统的动态耦合。
Proc Natl Acad Sci U S A. 2020 Apr 28;117(17):9566-9576. doi: 10.1073/pnas.1921475117. Epub 2020 Apr 13.
3
Before and beyond the Wilson-Cowan equations.
星形胶质细胞与神经元网络之间的对话机制:一种全脑建模方法。
PLoS Comput Biol. 2025 Jan 13;21(1):e1012683. doi: 10.1371/journal.pcbi.1012683. eCollection 2025 Jan.
4
Secondary thalamic dysfunction underlies abnormal large-scale neural dynamics in chronic stroke.继发性丘脑功能障碍是慢性中风异常大规模神经动力学的基础。
Proc Natl Acad Sci U S A. 2024 Nov 12;121(46):e2409345121. doi: 10.1073/pnas.2409345121. Epub 2024 Nov 6.
5
Preparatory activity of anterior insula predicts conflict errors: integrating convolutional neural networks and neural mass models.前脑岛的预备活动预测冲突错误:卷积神经网络与神经质量模型的整合。
Sci Rep. 2024 Jul 19;14(1):16682. doi: 10.1038/s41598-024-67034-5.
6
Macroscopic resting state model predicts theta burst stimulation response: A randomized trial.宏观静息态模型预测经颅磁刺激反应:一项随机试验。
PLoS Comput Biol. 2023 Mar 6;19(3):e1010958. doi: 10.1371/journal.pcbi.1010958. eCollection 2023 Mar.
在威尔逊-考恩方程之前和之后。
J Neurophysiol. 2020 May 1;123(5):1645-1656. doi: 10.1152/jn.00404.2019. Epub 2020 Mar 18.
4
Spherical-harmonics mode decomposition of neural field equations.神经场方程的球谐模式分解
Phys Rev E. 2020 Jan;101(1-1):012202. doi: 10.1103/PhysRevE.101.012202.
5
COALIA: A Computational Model of Human EEG for Consciousness Research.COALIA:用于意识研究的人类脑电图计算模型。
Front Syst Neurosci. 2019 Nov 13;13:59. doi: 10.3389/fnsys.2019.00059. eCollection 2019.
6
Adaptive frequency-based modeling of whole-brain oscillations: Predicting regional vulnerability and hazardousness rates.基于自适应频率的全脑振荡建模:预测区域易损性和危险性发生率。
Netw Neurosci. 2019 Sep 1;3(4):1094-1120. doi: 10.1162/netn_a_00104. eCollection 2019.
7
Linking Molecular Pathways and Large-Scale Computational Modeling to Assess Candidate Disease Mechanisms and Pharmacodynamics in Alzheimer's Disease.将分子途径与大规模计算建模相结合以评估阿尔茨海默病的候选疾病机制和药效学
Front Comput Neurosci. 2019 Aug 13;13:54. doi: 10.3389/fncom.2019.00054. eCollection 2019.
8
Optimization of surgical intervention outside the epileptogenic zone in the Virtual Epileptic Patient (VEP).优化虚拟癫痫患者(VEP)中的致痫区外手术干预。
PLoS Comput Biol. 2019 Jun 26;15(6):e1007051. doi: 10.1371/journal.pcbi.1007051. eCollection 2019 Jun.
9
Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics.人类大脑皮层的层次异质性塑造了大规模神经动力学。
Neuron. 2019 Mar 20;101(6):1181-1194.e13. doi: 10.1016/j.neuron.2019.01.017. Epub 2019 Feb 7.
10
Whole-Brain Multimodal Neuroimaging Model Using Serotonin Receptor Maps Explains Non-linear Functional Effects of LSD.使用血清素受体图谱的全脑多模态神经影像学模型解释 LSD 的非线性功能效应。
Curr Biol. 2018 Oct 8;28(19):3065-3074.e6. doi: 10.1016/j.cub.2018.07.083. Epub 2018 Sep 27.