A new neuroinformatics approach to personalized medicine in neurology: The Virtual Brain

被引:34
作者
Falcon, Maria I. [1 ]
Jirsa, Viktor [3 ,4 ]
Solodkin, Ana [1 ,2 ]
机构
[1] UC Irvine Hlth Sch Med, Dept Anat & Neurobiol, Irvine, CA USA
[2] UC Irvine Hlth Sch Med, Dept Neurol, Irvine, CA USA
[3] Aix Marseille Univ, Fac Med, Inst Neurosci Syst, Marseille, France
[4] INSERM, Marseille, France
基金
美国国家卫生研究院;
关键词
brain modeling; computational neuroscience; connectome; epilepsy; neural coupling; neuroinformatics; neurology; personalized medicine; stroke; LARGE-SCALE BRAIN; STROKE; CONNECTOMICS; DEGENERATION; RESOLUTION; NETWORKS; DYNAMICS; SIGNAL; MODEL;
D O I
10.1097/WCO.0000000000000344
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Purpose of review An exciting advance in the field of neuroimaging is the acquisition and processing of very large data sets (so called 'big data'), permitting large-scale inferences that foster a greater understanding of brain function in health and disease. Yet what we are clearly lacking are quantitative integrative tools to translate this understanding to the individual level to lay the basis for personalized medicine. Recent findings Here we address this challenge through a review on how the relatively new field of neuroinformatics modeling has the capacity to track brain network function at different levels of inquiry, from microscopic to macroscopic and from the localized to the distributed. In this context, we introduce a new and unique multiscale approach, The Virtual Brain (TVB), that effectively models individualized brain activity, linking large-scale (macroscopic) brain dynamics with biophysical parameters at the microscopic level. We also show how TVB modeling provides unique biological interpretable data in epilepsy and stroke. Summary These results establish the basis for a deliberate integration of computational biology and neuroscience into clinical approaches for elucidating cellular mechanisms of disease. In the future, this can provide the means to create a collection of disease-specific models that can be applied on the individual level to personalize therapeutic interventions.
引用
收藏
页码:429 / 436
页数:8
相关论文
共 54 条
  • [1] The CONNECT project: Combining macro- and micro-structure
    Assaf, Yaniv
    Alexander, Daniel C.
    Jones, Derek K.
    Bizzi, Albero
    Behrens, Tim E. J.
    Clark, Chris A.
    Cohen, Yoram
    Dyrby, Tim B.
    Huppi, Petra S.
    Knoesche, Thomas R.
    LeBihan, Denis
    Parker, Geoff J. M.
    Poupon, Cyril
    [J]. NEUROIMAGE, 2013, 80 : 273 - 282
  • [2] Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework
    Atkinson, AJ
    Colburn, WA
    DeGruttola, VG
    DeMets, DL
    Downing, GJ
    Hoth, DF
    Oates, JA
    Peck, CC
    Schooley, RT
    Spilker, BA
    Woodcock, J
    Zeger, SL
    [J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2001, 69 (03) : 89 - 95
  • [3] Intra-subject reliability of the high-resolution whole-brain structural connectome
    Besson, Pierre
    Lopes, Renaud
    Leclerc, Xavier
    Derambure, Philippe
    Tyvaert, Louise
    [J]. NEUROIMAGE, 2014, 102 : 283 - 293
  • [4] Breakspear M., 2007, UNDERST COMPLEX SYST, P3
  • [5] Complex brain networks: graph theoretical analysis of structural and functional systems
    Bullmore, Edward T.
    Sporns, Olaf
    [J]. NATURE REVIEWS NEUROSCIENCE, 2009, 10 (03) : 186 - 198
  • [6] Exploring the network dynamics underlying brain activity during rest
    Cabral, Joana
    Kringelbach, Morten L.
    Deco, Gustavo
    [J]. PROGRESS IN NEUROBIOLOGY, 2014, 114 : 102 - 131
  • [7] Rethinking segregation and integration: contributions of whole-brain modelling
    Deco, Gustavo
    Tononi, Giulio
    Boly, Melanie
    Kringelbach, Morten L.
    [J]. NATURE REVIEWS NEUROSCIENCE, 2015, 16 (07) : 430 - U81
  • [8] How Local Excitation-Inhibition Ratio Impacts the Whole Brain Dynamics
    Deco, Gustavo
    Ponce-Alvarez, Adrian
    Hagmann, Patric
    Romani, Gian Luca
    Mantini, Dante
    Corbetta, Maurizio
    [J]. JOURNAL OF NEUROSCIENCE, 2014, 34 (23) : 7886 - 7898
  • [9] How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model
    Deco, Gustavo
    Senden, Mario
    Jirsa, Viktor
    [J]. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2012, 6 : 1 - 7
  • [10] The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields
    Deco, Gustavo
    Jirsa, Viktor K.
    Robinson, Peter A.
    Breakspear, Michael
    Friston, Karl J.
    [J]. PLOS COMPUTATIONAL BIOLOGY, 2008, 4 (08)