Inferring the dynamical effects of stroke lesions through whole-brain modeling

被引:11
|
作者
Idesis, Sebastian [1 ]
Favaretto, Chiara [2 ,3 ]
V. Metcalf, Nicholas [4 ]
Griffis, Joseph C. [4 ]
Shulman, Gordon L. [4 ,5 ]
Corbetta, Maurizio [2 ,3 ,4 ,5 ,6 ,7 ]
Deco, Gustavo [1 ]
机构
[1] Pompeu Fabra Univ, Ctr Brain & Cognit CBC, Dept Informat Technol & Commun DT, Edif Merce Rodoreda, Carrer Trias i Fargas 25-27, Barcelona 08005, Spain
[2] Univ Padua, Padova Neurosci Ctr PNC, via Orus 2-B, I-35129 Padua, Italy
[3] Univ Padua, Dept Neurosci DNS, via Giustiniani 2, I-35128 Padua, Italy
[4] Washington Univ Sch Med, Dept Neurol, 660 S Euclid Ave, St. Louis, MO 63110 USA
[5] Washington Univ Sch Med, Dept Radiol, 660 S Euclid Ave, St. Louis, MO 63110 USA
[6] Biomed Fdn, Venetian Inst Mol Med VIMM, VIMM, via Orus 2, I-35129 Padua, Italy
[7] Inst Catalana Recerca I Estudis Avancats ICREA, Passeig Lluis Co 23, Barcelona 08010, Spain
关键词
Dynamical effects; Generative model; Stroke; Structural disconnection; Whole-brain model; FUNCTIONAL CONNECTIVITY; NETWORK; INTEGRATION; SEGREGATION; ORGANIZATION; ATTENTION; DEFICITS; ATLAS; MOTOR; HUBS;
D O I
10.1016/j.nicl.2022.103233
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
Understanding the effect of focal lesions (stroke) on brain structure-function traditionally relies on behavioral analyses and correlation with neuroimaging data. Here we use structural disconnection maps from individual lesions to derive a causal mechanistic generative whole-brain model able to explain both functional connectivity alterations and behavioral deficits induced by stroke. As compared to other models that use only the local lesion information, the similarity to the empirical fMRI connectivity increases when the widespread structural disconnection information is considered. The presented model classifies behavioral impairment severity with higher accuracy than other types of information (e.g.: functional connectivity). We assessed topological measures that characterize the functional effects of damage. With the obtained results, we were able to understand how network dynamics change emerge, in a nontrivial way, after a stroke injury of the underlying complex brain system. This type of modeling, including structural disconnection information, helps to deepen our understanding of the underlying mechanisms of stroke lesions.
引用
收藏
页数:17
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