Decreased integration and information capacity in stroke measured by whole brain models of resting state activity

被引:71
作者
Adhikari, Mohit H. [1 ]
Hacker, Carl D. [2 ]
Siegel, Josh S. [1 ]
Griffa, Alessandra [3 ,4 ,5 ]
Hagmann, Patric [3 ,4 ,5 ]
Deco, Gustavo [1 ,6 ]
Corbetta, Maurizio [2 ,7 ,8 ]
机构
[1] Univ Pompeu Fabra, Ctr Brain & Cognit, Dept Informat & Commun Technol, Computat Neurosci Grp, Ramon Trias Fargas 25-27, Barcelona 08005, Spain
[2] Washington Univ, Dept Bioengn, St Louis, MO USA
[3] Univ Lausanne Hosp, Dept Radiol, CH-1011 Lausanne, Switzerland
[4] Univ Lausanne CHUV UNIL, CH-1011 Lausanne, Switzerland
[5] Ecole Polytech Fed Lausanne, Signal Proc Lab, CH-1015 Lausanne, Switzerland
[6] Univ Pompeu Fabra, Inst Catalana Recerca Estudis Avancats ICREA, Barcelona 08010, Spain
[7] Washington Univ, Sch Med, Dept Radiol & Neurosci, St Louis, MO USA
[8] Univ Padua, Dept Neurosci, Padua, Italy
基金
欧洲研究理事会;
关键词
functional connectivity; information capacity; integration; whole-brain modelling; FUNCTIONAL CONNECTIVITY MRI; SPATIAL NEGLECT; HEAD MOTION; NETWORKS; REORGANIZATION; SEGREGATION; RECOVERY; COMPETITION; ATTENTION; DYNAMICS;
D O I
10.1093/brain/awx021
中图分类号
R74 [神经病学与精神病学];
学科分类号
100204 [神经病学];
摘要
While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: ` integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and ` information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention.
引用
收藏
页码:1068 / 1085
页数:18
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