Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École polytechnique fédérale de Lausanne (EPFL), Geneva, Switzerland (G.G.E., P.E., J.B., E.B., M.C., L.F., A.C.-M., D.d.L.R., T.M., M.J.W., F.C.H.).
Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Switzerland (G.G.E., P.E., J.B., E.B., M.C., L.F., A.C.-M., T.M., D.d.L.R., M.J.W., F.C.H.).
Stroke. 2023 Apr;54(4):955-963. doi: 10.1161/STROKEAHA.122.040001. Epub 2023 Feb 27.
Most studies on stroke have been designed to examine one deficit in isolation; yet, survivors often have multiple deficits in different domains. While the mechanisms underlying multiple-domain deficits remain poorly understood, network-theoretical methods may open new avenues of understanding.
Fifty subacute stroke patients (7±3days poststroke) underwent diffusion-weighted magnetic resonance imaging and a battery of clinical tests of motor and cognitive functions. We defined indices of impairment in strength, dexterity, and attention. We also computed imaging-based probabilistic tractography and whole-brain connectomes. To efficiently integrate inputs from different sources, brain networks rely on a rich-club of a few hub nodes. Lesions harm efficiency, particularly when they target the rich-club. Overlaying individual lesion masks onto the tractograms enabled us to split the connectomes into their affected and unaffected parts and associate them to impairment.
We computed efficiency of the unaffected connectome and found it was more strongly correlated to impairment in strength, dexterity, and attention than efficiency of the total connectome. The magnitude of the correlation between efficiency and impairment followed the order attention>dexterity ≈ strength (strength: ||=.03, =0.02, dexterity: ||=.30, =0.05, attention: ||=.55, <0.001). Network weights associated with the rich-club were more strongly correlated to efficiency than non-rich-club weights.
Attentional impairment is more sensitive to disruption of coordinated networks between brain regions than motor impairment, which is sensitive to disruption of localized networks. Providing more accurate reflections of actually functioning parts of the network enables the incorporation of information about the impact of brain lesions on connectomics contributing to a better understanding of underlying stroke mechanisms.
大多数关于中风的研究都是为了单独研究一种缺陷；然而，幸存者通常在不同领域存在多种缺陷。虽然多领域缺陷的潜在机制仍知之甚少，但网络理论方法可能为理解开辟新途径。
50 名亚急性中风患者（中风后 7±3 天）接受了弥散加权磁共振成像和一系列运动和认知功能的临床测试。我们定义了力量、灵巧性和注意力受损的指标。我们还计算了基于成像的概率性束追踪和全脑连接组。为了有效地整合来自不同来源的输入，大脑网络依赖于少数几个枢纽节点的丰富俱乐部。病变会损害效率，特别是当它们针对丰富俱乐部时。将个体病变掩模叠加到束追踪图上，使我们能够将连接组分为受影响和未受影响的部分，并将其与损伤相关联。
我们计算了未受影响的连接组的效率，发现它与力量、灵巧性和注意力的损伤比总连接组的效率更密切相关。效率与损伤之间的相关性大小遵循注意力>灵巧性≈力量的顺序（力量：||=.03，=0.02，灵巧性：||=.30，=0.05，注意力：||=.55，<0.001）。与丰富俱乐部相关联的网络权重与效率的相关性强于非丰富俱乐部权重。
注意力损伤比运动损伤更敏感于大脑区域之间协调网络的中断，而运动损伤则更敏感于局部网络的中断。更准确地反映网络中实际运行部分的情况，使我们能够将有关大脑病变对连接组学影响的信息纳入其中，从而更好地理解潜在的中风机制。
