Abstract
Perinatal stroke occurs early in life and often leads to a permanent, disabling weakness to one side of the body. To test the hypothesis that non-lesioned hemisphere sensorimotor network structural connectivity in children with perinatal stroke is different from controls, we used diffusion imaging and graph theory to explore structural topology between these populations. Children underwent diffusion and anatomical 3T MRI. Whole-brain tractography was constrained using a brain atlas creating an adjacency matrix containing connectivity values. Graph theory metrics including betweenness centrality, clustering coefficient, and both neighbourhood and hierarchical complexity of sensorimotor nodes were compared to controls. Relationships between these connectivity metrics and validated sensorimotor assessments were explored. Eighty-five participants included 27 with venous stroke (mean age = 11.5 ± 3.7 years), 26 with arterial stroke (mean age = 12.7 ± 4.0 years), and 32 controls (mean age = 13.3 ± 3.6 years). Non-lesioned primary motor (M1), somatosensory (S1) and supplementary motor (SMA) areas demonstrated lower betweenness centrality and higher clustering coefficient in stroke groups. Clustering coefficient of M1, S1, and SMA were inversely associated with clinical motor function. Hemispheric betweenness centrality and clustering coefficient were higher in stroke groups compared to controls. Hierarchical and average neighbourhood complexity across the hemisphere were lower in stroke groups. Developmental plasticity alters the connectivity of key nodes within the sensorimotor network of the non-lesioned hemisphere following perinatal stroke and contributes to clinical disability.
Highlights
Perinatal stroke occurs early in life and often leads to a permanent, disabling weakness to one side of the body
The final sample consisted of 85 participants, including 27 with periventricular venous infarction (PVI) (63% male; mean age = 11.5 ± 3.7 years; range 6.6–19.7 years), 26 with arterial ischemic stroke (AIS) (58% male; mean age = 12.7 ± 4.0 years; range 6.6–19.0), and 32 Typically developing controls (TDC) (53% male; mean age = 13.3 ± 3.6 years; range 6.4– 19.0 years)
We have consistently found in this perinatal stroke population, altered functional and structural connectivity in sensorimotor networks of both hemispheres with many metrics showing strong associations with sensorimotor function[36–40]
Summary
A list of abbreviation can be seen in Supplementary Table 1. The brain is a complex system, and as such, models of its topology require an appropriate tool to represent this complexity To this end, hierarchical complexity has been proposed as a tool which can assess network-wide patterns in connectivity for nodes of the same degree. Neighbourhood complexity assesses how many nodes is a given node connected to This metric is calculated at the nodal level, e.g. each node’s unique neighborhood is investigated with respect to their relative complexity. Betweenness centrality, clustering coefficient, and neighbourhood complexity was assessed for seven individual sensorimotor-related nodes including M1, S1, SMA, thalamus, caudate, putamen, pallidum and one negative control node (IOG). The above metrics (BC, CC, and NC) and hierarchical complexity were assessed the non-lesioned hemisphere in its entirety (i.e. encompassing an average of all 47 nodes) between groups using either an analysis of variance or a Kruskal–Wallis test. Post-hoc power calculations were performed using G*Power[30] with an alpha-level of 0.05, an effect size of 1.0 (a conservative estimate based on current observed effect sizes), and the sample size of the two smallest groups in our study
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