Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA.
Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA.
Brain Connect. 2021 Oct;11(8):651-662. doi: 10.1089/brain.2020.0866. Epub 2021 May 6.
Traumatic brain injury (TBI)-induced attention deficits are among the most common long-term cognitive consequences in children. Most of the existing studies attempting to understand the neuropathological underpinnings of cognitive and behavioral impairments in TBI have utilized heterogeneous samples and resulted in inconsistent findings. The current research proposed to investigate topological properties of the structural brain network in children with TBI and their relationship with post-TBI attention problems in a more homogeneous subgroup of children who had severe post-TBI attention deficits (TBI-A). A total of 31 children with TBI-A and 35 group-matched controls were involved in the study. Diffusion tensor imaging-based probabilistic tractography and graph theoretical techniques were used to construct the structural brain network in each subject. Network topological properties were calculated in both global level and regional (nodal) level. Between-group comparisons among the topological network measures and analyses for searching brain-behavioral were all corrected for multiple comparisons using Bonferroni method. Compared with controls, the TBI-A group showed significantly higher nodal local efficiency and nodal clustering coefficient in left inferior frontal gyrus and right transverse temporal gyrus, whereas significantly lower nodal clustering coefficient in left supramarginal gyrus and lower nodal local efficiency in left parahippocampal gyrus. The temporal lobe topological alterations were significantly associated with the post-TBI inattentive and hyperactive symptoms in the TBI-A group. The results suggest that TBI-related structural re-modularity in the white matter subnetworks associated with temporal lobe may play a critical role in the onset of severe post-TBI attention deficits in children. These findings provide valuable input for understanding the neurobiological substrates of post-TBI attention deficits, and have the potential to serve as quantitatively measurable criteria guiding the development of more timely and tailored strategies for diagnoses and treatments to the affected individuals. Impact statement This study provides a new insight into the neurobiological substrates associated with post-traumatic brain injury attention deficits (TBI-A) in children, by evaluating topological alterations of the structural brain network. The results demonstrated that relative to group-matched controls, the children with TBI-A had significantly altered nodal local efficiency and nodal clustering coefficient in temporal lobe, which strongly linked to elevated inattentive and hyperactive symptoms in the TBI-A group. These findings suggested that white matter structural re-modularity in subnetworks associated with temporal lobe may serve as quantitatively measurable biomarkers for early prediction and diagnosis of post-TBI attention deficits in children.
创伤性脑损伤（TBI）引起的注意力缺陷是儿童中最常见的长期认知后果之一。大多数试图了解 TBI 认知和行为障碍神经病理学基础的现有研究都使用了异质样本，导致结果不一致。目前的研究旨在更同质的严重 TBI 后注意力缺陷（TBI-A）儿童亚组中，研究 TBI 儿童的结构脑网络拓扑性质及其与 TBI 后注意力问题的关系。共有 31 名 TBI-A 儿童和 35 名匹配的对照组参与了这项研究。使用基于弥散张量成像的概率追踪和图论技术构建每个受试者的结构脑网络。在全局水平和区域（节点）水平计算网络拓扑性质。使用 Bonferroni 方法对组间拓扑网络测量比较和搜索脑-行为的分析进行了多重比较校正。与对照组相比，TBI-A 组在左侧额下回和右侧横颞回的节点局部效率和节点聚类系数显著升高，而左侧缘上回的节点聚类系数和左侧海马旁回的节点局部效率显著降低。TBI-A 组颞叶的拓扑改变与 TBI 后注意力不集中和多动症状显著相关。研究结果表明，与颞叶相关的白质子网的 TBI 相关结构再模块化可能在儿童严重 TBI 后注意力缺陷的发生中起关键作用。这些发现为理解 TBI 后注意力缺陷的神经生物学基础提供了有价值的信息，并有可能作为定量可测量的标准，指导针对受影响个体的诊断和治疗的更及时和定制化策略的发展。影响声明本研究通过评估结构脑网络的拓扑改变，为儿童创伤后脑损伤注意力缺陷（TBI-A）相关的神经生物学基础提供了新的见解。结果表明，与匹配对照组相比，TBI-A 儿童的颞叶节点局部效率和节点聚类系数明显改变，与 TBI-A 组注意力不集中和多动症状升高强烈相关。这些发现表明，与颞叶相关的白质子网的结构再模块化可能作为儿童 TBI 后注意力缺陷早期预测和诊断的定量可测量生物标志物。
