Developmental differences in canonical cortical networks: Insights from microstructure-informed tractography.

IF 3.6 3区 医学 Q2 NEUROSCIENCES Network Neuroscience Pub Date : 2024-10-01 eCollection Date: 2024-01-01 DOI:10.1162/netn_a_00378
Sila Genc, Simona Schiavi, Maxime Chamberland, Chantal M W Tax, Erika P Raven, Alessandro Daducci, Derek K Jones
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Abstract

In response to a growing interest in refining brain connectivity assessments, this study focuses on integrating white matter fiber-specific microstructural properties into structural connectomes. Spanning ages 8-19 years in a developmental sample, it explores age-related patterns of microstructure-informed network properties at both local and global scales. First, the diffusion-weighted signal fraction associated with each tractography-reconstructed streamline was constructed. Subsequently, the convex optimization modeling for microstructure-informed tractography (COMMIT) approach was employed to generate microstructure-informed connectomes from diffusion MRI data. To complete the investigation, network characteristics within eight functionally defined networks (visual, somatomotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, and subcortical networks) were evaluated. The findings underscore a consistent increase in global efficiency across child and adolescent development within the visual, somatomotor, and default mode networks (p < 0.005). Additionally, mean strength exhibits an upward trend in the somatomotor and visual networks (p < 0.001). Notably, nodes within the dorsal and ventral visual pathways manifest substantial age-dependent changes in local efficiency, aligning with existing evidence of extended maturation in these pathways. The outcomes strongly support the notion of a prolonged developmental trajectory for visual association cortices. This study contributes valuable insights into the nuanced dynamics of microstructure-informed brain connectivity throughout different developmental stages.

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典型皮质网络的发育差异:微观结构信息牵引成像的启示
为了回应人们对完善大脑连通性评估日益增长的兴趣,本研究侧重于将白质纤维特异性微结构属性整合到结构连通组中。在一个年龄跨度为 8-19 岁的发育样本中,该研究在局部和全局尺度上探索了与年龄相关的微结构网络属性模式。首先,构建了与每条牵引成像重建流线相关的扩散加权信号分数。随后,采用微结构信息牵引成像凸优化建模(COMMIT)方法从扩散核磁共振成像数据中生成微结构信息连接组。为了完成这项研究,研究人员评估了八个功能定义网络(视觉网络、躯体运动网络、背侧注意网络、腹侧注意网络、边缘网络、前顶叶网络、默认模式网络和皮层下网络)的网络特征。研究结果表明,在儿童和青少年的发育过程中,视觉、躯体运动和默认模式网络的整体效率不断提高(p < 0.005)。此外,躯体运动网络和视觉网络的平均强度呈上升趋势(p < 0.001)。值得注意的是,背侧和腹侧视觉通路中的节点表现出与年龄相关的局部效率的显著变化,这与这些通路成熟期延长的现有证据一致。研究结果有力地支持了视觉联想皮层发育轨迹延长的观点。这项研究为我们深入了解微观结构影响的大脑连接在不同发育阶段的微妙动态提供了宝贵的见解。
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来源期刊
Network Neuroscience
Network Neuroscience NEUROSCIENCES-
CiteScore
6.40
自引率
6.40%
发文量
68
审稿时长
16 weeks
期刊最新文献
A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence. Analyzing asymmetry in brain hierarchies with a linear state-space model of resting-state fMRI data. Brain sodium MRI-derived priors support the estimation of epileptogenic zones using personalized model-based methods in epilepsy. Developmental differences in canonical cortical networks: Insights from microstructure-informed tractography. Frequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study.
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