A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age.

IF 2.4 3区 医学 Q3 NEUROSCIENCES Brain connectivity Pub Date : 2024-03-01 DOI:10.1089/brain.2023.0040
Rekha Saha, Debbrata K Saha, Md Abdur Rahaman, Zening Fu, Jingyu Liu, Vince D Calhoun
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引用次数: 0

Abstract

Aim: To develop an approach to evaluate multiple overlapping brain functional change patterns (FCPs) in functional network connectivity (FNC) and apply to study developmental changes in brain function. Introduction: FNC, the network analog of functional connectivity (FC), is commonly used to capture the intrinsic functional relationships among brain networks. Ongoing research on longitudinal changes of intrinsic FC across whole-brain functional networks has proven useful for characterizing age-related changes, but to date, there has been little focus on capturing multivariate patterns of FNC change with brain development. Methods: In this article, we introduce a novel approach to evaluate multiple overlapping FCPs by utilizing FNC matrices. We computed FNC matrices from the large-scale Adolescent Brain Cognitive Development data using fully automated spatially constrained independent component analysis (ICA). We next evaluated changes in these patterns for a 2-year period using a second-level ICA on the FNC change maps. Results: Our proposed approach reveals several highly structured (modular) FCPs and significant results including strong brain FC between visual and sensorimotor domains that increase with age. We also find several FCPs that are associated with longitudinal changes of psychiatric problems, cognition, and age in the developing brain. Interestingly, FCP cross-covariation, reflecting coupling between maximally independent FCPs, also shows significant differences between upper and lower quartile loadings for longitudinal changes in age, psychiatric problems, and cognition scores, as well as baseline age in the developing brain. FCP patterns and results were also found to be highly reliable based on analysis of data collected in a separate scan session. Conclusion: In sum, our results show evidence of consistent multivariate patterns of functional change in emerging adolescents and the proposed approach provides a useful and general tool to evaluate covarying patterns of whole-brain functional changes in longitudinal data. Impact statement In this article, we introduce a novel approach utilizing functional network connectivity (FNC) matrices to estimate multiple overlapping brain functional change patterns (FCPs). The findings demonstrate several well-structured FCPs that exhibit significant changes for a 2-year period, particularly in the functional connectivity between the visual and sensorimotor domains. In addition, we discover several FCPs that are associated with psychopathology, cognition, and age. Finally, our proposed approach for studying age-related FCPs represents a pioneering method that provides a valuable tool for assessing interconnected patterns of whole-brain functional changes in longitudinal data and may be useful to study change over time with applicability to many other areas, including the study of longitudinal changes within diagnostic groups, treatment effects, aging effects, and more.

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一种估算与精神问题、认知和年龄有关的发育中大脑功能网络连接纵向变化模式的方法。
目的:开发一种在功能网络连通性(FNC)中评估多个重叠的大脑功能变化模式(FCPs)的方法,并将其应用于研究大脑功能的发育变化:功能网络连通性是功能连通性的网络类似物,通常用于捕捉大脑网络之间的内在功能关系。对全脑功能网络内在功能连通性纵向变化的持续研究已被证明有助于描述与年龄有关的变化,但迄今为止,人们很少关注捕捉 FNC 随大脑发育而变化的多变量模式:本文介绍了一种利用 FNC 矩阵评估多个重叠 FCP 的新方法。我们利用全自动空间约束独立成分分析(ICA)从大规模青少年大脑和认知发展(ABCD)数据中计算出FNC矩阵。接下来,我们在 FNC 变化图上使用二级 ICA 评估了这些模式在两年内的变化:结果:我们提出的方法揭示了几种高度结构化(模块化)的功能变化模式和重要结果,包括视觉(VS)和感觉运动(SM)领域之间强大的大脑功能连接,这种连接随着年龄的增长而增加。我们还发现了几个与发育中大脑的精神问题、认知和年龄的纵向变化相关的FCP。有趣的是,反映最大独立 FCP 之间耦合的 FCP 交叉协变也显示出年龄、精神问题和认知分数以及发育中大脑基线年龄纵向变化的上下四分位数载荷之间的显著差异。根据对单独扫描过程中收集的数据进行的分析,还发现 FCP 模式和结果具有高度可靠性:总之,我们的研究结果表明,新兴青少年的功能变化具有一致的多变量模式,所提出的方法为评估纵向数据中全脑功能变化的共变模式提供了有用的通用工具。
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来源期刊
Brain connectivity
Brain connectivity Neuroscience-General Neuroscience
CiteScore
4.80
自引率
0.00%
发文量
80
期刊介绍: Brain Connectivity provides groundbreaking findings in the rapidly advancing field of connectivity research at the systems and network levels. The Journal disseminates information on brain mapping, modeling, novel research techniques, new imaging modalities, preclinical animal studies, and the translation of research discoveries from the laboratory to the clinic. This essential journal fosters the application of basic biological discoveries and contributes to the development of novel diagnostic and therapeutic interventions to recognize and treat a broad range of neurodegenerative and psychiatric disorders such as: Alzheimer’s disease, attention-deficit hyperactivity disorder, posttraumatic stress disorder, epilepsy, traumatic brain injury, stroke, dementia, and depression.
期刊最新文献
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