Yali Huang, Charles M Glasier, Xiaoxu Na, Xiawei Ou
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However, white matter functional networks, given the much weaker fMRI signal, have not been characterized until recently, and changes in white matter functional networks in the developing brain remain unclear.</p><p><strong>Purpose: </strong>Aims to examine and compare white matter functional networks in neonates and 8-year-old children.</p><p><strong>Methods: </strong>We acquired resting-state fMRI data on 69 full-term healthy neonates and 38 healthy 8-year-old children using a same imaging protocol and studied their brain white matter functional networks using a similar pipeline. First, we utilized the ICA method to extract white matter functional networks. Next, we analyzed the characteristics of the white matter functional networks from both time-domain and frequency-domain perspectives, specifically, intra-network functional connectivity (intra-network FC), inter-network functional connectivity (inter-network FC), and fractional amplitude of low-frequency fluctuation (fALFF). Finally, the differences in the above functional networks' characteristics between the two groups were evaluated. As a supplemental measure and to confirm with literature findings on gray matter functional network changes in the developing brain, we also studied and reported functional networks in gray matter.</p><p><strong>Results: </strong>White matter functional networks in the developing brain can be depicted for both the neonates and the 8-year-old children. White matter intra-network FC within the optic radiations, corticospinal tract, and anterior corona radiata was lower in 8-year-old children compared to neonates (<i>p</i> < 0.05). Inter-network FC between cerebral peduncle (CP) and anterior corona radiation (ACR) was higher in 8-year-olds (<i>p</i> < 0.05). Additionally, 8-year-olds showed a greater distribution of brain activity energy in the high-frequency range of 0.01-0.15 Hz. Significant developmental differences in brain white matter functional networks exist between the two group, characterized by increased inter-network FC, decreased intra-network FC, and higher high-frequency energy distribution. Similar findings were also observed in gray matter functional networks.</p><p><strong>Conclusion: </strong>White matter functional networks can be reliably measured in the developing brain, and the differences in these networks reflect functional differentiation and integration in brain development.</p>","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":"18 ","pages":"1467446"},"PeriodicalIF":3.2000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11538026/pdf/","citationCount":"0","resultStr":"{\"title\":\"White matter functional networks in the developing brain.\",\"authors\":\"Yali Huang, Charles M Glasier, Xiaoxu Na, Xiawei Ou\",\"doi\":\"10.3389/fnins.2024.1467446\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Functional magnetic resonance imaging (fMRI) is widely used to depict neural activity and understand human brain function. Studies show that functional networks in gray matter undergo complex transformations from neonatal age to childhood, supporting rapid cognitive development. However, white matter functional networks, given the much weaker fMRI signal, have not been characterized until recently, and changes in white matter functional networks in the developing brain remain unclear.</p><p><strong>Purpose: </strong>Aims to examine and compare white matter functional networks in neonates and 8-year-old children.</p><p><strong>Methods: </strong>We acquired resting-state fMRI data on 69 full-term healthy neonates and 38 healthy 8-year-old children using a same imaging protocol and studied their brain white matter functional networks using a similar pipeline. First, we utilized the ICA method to extract white matter functional networks. Next, we analyzed the characteristics of the white matter functional networks from both time-domain and frequency-domain perspectives, specifically, intra-network functional connectivity (intra-network FC), inter-network functional connectivity (inter-network FC), and fractional amplitude of low-frequency fluctuation (fALFF). Finally, the differences in the above functional networks' characteristics between the two groups were evaluated. As a supplemental measure and to confirm with literature findings on gray matter functional network changes in the developing brain, we also studied and reported functional networks in gray matter.</p><p><strong>Results: </strong>White matter functional networks in the developing brain can be depicted for both the neonates and the 8-year-old children. White matter intra-network FC within the optic radiations, corticospinal tract, and anterior corona radiata was lower in 8-year-old children compared to neonates (<i>p</i> < 0.05). Inter-network FC between cerebral peduncle (CP) and anterior corona radiation (ACR) was higher in 8-year-olds (<i>p</i> < 0.05). Additionally, 8-year-olds showed a greater distribution of brain activity energy in the high-frequency range of 0.01-0.15 Hz. Significant developmental differences in brain white matter functional networks exist between the two group, characterized by increased inter-network FC, decreased intra-network FC, and higher high-frequency energy distribution. 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引用次数: 0
摘要
背景:功能磁共振成像(fMRI功能磁共振成像(fMRI)被广泛用于描述神经活动和了解人脑功能。研究表明,从新生儿期到儿童期,灰质的功能网络会发生复杂的转变,从而支持认知能力的快速发展。目的:研究并比较新生儿和 8 岁儿童的白质功能网络:我们采用相同的成像方案获取了 69 名足月健康新生儿和 38 名 8 岁健康儿童的静息态 fMRI 数据,并采用相似的方法研究了他们的脑白质功能网络。首先,我们利用 ICA 方法提取脑白质功能网络。接着,我们从时域和频域两个角度分析了白质功能网络的特征,特别是网络内功能连通性(intra-network FC)、网络间功能连通性(inter-network FC)和低频波动分数振幅(fractional amplitude of low-frequency fluctuation, fALFF)。最后,评估了两组间上述功能网络特征的差异。作为补充措施,并为了与灰质功能网络在大脑发育过程中的变化的文献研究结果相印证,我们还研究并报告了灰质的功能网络:结果:新生儿和 8 岁儿童都能描绘出大脑发育中的白质功能网络。与新生儿相比,8 岁儿童视神经根、皮质脊髓束和放射冠前部的白质网络内 FC 更低(p p 结论:白质功能网络可以可靠地反映发育中大脑的功能变化:白质功能网络可以在发育中的大脑中进行可靠测量,这些网络的差异反映了大脑发育过程中的功能分化和整合。
White matter functional networks in the developing brain.
Background: Functional magnetic resonance imaging (fMRI) is widely used to depict neural activity and understand human brain function. Studies show that functional networks in gray matter undergo complex transformations from neonatal age to childhood, supporting rapid cognitive development. However, white matter functional networks, given the much weaker fMRI signal, have not been characterized until recently, and changes in white matter functional networks in the developing brain remain unclear.
Purpose: Aims to examine and compare white matter functional networks in neonates and 8-year-old children.
Methods: We acquired resting-state fMRI data on 69 full-term healthy neonates and 38 healthy 8-year-old children using a same imaging protocol and studied their brain white matter functional networks using a similar pipeline. First, we utilized the ICA method to extract white matter functional networks. Next, we analyzed the characteristics of the white matter functional networks from both time-domain and frequency-domain perspectives, specifically, intra-network functional connectivity (intra-network FC), inter-network functional connectivity (inter-network FC), and fractional amplitude of low-frequency fluctuation (fALFF). Finally, the differences in the above functional networks' characteristics between the two groups were evaluated. As a supplemental measure and to confirm with literature findings on gray matter functional network changes in the developing brain, we also studied and reported functional networks in gray matter.
Results: White matter functional networks in the developing brain can be depicted for both the neonates and the 8-year-old children. White matter intra-network FC within the optic radiations, corticospinal tract, and anterior corona radiata was lower in 8-year-old children compared to neonates (p < 0.05). Inter-network FC between cerebral peduncle (CP) and anterior corona radiation (ACR) was higher in 8-year-olds (p < 0.05). Additionally, 8-year-olds showed a greater distribution of brain activity energy in the high-frequency range of 0.01-0.15 Hz. Significant developmental differences in brain white matter functional networks exist between the two group, characterized by increased inter-network FC, decreased intra-network FC, and higher high-frequency energy distribution. Similar findings were also observed in gray matter functional networks.
Conclusion: White matter functional networks can be reliably measured in the developing brain, and the differences in these networks reflect functional differentiation and integration in brain development.
期刊介绍:
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