Huang Yali, Glasier Charles M, Na Xiaoxu, Ou Xiawei
Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Front Neurosci. 2024 Oct 23;18:1467446. doi: 10.3389/fnins.2024.1467446. eCollection 2024.
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.
Aims to examine and compare white matter functional networks in neonates and 8-year-old children.
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.
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 ( < 0.05). Inter-network FC between cerebral peduncle (CP) and anterior corona radiation (ACR) was higher in 8-year-olds ( < 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.
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.
功能磁共振成像（fMRI）被广泛用于描绘神经活动和理解人类大脑功能。研究表明，灰质中的功能网络从新生儿期到儿童期经历复杂的转变，这支持了快速的认知发展。然而，由于fMRI信号弱得多，白质功能网络直到最近才得到描述，并且发育中大脑白质功能网络的变化仍不清楚。
旨在检查和比较新生儿和8岁儿童的白质功能网络。
我们使用相同的成像方案获取了69名足月健康新生儿和38名健康8岁儿童的静息态fMRI数据，并使用类似的流程研究了他们的脑白质功能网络。首先，我们利用独立成分分析（ICA）方法提取白质功能网络。接下来，我们从时域和频域角度分析白质功能网络的特征，具体而言，包括网络内功能连接性（网络内FC）、网络间功能连接性（网络间FC）和低频波动分数振幅（fALFF）。最后，评估两组之间上述功能网络特征的差异。作为补充措施，并为了与关于发育中大脑灰质功能网络变化的文献研究结果相印证，我们还研究并报告了灰质中的功能网络。
发育中大脑的白质功能网络在新生儿和8岁儿童中均可描绘。与新生儿相比，8岁儿童视辐射、皮质脊髓束和前放射冠内的白质网络内FC较低（< 0.05）。8岁儿童脑桥（CP）和前放射冠（ACR）之间的网络间FC较高（< 0.05）。此外，8岁儿童在0.01 - 0.15 Hz高频范围内的脑活动能量分布更大。两组之间脑白质功能网络存在显著的发育差异，其特征为网络间FC增加、网络内FC减少以及高频能量分布更高。在灰质功能网络中也观察到类似的结果。
发育中大脑的白质功能网络可以可靠地测量，并且这些网络的差异反映了大脑发育中的功能分化和整合。
