Curtis Marilyn, Bayat Mohammadreza, Garic Dea, Alfano Alliete R, Hernandez Melissa, Curzon Madeline, Bejarano Andrea, Tremblay Pascale, Graziano Paulo, Dick Anthony Steven
bioRxiv. 2025 Feb 11:2024.08.23.609470. doi: 10.1101/2024.08.23.609470.
Characterizing the structural development of the neural speech network in early childhood is important to understand speech acquisition. To investigate speech in the developing brain, 94 children aged 4-7-years-old were scanned using diffusion weighted imaging (DWI) magnetic resonance imaging (MRI). In order to increase sample size and performance variability, we included children who were diagnosed with attention-deficit hyperactivity disorder (ADHD) from a larger ongoing study. Additionally, each child completed the Syllable Repetition Task (SRT), a validated measure of phoneme articulation. The DWI data were modeled using restriction spectrum imaging (RSI) to measure restricted and hindered diffusion properties in both grey and white matter. Consequently, we analyzed the diffusion data using both whole brain analysis, and automated fiber quantification (AFQ) analysis to establish tract profiles for each of six fiber pathways thought to be important for supporting speech development. In the whole brain analysis, we found that SRT performance was associated with restricted diffusion in bilateral inferior frontal gyrus, , right pre-supplementary and supplementary motor area, and bilateral cerebellar grey matter ( < .005). Age moderated these associations in left and frontal aslant tract (FAT). However, in both cases only the cerebellar findings survived a cluster correction. We also found associations between SRT performance and restricted diffusion in cortical association fiber pathways, especially left FAT, and in the cerebellar peduncles. Analyses using automated fiber quantification (AFQ) highlighted differences in high and low performing children along specific tract profiles, most notably in left but not right FAT, in bilateral SLFIII, and in the cerebellar peduncles. These findings suggest that individual differences in speech performance are reflected in structural grey and white matter differences as measured by restricted and hindered diffusion metrics, and offer important insights into developing brain networks supporting speech in very young children.
了解幼儿期神经言语网络的结构发育对于理解言语习得至关重要。为了研究发育中大脑的言语情况，我们使用扩散加权成像（DWI）磁共振成像（MRI）对94名4至7岁的儿童进行了扫描。为了增加样本量和表现变异性，我们从一项正在进行的更大规模研究中纳入了被诊断患有注意力缺陷多动障碍（ADHD）的儿童。此外，每个孩子都完成了音节重复任务（SRT），这是一种经过验证的音素发音测量方法。DWI数据使用受限谱成像（RSI）进行建模，以测量灰质和白质中的受限和受阻扩散特性。因此，我们使用全脑分析和自动纤维定量（AFQ）分析来分析扩散数据，以建立被认为对支持言语发展很重要的六条纤维通路中每条通路的纤维束轮廓。在全脑分析中，我们发现SRT表现与双侧额下回、右侧前辅助运动区和辅助运动区以及双侧小脑灰质中的受限扩散有关（P <.005）。年龄调节了左侧额斜束（FAT）中的这些关联。然而，在这两种情况下，只有小脑的结果在簇校正后仍然显著。我们还发现SRT表现与皮质联合纤维通路，特别是左侧FAT以及小脑脚中的受限扩散之间存在关联。使用自动纤维定量（AFQ）进行的分析突出了高表现和低表现儿童在特定纤维束轮廓上的差异，最明显的是在左侧而非右侧FAT、双侧上纵束III以及小脑脚中。这些发现表明，言语表现的个体差异反映在通过受限和受阻扩散指标测量的结构灰质和白质差异中，并为支持幼儿言语发展的大脑网络提供了重要见解。
