Centre for Research in Child Development, National Institute of Education, Nanyang Technological University, Singapore.
Macquarie School of Education, Macquarie University, Sydney, New South Wales, Australia.
Hum Brain Mapp. 2023 Dec 15;44(18):6308-6325. doi: 10.1002/hbm.26495. Epub 2023 Nov 1.
Functional neuroimaging serves as a tool to better understand the cerebral correlates of atypical behaviors, such as learning difficulties. While significant advances have been made in characterizing the neural correlates of reading difficulties (developmental dyslexia), comparatively little is known about the neurobiological correlates of mathematical learning difficulties, such as developmental dyscalculia (DD). Furthermore, the available neuroimaging studies of DD are characterized by small sample sizes and variable inclusion criteria, which make it problematic to compare across studies. In addition, studies to date have focused on identifying single deficits in neuronal processing among children with DD (e.g., mental arithmetic), rather than probing differences in brain function across different processing domains that are known to be affected in children with DD. Here, we seek to address the limitations of prior investigations. Specifically, we used functional magnetic resonance imaging (fMRI) to probe brain differences between children with and without persistent DD; 68 children (8-10 years old, 30 with DD) participated in an fMRI study designed to investigate group differences in the functional neuroanatomy associated with commonly reported behavioral deficits in children with DD: basic number processing, mental arithmetic and visuo-spatial working memory (VSWM). Behavioral data revealed that children with DD were less accurate than their typically achieving (TA) peers for the basic number processing and arithmetic tasks. No behavioral differences were found for the tasks measuring VSWM. A pre-registered, whole-brain, voxelwise univariate analysis of the fMRI data from the entire sample of children (DD and TA) revealed areas commonly associated with the three tasks (basic number processing, mental arithmetic, and VSWM). However, the examination of differences in brain activation between children with and without DD revealed no consistent group differences in brain activation. In view of these null results, we ran exploratory, Bayesian analyses on the data to quantify the amount of evidence for no group differences. This analysis provides supporting evidence for no group differences across all three tasks. We present the largest fMRI study comparing children with and without persistent DD to date. We found no group differences in brain activation using univariate, frequentist analyses. Moreover, Bayesian analyses revealed evidence for the null hypothesis of no group differences. These findings contradict previous literature and reveal the need to investigate the neural basis of DD using multivariate and network-based approaches to brain imaging.
功能神经影像学是一种工具,可以更好地理解学习困难等非典型行为的大脑相关性。虽然在描述阅读困难(发育性阅读障碍)的神经相关性方面取得了重大进展,但对于数学学习困难(发育性计算障碍)等神经生物学相关性知之甚少。此外,现有的发育性计算障碍神经影像学研究存在样本量小和纳入标准不同的特点,使得难以进行跨研究比较。此外,迄今为止的研究主要集中在识别发育性计算障碍儿童中神经元处理的单一缺陷上(例如心算),而不是探测已知在发育性计算障碍儿童中受到影响的不同处理领域的大脑功能差异。在这里,我们试图解决以前研究的局限性。具体来说,我们使用功能磁共振成像(fMRI)来探测有和没有持续发育性计算障碍的儿童之间的大脑差异;68 名儿童(8-10 岁,30 名患有发育性计算障碍)参加了一项 fMRI 研究,旨在研究与发育性计算障碍儿童常见行为缺陷相关的功能神经解剖结构的组间差异:基本数字处理、心算和视空间工作记忆(VSWM)。行为数据显示,患有发育性计算障碍的儿童在基本数字处理和算术任务中的准确性低于其典型表现(TA)的同龄人。在测量 VSWM 的任务中没有发现行为差异。对整个儿童样本(发育性计算障碍和 TA)的 fMRI 数据进行了预注册的全脑、体素水平的单变量分析,结果显示出与三个任务(基本数字处理、心算和 VSWM)相关的常见区域。然而,对有和没有发育性计算障碍的儿童之间的大脑激活差异进行检查后,发现大脑激活没有一致的组间差异。鉴于这些无效结果,我们对数据进行了探索性的贝叶斯分析,以量化没有组间差异的证据量。该分析为所有三个任务均无组间差异提供了支持性证据。我们呈现了迄今为止比较有和没有持续发育性计算障碍的儿童的最大 fMRI 研究。我们使用单变量、频率主义分析在大脑激活方面没有发现组间差异。此外,贝叶斯分析显示了没有组间差异的假设的证据。这些发现与以前的文献相矛盾,表明需要使用多变量和基于网络的脑成像方法来研究发育性计算障碍的神经基础。