Cara Cristina, Zantonello Giulia, Ghio Marta, Tettamanti Marco
CIMeC-Center for Mind/Brain Sciences, University of Trento, Corso Bettini 31, 38068 Rovereto (TN), Italy.
Institute of Experimental Psychology, Heinrich Heine University, Universitätsstrasse 1, 40225 Düsseldorf, Germany.
Cereb Cortex. 2025 Oct 2;35(10). doi: 10.1093/cercor/bhaf193.
Dyslexia is a neurobiological disorder characterized by reading difficulties, yet its causes remain unclear. Neuroimaging and behavioral studies found anomalous responses in tasks requiring phonological processing, motion perception, and implicit learning, and showed gray and white matter abnormalities in dyslexics compared to controls, indicating that dyslexia is highly heterogeneous and promoting a multifactorial approach. To evaluate whether combining behavioral and multimodal MRI improves sensitivity in identifying dyslexia neurocognitive traits compared to monocomponential approaches, 19 dyslexic and 19 control subjects underwent cognitive assessments, multiple (phonological, visual motion, rhythmic) mismatch-response functional MRI tasks, structural diffusion-weighted imaging (DWI) and T1-weighted imaging. Between group differences in the neurocognitive measures were tested with univariate and multivariate approaches. Results showed that dyslexics performed worse than controls in phonological tasks and presented reduced cerebellar responses to mismatching rhythmic stimuli, as well as structural disorganization in white matter tracts and cortical regions. Most importantly, a machine learning model trained with features from all three MRI modalities discriminated between dyslexics and controls with greater accuracy than single-modality models. The individual classification scores in the multimodal machine learning model correlated with behavioral reading accuracy. These results characterize dyslexia as a composite condition with multiple distinctive cognitive and brain traits.
阅读障碍是一种以阅读困难为特征的神经生物学障碍,但其病因仍不清楚。神经影像学和行为学研究发现,在需要语音处理、运动感知和内隐学习的任务中存在异常反应,并且与对照组相比,阅读障碍者的灰质和白质存在异常,这表明阅读障碍具有高度异质性,并促使采用多因素研究方法。为了评估与单成分方法相比,结合行为学和多模态磁共振成像(MRI)是否能提高识别阅读障碍神经认知特征的敏感性,19名阅读障碍者和19名对照者接受了认知评估、多项(语音、视觉运动、节奏)失配反应功能MRI任务、结构扩散加权成像(DWI)和T1加权成像。使用单变量和多变量方法测试了神经认知测量中的组间差异。结果显示,阅读障碍者在语音任务中的表现比对照组差,小脑对不匹配节奏刺激的反应降低,白质束和皮质区域存在结构紊乱。最重要的是,一个用来自所有三种MRI模态的特征训练的机器学习模型在区分阅读障碍者和对照组方面比单模态模型具有更高的准确性。多模态机器学习模型中的个体分类分数与行为阅读准确性相关。这些结果将阅读障碍描述为一种具有多种独特认知和大脑特征的复合病症。