基于磁共振成像的发展性阅读障碍儿童脑结构与功能特征研究

Magnetic resonance imaging-based structural and functional brain characteristics in children with developmental dyslexia

摘要

发展性阅读障碍是儿童期常见的神经发育障碍,严重影响个体的学业与社会功能。磁共振成像(MRI)作为非侵入性神经影像技术,近年来广泛应用于其神经机制及干预效应的研究中。本文综述了国内外关于阅读障碍儿童的结构MRI与功能MRI研究进展,重点涉及阅读相关脑区的灰质、白质改变特征,静息态与任务态功能连接模式,以及干预前后的神经可塑性变化。采用多模态MRI与人工智能辅助分析的结合,为发展性阅读障碍的早期识别与精准干预提供了新的方向。当前研究尚存在样本代表性不足、方法标准不统一、结果重复性较差等问题。未来应加强多中心协作、纵向追踪与多模态融合研究,推动神经影像学在儿童发展性阅读障碍中的临床转化与实践应用。

Abstract

Developmental dyslexia is a common childhood neurodevelopmental disorder that substantially affects academic performance and social functioning. Magnetic resonance imaging (MRI), a noninvasive neuroimaging technique, has been widely used in recent years to investigate its neural mechanisms and the effects of intervention. This review summarizes recent structural and functional MRI findings in children with developmental dyslexia, with emphasis on gray- and white-matter alterations in reading-related brain regions, resting-state and task-based functional connectivity, and intervention-related neuroplastic changes. Integrating multimodal MRI with artificial intelligence-assisted analysis may facilitate early identification and individualized intervention. However, current studies are limited by inadequate sample representativeness, a lack of methodological standardization, and limited reproducibility. Future research should prioritize multicenter collaboration, longitudinal follow-up, and multimodal integration to facilitate the clinical translation and application of neuroimaging in childhood developmental dyslexia.

关键词

阅读障碍 / 磁共振成像 / 神经机制 / 多模态影像 / 儿童

Key words

developmental dyslexia / magnetic resonance imaging / neural mechanisms / multimodal imaging / children

[1] 伊力扎提·麦麦提, 买合甫来提·坎吉, 迪拉热·达吾提, 等. 不同文字阅读障碍儿童的视知觉加工特点[J].中国临床心理学杂志, 2020, 28(3): 460-464.
YILIZHATI Maimaiti, MAIHEFULAITI Kanji, DILARE Dawuti, et al.Visual perception with different types of dyslexia[J].Chin J Clin Psychol, 2020, 28(3): 460-464.(in Chinese)
[2] Prasad S, Sagar R, KumaranSS, et al. Study of functional magnetic resonance imaging (fMRI) in children and adolescents with specific learning disorder (dyslexia)[J]. Asian J Psychiatry, 2020, 50: 101945.
[3] Yang LP, Li CB, Li XM, et al. Prevalence of developmental dyslexia in primary school children: A protocol for systematic review and Meta-analysis[J].World J Pediatr,2022,18(12):804-809.
[4] Wat EK, Jangraw DC, Finn ES, et al. Will you read how I will read? Naturalistic fMRI predictors of emergent reading[J]. Neuropsychologia, 2024, 193: 108763.
[5] 姜琦,骆艳,邓冰.发展性阅读障碍儿童工作记忆缺陷及其干预研究[J].中国学校卫生, 2019, 40(8): 1270-1273.
[6] Leskinen S, Singha S, Mehta NH, et al. Applications of functional magnetic resonance imaging to the study of functional connectivity and activation in neurological disease:A scoping review of the literature[J].World Neurosurg,2024,189:185-192.
[7] Liu YF, Qian Y, Bi HY. Visual motion processing in Chinese children with developmental dyslexia: An fMRI study[J].Dyslexia,2022,28(4):431-447.
[8] Eckert MA, Berninger VW, Vaden KI Jr, et al. Gray matter features of reading disability: A combined meta-analytic and direct analysis approach[J]. Eneuro, 2016, 3(1): ENEURO.0103-15.2015.
[9] Ren H, Li YZ, Bi HY, et al. The shared neurobiological basis of developmental dyslexia and developmental stuttering:A Meta-analysis of functional and structural MRI studies[J].Int J Clin Heal Psychol,2024,24(4):100519.
[10] Ligges C, Ligges M, Gaser C.Cross-sectional investigation of brain volume in dyslexia[J].Front Neurol,2022,13:847919.
[11] Sihvonen AJ, Virtala P, Thiede A, et al. Structural white matter connectometry of reading and dyslexia[J]. NeuroImage, 2021, 241: 118411.
[12] El-Sady S, Mohammad SA, Aboualfotouh Ahmed K, et al. Correlation between diffusion tensor imaging measures and the reading and cognitive performance of Arabic readers: Dyslexic children perspective[J]. Neuroradiology,2020,62(4):525-531.
[13] Richards T, Stevenson J, Crouch J, et al. Tract-based spatial statistics of diffusion tensor imaging in adults with dyslexia[J]. AJNR Am J Neuroradiol, 2008, 29(6): 1134-1139.
[14] Sadeghi N, Arrigoni F, D′Angelo MG, et al. Tensor-based morphometry using scalar and directional information of diffusion tensor MRI data (DTBM): Application to hereditary spastic paraplegia[J]. Hum Brain Mapp, 2018, 39(12): 4643-4651.
[15] Van Der Auwera S, Vandermosten M, Wouters J, et al. A three-time point longitudinal investigation of the arcuate Fasciculus throughout reading acquisition in children developing dyslexia[J]. Neuroimage, 2021, 237: 118087.
[16] Banfi C, Koschutnig K, Moll K,et al. White matter alterations and tract lateralization in children with dyslexia and isolated spelling deficits[J]. Hum Brain Mapp, 2019, 40(3): 765-776.
[17] Schurz M, Wimmer H, Richlan F, et al. Resting-state and task-based functional brain connectivity in developmental dyslexia[J]. Cereb Cortex. 2015,25(10):3502-3514.
[18] Raschle NM, Zuk J, Gaab N. Functional characteristics of developmental dyslexia in left-hemispheric posterior brain regions predate reading onset[J]. Proc Natl Acad Sci U S A,2012,109(6):2156-2161.
[19] 胡晓云, 静进, 范淼, 等. 汉语发育性阅读障碍儿童语音与视空间记忆研究[J]. 中国当代儿科杂志, 2018, 20(4): 314-317.
Hu XY, Jing J, Fan M, et al. Verbal and visual-spatial memory in Chinese children with developmental dyslexia[J]. Chin J Contemp Pediatr, 2018, 20(4): 314-317. (in Chinese)
[20] 王霞,潘雪瑶,李西,等. 后基因组时代基因与语言障碍的相关性研究[J].中华医学遗传学杂志,2024,41(3):377-384.
Wang X, Pan XY, Li X,et al. Studies on the association of genes with language disorders in the post-genomic era[J].Chin J Med Genet,2024,41(3):377-384. (in Chinese)
[21] Hoeft F, Meyler A, Hernandez A, et al. Functional and morphometric brain dissociation between dyslexia and reading ability[J]. Proc Natl Acad Sci U S A, 2007,104(10):4234-4239.
[22] Demirci E, Gengeç Benli Ş, Içer S, et al. Assessment of alterations in regional homogeneity and amplitude of low-frequency fluctuations in children with dyslexia[J].Turk J Med Sci,2025,55(5):1174-1187.
[23] Finn ES, Shen X, Holahan JM, et al. Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity[J].Biol Psychiatry,2014, 76(5): 397-404.
[24] Wolf M, Katzir-Cohen T. Reading fluency and its intervention[J].Sci Stud Read, 2001, 5(3): 211-239.
[25] Taran N, Gatenyo R, Hadjadj E,et al. Distinct connectivity patterns between perception and attention-related brain networks characterize dyslexia: Machine learning applied to resting-state fMRI[J]. Cortex,2024,181:216-232.
[26] Twait E, Farah R, Horowitz-Kraus T. Decreased functional connectivity of the salience network during narrative comprehension in children with reading difficulties: An fMRI study[J]. Neuroimage Clin,2018,20:987-992.
[27] Temple E, Deutsch GK, Poldrack RA, et al. Neural deficits in children with dyslexia ameliorated by behavioral remediation: Evidence from functional MRI[J].Proc Natl Acad Sci U S A, 2003,100(5):2860-2865.
[28] Feng G, Shen L, Shi L, et al. Brain changes following two reading interventions in Chinese children with reading disability[J].Dev Sci,2025,28(4):e70038.
[29] Horowitz-Kraus T, Toro-Serey C, DiFrancesco M. Increased resting-state functional connectivity in the cingulo-opercular cognitive-control network after intervention in children with reading difficulties[J].PLoS One, 2015,10(7):e0133762.
[30] Aboud KS, Barquero LA, Cutting LE. Prefrontal mediation of the reading network predicts intervention response in dyslexia[J]. Cortex,2018,101:96-106.
[31] Economou M, Vanden Bempt F, Van Herck S, et al. Cortical structure in pre-readers at cognitive risk for dyslexia: Baseline differences and response to intervention[J]. Neurobiol Lang (Camb). 2024,5(2):264-287.
[32] Yang Y, Yang YH, Li J, et al. An audiovisual integration deficit underlies reading failure in nontransparent writing systems: An fMRI study of Chinese children with dyslexia[J]. J Neurolinguistics, 2020, 54: 100884.
[33] Liu L,Tao R, Wang W, et al.Chinese dyslexics show neural differences in morphological processing[J].Dev Cogn Neurosci,2013,6:40-50.
[34] Zhang J, Liu L, Li H, et al.Large-scale network topology reveals brain functional abnormality in Chinese dyslexic children[J].Neuropsychologia,2021,157:107886.
[35] Cara C, Zantonello G, Ghio M, et al. Multimodal investigation of the neurocognitive deficits underlying dyslexia in adulthood[J]. Cereb Cortex, 2025, 35(10): bhaf193.
[36] Harismithaa LR, Sadasivam GS. Multimodal screening for dyslexia using anatomical and functional MRI data[J]. JCM, 2022, 22(4): 1105-1116.
[37] Ouyang M, Whitehead MT, Mohapatra S, et al. Machine-learning based prediction of future outcome using multimodal MRI during early childhood[J]. Semin Fetal Neonatal Med, 2024, 29(2-3): 101561.
[38] Meena YK, Cecotti H, Bhushan B, et al. Detection of dyslexic children using machine learning and multimodal Hindi language eye-gaze-assisted learning system[J]. IEEE Trans Hum Mach Syst, 2023, 53(1): 122-131.
[39] Yan K, Li T, Marques JAL, et al. A review on multimodal machine learning in medical diagnostics[J]. Math Biosci Eng, 2023, 20(5): 8708-8726.
[40] Mahowald K, Fedorenko E. Reliable individual-level neural markers of high-level language processing: A necessary precursor for relating neural variability to behavioral and genetic variability[J]. Neuroimage,2016,139:74-93.
[41] Shurrab S, Guerra-Manzanares A, Magid A, et al. Multimodal machine learning for stroke prognosis and diagnosis: A systematic review[J].IEEE J Biomed Health Inform,2024,28(11):6958-6973.

基金资助

南通大学临床医学专项科研基金项目(重点项目)(2024LZ013);常州市应用基础研究计划(CJ20253120)