与发育性计算障碍有关的大脑功能连接的改变。

IF 2.3 4区 医学 Q3 CLINICAL NEUROLOGY
Roger Mateu-Estivill, Ana Adan, Sergi Grau, Xavier Rifà-Ros, Xavier Caldú, Núria Bargalló, Josep M Serra-Grabulosa
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引用次数: 0

摘要

背景和目的:近年来,人们对不同神经和精神疾病中静息神经网络的研究越来越感兴趣。以往的研究表明,默认模式网络(DMN)可能在计算障碍中发生改变,但对静息态网络在计算技能发展中的作用,尤其是发育性计算障碍(DD)儿童的静息态网络的研究却相对较少。基于此,本研究利用功能连通性多变量模式分析(fc-MVPA)研究了发育性计算障碍儿童的静息态功能连通性(rs-FC)数据的差异:我们对一组 DD 儿童(n = 19,8.06 ± 0.87 岁)和一组年龄与性别匹配的发育正常对照组儿童(n = 23,7.76 ± 0.46 岁)的静息态图像进行了 fc-MVPA 分析:结果:fc-MVPA分析表明,在左右颞内侧回分配的两个群组中,组间连通性特征存在显著差异。事后效应大小结果显示,DD患儿每个颞极与DMN之间的rs-FC减少,而每个颞极与感觉运动网络之间的rs-FC增加:我们的研究结果表明,DD患儿静息态网络之间的信息流出现异常,这表明这些网络对算术的发展非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alterations in functional brain connectivity associated with developmental dyscalculia.

Background and purpose: In recent years, there has been a growing interest in the study of resting neural networks in different neurological and mental disorders. While previous studies suggest that the default mode network (DMN) may be altered in dyscalculia, the study of resting-state networks in the development of numerical skills, especially in children with developmental dyscalculia (DD), is scarce and relatively recent. Based on this, this study examines differences in resting-state functional connectivity (rs-FC) data of children with DD using functional connectivity multivariate pattern analysis (fc-MVPA), a data-driven methodology that summarizes properties of the entire connectome.

Methods: We performed fc-MVPA on resting-state images of a sample composed of a group of children with DD (n = 19, 8.06 ± 0.87 years) and an age- and sex-matched control group of typically developing children (n = 23, 7.76 ± 0.46 years).

Results: Analysis of fc-MVPA showed significant differences between group connectivity profiles in two clusters allocated in both the right and left medial temporal gyrus. Post hoc effect size results revealed a decreased rs-FC between each temporal pole and the DMN in children with DD and an increased rs-FC between each temporal pole and the sensorimotor network.

Conclusions: Our results suggest an aberrant information flow between resting-state networks in children with DD, demonstrating the importance of these networks for arithmetic development.

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来源期刊
Journal of Neuroimaging
Journal of Neuroimaging 医学-核医学
CiteScore
4.70
自引率
0.00%
发文量
117
审稿时长
6-12 weeks
期刊介绍: Start reading the Journal of Neuroimaging to learn the latest neurological imaging techniques. The peer-reviewed research is written in a practical clinical context, giving you the information you need on: MRI CT Carotid Ultrasound and TCD SPECT PET Endovascular Surgical Neuroradiology Functional MRI Xenon CT and other new and upcoming neuroscientific modalities.The Journal of Neuroimaging addresses the full spectrum of human nervous system disease, including stroke, neoplasia, degenerating and demyelinating disease, epilepsy, tumors, lesions, infectious disease, cerebral vascular arterial diseases, toxic-metabolic disease, psychoses, dementias, heredo-familial disease, and trauma.Offering original research, review articles, case reports, neuroimaging CPCs, and evaluations of instruments and technology relevant to the nervous system, the Journal of Neuroimaging focuses on useful clinical developments and applications, tested techniques and interpretations, patient care, diagnostics, and therapeutics. Start reading today!
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