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相关概念视频

Autism Spectrum Disorder01:19

Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.

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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
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粗融合:基于图形粗化的多图表功能连接融合用于自闭症谱系障碍诊断

Ekta Srivastava, Siddhant Ujjain, Tapan Kumar Gandhi

    IEEE journal of biomedical and health informatics
    |December 19, 2025
    PubMed
    概括

    使用静止状态fMRI诊断自闭症谱系障碍 (ASD) 的新框架CoarseFuse通过融合多图谱数据来提高准确性和可解释性. 这种方法提高了诊断性能,并提供了透明的网络洞察力.

    科学领域:

    • 神经成像是一种神经成像.
    • 计算神经科学是一种神经科学.
    • 生物医学工程 生物医学工程

    背景情况:

    • 自闭症谱系障碍 (ASD) 影响人口的1-2%,但缺乏可靠的成像生物标志物.
    • 休息状态fMRI (rs-fMRI) 绘制了大脑连接,但单个地图分析有局限性.
    • 现有的融合方法往往会为了复杂性而牺牲解释性.

    研究的目的:

    • 开发一个名为CoarseFuse的专题特定的,图形硬化多地图融合框架.
    • 提高RS-fMRI分析对ASD诊断的准确性和可解释性.
    • 创建低维的伪图书馆,保持ROI级别的可解释性.

    主要方法:

    • CoarseFuse从多个分片中构建一个统一的超图,使用跨地图谱的亲和关系.
    • 它采用封闭形式,相关联信息的拉普拉斯精细化与投影.
    • 具有特征意识的局部变化粗化 (LVN) 产生可解释的,低维的伪图表.

    主要成果:

    • 在ABIDE I数据集上,CoarseFuse实现了82.1%的平衡精度和82.0%的F1得分,超过了基线融合方法.
    • LVN 减少了大约 73% 的维度,从 450 个节点减少到 120 个节点.

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  • 一个离开一个站点的评估证实了对扫描仪和协议变化的稳定性,宏观BA为79.2%,宏观F1为80.1%.

    • 结论:

    • CoarseFuse为基于rs-fMRI的ASD诊断提供了一个准确,可扩展和可解释的方法.
    • 该框架的学习超级节点与正规的静态网络保持一致,支持生物解释性.
    • 本研究介绍了首个针对多图谱rs-fMRI融合的封闭形式拉普拉斯更新,从而提升了诊断能力.