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基于连接组学的指纹识别:可重复性、精确性和行为预测。

Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction.

机构信息

Department of Psychology, Yale University, New Haven, CT, USA.

Kavli Institute for Neuroscience, Yale University, New Haven, CT, USA.

出版信息

Neuropsychopharmacology. 2024 Nov;50(1):114-123. doi: 10.1038/s41386-024-01962-8. Epub 2024 Aug 15.

Abstract

Functional magnetic resonance imaging-based functional connectivity enables the non-invasive mapping of individual differences in brain functional organization to individual differences in a vast array of behavioral phenotypes. This flexibility has renewed the search for neuroimaging-based biomarkers that exhibit reproducibility, prediction, and precision. Functional connectivity-based measures that share these three characteristics are key to achieving this goal. Here, we review the functional connectome fingerprinting approach and discuss its value, not only as a simple and intuitive conceptualization of the "functional connectome" that provides new insights into how the connectome is altered in association with psychiatric symptoms, but also as a straightforward and interpretable method for indexing the reproducibility of functional connectivity-based measures. We discuss how these advantages provide new avenues for strengthening reproducibility, precision, and behavioral prediction for functional connectomics and we consider new directions toward discovering better biomarkers for neuropsychiatric conditions.

摘要

基于功能磁共振成像的功能连接使我们能够无创地将大脑功能组织的个体差异映射到广泛的行为表型的个体差异上。这种灵活性激发了对具有可重复性、可预测性和精确性的基于神经影像学的生物标志物的新探索。具有这三个特征的基于功能连接的测量是实现这一目标的关键。在这里,我们回顾了功能连接指纹识别方法,并讨论了它的价值,不仅作为“功能连接组”的一种简单直观的概念化,提供了关于连接组如何与精神症状相关的改变的新见解,而且作为一种直接和可解释的方法,用于索引基于功能连接的测量的可重复性。我们讨论了这些优势如何为功能连接组学的可重复性、精确性和行为预测提供新的途径,并考虑了发现神经精神疾病更好的生物标志物的新方向。

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