自闭症梭状回内面部加工的多模态神经特征

Dorothea L. Floris, Alberto Llera, Mariam Zabihi, Carolin Moessnang, Emily J. H. Jones, Luke Mason, Rianne Haartsen, Nathalie E. Holz, Ting Mei, Camille Elleaume, Bruno Hebling Vieira, Charlotte M. Pretzsch, Natalie J. Forde, Sarah Baumeister, Flavio Dell’Acqua, Sarah Durston, Tobias Banaschewski, Christine Ecker, Rosemary J. Holt, Simon Baron-Cohen, Thomas Bourgeron, Tony Charman, Eva Loth, Declan G. M. Murphy, Jan K. Buitelaar, Christian F. Beckmann, the EU–AIMS LEAP group, Nicolas Langer
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引用次数: 0

摘要

非典型面部处理通常在自闭症中被报道。其神经相关性已经在面部处理网络的关键区域,如梭状回(FFG)中通过单一神经成像模式进行了广泛的探索。尽管如此,人们对大脑解剖结构和功能的变化如何共同影响面部处理和社会功能知之甚少。本研究利用大型多模态样本,通过四种成像模式(结构磁共振成像(MRI)、静息状态功能磁共振成像、任务功能磁共振成像和脑电图)研究了204名7-30岁自闭症和非自闭症个体的FFG面部处理的跨模态特征(病例对照设计)。我们结合了两种方法上的创新——规范建模和关联的独立成分分析——来整合跨模式的个体水平偏差,并评估多模式成分如何区分自闭症群体和告知社会功能。在面部选择和视网膜定位FFG中,各组在由双侧静息状态功能MRI、双侧结构、右侧任务功能MRI和左侧脑电图负荷驱动的多模态成分上存在显著差异。在不同的群体中,多模态组件的表现优于单模态组件。在自闭症个体中,多模态成分与认知和临床特征有关,这些特征与社会功能有关,但与非社会功能无关。这些发现强调了阐明自闭症社会功能的多模态神经关联的重要性,为识别机制和预后生物标志物提供了潜力。作者利用大量的多模态样本,结合规范建模和关联独立成分分析来研究自闭症梭状回内面部处理的跨模态特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A multimodal neural signature of face processing in autism within the fusiform gyrus

A multimodal neural signature of face processing in autism within the fusiform gyrus
Atypical face processing is commonly reported in autism. Its neural correlates have been explored extensively across single neuroimaging modalities within key regions of the face processing network, such as the fusiform gyrus (FFG). Nonetheless, it is poorly understood how variation in brain anatomy and function jointly impacts face processing and social functioning. Here we leveraged a large multimodal sample to study the cross-modal signature of face processing within the FFG across four imaging modalities (structural magnetic resonance imaging (MRI), resting-state functional magnetic resonance imaging, task-functional magnetic resonance imaging and electroencephalography) in 204 autistic and nonautistic individuals aged 7–30 years (case–control design). We combined two methodological innovations—normative modeling and linked independent component analysis—to integrate individual-level deviations across modalities and assessed how multimodal components differentiated groups and informed social functioning in autism. Groups differed significantly in a multimodal component driven by bilateral resting-state functional MRI, bilateral structure, right task-functional MRI and left electroencephalography loadings in face-selective and retinotopic FFG. Multimodal components outperformed unimodal ones in differentiating groups. In autistic individuals, multimodal components were associated with cognitive and clinical features linked to social, but not nonsocial, functioning. These findings underscore the importance of elucidating multimodal neural associations of social functioning in autism, offering potential for the identification of mechanistic and prognostic biomarkers. The authors leveraged a large multimodal sample and combined normative modeling and linked independent component analysis to study a cross-modal signature of face processing within the fusiform gyrus in autism.
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