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多模态神经认知标志物可对自然话语类型进行神经退行性疾病分类。

Multimodal Neurocognitive Markers of Naturalistic Discourse Typify Diverse Neurodegenerative Diseases.

机构信息

Centro de Neurociencias Cognitivas, Universidad de San Andrés, B1644BID Buenos Aires, Argentina.

National Scientific and Technical Research Council (CONICET), C1425FQD Buenos Aires, Argentina.

出版信息

Cereb Cortex. 2022 Aug 3;32(16):3377-3391. doi: 10.1093/cercor/bhab421.

DOI:10.1093/cercor/bhab421
PMID:34875690
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9376869/
Abstract

Neurodegeneration has multiscalar impacts, including behavioral, neuroanatomical, and neurofunctional disruptions. Can disease-differential alterations be captured across such dimensions using naturalistic stimuli? To address this question, we assessed comprehension of four naturalistic stories, highlighting action, nonaction, social, and nonsocial events, in Parkinson's disease (PD) and behavioral variant frontotemporal dementia (bvFTD) relative to Alzheimer's disease patients and healthy controls. Text-specific correlates were evaluated via voxel-based morphometry, spatial (fMRI), and temporal (hd-EEG) functional connectivity. PD patients presented action-text deficits related to the volume of action-observation regions, connectivity across motor-related and multimodal-semantic hubs, and frontal hd-EEG hypoconnectivity. BvFTD patients exhibited social-text deficits, associated with atrophy and spatial connectivity patterns along social-network hubs, alongside right frontotemporal hd-EEG hypoconnectivity. Alzheimer's disease patients showed impairments in all stories, widespread atrophy and spatial connectivity patterns, and heightened occipitotemporal hd-EEG connectivity. Our framework revealed disease-specific signatures across behavioral, neuroanatomical, and neurofunctional dimensions, highlighting the sensitivity and specificity of a single naturalistic task. This investigation opens a translational agenda combining ecological approaches and multimodal cognitive neuroscience for the study of neurodegeneration.

摘要

神经退行性变具有多尺度的影响,包括行为、神经解剖和神经功能的紊乱。是否可以使用自然刺激在这些维度上捕捉到疾病特异性的改变?为了解决这个问题,我们评估了帕金森病(PD)和行为变异额颞叶痴呆(bvFTD)患者相对于阿尔茨海默病患者和健康对照组对四个自然故事的理解,这些故事突出了动作、非动作、社会和非社会事件。通过基于体素的形态测量学、空间(fMRI)和时间(hd-EEG)功能连接来评估与文本特异性相关的指标。PD 患者表现出与动作观察区域体积、运动相关和多模态语义中枢之间的连接以及额叶 hd-EEG 低连接性相关的动作文本缺陷。bvFTD 患者表现出与社会网络中枢的萎缩和空间连接模式以及右额颞叶 hd-EEG 低连接性相关的社会文本缺陷。阿尔茨海默病患者在所有故事中都表现出损伤,广泛的萎缩和空间连接模式,以及枕颞叶 hd-EEG 连接性增加。我们的框架揭示了行为、神经解剖和神经功能维度上的疾病特异性特征,突出了单个自然任务的敏感性和特异性。这项研究为神经退行性变的研究开辟了一个结合生态方法和多模态认知神经科学的转化议程。

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Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases.跨神经退行性疾病的人类社会强化学习的多模态机制。
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