大脑激活的梯度理论：一种研究亲代大脑的新应用。
Gradient theories of brain activation: A novel application to studying the parental brain.
作者信息
Rutherford Helena J V, Xu Jiansong, Worhunsky Patrick D, Zhang Rubin, Yip Sarah W, Morie Kristen P, Calhoun Vince D, Kim Sohye, Strathearn Lane, Mayes Linda C, Potenza Marc N
机构信息
Child Study Center, Yale University School of Medicine, New Haven, CT 06510, United States.
Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, United States.
出版信息
Curr Behav Neurosci Rep. 2019 Sep;6(3):119-125. doi: 10.1007/s40473-019-00182-5. Epub 2019 Jul 5.
PURPOSE OF REVIEW
Parental brain research primarily employs general-linear-model-based (GLM-based) analyses to assess blood-oxygenation-level-dependent responses to infant auditory and visual cues, reporting common responses in shared cortical and subcortical structures. However, this approach does not reveal intermixed neural substrates related to different sensory modalities. We consider this notion in studying the parental brain.
RECENT FINDINGS
Spatial independent component analysis (sICA) has been used to separate mixed source signals from overlapping functional networks. We explore relative differences between GLM-based analysis and sICA as applied to an fMRI dataset acquired from women while they listened to infant cries or viewed infant sad faces.
SUMMARY
There is growing appreciation for the value of moving beyond GLM-based analyses to consider brain functional organization as continuous, distributive, and overlapping gradients of neural substrates related to different sensory modalities. Preliminary findings suggest sICA can be applied to the study of the parental brain.
综述目的
父母脑研究主要采用基于通用线性模型（GLM）的分析方法，以评估对婴儿听觉和视觉线索的血氧水平依赖反应，报告在共享的皮质和皮质下结构中的共同反应。然而，这种方法无法揭示与不同感觉模态相关的混合神经基质。我们在研究父母脑时考虑了这一概念。
最新发现
空间独立成分分析（sICA）已被用于从重叠的功能网络中分离混合源信号。我们探讨了基于GLM的分析与应用于女性功能性磁共振成像（fMRI）数据集的sICA之间的相对差异，该数据集是在女性听婴儿哭声或观看婴儿悲伤面孔时获取的。
总结
人们越来越认识到，超越基于GLM的分析，将脑功能组织视为与不同感觉模态相关的神经基质的连续、分布和重叠梯度具有重要价值。初步研究结果表明，sICA可应用于父母脑的研究。
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