Brain Imaging Research Center, University of Arkansas for Medical Sciences, 4301 W. Markham St., Little Rock, AR, 72205-7199, USA.
College of Medicine, University of Arkansas for Medical Sciences, 4301 W. Markham St., Little Rock, AR, 72205-7199, USA.
Sci Rep. 2018 Oct 18;8(1):15444. doi: 10.1038/s41598-018-33621-6.
Multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data has critically advanced the neuroanatomical understanding of affect processing in the human brain. Central to these advancements is the brain state, a temporally-succinct fMRI-derived pattern of neural activation, which serves as a processing unit. Establishing the brain state's central role in affect processing, however, requires that it predicts multiple independent measures of affect. We employed MVPA-based regression to predict the valence and arousal properties of visual stimuli sampled from the International Affective Picture System (IAPS) along with the corollary skin conductance response (SCR) for demographically diverse healthy human participants (n = 19). We found that brain states significantly predicted the normative valence and arousal scores of the stimuli as well as the attendant individual SCRs. In contrast, SCRs significantly predicted arousal only. The prediction effect size of the brain state was more than three times greater than that of SCR. Moreover, neuroanatomical analysis of the regression parameters found remarkable agreement with regions long-established by fMRI univariate analyses in the emotion processing literature. Finally, geometric analysis of these parameters also found that the neuroanatomical encodings of valence and arousal are orthogonal as originally posited by the circumplex model of dimensional emotion.
功能磁共振成像(fMRI)数据的多元模式分析(MVPA)极大地促进了人类大脑情感处理的神经解剖学理解。这些进展的核心是大脑状态,这是一种短暂的 fMRI 衍生的神经活动模式,作为一个处理单元。然而,要确立大脑状态在情感处理中的核心作用,就需要它能够预测多种独立的情感测量。我们采用基于 MVPA 的回归分析,对来自国际情感图片系统(IAPS)的视觉刺激的效价和唤醒特性进行预测,同时对人口统计学上多样化的健康人类参与者的伴随皮肤电反应(SCR)进行预测(n=19)。我们发现,大脑状态可以显著预测刺激的规范效价和唤醒评分,以及伴随的个体 SCR。相比之下,SCR 仅显著预测唤醒。大脑状态的预测效果大小是 SCR 的三倍多。此外,回归参数的神经解剖学分析与 fMRI 单变量分析情感处理文献中确立的区域具有显著的一致性。最后,这些参数的几何分析还发现,效价和唤醒的神经解剖编码是正交的,正如维度情感的环面模型最初提出的那样。