State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute of Brain Research, Beijing Normal University, Beijing 100875, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875, PR China.
Department of Psychology and Social Behavior, University of California, Irvine 92697, United States.
Neuroimage. 2016 Jul 1;134:540-549. doi: 10.1016/j.neuroimage.2016.04.010. Epub 2016 Apr 12.
There is a growing consensus that impulsivity is a multifaceted construct that comprises several components such as impulsive choice and impulsive action. Although impulsive choice and impulsive action have been shown to be the common characteristics of some impulsivity-related psychiatric disorders, surprisingly few studies have directly compared their neural correlates and addressed the question whether they involve common or distinct neural correlates. We addressed this important empirical gap using an individual differences approach that could characterize the functional relevance of neural networks in behaviors. A large sample (n=227) of college students was tested with the delay discounting and stop-signal tasks, and their performances were correlated with the neuroanatomical (gray matter volume, GMV) and functional (resting-state functional connectivity, RSFC) measures, using multivariate pattern analysis (MVPA) and 10-fold cross-validation. Behavioral results showed no significant correlation between impulsive choice measured by discounting rate (k) and impulsive action measured by stop signal reaction time (SSRT). The GMVs in the right frontal pole (FP) and left middle frontal gyrus (MFG) were predictive of k, but not SSRT. In contrast, the GMVs in the right inferior frontal gyrus (IFG), supplementary motor area (SMA), and anterior cingulate cortex (ACC) could predict individuals' SSRT, but not k. RSFC analysis using the FP and right IFG as seed regions revealed two distinct networks that correspond well to the "waiting" and "stopping" systems, respectively. Furthermore, the RSFC between the FP and ventromedial prefrontal cortex (VMPFC) was predictive of k, whereas the RSFC between the IFG and pre-SMA was predictive of SSRT. These results demonstrate clearly neural dissociations between impulsive choice and impulsive action, provide new insights into the nature of impulsivity, and have implications for impulsivity-related disorders.
人们越来越认为，冲动是一个多方面的结构，包括冲动选择和冲动行为等几个组成部分。虽然冲动选择和冲动行为已被证明是一些与冲动相关的精神障碍的共同特征，但令人惊讶的是，很少有研究直接比较它们的神经相关性，并解决它们是否涉及共同或不同的神经相关性的问题。我们使用个体差异方法解决了这一重要的经验差距，该方法可以描述神经网络在行为中的功能相关性。通过多元模式分析 (MVPA) 和 10 倍交叉验证，对 227 名大学生进行了延迟折扣和停止信号任务测试，并将他们的表现与神经解剖学（灰质体积，GMV）和功能（静息态功能连接，RSFC）测量值相关联。行为结果表明，冲动选择的测量值（折扣率 k）与冲动行为的测量值（停止信号反应时间 SSRT）之间没有显著相关性。右侧额极（FP）和左侧额中回（MFG）的 GMV 可以预测 k，但不能预测 SSRT。相反，右侧额下回（IFG）、辅助运动区（SMA）和前扣带皮层（ACC）的 GMV 可以预测个体的 SSRT，但不能预测 k。使用 FP 和右侧 IFG 作为种子区域的 RSFC 分析揭示了两个截然不同的网络，分别对应于“等待”和“停止”系统。此外，FP 与腹内侧前额叶皮层（VMPFC）之间的 RSFC 可以预测 k，而 IFG 与前 SMA 之间的 RSFC 可以预测 SSRT。这些结果清楚地表明冲动选择和冲动行为之间存在神经分离，为冲动的本质提供了新的见解，并对与冲动相关的障碍具有启示意义。
