Proj 3: Emotion and Executive fnct. (170-196)

积极情绪改善了执行功能任务的表现，但抑郁症损害了执行功能任务的表现（Levin等人，出版中）。极端的情绪并不是这些效应的必要条件：即使是温和的积极情绪或情绪低落，也会对人们处理信息的方式产生明显的影响。我们认为，这些效应的机制取决于大脑区域活动中的情绪依赖性变化，这些变化会增强或削弱表现，这取决于特定大脑区域在执行任务时所扮演的角色。然而，迄今为止，还没有系统地评估 具体的情绪状态对执行功能的影响，也没有对所涉及的大脑活动进行评估。目前的项目，在美国的基础上。伊利诺伊州，将检查情绪的状态和特质对执行功能的贡献，并有两个具体的目标。在第一，状态情绪对大脑活动的影响将评估诱导情绪测量功能磁共振成像过程中的颜色词Stroop任务。我们在情绪处理过程中的区域大脑活动模型将与Banich的注意力控制级联模型相结合。此外，我们还将研究模拟情绪状态对计算模型的影响， 项目1。第二个目标是将我们的不同情绪的大脑组织模型与美国的大脑组织模型相结合。 科罗拉多同事的模型描绘了执行功能的子组件（抑制，转移和更新）。神经影像学发现表明，跨域涉及共同和不同的神经网络（Collette等人，2005年）。这些神经网络的活动也与我们的情绪体验和调节模型有关。这些数据表明，不同的情绪可能与执行功能受损或增强的不同模式有关。目标2的重点是通过选择在情感维度上得分高的人来研究特质情绪对执行功能的影响，我们已经证明这些情感维度与fMRI和ERPs测量的不同大脑活动模式相关。了解状态和特质影响的方式可能会影响认知过程和相关的大脑活动模式，这将有助于深入了解常见的日常经历以及与人格特质个体差异相关的情感/认知相互作用，这些人格特质可能与当前或未来的抑郁发作有关。

Positive affect improves, but depression impairs, performance on tasks of executive function (Levin et al., in press). Extreme emotions are not necessary for these effects: even mild conditions of positive affect or feeling down have observable influences on the way in which people process information. We have argued that the mechanism of these effects depends on emotion-dependent changes in regional brain activity that either enhance or impair performance, depending on the role that a particular brain region plays in the implementation of a task. To date, however, there has been no systematic evaluation of the impact of specific emotional states on executive function, nor has there been an assessment of the brain activity involved. The present project, based at U. Illinois, will examine both state and trait contributions of emotion to executive function and has two specific aims. In the first, the effects of state emotion on brain activity will be assessed by inducing mood measuring fMRI during the color-word Stroop task. Our model of regional brain activity during emotional processing will be integrated with Banich's cascade model of attentional control. In addition, we will examine the effect of simulated emotional states on the computational model developed in Project 1. The second aim is to integrate our model of brain organization for different emotions with U. Colorado colleagues' model delineating subcomponents of executive function (inhibition, shifting, and updating). Neuroimaging findings suggest that there are both common and distinct neural networks involved across the domains (Collette et al., 2005). Activity in these same neural networks has been implicated in our models of emotional experience and regulation. These data suggest that different emotions may be asssociated with distinct patterns of impaired or enhanced executive function. The focus of Aim 2 is to examine the influence of trait emotion on executive function by selecting people who score high on affective dimensions that we have shown to be associated with distinct patterns of brain activity as measured by fMRI and ERPs. Understanding the ways that both state and trait affect might influence cognitive processes and associated patterns of brain activity will provide insight into common everyday experiences as well as emotion/cognition interactions associated with individual differences in personality traits that might be related to current or future depressive episodes.