Porj 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，在 Press）。极端的情绪并不是这些效果所必需的：即使是温和的积极情绪或 情绪低落对人们处理信息的方式有明显的影响。我们已经论证 这些影响的机制取决于区域大脑活动的情绪依赖性变化， 增强或削弱表现，这取决于特定的大脑区域在大脑中所扮演的角色。 执行一项任务。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，也没有对大脑活动的评估 涉案目前的项目位于美国。伊利诺斯州，将研究情绪的状态和特质贡献， 执行功能，有两个具体目标。首先，状态情绪对大脑活动的影响将是 通过在颜色词Stroop任务中诱导情绪测量fMRI来评估。我们的大脑区域模型 情绪处理过程中的活动将与Banich的注意力控制级联模型相结合。在 此外，我们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成分（抑制，转移， 更新）。神经影像学研究结果表明，有共同的和不同的神经网络参与 跨域（Collette等人，2005年）。这些神经网络中的活动与我们的 情绪体验和调节的模型。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相关。目标2的重点是 通过选择情感维度得分高的被试，检验特质情绪对执行功能的影响。 我们已经证明，这些维度与功能性磁共振成像测量的大脑活动的不同模式有关 的ERP。了解状态和特质的影响方式可能会影响认知过程， 大脑活动的相关模式将提供对常见日常经历的洞察， 情绪/认知相互作用与个性特征的个体差异相关， 当前或未来的抑郁发作。

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.