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

在执行功能的任务中，积极情绪改善了，但抑郁损害了执行功能的表现(Levin等人，in 按下)。这些效果并不需要极端的情绪：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。我们已经争论过了 这些效应的机制依赖于情绪依赖的局部大脑活动的变化 提高或削弱表现，取决于特定的大脑区域在 任务的执行。然而，到目前为止，还没有对《公约》的影响进行系统评估。 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 牵涉其中。这项位于美国伊利诺伊州大学的研究项目将考察情绪对情绪状态和特质的影响。 执行职能，并有两个具体目标。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功能磁共振进行评估。我们的区域脑模型 情绪处理过程中的活动将与巴尼奇的注意力控制级联模型相结合。在……里面 此外，我们还将检查模拟情绪状态对 项目1.第二个目标是将我们针对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、转移和 更新)。神经成像结果表明，有共同的和不同的神经网络参与其中。 跨域(Collette等人，2005年)。这些神经网络中的活动被认为与我们的 情绪体验和调节的模型。这些数据表明，不同的情绪可能 与明显的执行功能受损或增强模式有关。目标2的重点是 通过选择情绪得分较高的人来考察特质情绪对执行功能的影响 我们已经证明的维度与fMRI测量的大脑活动的不同模式有关 和事件相关电位。了解状态和特质影响的方式可能会影响认知过程和 大脑活动的相关模式将提供对常见日常体验的洞察以及 情绪/认知交互作用与个性特征的个体差异可能相关 到目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.