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

点击翻译按钮获取中文摘要

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.