Strategic Regulation of Cognitive Control by Emotional Salience: A Neural Network Model

We present a neural network model of stimulus processing, which uses a mechanism of adaptive attentional control to regulate the moment to moment deployment of attention according to both the demands of the current task, and the demands of emotionally salient information. This mechanism allows negative emotional information to reduce cognitive control to aid in the detection of threats, which produces a momentary withdrawal from the current task set to allow unbiased processing of available information. The combination of cognitive and emotional regulation of task set allows this model to address inter-trial aspects of emotional interference in colour naming. In particular, we focus on the nature of the emotional interference in colour naming (McKenna Sharma, 2004) as well as in word reading (Algom, Chajut, Lev, 2004) and show how this form of interference is functionally distinct from the classic Stroop effect. Our model addresses a range of findings in colour naming and word reading tasks and is informed by recent neuroimaging data concerning the interaction between the anterior cingulate and prefrontal cortices. The model is used to explore the interface between cognition and emotion with a series of predictions, including a qualitative distinction between state and trait forms of anxiety.