(The) role of emotional stimuli in learning and decision making

Abstract

Understanding the role of emotion in human rationality is a prerequisite for an understanding of process of human cognition. If emotion is included in the experimental task of setting up an uncertain environment in which learning and decision making takes place, an individual’s assimilated emotion will affect the intrinsic generative model of signification. And the difference in each individual’s learning and decision making can be measured and evaluated by a behavioural task and computational modelling. In general, people then appropriately respond to emotional situations in order to avoid excessive stress. Based on this sequential process, my research attempted to further explore the effects of emotion in incremental learning and one-shot learning as well as the individual's cognitive control ability on emotional stimulation.

First, the hierarchical Gaussian filter, which is a Bayesian generative model and known to best reflect individual differences in learning and decision making was added an emotional noise parameter, and this modified model appropriately explains behavioural data of probabilistic association learning with emotional noise. Through this experiment and computational modelling, I identified that subjects with a higher emotional noise parameter in generative model and higher neural responses to emotional faces change their minds more frequently when making decisions in a volatile environment with emotional noise. Next, in the analysis of behaviour data of the one-shot learning task in subliminal affective priming, the betting results for additional rewards in subliminal sad face conditions were considerably more biased than in subliminal neutral face conditions. Furthermore, through a probabilistic association learning and psychiatric questionnaire, I explained the function that cognitively controls the emotional effect on the stress situation by the history of emotional abuse in early childhood and the present Bayesian model parameter, which reflects the degree of the external stimuli updated into the model.

In summary, I sought to clarify the effects of emotion on human cognitive processes mainly through computational modelling and emotion related experiments under an uncertain environment. Experimental results showed us that emotion interfered with the learning and decision making process, and the function of controlling emotional effects in stressful situations could be properly explained. Current findings can provide a clue to realistically understanding the cognitive process in situations where uncertainty and emotional stimuli is implicated, such as our daily life.