M.S. (Master of Science)
Department of Mechanical Engineering
Emotions are an integral part of human expression and are often communicated nonverbally through behavioral actions. With advancements in electroencephalography (EEG) technology it is now possible to measure the dynamics of emotion generation in an individual on the basis of patterns in their brain activity. This thesis aims to model the temporal dynamics of human emotion generation upon exposure to aversive stimuli and measure the effect of external distractions as a viable emotion regulation strategy.
This research builds on previous work in the literature that has shown that the ability of humans to regulate their emotions intrinsically (based on their own interpretation of the situation) is captured within their EEG response through significant differences in event related potentials (ERP). Here, we conduct behavioral experiments to investigate if emotion regulation can be achieved through the use of extrinsic stimuli. Subjects in our experiments were exposed to aversive images as their EEG and video data were recorded. In test conditions, an image that would induce positive feelings was introduced at a random location in the inset after a delay of 1 second. Our findings reproduce an existing result that the average ERP response to an aversive image is significantly different than to a neutral image with a consumer grade EEG headset thus establishing the robustness of the ERP response. Importantly, we show that the post-distraction average ERP response shows a significant difference from that where no such distraction was placed. Finally, as a first attempt to build a dynamical model of the ERP response we fit individual ERP time series measured in response to aversive images to a linear dynamical system subject to a step input. We investigate the variability in the coefficients of the resulting dynamical systems representation.
Results from this thesis pave the way for further research on engineering design strategies for emotion regulation in the real world that can be used to contain the spread of fear contagion through large groups. The modeling framework provides the basis for a data-driven dynamical interpretation of the ERP response to visual stimuli.
Kempel, Joseph Lawence, "Temporal Dynamics of Human Emotional Response to Aversive Stimuli" (2019). Graduate Research Theses & Dissertations. 7248.
Northern Illinois University
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