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Abstract: This dissertation is comprised of three related, but distinct projects. Chapters 1 and 2 explore the processing of emotional stimuli and how emotional properties of stimuli interact with context, goals, schemas, and basic cognitive processes. Chapter 1 presents a functional MRI study showing that self-related processing in the medial prefrontal cortex (a brain region long associated with... read morethe self) is modulated by the emotional valence of social scenarios. Specifically, self-relevance only increased activation in this region for positive scenarios, suggesting the mPFC may be sensitive to self-positivity biases and may even play a role in maintaining these biases. Chapter 2 reviews the late positive potential of the ERP commonly observed to emotional stimuli, proposes a functional theory of this component, and presents an initial study testing this theory. Chapter 3 is a methodological chapter exploring issues in the statistical analysis of ERP data, particularly the problem of multiple comparisons presented by the large amount of data across time and space. I present new software to implement permutation-based mass univariate statistics for factorial designs, and simulation data on the relative power and flexibility of these statistical tests.
Thesis (Ph.D.)--Tufts University, 2017.
Submitted to the Dept. of Psychology.
Advisor: Gina Kuperberg.
Committee: Phillip Holcomb, Elizabeth Race, and Jonathan Freeman.
Keywords: Neurosciences, Cognitive psychology, and Social psychology.read less
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