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Neural Mechanisms of Aversive Prediction Errors:

Thesis advisor: Michael McDannald / Uncertainty is a pervasive facet of life, and responding appropriately and proportionally to uncertain threats is critical for adaptive behavior. Aversive prediction errors are signals that allow for appropriate fear responses, especially in the face of uncertainty, and provide a critical updating mechanism to adapt to change. Positive prediction errors (+PE) are generated when an actual outcome of an event is worse than the predicted outcome and increase fear upon future encounters with the related predictive cue. Negative prediction errors (-PE) are generated when the predicted outcome is worse than the actual outcome and decrease fear upon future encounters with the related predictive cue. While some regions have been offered as the neural source of positive and negative prediction errors, no causal evidence has been able to identify their sources of generation. The objective of this dissertation was to causally identify the neural basis of aversive prediction error signaling. Using precise neural manipulations paired with a robust behavioral fear discrimination task, I present causal evidence for vlPAG generation of +PEs and for a ventrolateral periaqueductal grey (vlPAG) to medial central amygdala (CeM) pathway to carry out +PE fear updating. Further, I demonstrate that while dorsal raphe serotonergic neurons are not the source of -PE generation, they appear to receive and utilize this signal. Understanding the neural network responsible for aversive prediction error signaling will not only inform understanding of the neurological basis of fear but also may provide insights into disorders, such as PTSD and anxiety disorders, that are characterized by excessive/inappropriate fear responses. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Psychology.

Identiferoai:union.ndltd.org:BOSTON/oai:dlib.bc.edu:bc-ir_109027
Date January 2020
CreatorsWalker, Rachel Ann
PublisherBoston College
Source SetsBoston College
LanguageEnglish
Detected LanguageEnglish
TypeText, thesis
Formatelectronic, application/pdf
RightsCopyright is held by the author. This work is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0).

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