Citation
Qi, Song (2020) Decision Making Under Threat: An Ecological Framework. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/p7j5-bw96. https://resolver.caltech.edu/CaltechTHESIS:04242020-001419374
Abstract
Humans, like other animals, have evolved a set of neural circuits whose primary function is survival. In the case of predation, these circuits include "reactive fear" circuits involved in fast escape decisions, and "cognitive fear" circuits that are involved in more complex processing associated with slow strategic escape. In the context of flight initiation distance (FID), using neuroimaging combined with computational modeling, we support this differentiation of fear circuits by showing that fast escape decisions are elicited by the periaqueductal gray and midcingulate cortex, regions involved in reactive flight. Conversely, slower escape decisions rely on the hippocampus, posterior cingulate cortex, and prefrontal cortex, a circuit implicated in behavioral flexibility. We further tested whether individual differences in trait anxiety would impact escape behavior and neural responses to slow and fast attacking predators. Behaviorally, we found that trait anxiety was not related to escape decisions for fast threats, but individuals with higher trait anxiety escaped earlier during slow threats. Functional MRI showed that when subjects faced slow threats, trait anxiety positively correlated with activity in the vHPC, mPFC, amygdala and insula. Further, the strength of the functional coupling between the vHPC and mPFC was correlated with the degree of trait anxiety. A similar pattern of separation in survival circuits is also found in a follow up study utilizing the concept of margin of safety (MOS) with multivariate pattern analysis of fMRI data. In addition, we also discussed how decision making under threat was influenced by social factors such as reputation. Overall, these results provide new insights into decision making under threat and a separation of fear into reactive and cognitive circuits.
Item Type: | Thesis (Dissertation (Ph.D.)) | ||||||||||||
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Subject Keywords: | Psychology, Neuroscience | ||||||||||||
Degree Grantor: | California Institute of Technology | ||||||||||||
Division: | Humanities and Social Sciences | ||||||||||||
Major Option: | Social and Decision Neuroscience | ||||||||||||
Thesis Availability: | Public (worldwide access) | ||||||||||||
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Defense Date: | 16 May 2019 | ||||||||||||
Non-Caltech Author Email: | songqi.uest (AT) gmail.com | ||||||||||||
Record Number: | CaltechTHESIS:04242020-001419374 | ||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechTHESIS:04242020-001419374 | ||||||||||||
DOI: | 10.7907/p7j5-bw96 | ||||||||||||
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Default Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||
ID Code: | 13682 | ||||||||||||
Collection: | CaltechTHESIS | ||||||||||||
Deposited By: | Song Qi | ||||||||||||
Deposited On: | 27 Apr 2020 22:45 | ||||||||||||
Last Modified: | 08 May 2020 16:08 |
Thesis Files
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