Use this URL to cite or link to this record in EThOS:
Title: Integrating information into beliefs : good and bad news
Author: Garrett, N. J.
ISNI:       0000 0004 8498 2741
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
When integrating new information into our beliefs, an important factor is valence: whether a piece of news is good or bad. Evidence suggests that for self-relevant beliefs, separate rules and mechanisms underlie integration of these different types of news with good news being integrated to a greater degree than bad news. This asymmetry results in a positive bias. In this thesis, I present 4 studies that explore the boundaries of this asymmetry. In study 1, I explore how the asymmetry is altered in clinical depression. I show that depressed patients update beliefs regarding their future in response to bad news to a greater degree than healthy controls resulting in unbiased updating. fMRI results suggest that this increased capacity to integrate bad news is the result of greater responsiveness in the receipt of undesirable information. These findings suggest that a positive state of mental health is linked to biased processing of information that supports positively skewed views of the future. In study 2, I examine whether the asymmetry varies in response to changes in the environment. Two separate experiments show that information integration in response to bad news (but not good news) is enhanced in threatening environments. These findings suggest that biased processing of information is not set in stone, but flexibly changes in response to the environment. In study 3, I adapt the update bias paradigm to investigate if a positive update bias exists under an alternative method of classifying good and bad news. A positive update bias remains under this alternative classification. In addition, under both the original and this alternative method of classification, updating is shown to correspond more closely to a rational Bayesian agent for good compared to bad news. These findings suggest that the update bias is robust to variations in classification schemes and analysis. In study 4, I explore whether an asymmetry in updating exists for positive as well as for negative lifeevents. I show that participants update their beliefs to a greater extent when receiving good news compared to bad news, regardless of whether the information concerns a positive or a negative life event. These findings suggest that the bias is not a phenomenon specific to negative life events and is robust to variations in task stimuli. Taken together with the findings of study 3, the results make a strong case for a true optimistic asymmetry in belief updating. The four studies presented in this thesis expand our knowledge of how individuals integrate information about the world, characterize the boundaries of asymmetric information integration, examine the neural mechanisms that support it and its responsiveness to environmental threat.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available