The Neural Coding of Loss Público
Brooks, Andrew Michael (2012)
Published
Abstract
After decades of research, we know that the mesolimbic dopamine pathway is heavily involved in nearly all aspects of financial decision-making. Its role has been defined by its involvement in reward-related learning as it relates to monetary gains. There is little evidence implicating it in aversive or loss-related learning. This dissertation was designed to advance our understanding of this systems involvement in aversive and loss related decision making. To do this, we use functional magnetic resonance imaging while human participants engage in experimental economic tasks that deal with financial decisions over gains and losses. We show that, 1) during decision-making, the ventral striatum tracks the expected values of gambles that are entirely aversive, 2) heterogeneity in loss-holding behavior in the stock market can be explained via activity within the ventral striatum, and 3) the ventral striatal processes earnings announcements which lead to financial loss, and are correlated with subsequent changes in stock price. We find that the BOLD response in the ventral striatum to loss outcomes in all three of our experiments fit with the prediction error hypothesis of dopamine activity. Finally, we discuss future research in financial loss, and its implications for sub-optimal behavior, such as gambling addiction.
Table of Contents
Chapter 1
Introduction. 1
Goals of the Research Project 1
Background. 2
The Mesolimbic Dopamine System.. 2
Reward Prediction Error. 4
Functional Magnetic Resonance Imaging. 8
Gains and Losses in the Brain. 15
Experiment Overview.. 19
Figures and Tables. 22
Chapter 2
Introduction. 24
Materials and Methods. 26
Participants. 26
Experimental Procedures. 26
fMRI Measurements. 29
fMRI Analysis. 29
Results. 31
Behavioral 31
fMRI. 33
Discussion. 35
Conflict of Interest Statement 39
Acknowledgments. 39
Figures and References. 40
Chapter 3
Introduction. 47
Materials and Methods. 49
Asset trading task. 50
Behavioral data analysis. 52
fMRI data acquisition and analysis. 53
Results. 55
Imaging. 58
Discussion. 60
Acknowledgments. 65
Figures and Tables. 66
Supplementary Material 73
Chapter 4
Introduction. 81
Materials and Methods. 83
Participants. 83
Forecasting Task. 84
Firm Selection. 85
fMRI data acquisition and analysis. 86
Results. 88
Discussion. 90
Figures and Tables. 94
Chapter 5
Summary of Findings. 100
Significance. 103
Basic Knowledge. 103
Clinical Relevance. 104
Applications. 105
Cellular Speculation. 106
Future Directions. 108
Final Words. 110
References
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