The Neural Coding of Loss 公开

Brooks, Andrew Michael (2012)

Permanent URL:


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


About this Dissertation

Rights statement
  • Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.
Subfield / Discipline
  • English
Research field
Committee Chair / Thesis Advisor
Committee Members

Primary PDF

Supplemental Files