Neuroeconomics Course

Contents:

• Introduction
• Course requirements
• Class meeting schedule
• Related links
  

Introduction

The study of individual decision making has been a major thrust of microeconomics for most of the last century; however, it has only received significant attention from psychologists in the last few decades. Early behavioral studies provided simple cognitive accounts of preferences between chance gambles, multiattribute consequences or streams of payment over time. More recent studies have explored the role of affect, motivation, and social context in such decisions. The newest, and possibly most exciting, frontier in this research area is the effort to understand the ways in which neural processes mediate decision making behavior. The last few years have seen a tremendous push by neuroscientists and their collaborators to apply modern neuroscience methods (e.g., ERP, fMRI, and animal models) to economic decisions.

In this seminar we will survey research in the new field of neuroeconomics. In so doing we will take rational choice theory as a point of departure and ground our exploration in behavioral decision theory. Our main goal is to ask what behavioral insights can be gleaned by applying the tools of neuroscience to the study of economic behavior.

The course is open to all UCLA Ph.D. students (and other students with permission of the instructors). It will complement courses taught at the Anderson School on behavioral decision theory and courses in the Psychology department on cognitive neuroscience, but we will assume no previous course work on either topic. We will assume only a modest degree of mathematical sophistication and rudimentary knowledge of the basics of neuroscience. Some background in experimental research methods and passing familiarity with elementary concepts in probability, statistics, and microeconomics will be helpful. We hope that this course will be accessible and useful to students in management and social sciences as well as the cognitive and brain sciences.

The course will meet for approximately three hours, once per week, for ten weeks. Each week we will take up a separate topic. The first sessions will provide some introduction into behavioral decision theory and neuroscience. Later sessions will explore the neurophysiology of preference formation, likelihood judgment, risk and uncertainty preferences, intertemporal choice and self-control, and behavior in simple games. For each session we will ask that participants read 4 foundational articles (generally two review papers and two primary experimental papers); in addition, we will provide a list of additional articles from which the students can choose to read 1 or 2 additional papers.

Course Requirements

Other than prepared attendance, we have two requirements for the course:

1) Each week, prepare 2-3 discussion questions for the group. Please e-mail these questions to participants at least 24 hours before the next class session.

2) Write a 6-8 page paper proposing studies for a research project on some topic involving the neurophysiology of judgment and/or decision making. This paper should include a brief introduction motivating the topic and situating it within the relevant research literature, a specific description of experimental methods, a discussion of the planned analysis and expected results, and a brief discussion of the implications of these results.

April 5: Course introduction/Introduction to neuroscience
Guest lecturer: David Jentsch (4-5 pm), Introduction to Neuropharmacology

The goal of this first lecture will be to provide a broad overview of neuroscience concepts and methods. The lecture is primarily aimed at students from Management and others who may not have any background in neuroscience, but it should also serve as a useful refresher for students from Psychology and Neuroscience.  The third hour will include a lecture on neurotransmitter systems by Dr. David Jentsch. 

Lecture slides

Required readings:

• Camerer, Loewenstein & Prelec. Neuroeconomics: How neuroscience can inform economics. Journal of Economic Literature 2005, XLIII, 9-64. (an overall introduction to the field)

• Robbins & Everett.  Chapter 43: Motivation and reward. From L. R. Squire et al. (Eds.), Fundamental Neuroscience, Second Edition.  Academic Press.  (an introduction to neuromodulatory systems - to accompany Dr. Jentsch's lecture)

• Sejnowski & Churchland. Brain and Cognition.  From M. Posner (Ed.), Fundamentals of Cognitive Science.  MIT Press. (an overview of the methods and concepts of cognitive neuroscience, for those students without a background in this area)

• Wikipedia entry for functional MRI

Optional readings:

• Purves et al., Neuroscience (online textbook at PubMed - not easily browsable, but useful for reference)

• Hornak's Basics of MRI Site (an outstanding online introduction to the basics of MRI)
  

• Fellows, LK.  The cognitive neuroscience of human decision making: a review and conceptual framework. Behav Cogn Neurosci Rev. 2004 Sep;3(3):159-72.
  

• Hobson & Pace-Shott.  Chapter 42:  Sleep, dreaming, and wakefulness. From L.R. Squire et al. (Eds.) Fundamental Neuroscience.  Academic Press.  (additional reading on arousal systems for Dr. Jentsch's lecture)
  

April 12: Intro to behavioral decision research

Lecture slides

Required readings:

• Camerer, C.F.. (1995).  Individual decision making.  Chapter in J. Kagel and A.E. Roth (Eds.).  Handbook of Experimental Economics.  (pp. 587-703).  Princeton, NJ: Princeton University Press.
  
• Kahneman, D. (2003).  Perspectives on judgment and choice: Mapping bounded rationality.  American Psychologist, 58, 697-720.
  
• Kahneman, D. & Tversky, A. (1984).  Choices, values, and frames.  American Psychologist, 39, 341-350.
  

Optional readings:

• Camerer, C.F. & Loewenstein, G. (2004).  Behavioral economics: Past, present, and future.  Chapter in C.F. Camerer, G. Loewenstein & M. Rabin (Eds.) Handbook of Behavioral Economics.  New York: Princeton University Press.
• Kaheneman, D. & Tversky, A. (1979).  Prospect theory: An analysis of decision under risk.  Econometrica, 47, 263-292.
  
• Sanfey, A.G., Loewenstein, G., McClure, S.M. & Cohen, J.D. (2006).  Neuroeconomics: Cross-currents in research on decision-making.  TRENDS in Cognitive Sciences, 10, 108-116.
  

• Kahneman, D. & Tversky, A. (2000).  Choices, Values, and Frames.  Cambridge, UK: Cambridge University Press.  (Collection of important readings on behavioral decision making).
  
• Koehler, D. & Harvey, N. (2005).  Handbook of Judgment and Decision Making.  Oxford, UK: Blackwell.  (Collection of recent readings and reviews).
  
• Gilovich, T., Griffin, D. & Kahneman, D. (2002).  Heuristics and Biases: The Psychology of Intuitive Judgment.  New York: Cambridge University Press. (Collection of recent readings on judgmental heuristics).

April 19: Decision making at the single-cell level: The neurophysiology of decisions
Guest discussant: James Bisley

Lecture slides

Required readings:

• Smith & Ratcliff, Psychology and neurobiology of simple decisions.  Trends in Neurosciences, 2004, 27: 161-168. (Review)
  
• Platt & Glimcher, Neural correlates of decision variables in parietal cortex. Nature. 1999 Jul 15;400(6741):233-8.
• Gold & Shadlen, Banburismus and the brain: decoding the relationship between sensory stimuli, decisions, and reward. Neuron. 2002 Oct 10;36(2):299-308. (Review)
  
• Sugrue, Corrado, & Newsome.  Matching behavior and the representation of value in the parietal cortex. Science. 2004 Jun 18;304(5678):1782-7.
  

Optional readings:

• Mazurek et al., A role for neural integrators in perceptual decision making.  Cerebral Cortex.  2003 Nov;13(11):1257-69.
• Sugrue, Corrado, & Newsome, Choosing the greater of two goods: neural currencies for valuation and decision making. Nat Rev Neurosci. 2005 May;6(5):363-75. (Review)
• Shadlen, M.N., T.D. Hanks, A.K. Churchland, R. Kiani, and T. Yang, The speed and accuracy of a simple perceptual decision: a mathematical primer, in Bayesian Brain: Probabilistic Approaches to Neural Coding. , K. Doya, S. Ishii, R. Rao, and A. Pouget, Editors. 2006, MIT Press: Cambridge.   (a mathematically detailed outline of the models discussed in the other papers)
  

• Wu, G., Zhang, J. & Gonzalez, R. (2005).  Decision under risk.  Chapter in D. Koehler & N. Harvey (Eds.), Handbook of Judgment and Decision Making.  Oxford, UK: Blackwell.
• Lowenstein, G.F., Weber, E.U., Hsee, C., & Welch, N. (2001).  Risk as feelings.  Psychological Bulletin, 127, 267-286.

• Bechara & Damasio. The somatic marker hypothesis: A neural theory of economic decision.  Games and Economic Behavior, 52, 336-372. (Review)

• Shiv et al., Investment behavior and the negative side of emotion. Psychol Sci. 2005 Jun;16(6):435-9. (Optional)
  
• Kuhnen & Knutston, The neural basis of financial risk taking. Neuron. 2005 Sep 1;47(5):763-70.
• Rogers et al., Effects of beta-adrenoceptor blockade on components of human decision-making. Psychopharmacology (Berl). 2004 Mar;172(2):157-64.
• Camile, N., Coricelli, G., Sallet, J., Pradat-Diehl, P., Duhamel, J-R, & Sirigu, A. (2004).  Involvement of the orbitofrontal cortex in the experience of regret.  Science, 304, 1167-1170. (Supplement)
  

• Dunn, Dagleish, & Lawrence. The somatic marker hypothesis: A critical evaluation.Neurosci Biobehav Rev. 2006;30(2):239-71.
• Rogers et al., Choosing between small, likely rewards and large, unlikely rewards activates inferior and orbital prefrontal cortex. J Neurosci. 1999 Oct 15;19(20):9029-38.
• Yechiam et al., Using cognitive models to map relations between neuropsychological disorders and human decision-making deficits. Psychol Sci. 2005 Dec;16(12):973-8.
• Fellows & Farah, Different underlying impairments in decision-making following ventromedial and dorsolateral frontal lobe damage in humans. Cereb Cortex. 2005 Jan;15(1):58-63.
• McCoy & Platt.  Risk-sensitive neurons in macaque posterior cingulate cortex.  Nature Neuroscience. 2005. 8, 1220-7.

• Fox, C.R. & See, K.E. (2003).  Belief and preference in decision under uncertainty.  Chapter in D. Hardman & L. Macchi (Eds.).  Thinking: Psychological Perspectives on Reasoning and Decision Making.  New York: Wiley.

• Hsu et al., Neural systems responding to degrees of uncertainty in human decision-making. Science. 2005 Dec 9;310(5754):1680-3.
• Huettel, et al., Neural signatures of economic preferences for risk and ambiguity. Neuron. 2006 Mar 2;49(5):765-75.
• Knutson et al. (2005).  Distributed neural representation of expected value.  The Journal of Neuroscience, 25, 4806-4812.
  

• Parsons, L.M. & Osherson, D. (2001).  New evidence for distinct right and left brain systems for deductive versus probabilistic reasoning.  Cerebral Cortex, 11, 954-965.
• Huettel et al (2005).  Decisions under uncertainty: Probabilistic context influences activation of prefrontal and parietal cortices.  The Journal of Neuroscience, 25, 3304-3311.

• Kahneman, D., Wakker, P.P. & Sarin, R. (1997).  Back to Bentham?  Explorations of Experienced Utility.  Quarterly Journal of Economics, 112, 375-405.
• McClure et al. Neural correlates of behavioral preference for culturally familiar drinks.  Neuron. 2004 Oct 14;44(2):379-87.
• Schultz, W.  Multiple reward signals in the brain. Nat Rev Neurosci. 2000 Dec;1(3):199-207. Review.
• Padoa-Schioppa & Assad, Neurons in the orbitofrontal cortex encode economic value.
  Nature. 2006 Apr 23; [Epub ahead of print]

Optional readings:

• Gehring & Willoughby, The medial frontal cortex and the rapid processing of monetary gains and losses. Science. 2002 Mar 22;295(5563):2279-82.
• Montague, Hyman, & Cohen, Computational roles for dopamine in behavioural control. Nature. 2004 Oct 14;431(7010):760-7. (Review)
• Montague, R.P. & Berns, G.S. (2002).  Neural economics and the biological substrates of valuation.  Neuron, 36, 265-284.
• Tobler, Fiorillo, & Schultz. Adaptive coding of reward value by dopamine neurons. Science. 2005 Mar 11;307(5715):1642-5.
• Glimcher, Dorris, & Bayer.  Physiological utility theory and the neuroeconomics of choice.  2005.  Games & Economic Behavior, 52, 213-256.
• Breiter, H.C., Aharon, I., Kahneman, D., Anders, D. & Shizgal, P. (2001). Functional imaging of neural responses to expectancy and experience of monetary gains and losses.  Neuron, 30, 619-639.
• Bar-Gad, I., Morris, G., & Bergman, H.  (2003).  Information processing, dimensionality reduction and reinforcement learning in the basal ganglia.  Progress in Neurobiology, 71, 439-473.  (A nice review of current models of basal ganglia function)
• Adcock et al. (2006).  Reward-motivated learning:  Mesolimbic activation precedes memory formation.  Neuron, 50, 507-517.
  

May 17: Reward: hedonics, motivation, and habits

Guest discussant: Bernard Balleine

Lecture slides

Required readings:

• Berridge & Robinson, Parsing reward. Trends Neurosci. 2003 Sep;26(9):507-13. (Review)
• Daw & Doya (2006).  The computational neurobiology of learning and reward.  Current Opinion in Neurobiology, 16, 199-204.
• Balleine, B.W. (in press).  Neural basesof food-seeking: Affect, arousal and reward in corticostriatolimbic circuits.  Physiology and Behavior.
  

• Dijksterhuis et al., (2006). On making the right choice: the deliberation-without-attention effect.  Science, 311, 1005-7.
  

Optional readings:

• Erev & Barron (2005).  On adaptation, maximization, and reinforcement learning among cognitive strategies.  Psychological Review.
• Bayer & Glimcher, Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron. 2005 Jul 7;47(1):129-41. 
• Dayan & Balleine, Reward, motivation, and reinforcement learning. Neuron. 2002 Oct 10;36(2):285-98. (Review)
  
• Berridge & Robinson, What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res Brain Res Rev. 1998 Dec;28(3):309-69. (Review)
• Sutton & Barto (1998).  Reinforcement learning: An introduction.  (online version of their influential book)
  

May 24: Games: trust and fairness
Guest lecturer: David Levine

Required readings:

• Camerer, C.F. (2005). Behavioral game theory: Predicting human behavior in strategic interactions.  Chapter 13 in C.Camerer, G. Loewenstein & M. Rabin (Eds.) Advances in Behavioral Economics.  Princeton, NJ: Princeton University Press.
  
• Camerer, C.F. (2003).  Strategizing in the brain.  Science, 300, 1673-1675.
• Tomlin et al., Agent-specific responses in the cingulate cortex during economic exchanges.
  Science. 2006 May 19;312(5776):1047-50.
• Sanfey et al., The neural basis of economic decision-making in the Ultimatum Game. Science. 2003 Jun 13;300(5626):1755-8.
• Kosfeld et al., Oxytocin increases trust in humans. Nature. 2005 Jun 2;435(7042):673-6.
• van't Wout et al. Repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex affects strategic decision-making. Neuroreport. 2005 Nov 7;16(16):1849-52.

Optional readings:

• King-Casas et al., Getting to know you: reputation and trust in a two-person economic exchange. Science. 2005 Apr 1;308(5718):78-83.
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• McCabe et al., A functional imaging study of cooperation in two-person reciprocal exchange. Proc Natl Acad Sci U S A. 2001 Sep 25;98(20):11832-5.
• Bhatt, M. & Camerer, C.F. (2005).  Self-referential thinking an equilibrium as states of mind in games: fMRI evidence.  Games and Economic Behavior, 52, 424-459.
• Montague, P.R., Berns, G.S., Cohen, J.D., McClure, S.M., Pagnoni, G., Dhamala, M., Wiest, M.C., Karpov, I., King, R.D., Apple, N., Fisher, R.E. (2002). Hyperscanning: Simultaneous fMRI during linked social interactions. Neuroimage, 16, 1159-1164.
• Brosnan, S.F. & de Waal, F.B.M. (2003).  Monkeys reject unequal pay.  Nature, 425, 297-299.
  

May 31: Intertemporal choice, self-control, and impulsivity

Lecture slides--Fox
Discussion slides - Poldrack

Required readings:

• Frederick, S., Loewenstein, G., & O'Donoghue, T. (2004).  Time discounting and time preference: A critical review.  Chapter 1 in G. Loewenstein, D. Read & R.F. Baumeister (Eds.), Time and Decision: Economic and Psychological Perspectives on Intertemporal Choice.
  
• McClure et al., Separate neural systems value immediate and delayed monetary rewards.Science. 2004 Oct 15;306(5695):503-7.
•  Berns et al., Neurobiological substrates of dread. Science. 2006 May 5;312(5774):754-8.

Optional readings:

• Kalenscher et al., Single units in the pigeon brain integrate reward amount and time-to-reward in an impulsive choice task. Curr Biol. 2005 Apr 12;15(7):594-602.
• Loewenstein, G. & O'Donoghue, T. (2004).  Animal spirits: Affective and deliberative processes in economic behavior.  Unpublished manuscript, Carnegie Mellon University.
  
• Loewenstein and O'Donoghue. A review of intertemporal choice. J Economic Literature, 90,: 351-401, 2001,
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