Neuroscience of human decision making: from dopamine to culture. G. CHRISTOPOULOS Culture Science Institute Nanyang Business School

Transcription

1 Neuroscience of human decision making: from dopamine to culture G. CHRISTOPOULOS Culture Science Institute Nanyang Business School

2 A neuroscientist in a Business School?

3 A visual discrimination task: Spot the Neuroscientist (vs. Business Prof)

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5 Stylistic evolution (Social Pressure)

6 Charles Darwin

7 Reproductive Success Battle for survival Charles Darwin New Species

8 Profit Reproductive Success Adam Smith Economic competition Battle for survival Charles Darwin Division of Labor New Species

9 Adam Smith Charles Darwin Economic Agents Both have to solve similar problems Organisms

10 Adam Smith CHOICE Charles Darwin

11 MAJOR PROBLEM TO BE SOLVED BY THE BRAIN: UNCERTAINTY Decision Maker Journal of Neuroscience, 2009 PNAS, 2009

12 Decisions, Decisions, Decisions Many behavioral deviations and neuropsychiatric diseases can be described as malfunctions of decision making, valuation - especially assessment of uncertainty: Depression Addiction Gambling Obesity Alcoholism Aggression Stress-related diseases, including cardiovascular diseases

13 Dopamine - Parkinson s disease - Addiction - Psychiatric drugs (antipsychotics, antidepressants) target dopamine - Obesity - Gambling - Depression - Obsessive compulsive disorder - Ageing

14 The agent, first of all, needs to represent the environment Decision Maker Journal of Neuroscience, 2009 PNAS, 2009

15 Mean- Variance Approach Decision Maker Harry Markowitz Nobel Prize in Economics Journal of Neuroscience, 2009 PNAS, 2009

16 Decision Maker Harry Markowitz Nobel Prize in Economics Journal of Neuroscience, 2009 PNAS, 2009

17 Decision Maker Harry Markowitz Nobel Prize in Economics Journal of Neuroscience, 2009 PNAS, 2009

18 38 FOR SURE Decision Maker % EACH

19 Parameter Estimate Mean- Variance Approach or or 80 Ventral striatum computes the Expected Value of both safe and risky options

20 Mean- Variance Approach 40 or or 90 ACC signal higher risk; not utility (not shown)

21 Mean- Variance Approach Variance Mean

22 Risk Aversion

23 Mean- Variance Approach Variance Mean

24 Mean- Variance Approach Variance Mean

25 Mean- Variance Approach Variance Mean Risk aversion

26 Are the measurements behaviorally relevant? Variance Mean Risk aversion Choice

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29 TMS shut down rdlpfc Decreased risk aversion (participants became more risk seeking) Knoch et al.

30 adolescence is a period of functional activation of basic motivational and emotional systems at a time when prefrontal cortical systems involving rational decisions and actions are not fully mature. Elevation in dopamine-rich circuitry being related to risky behavior and sensitivity to reward

31 You have to submit a research paper for two different journals. Deadline is tomorrow. You have one day left. - If you devote the last day to revise the paper for journal A you will increase the probability of acceptance from 85% to 90%; - If you devote the last day to revise the paper for journal B you will increase the probability of acceptance from 25% to 30%; How do you spend the rest of the day? (Option C: There is no hope; go to Sentosa)

32 Journal of Neuroscience, 2008

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36 if any one species does not become modified and improved in a corresponding degree with its competitors it will be exterminated. Adam Smith ADAPTATION Every individual is continually exerting himself to find out the most advantageous employment for whatever capital he can command. Charles Darwin

37 The world is not static. How do organisms learn the meaning of new stimuli to select better actions?

38 Basic behavior: Pavlov s dog

39 REINFORCEMENT LEARNING How systems improve predictions of their choices Machine Learning Prediction Error = What happened minus What I was expecting Psychology Biology Finance

40 Computations Value of can Value of liquid 0 1 Prediction error

41 Neurobiology of prediction error Schultz, Dayan, Montague (Science, 1997) Wolfram Schultz

42 Stimuli Choice Outcome

43 Self: +70 p=0.8 Self: -70 p=0.2 OR Self: +70 p=0.2 Self: -70 p=0.8

44 Dopamine pharmacological manipulation has an effect in learning? Haloperidol : dopamine L-DOPA: dopamine Placebo: dopamine Pessiglione et al. (Nature, 2006)

45 Are Decision Making systems hi-jacked to explain the Social World?? For instance, how do we learn to trust another person? How do we learn to

46 Social brain hypothesis Humans s extraordinary collection of cognitive abilities, including coalitions, leadership etc. is an outcome of the interaction with the social world Social arms race Richard Alexander (1989, 1990a); Flinn et al.

47 Studying Social Behavior with Game Theory? Keep $10 Send $0 $10 Keep $6 Send $4

48 Studying Social Behavior with Game Theory? Keep $10 Send $0 $0 $10 Keep $6 Send $4 $4x3=$12 $12

49 Studying Social Behavior with Game Theory? Keep $10 Send $0 $0 $10 Keep $6 Send $4 $4x3=$12 $12 Reciprocate: $12 $6 $12 $6 Betray: $0

50 T(279) % signal change fraction sent to partner Social reward signal 1 Positive deviation Neutral reciprocity Negative deviation investor trustee rounds back 1 round back now 2 rounds back 1 round back now 2 rounds back 1 round back now 3 - positive deviation > negative deviation y = 20 x = * * * p <.005 p < King-Casas et al., 2005; Science 0 negative neutral positiive investor reciprocity

51 Social rewards: Example Cooperative Individualist Competitive argmax{s+o} argmax{s} argmax{s-o} Self: $70 OR Other: $70 Self: $100 Other: $0 Self: $70 OR Other: -$70

52 Other Social Value Orientation Altruistic argmax{s+o} Self: +$70 Other: +$ Self Individualistic argmax{s} Self: +$100 Other: argmax{s-o} Self: +$70 Other: -$70

53 Identifying Social Value Orientation (1 st part of experiment)

54 Other Measuring Social preferences Altruistic Self: +$20 Other: -$ OR Self Individualistic -60 Self: -$20 Other: -$

55 Other Measuring Social preferences Altruistic Self: +$20 Other: -$ OR Self Individualistic -60 Self: -$20 Other: -$

56 Other Social orientation Altruistic Self Individualistic

57 Other Social orientation Altruistic Self Individualistic

58 Other Social orientation Altruistic Self Individualistic

59 Dollars to Other Results: social value orientation Dollars to Self

60 How people LEARN to select social actions (2nd part of experiment)

61 + + Self: +70 Stimuli Choice Outcome

62 + + Self: +70 Other: -70 Stimuli Choice Outcome

63 Neuroimage, Accepted

64 Social Risks

65 How are social uncertainties processed?

66 Source of risk: Nature OR Frontiers in Neuroscience, 2012

67 Source of risk: Social OR

68 Social Risk Aversion - Non Social Risk Aversion Behavior: Two groups: Group A became MORE RISK AVERSE in social situation (preference for stocks) Group B became MORE RISK SEEKING in social situation (preference for humans) 0.3 Social - Non Social Risk Aversion Socially risk averse group Socially risk seeking group

69 Social Risk Aversion - Non Social Risk Aversion Behavior: Two groups: Group A became MORE RISK AVERSE in social situation (preference for stocks) Group B became MORE RISK SEEKING in social situation (preference for humans) 0.3 Social - Non Social Risk Aversion Socially risk averse group Socially risk seeking group Betrayal Aversion

70 Social Risk Aversion - Non Social Risk Aversion Behavior: Two groups: Group A became MORE RISK AVERSE in social situation (preference for stocks) Group B became MORE RISK SEEKING in social situation (preference for humans) 0.3 Social - Non Social Risk Aversion Socially risk averse group Socially risk seeking group Altruistic Preferences

71 Striatal response to social outmes - striatal response to non social outcomes During outcome evaluation striatal response signals outcomes of interest. Stronger striatal response to outcomes of social interactions Social risk averse group Socially risk seeking group Stronger striatal response to outcomes of non social interactions

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73 East Meets West studies Cultural Mixing Emotions Mega-cities (Just Funded)

74 Culture Mixing/Contamination Bobby Cheon G. Christopoulos Y-y. Hong

75 Physical Disgust Comparison Pure Object

76 Physical Disgust Comparison Pure Object Pure Contaminant

77 Physical Disgust Comparison Pure Object Pure Contaminant Mixing

78 Cultural Mixing Starbucks in China

79 Cultural Mixing X Starbucks inside the Forbidden City

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81 Real Coca Cola ad ( 90s). It was quickly retracted

82 Cultural Mixing as Contamination Rozin, Haidt, & Fincher, 2009

83 Stimuli Pure American

84 Stimuli Pure American Pure Chinese

85 Stimuli Pure American Pure Chinese Side by Side (Cultures in proximity, but not actually mixing)

86 Stimuli Pure American Pure Chinese Side by Side (Cultures in proximity, but not actually mixing) Mixed

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88 Disgust Disgust Pilot Results Culture Images Contamination Images American Chinese SBS Mixed 1.00 Object Contaminant SBS Mixed As contaminant (cultural or physical) gets closer to the target (American or pure object), disgust increases Highest reported disgust when contaminant is mixed with American representation / pure object

89 Asian Faces Database Chan, Wei, Christopoulos

90 Facial emotion recognition Psychology Neuroscience Psychiatry Social interactions Development Culture

91 Jack et al., 2012, PNAS)

92 and 15 East Asian (Chinese, seven males, mean age 22.9 y, SD 1.3 y). All EA observers had newly arrived in a Western country (mean residence 5.2 mo, SD 0.94 mo) with International English Language Testing System score 6.0 (competent user).

93 Elfenbein & Ambady (2003) Noted that: there are several decades of research supporting an ingroup advantage in emotional recognition. Meta-analysis by Elfenbein & Ambady(2010) found that the more different the population studied against the FACES database, the less accurate the participants in recognizing facial expressions. (may be due to cultural differences in expression of emotions)

94 Surprisingly, there is a lack of a standardized, well-developed database of facial stimuli in Asian population.

95 Purpose: Constructing an Asian/Multi-racial FACES database Possible hypotheses that may be tested with the NEW FACES database:- People recognize expressions of faces from their own race with greater accuracy than faces of other races. (in-group advantage & dialect theory) People from Western cultures are simply better at recognizing facial expressions regardless of race (Universality theory) Western participants are less accurate at detecting facial expressions of Asian faces than white faces. Age related differences in expression recognition generalize across cultures (Ebner FACES study)

96 Research Objectives-1 Megacities, urbanization, population growth and ageing mean less usable space and different needs. Major impact on human Health, Productivity and Psychology We will study engineering, health, psychological and social issues. We aim in a human-centric engineering.

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102 A holistic approach Brain / Behavior (BIO-PSYCHOLOGY) Environment ENGINEERING Body (HEALTH) Opinions SOCIAL

103 Underground Above ground Groups of users Above-ground Shallow Depth Deep Depth