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Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
Neural mechanisms of decision making - emotion vs. cognition
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Neural mechanisms of decision making - emotion vs. cognition

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  • 1. Neural mechanisms of decision making - emotion vs. cognition Prepared for Lab seminar 2008 06 09 9a.m. #3239, CT 2008.06.09, 9 #3239 Kyongsik Yun Ph D Candidate Yun, Ph.D. KAIST yunks@kaist.edu
  • 2. “The mind is a charioteer driving twin horses of reason and emotion Except emotion. cognition is a smart pony, and emotion an elephant” — Colin Camerer & George Loewenstein 2
  • 3. Research Summary [Resarch interests] U d t di th lb fd i i ki i t t i i t ti - Understanding the neural bases of decision making in strategic interaction - Computational modeling of neural networks underlying reward and learning - Behavioral game theory and neuroeconomics - Theoretical neuroscience with reinforcement learning, nonlinear dynamics, information theory g, y , y - Functional neuroimaging data analysis including fMRI and EEG Understanding the Neural mechanisms of Decision Making in the context of Emotion vs Cognition vs. Behavioral game theory and Impaired decision making in p g Computational modeling and neuroeconomics – Ulti t i Ultimatum neuropsychiatric disorders – i l ti i f t simulation – reinforcement game methamphetamine addiction, learning schizophrenia, Alzheimer’s Disease, Disease adolescence Methods - Nonlinear dynamic analysis - EEG analysis for high temporal resolution information processing - fMRI analysis for functional connectivity and large-scale communication between the brain regions
  • 4. I Important questions t t ti • Behavior: How do we valuate ‘fairness’ at the behavioral level? • Physiology: what are the neural y gy mechanisms within and between the brain that implement the decision making? • Th Theory: C we formally d Can f ll describe h ib how ‘fairness’ is computed within the brain p (i.e. can we build a model?)
  • 5. What are the temporal dynamics of p y social interaction? proposer responder 5
  • 6. What are the temporal dynamics of p y social interaction? proposer responder 1. Make an offer: 9:1 (send emotional cue) Reward anticipation (NAcc) 6
  • 7. What are the temporal dynamics of p y social interaction? proposer responder 1. Make an offer: 9:1 2. Conflict btwn emotion & cognition (send emotional cue) ACC, Ins ACC Ins, dlPFC activation (interaction) acti ation Reward anticipation (NAcc) 7
  • 8. What are the temporal dynamics of p y social interaction? proposer responder 1. Make an offer: 9:1 2. Conflict btwn emotion & cognition (send emotional cue) ACC, Ins ACC Ins, dlPFC activation (interaction) acti ation Reward anticipation (NAcc) 3. Make a decision (reject: Ins) 8
  • 9. What are the temporal dynamics of p y social interaction? proposer responder 1. Make an offer: 9:1 2. Conflict btwn emotion & cognition (send emotional cue) ACC, Ins ACC Ins, dlPFC activation (interaction) acti ation Reward anticipation (NAcc) 3. Make a decision (reject: Ins) 4. Reward prediction error 9
  • 10. Normal be a o of soc a interaction o a behavior o social te act o - responder behavior • Face to face interaction – Lower acceptance rate 100 single interaction multiple interaction – Different valuation mechanism between the 80 single interaction and Acceptance rates (%) multiple interactions 60 * e 40 * A 20 0 5:5 7:3 8:2 9:1 Offer Yun et al. OHBM 2007 10
  • 11. Normal behavior of social interaction – proposer behavior • Face to face interaction – More fairness valuation 100 5 90 80 4 70 Ne offer 3 Offer rate (%) 60 ext es 50 2 40 1 30 20 0 0 1 2 3 4 5 10 Current offer 0 Slope: 0.86, R:0.73, P<0.0001 5:5 6:4 7:3 8:2 9:1 Offer
  • 12. Normal behavior of social interaction – dictator behavior 100 Ultimatum Game • In the dictator game 90 Dictator Game – No wish to maximize other’s benefit 80 70 * – fairness Offer rates (%) 60 ( 50 – Avoid being seen as greedy 40 30 20 10 * 0 5:5 6:4 7:3 8:2 9:1 Offer
  • 13. I Important questions t t ti • Behavior: How do we valuate ‘fairness’ at the behavioral level? • Physiology: what are the neural y gy mechanisms within and between the brain that implement the decision making? • Th Theory: C we formally d Can f ll describe h ib how ‘fairness’ is computed within the brain p (i.e. can we build a model?)
  • 14. P i Previous studies: t di emotion vs cognition vs. Sanfey et al. Science, 2003 14
  • 15. Previous studies: reward anticipation Optimal investment strategy Risk neutral Risk Risk seeking aversion mistake mistake NAcc preceded risky choices aIns preceded riskless choices Distinct neural circuits Consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making Kuhnen & Knutson, Neuron, 2005 15
  • 16. What are the neural mechanisms of human decision making in the context of emotion and cognition? dlPFC Anterior i insula ACC CC 16
  • 17. How does the brain process reward o t e b a p ocess e a d anticipation in the decision making? Anterior NAcc insula Proposer divides the pie as 9:1 8:2 7:3 6:4 5:5 Risk taking ---------------------------------- risk averse 17
  • 18. Electrophysiological correlates of decision ect op ys o og ca co e ates o dec s o making in the Ultimatum game Yun et al OHBM 2007 al. 18
  • 19. Functional connectivity y in the Ultimatum game Yun et al. OHBM 2007 19
  • 20. EEG hyperscanning Client Client Hyperscan server and database Controller Controller 20
  • 21. Proposer Proposer offer Responder decision Responder
  • 22. Information processing in social interaction (proposer offer -2sec ~ -1sec) ( ff 2 1 ) Proposer p Responder p proposer responder proposer responder from to from to from to from to FC4 FC3 F5 FC3 FC4 CP1 FC3 F5 FC4 P1 FC3 C1 CP6 FP1 C1 FC3 CP6 C6 FC3 CP1 C6 CP6 CP1 FC3 CP6 P6 FC3 P1 22 P1 FC3
  • 23. I Important questions t t ti • Behavior: How do we valuate ‘fairness’ at the behavioral level? • Physiology: what are the neural y gy mechanisms within and between the brain that implement the decision making? • Th Theory: C we formally d Can f ll describe h ib how ‘fairness’ is computed within the brain p (i.e. can we build a model?)
  • 24. Temporal difference learning δ(t) = r(t) + γV(s(t+1)) - V(s(t)) 24 Schultz, Dayan, & Montague, Science, 1997
  • 25. Temporal difference learning δ(t) = r(t) + γV(s(t+1)) - V(s(t)) 25 Schultz, Dayan, & Montague, Science, 1997
  • 26. Temporal difference learning δ(t) = r(t) + γV(s(t+1)) - V(s(t)) r V δ r V δ r V δ Schultz, Dayan, & Montague, Science, 1997
  • 27. Emotion vs. Cognition interaction model Anterior dlPFC insula Vinsula = -Ψ*( (ERO-ER) * F ) Vdlpfc = Ψ * ( ER ) TD learning Ψ: the hyperbolic tangent function ACC VACC = Ψ * ( Vdlpfc + Vinsula ) ER: expected reward p ERO: expected reward of opponent (theory of mind) F: fairness representation (0~1) 27
  • 28. 28
  • 29. Modeling results of each fairness valuation parameters and th d i i d the decision making strategy ki t t fair (5:5) ( ) 0.5 conflict (7:3) unfair (9:1) 0.4 0.3 0.2 decision ratio 0.1 0.0 -0.1 -0.2 -0.3 -0 4 0.4 -0.5 0.0 0.2 0.4 0.6 0.8 1.0 Fairness 29
  • 30. Modeling results of brain regional activation Conflict it ti C fli t situation (7:3) fairness value = 1 (7 3) f i l High fairness valuation -> insula activation 0.5 dlPFC 0.4 04 Insula ACC 0.3 V) Model expected value (V 0.2 02 0.1 d 0.0 -0.1 -0.2 -0.3 -0.4 -0.5 0 2 4 6 8 Time steps (cycle) 30
  • 31. I Important questions (1) t t ti • What are the neural mechanisms of human decision making in the context of emotion and cognition? • H How does the brain process reward anticipation in the d th b i d ti i ti i th decision making? • What are the temporal dynamics of reward circuitry? (including reward anticipation, prediction error) What h l l f i li i ? • Wh are the neural correlates of social interaction? (personal interaction) • Are ultimatum rejections due to emotions, learned heuristics, evolved modules, or combinations of these and other mechanisms? – Camerer Trnds Cog Sci. 2003 Camerer, Trnds. Cog. Sci 31
  • 32. I Important questions (2) t t ti • Under what circumstances do these various systems cooperate or compete? When there is competition, how and where is it adjudicated? – Sanfey et al., Trnds Cog Sci. al Trnds, Cog. Sci 2006 • Psychologists, neuroscientists and behavioral economists all seem to agree that various automatic forms of behavior (including emotional responses) reflect the operation of a multiplicity of mechanisms. However, do higher-level deliberative d lib ti processes rely similarly on multiple mechanisms, l i il l lti l h i or a single, more tightly integrated (unitary) set of mechanisms? – Sanfey et al., Trnds, Cog. Sci. 2006 y g 32
  • 33. F t Future implications i li ti • Prescriptive game theory • Better theories of how people behave will help in the design of economic institutions • Treatment of patients with impaired decision making 33
  • 34. Future applications pp Treatments – Novel Approaches • damage to the insula disrupts addiction to cigarette smoking Naqvi et al. Science 2007 R h i d h ki i i hi i f i l Researchers monitored the smoking quitting histories of approximately 70 smokers who had suffered various brain injuries, and found that smokers with specific damage to the insula were much more likely to quit easily and immediately and to remain abstinent than those with damage to other brain areas
  • 35. Fool me o ce, s a e o you. oo e once, shame on Fool me twice, shame on oxytocin. Baumgartner et al. Neuron 2008
  • 36. VM FC l i VMpFC lesion vs. rPFC rTMS di PFC TMS disruption ti • The rejection rate of the VMPC group was higher than the rejection rates of the comparison groups for each of the most unfair offers ($7/$3, $8/$2, $9/$1). ($7/$3 $8/$2 $9/$1) • Disruption of the right, but not the left, dorsolateral prefrontal cortex (DLPFC) by low-frequency repetitive transcranial magnetic stimulation substantially reduces subjects subjects' willingness to reject their partners' intentionally partners unfair offers, which suggests that subjects are less able to resist the economic temptation to accept these offers. • Importantly, however, subjects still judge such offers as very unfair, which indicates that the right DLPFC plays a key role in the implementation of fairness-related behaviors. Koenigs & Tranel J Neurosci 2007 Tranel, Neurosci. Knoch et al. Science 2006
  • 37. Emotion expression in human p punishment behavior 37
  • 38. C Conclusions l i • My research will provide evidence for behavioral, physiological and computational approaches to social interaction and decision making that stress the fundamental role of cortical and subcortical areas in neural networks that support deliberative and emotional fairness valuation and reward learning processes in human decision making. 38

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