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Neural Correlates of Trust and Adaptation in a Dynamic Neuroeconomic Task Project Presentation

Neural Correlates of Trust and Adaptation in a Dynamic Neuroeconomic Task Project Presentation. Adam P.R. Smith, Esther Kessler, Chiara Fiorentini, Fiona Roberts, David Skuse Behavioural and Brain Sciences Unit, Institute of Child Health. Background. Social Decision Making. Risk / Reward.

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Neural Correlates of Trust and Adaptation in a Dynamic Neuroeconomic Task Project Presentation

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  1. Neural Correlates of Trust and Adaptation in a Dynamic Neuroeconomic Task Project Presentation Adam P.R. Smith, Esther Kessler, Chiara Fiorentini, Fiona Roberts, David Skuse Behavioural and Brain Sciences Unit, Institute of Child Health

  2. Background Social Decision Making Risk / Reward Reputation Experience / Learning Punishment Neuromodulators Expectation / Trust Altruism & ‘fairness’ ‘Competition’ ‘Cooperation’ Optimise outcome for self Optimise outcome for group • Appropriate social decision making key aspect of human interaction • Economic models provide a model framework of interactive behaviour • In real world, heavily influenced by previous interactions with others, but little done on influence of memory on social decisions

  3. You Invest 100 Your partner returns 200 You now have 1100 points You have 1000 points. Your playing partner is shown below Invest 100 Do not invest Multi-Round Trust Game • Basic structure of the trust game: • Players A and B each have an amount of money (or points) for participating in the study • Player A chooses to give a certain amount of their money (MA) to Player B • The money given is increased (xMA) (e.g. if tripled x =3) • Player B decides how much to return kB(xMA) • In the current study, the subject is always player A and makes a binary decision to invest money with player B or not. Player B (whose responses are pre-determined in an economics lab elsewhere) will either return nothing or half of the money. 4s 3s 2 – 4s (jittered) Round 1: 60 games, each with a novel partner represented by a photograph of an emotionally neutral female face. ~50% will reciprocate and return some points. If players do not invest they will still be told whether or not the partner would have reciprocated Round 2: In round 2, there is no choice as to whether or not to invest. 60 games, 30 with partners seen in round 1, 30 with novel partners. ~50% will reciprocate and return some points Round 3: In round 3, subject again has the choice whether or not to invest. 90 games - 30 from round 1 who were not in round 2, 30 from round 2 who were not in round 1 and 30 novel partners

  4. Subjects, Scanning and Analysis • 48 subjects allows counterbalancing across conditions of 120 emotionally neutral female faces representing playing partners. Each will be used an equal number of times as old/new, cooperator/defector and across the 3 rounds. To obviate effects of gender related subject/partner effects, all R handed females. • Expected scanning duration ~ 1h 15m – 1h 30m / subject . Estimated total scanner time ~ 75h • Experimental script implemented in Cogent. Scanning on Siemens Avanto 1.5T with 32 channel head coil. 30 slices of 2.5mm with 1.3mm gap to give near whole brain coverage (-vertex). TR ~2.5 – 3s. ?Use of pre-pulse to reduce OFC dropout . • Event-related fMRI analysis in SPM 8. Key within-subject contrasts of interest: • Invest vs. non-invest decision in round 1 (non-informed trust judgment) • Betrayed vs. reciprocated trust in R1 • ‘Old’ vs. ‘new’ partners in R2 (Old/New effects without need to adjust behaviour) • ‘Old’ co-operators vs. ‘old’ defectors in R2 (‘Emotional’ memory effects without need to adjust behaviour; Conflict effects) • Same contrasts from R2 in R3, where successful memory of partner’s behaviour should influence decision to trust • Post-hoc group-wise comparison of above effects according to genetic polymorphisms affecting neuromodulation

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