Table 7.
Estimated model parameters for instructed learning manipulation.
| Mean αgain (SD) | Mean αloss (SD) | Mean β (SD) | Mean AIC (SD) | |
|---|---|---|---|---|
| NL | 1.00 (0.00) | 70.96 (1.79)- | ||
| NL – Init | 0.42 (0.12) | 65.70 (6.05)- | ||
| LG | 0.50 (0.30) | 0.08 (0.11) | 0.43 (0.22) | 63.04 (6.00)* |
| LG – Init | 0.16 (0.24) | 0.04 (0.04) | 0.12 (0.12) | 65.52 (6.00)- |
| LG – Good | 0.83 (0.23)* | 0.08 (0.11) | 0.39 (0.26)- | 18.79 (2.66) |
| LG – Neutral | 0.71 (0.35) | 0.07 (0.10)- | 0.54 (0.29)* | 20.14 (2.16) |
| LG – Bad | 0.44(0.35)- | 0.19 (0.23)* | 0.28 (0.20)- | 18.29 (2.70) |
| LG – Lottery | 0.64 (0.34)- | 0.10 (0.19) | 0.39 (0.26)- | 18.84 (2.88) |
NL refers to the No Learning model estimated for each subject, which assumed a reciprocation rate of 50%. NL – Init refers to the No Learning Initialization model, which estimated a parameter for each partner reflecting the probability of their reciprocation. LG refers to the overall Loss Gain reinforcement learning model estimated for each subject. LG – Init refers to an overall Loss Gain learning model that allowed for initial beliefs of partner reciprocation to vary LG – Good/Neutral/Bad/Lottery reflect parameters from the LG model estimated separately by condition for each subject. *p < 0.05, -comparison group.