Table 1. Experimental and computational model-derived variables.

Dependent variables	DATA	ABSOLUTE	RELATIVE
Learning test: correct choice rate
Reward partial (% correct)	0.73±0.03	0.75±0.02	0.74±0.02
Punishment partial (% correct)	0.74±0.03	0.70±0.02	0.72±0.02
Reward complete (% correct)	0.83±0.02	0.83±0.02	0.84±0.02
Punishment complete (% correct)	0.86±0.02	0.81±0.02*	0.84±0.02
Post-learning test: choice rate
G75 partial (% choices)	0.78±0.04	0.86±0.01	0.85±0.01
G25 partial (% choices)	0.51±0.06	0.58±0.01	0.54±0.01
L25 partial (% choices)	0.45±0.04	0.37±0.01	0.45±0.01
L75 partial (% choices)	0.25±0.03	0.17±0.01	0.16±0.01
G75 complete (% choices)	0.83±0.03	0.91±0.01	0.83±0.02
G25 complete (% choices)	0.40±0.04	0.66±0.01*	0.38±0.03
L25 complete (% choices)	0.61±0.03	0.37±0.01*	0.62±0.03
L75 complete (% choices)	0.17±0.03	0.08±0.01	0.16±0.02

ABSOLUTE, absolute value learning model; DATA, experimental data; RELATIVE, relative value learning model (best-fitting model).

The table summarizes for both tasks their experimental and model-derived dependent variables. Data are expressed as mean±s.e.m.

^*P<0.05, t-test, comparing the model-derived values with the actual data after correcting for multiple comparisons (N=28).