Fitting a model to behavior reveals what changes cognitively when under stress and with caffeine

A human subject experiment was conducted to investigate caffeine's effect on appraisal and performance of a mental serial subtraction task. Serial subtraction performance data was collected from three treatment groups: placebo, 200, and 400 mg caffeine. The data were analyzed by caffeine treatment group and how subjects appraised the task (as challenging or threatening). A cognitive model of the serial subtraction task was developed. The model was fit to the individual human performance data using a parallel genetic algorithm (PGA). The best fitting parameters found by the PGA suggest how cognition changes due to caffeine and appraisal. Overall, the cognitive modeling and optimization results suggest that due to caffeine and task appraisal the speed of vocalization varies the most along with changes to declarative memory. This approach using a PGA provides a new method for computing how cognitive mechanisms change due to moderators or individual differences.