The flexibility of models of recognition memory: An analysis by the minimum-description length principle

► The Fisher information approximation is efficiently computed for ten memory models. ► A relatively general method to compute the normalized maximum likelihood is derived. ► The relative complexity of ten recognition-memory models is evaluated. ► The small-sample adequacy of the Fisher information approximation is evaluated. ► The minimum-description length indices outperform AIC and BIC in model recovery.