Improved understanding of the effects of variability in electrophysiological activity within the human heart is key to understanding and predicting cardiovascular response to disease and treatments. Previous studies have considered either regional variation in action potentials or inter-subject variability within a single region of the atria. In this study, we hypothesize that the regional differences in morphology derive not only from variation in dependence on individual conductances, but also from the relationship between multiple conductances. Using the Monte-Carlo Sampling Method and the Maleckar cellular model for electrophysiology, we created an In-Silico Population of Models. Each conductance was varied +/- 100% from the standard model. The population was divided into regional groups based on biomarkers. Results showed regional variation in the dependence on relationships between conductances. In the right atrial appendage the value of gK1 was found to be only twice as influential as the relationship between gK1 and gKur on the APD90 biomarker. Other relationships that had a significant impact included gTo-gKur; gKr-gK1; gNaK- gNaCa and gKur-gNaK for various regions. R2 values for first order linear regression models showed significant relationships were left out in the analysis. This was significantly improved in the second order R2 values.