Comparing functional and effective connectivity classifiers
Lastly, we compared the performances of classifiers trained on either FC or EC to test whether modelling additional physiological details (i.e., self-inhibition and asymmetry) translated into a better classification performance of drug condition. While BACs differed numerically between the FC and EC classification models (86% vs 91% BAC), a McNemar’s test comparing the models’ performances suggested that these differences were not significantly different (