Figure 2.

Linear regression of <Φ> as a function of entropy of nodes for all 3, 4 and 5-node networks. A linear fit is obtained between the dependent variable <Φ> and the explanatory variables ‘entropy’ of nodes and ‘number of nodes’. Y-axis represents the mean value of integrated information in all 3 graphs. (A) X-axis represents 10 different 3-node network configurations (refer Table S1(a) in ‘Supplementary Tables’). (B) X-axis represents 15 different 4-node network configurations (refer Table S1(b) in ‘Supplementary Tables’). (C) X-axis represents 21 different 5-node network configurations (refer Table S1(c) in ‘Supplementary Tables’). The blue plot represents the <Φ> values for each network configurations and the red plot represents the predicted values of <Φ> as a function of ‘entropy’ for each network configuration in all 3 graphs. The predicted <Φ> (in red) obtained from linear regression is a good fit when compared to the actual <Φ> (in blue) as indicated by the linear correlation coefficient values between them: 0.9746 (3-nodes), 0.9275 (4-nodes) and 0.6262 (5-nodes) respectively. For further details, please refer to ‘Supplementary Text’.