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. 2019 Feb 18;5(2):e01181. doi: 10.1016/j.heliyon.2019.e01181

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© 2019 The Authors

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

PMC Copyright notice

Interplay between differentiation, integration and entropy. (i) AABB has <Φ > =0.119, <_ETCΦ^C > =0.318, <_LZΦ^C > =1.020, (ii) AABC has <Φ > =0.325, <_ETCΦ^C > =0.720, <_LZΦ^C > =2.444, (iii) AACC has <Φ > =2.083, <_LZΦ^C > =0.730, <_ETCΦ^C > =2.683. The complexity of the simulated network AABB is lower than that of AABC, which is lesser than the complexity of AACC. This may seem counter-intuitive, but it is not, since the entropy of C (XOR gate) is higher than the entropies of both B (AND gate) and A (OR) gate. Thus, heterogeneity alone is insufficient to increase the value of integrated information of the network; the entropy of the individual nodes and their number in the network also matter.