Diversity improves performance in excitable networks
arXiv:1507.05249 · doi:10.7717/peerj.1912
Abstract
As few real systems comprise indistinguishable units, diversity is a hallmark of nature. Diversity among interacting units shapes properties of collective behavior such as synchronization and information transmission. However, the benefits of diversity on information processing at the edge of a phase transition, ordinarily assumed to emerge from identical elements, remain largely unexplored. Analyzing a general model of excitable systems with heterogeneous excitability, we find that diversity can greatly enhance optimal performance (by two orders of magnitude) when distinguishing incoming inputs. Heterogeneous systems possess a subset of specialized elements whose capability greatly exceeds that of the nonspecialized elements. Nonetheless, the behavior of the whole network can outperform all subgroups. We also find that diversity can yield multiple percolation, with performance optimized at tricriticality. Our results are robust in specific and more realistic neuronal systems comprising a combination of excitatory and inhibitory units, and indicate that diversity-induced amplification can be harnessed by neuronal systems for evaluating stimulus intensities.
17 pages, 7 figures
References in corpus (15)
- Emergent complex neural dynamics
- Recent advances in percolation theory and its applications
- Griffiths phases and the stretching of criticality in brain networks
- Diversity-induced resonance
- Dwelling Quietly in the Rich Club: Brain Network Determinants of Slow Cortical Fluctuations
- Frustrated hierarchical synchronization and emergent complexity in the human connectome network
- The frustrated brain: From dynamics on motifs to communities and networks
- Critical and maximally informative encoding between neural populations in the retina
- Mean field theory of assortative networks of phase oscillators
- Dynamic range of hypercubic stochastic excitable media
- How to enhance the dynamic range of excitatory-inhibitory excitable networks
- Signal integration enhances the dynamic range in neuronal systems
- Excitable Scale Free Networks
- Rounding of abrupt phase transitions in brain networks
- Physics of Psychophysics: it is critical to sense