Diversity improves performance in excitable networks

PeerJ

article

Leonardo L. Gollo¹  Mauro Copelli³  James A. Roberts¹ 

[1] Systems Neuroscience Group, QIMR Berghofer Medical Research Institute;Centre for Integrative Brain Function, QIMR Berghofer Medical Research Institute;Departamento de Física, Universidade Federal de Pernambuco

关键词: Diversity;    Criticality;    Intensity coding;    Nonlinear computation;    Sensory systems;   

DOI  :  10.7717/peerj.1912

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

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. 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.

【 授权许可】

CC BY