Scale-Free Exponents of Resting State are Biomarkers of Neuro-Typical and Atypical Brain Activity

Scale-free networks (SFN) arise from simple growth processes, which can encourage efficient, centralized and fault tolerant communication (1). Recently its been shown that stable network hub structure is governed by a phase transition at exponents (>2.0) causing a dramatic change in network structure including a loss of global connectivity, an increasing minimum dominating node set, and a shift towards increasing connectivity growth compared to node growth. Is this SFN shift identifiable in atypical brain activity? The Pareto Distribution (P(D)[~]D{wedge}-{beta}) on the hub Degree (D) is a signature of scale-free networks. During resting-state, we assess Degree exponents across a large range