title: Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems.
abstract: Self-organized critical states (SOCs) and stochastic oscillations (SOs) are simultaneously observed in neural systems, which appears to be theoretically contradictory since SOCs are characterized by scale-free avalanche sizes but oscillations indicate typical scales. Here, we show that SOs can emerge in SOCs of small size systems due to temporal correlation between large avalanches at the finite-size cutoff, resulting from the accumulation-release process in SOCs. In contrast, the critical branching process without accumulation-release dynamics cannot exhibit oscillations. The reconciliation of SOCs and SOs is demonstrated both in the sandpile model and robustly in biologically plausible neuronal networks. The oscillations can be suppressed if external inputs eliminate the prominent slow accumulation process, providing a potential explanation of the widely studied Berger effect or event-related desynchronization in neural response. The features of neural oscillations and suppression are confirmed during task processing in monkey eye-movement experiments. Our results suggest that finite-size, columnar neural circuits may play an important role in generating neural oscillations around the critical states, potentially enabling functional advantages of both SOCs and oscillations for sensitive response to transient stimuli.
authors.affiliation: Department of Physics, Shaanxi Normal University, Xi'An 710119, China.|Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
authors.forename: Sheng-Jun
authors.initials: SJ
authors.lastname: Wang
authors.affiliation: Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
authors.forename: Guang
authors.initials: G
authors.lastname: Ouyang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Guang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
authors.forename: Mingsha
authors.initials: M
authors.lastname: Zhang
authors.affiliation: Department of Physics, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong.
authors.forename: K Y Michael
authors.initials: KY
authors.lastname: Wong
authors.affiliation: Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Beijing Computational Science Research Center, Beijing 100084, China.|Research Centre, HKBU Institute of Research and Continuing Education, Virtual University Park Building, South Area Hi-tech Industrial Park, Shenzhen 518057, China.
authors.forename: Changsong
authors.initials: C
authors.lastname: Zhou
mesh_terms: D001683:Biological Clocks; D001921:Brain / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes