Papers by Joon-Young Moon
Scientific reports, Jan 20, 2017
Identifying how spatially distributed information becomes integrated in the brain is essential to... more Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network stru...
PLoS computational biology, 2015
The balance of global integration and functional specialization is a critical feature of efficien... more The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified. One critical step in elucidating this relationship is the identification of governing principles underlying the directionality of interactions between nodes. Here, we demonstrate such principles through analytical solutions based on the phase lead/lag relationships of general oscillator models in networks. We confirm analytical results with computational simulations using general model networks and anatomical brain networks, as well as high-density electroencephalography collected from humans in the conscious and anesthetized states. Analytical, computational, and empirical results demonstrate that network nodes with more connections (i.e., higher degrees) have larger amplitudes and are directional targets (phase lag) rather than sources (phase lea...
Physical Review E, 2011
Gathering and analyzing data of large-scale complex networks such as the World Wide Web (WWW), so... more Gathering and analyzing data of large-scale complex networks such as the World Wide Web (WWW), social and biological networks became possible in recent years with a rapid advance of information technology. It has been found that complex networks often exhibit small-world and scale-free properties, and some even have fractal scaling behavior if they are measured by the box-counting method. In this work, we investigate the empirical small-world scale-free networks and show that there is a disparity in fractal scaling behavior of the core and peripheral parts of the empirical networks. We first decompose the network into a core and a periphery, then measure the fractal dimension of each part separately using the box-counting method. We find that the core of small-world scale-free networks have a non-fractal structure, whereas the periphery often exhibit fractal scaling. The fractal dimension of the periphery is found to coincide with the fractal dimension of the whole network. We further discuss implications of the sub-network having non-fractal behavior while the original network has fractal behavior.
BMC Neuroscience, 2015
Brain anatomical connectivity is one of the main factors influencing information flow among the b... more Brain anatomical connectivity is one of the main factors influencing information flow among the brain areas [1] and phase lead/lag relationship between oscillations of brain areas is known to be related to the information flow . In this study, we analyze the network effect on the phases of coupled oscillators using Kuramoto model and obtain analytical relationship between phase lead/lag and degrees of network nodes. We also show robustness under various conditions, improving upon the result of ref. . Using the brain anatomical connectivity and the relationship, we can explain the phase distribution across the brain. At first, we investigate the relationship in the
RESEARCH ARTICLE General Relationship of Global Topology, Local Dynamics, and Directionality in Large- Scale Brain Networks
The balance of global integration and functional specialization is a critical feature of efficien... more The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified. One critical step in elucidating this relationship is the identification of governing principles underlying the directionality of interactions be-tween nodes. Here, we demonstrate such principles through analytical solutions based on the phase lead/lag relationships of general oscillator models in networks. We confirm ana-lytical results with computational simulations using general model networks and anatomical brain networks, as well as high-density electroencephalography collected from humans in the conscious and anesthetized states. Analytical, computational, and empirical results demonstrate that network nodes with more connections (i.e., higher degrees) have larger amplitudes and are directional targets (phase lag) rather than sources (phase l...
There is a strong need to develop novel strategies in using antiviral agents to efficiently treat... more There is a strong need to develop novel strategies in using antiviral agents to efficiently treat influenza infections. Thus, we constructed a rule-based mathematical model that reflects the complicated interactions of the host immunity and viral life cycle and analyzed the key controlling steps of influenza infections. The main characteristics of the pandemic and seasonal influenza strains were estimated using parameter values derived from cells infected with Influenza A/California/04/2009 and Influenza A/NewCaledonia/20/99, respectively. The quantitative dynamics of the infected host cells revealed a more aggressive progression of the pandemic strain than the seasonal strain. The perturbation of each parameter in the model was then tested for its effects on viral production. In both the seasonal and pandemic strains, the inhibition of the viral release (kC), the reinforcement of viral attachment (kV), and an increased transition rate of infected cells into activated cells (kI) exh...
Chaos, 2020
We investigated locking behaviors of coupled limit-cycle oscillators with phase and amplitude dyn... more We investigated locking behaviors of coupled limit-cycle oscillators with phase and amplitude dynamics. We focused on how the dynamics are affected by inhomogeneous coupling strength and by angular and radial shifts in coupling functions. We performed mean-field analyses of oscillator systems with inhomogeneous coupling strength, testing Gaussian, power-law, and brain-like degree distributions. Even for oscillators with identical intrinsic frequencies and intrinsic amplitudes, we found that the coupling strength distribution and the coupling function generated a wide repertoire of phase and amplitude dynamics. These included fully and partially locked states in which high-degree or low-degree nodes would phase-lead the network. The mean-field analytical findings were confirmed via numerical simulations. The results suggest that, in oscillator systems in which individual nodes can independently vary their amplitude over time, qualitatively different dynamics can be produced via shift...
arXiv: History and Philosophy of Physics, 2017
In this paper, we summarize the development of the concept of emergence in physical science and p... more In this paper, we summarize the development of the concept of emergence in physical science and propose key concepts of emergence in the form of conjectures. Our conjectures are threefold: I. A system having a broken-symmetry in membership relation with respect to micro and macro scales can have emergent properties. II. Spontaneous symmetry-breaking is an example of an emergent property. III. The phenomenon of hysteresis accompanies spontaneous symmetry-breaking. We argue that these conjectures and their relationship can illuminate the concept of emergence from the perspective of symmetry breaking.
PLOS Computational Biology
Hysteresis, the discrepancy in forward and reverse pathways of state transitions, is observed dur... more Hysteresis, the discrepancy in forward and reverse pathways of state transitions, is observed during changing levels of consciousness. Identifying the underlying mechanism of hysteresis phenomena in the brain will enhance the ability to understand, monitor, and control state transitions related to consciousness. We hypothesized that hysteresis in brain networks shares the same underlying mechanism of hysteresis as other biological and nonbiological networks. In particular, we hypothesized that the principle of explosive synchronization, which can mediate abrupt state transitions, would be critical to explaining hysteresis in the brain during conscious state transitions. We analyzed high-density electroencephalogram (EEG) that was acquired in healthy human volunteers during conscious state transitions induced by the general anesthetics sevoflurane or ketamine. We developed a novel method to monitor the temporal evolution of EEG networks in a parameter space, which consists of the strength and topography of EEG-based networks. Furthermore, we studied conditions of explosive synchronization in anatomically informed human brain network models. We identified hysteresis in the trajectory of functional brain networks during state transitions. The model study and empirical data analysis explained various hysteresis phenomena during the loss and recovery of consciousness in a principled way: (1) more potent anesthetics induce a larger hysteresis; (2) a larger range of EEG frequencies facilitates transitions into unconsciousness and impedes the return of consciousness; (3) hysteresis of connectivity is larger than that of EEG power; and (4) the structure and strength of functional brain networks reconfigure differently during the loss vs. recovery of consciousness. We conclude that the hysteresis phenomena observed during the loss and recovery of consciousness are generic network features. Furthermore, the state transitions are grounded in the same principle as state transitions in complex non-biological networks, especially during perturbation. These findings suggest the possibility of predicting and modulating hysteresis of conscious state transitions in large-scale brain networks.
Synchronized and Propagating States of Human Auditory Processing
2019 Conference on Cognitive Computational Neuroscience, 2019
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Papers by Joon-Young Moon