Introduction

The human brain is one of nature’s most complex systems, and studying the brain facilitates the development of new theoretical approaches that can be applied in fields beyond neuroscience. We are particularly interested in the dynamics and state transitions of the human brain, and we study this system in the framework of nonlinear dynamical systems. Our research is motivated by the idea that understanding the dynamics of information flow in the brain will be critical for identifying, monitoring, and ultimately controlling brain state transitions. Our work combines analytical modeling and numerical simulations with multi-modal recordings of neural dynamics (EEG, ECoG, fMRI) during real-world cognitive functions.

Jae Hyung Woo, Christopher J Honey, and Joon-Young Moon, Phase and Amplitude Dynamics of Coupled Oscillator Systems on Complex Networks (2020) Chaos 30, 121102.

Junhyeok Kim*, Joon-Young Moon*, UnCheol Lee, Seunghwan Kim, and Tae-Wook Ko, Various Synchronous States Due to Coupling Strength Inhomogeneity and Coupling Functions in Systems of Coupled Identical Oscillators (2019) Chaos 29, 011106.

Hyoungkyu Kim*, Joon-Young Moon*, George A. Mashour, and UnCheol Lee, Mechanism of Hysteresis in Human Brain Networks During Transitions of Consciousness and Unconsciousness: Theoretical Principles and Empirical Evidence (2018) PLoS Computational Biology 14(8), e1006424.

Joon-Young Moon, Junhyeok Kim, Tae-Wook Ko, Minkyung Kim, Yasser Inturria-Medina, Jee-Hyun Choi, Joseph Lee, George A. Mashour, and UnCheol Lee, Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species (2017) Scientific Reports 7, 46606.

Joon-Young Moon, UnCheol Lee, Stefanie Blain-Mraes, and George A. Mashour, General Relationship of Global Topology, Local Dynamics, and Directionality in Large-Scale Brain Networks (2015) PloS Computational Biology 11(4), e1004225.