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Lee, U.

Publications and source records attributed to Lee, U..

21 records · Page 2Linked to original sources

Criticality as a determinant of integrated information {Phi} in human brain networks

Integrated information theory (IIT) postulates that consciousness arises from the cause-effect structure of a system but the optimal network conditions for this structure have not been elucidated. In the study, we test the hypothesis that network criticality, a dynamically balanced state between a large variation of functional network configurations and a large constraint of structural network configurations, is a necessary condition for the emergence of a cause-effect structure that results in a large {Phi}, a surrogate of integrated information. We also hypothesized that if the brain deviates from criticality, the cause-effect structure is obscured and {Phi} diminishes. We tested these hypotheses with a large-scale brain network model and high-density electroencephalography (EEG) acquired during various levels of human consciousness during general anesthesia. In the modeling study, maximal criticality coincided with maximal {Phi}. The constraint of the structural network on the functional network is maximized in the maximal criticality. The EEG study demonstrated an explicit relationship between {Phi}, criticality, and level of consciousness. Functional brain network significantly correlated with structural brain network only in conscious states. The results support the hypothesis that network criticality maximizes {Phi}.

neuroscience↗

Oscillations, criticality and responsiveness in complex brain networks

Brain networks during unconscious states resulting from sleep, anesthesia, or traumatic injuries are associated with a limited capacity for complex responses to stimulation. Even during the conscious resting state, responsiveness to stimulus is highly dependent on spontaneous brain activities. Many empirical findings have been suggested that the brain responsiveness is determined mainly by the ongoing brain activity when a stimulus is given. However, there has been no systematic study exploring how such various brain activities with high or low synchronization, amplitude, and phase response to stimuli. In this model study, we simulated large-scale brain network dynamics in three brain states (below, near, and above the critical state) and investigated a relationship between ongoing oscillation properties and a stimulus decomposing the brain activity into fundamental oscillation properties (instantaneous global synchronization, amplitude, and phase). We identified specific stimulation conditions that produce varying levels of brain responsiveness. When a single pulsatile stimulus was applied to globally desynchronized low amplitude of oscillation, the network generated a large response. By contrast, when a stimulus was applied to specific phases of oscillation that were globally synchronized with high amplitude activity, the response was inhibited. This study proposes the oscillatory conditions to induce specific stimulation outcomes in the brain that can be systematically derived from networked oscillator properties, and reveals the presence of state-dependent temporal windows for optimal brain stimulation. The identified relationship will help advance understanding of the small/large responsiveness of the brain in different states of consciousness and suggest state-dependent methods to modulate responsiveness. Author SummaryA responsiveness of the brain network to external stimulus is different across brain states such as wakefulness, sleep, anesthesia, and traumatic injuries. It has been shown that responsiveness of the brain during conscious state also varies due to the diverse transient states of the brain characterized by different global and local oscillation properties. In this computational model study using large-scale brain network, we hypothesized that the brain responsiveness is determined by the interactions of networked oscillators when a stimulus is applied to the brain. We examined relationships between responsiveness of the brain network, global synchronization levels, and instantaneous oscillation properties such as amplitude and phase in different brain states. We found specific stimulation conditions of the brain that produce large or small levels of responsiveness. The identified relationship suggests the existence of temporal windows that periodically inhibit sensory information processing during conscious state and develops state-dependent methods to modulate brain responsiveness considering dynamically changed functional brain network.

neuroscience↗

Xbra and Smad-1 response elements cooperate in PV.1 promoter to inhibit the early neurogenesis in Xenopus embryos

Crosstalk of signaling pathways plays crucial roles in cell fate determination, cell differentiation and proliferation. Both BMP-4/Smad-1 and FGF/Xbra signaling induce the expression of PV.1, leading to neural inhibition. However, BMP-4/Smad-1 and FGF/Xbra signaling crosstalk in the regulation of PV.1 transcription is still largely unknown. In this study, Smad-1 and Xbra physically interacted and regulated the PV.1 transcriptional activation in a synergistic manner. Xbra and Smad-1 directly bound within the proximal region of the PV.1 promoter and cooperatively enhanced the binding of an interacting partner within the promoter. Maximum cooperation was achieved in the presence of intact DNA binding sites of both Smad-1 and Xbra. Collectively, BMP-4/Smad-1 and FGF/Xbra signal crosstalk was required to activate the PV.1 transcription, synergistically. Suggesting that crosstalk of BMP-4 and FGF signaling facilitates the fine-tuning regulation of PV.1 transcription to inhibit neurogenesis during embryonic development of Xenopus.\n\nSummary statementFGF/Xbra positively regulates the PV.1 expression in the Xenopus via an unknown mechanism. Our study shows that both BMP-4/Smad-1 and FGF/Xbra exhibits a signaling crosstalk to regulate PV.1 transcription activation, promoting to ectoderm and mesoderm formation and inhibiting the early neurogenesis in Xenopus.

developmental biology↗