Mechanisms of hysteresis in human brain networks during transitions of consciousness and unconsciousness: Theoretical principles and empirical evidence
Hyoungkyu Kim, Joon-Young Moon, George A. Mashour, UnCheol Lee
PLoS Computational Biology August 30, 2018 DOI: 10.1371/journal.pcbi.1006424 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Population | Healthy human volunteers |
| Interventions | Sevoflurane Ketamine |
| Topics | Default mode network |
| Keywords | Unconsciousness Hysteresis Electroencephalography Synchronization alternating current Condensed matter physics |
| Citations | 79 |
| Key findings | Hysteresis in brain networks during loss and recovery of consciousness follows the same principle of explosive synchronization seen in other complex networks, with specific patterns depending on anesthetic potency, EEG frequency range, and network measure. |
Abstract
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 non-biological 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.
Comparable studies
Other observational and cohort studies on default mode network, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| A default mode of brain function Normal adult human brain | 2001 | Observational study | |
| Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network Healthy subjects | 2008 | Observational cohort | |
| Meditation experience is associated with increased cortical thickness Participants with extensive Insight meditation experience and matched controls | 2005 | Observational cohort | n = 20 |
| Meditation experience is associated with differences in default mode network activity and connectivity Experienced meditators and matched meditation-naive controls | 2011 | Observational cohort | |
| The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis Healthy subjects | 2008 | Observational study |
Citations in the library
Cited by 12
- Consciousness and complexity: a consilience of evidence Neuroscience of Consciousness 2021
- General Anesthesia: A Probe to Explore Consciousness Frontiers in Systems Neuroscience August 14, 2019
- Brain network motifs are markers of loss and recovery of consciousness Scientific Reports February 16, 2021
- Consciousness and the Dying Brain. Anesthesiology June 1, 2024
- Perspectivas del estudio de la consciencia: aproximación desde las ciencias de la complejidad y la biología evolutiva Entreciencias diálogos en la Sociedad del Conocimiento March 4, 2024
and 7 more in the library
Cites 4
- General Relationship of Global Topology, Local Dynamics, and Directionality in Large-Scale Brain Networks PLoS Computational Biology April 14, 2015
- Integrating the Science of Consciousness and Anesthesia Anesthesia & Analgesia September 19, 2006
- Propofol Induction Reduces the Capacity for Neural Information Integration: Implications for the Mechanism of Consciousness and General Anesthesia Nature Precedings November 20, 2008
- Estimating the Integrated Information Measure Phi from High-Density Electroencephalography during States of Consciousness in Humans Frontiers in Human Neuroscience February 16, 2018