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Clevenger KR, Dexter F, Epstein RH, Sondekoppam R, Marian AA. Anesthesia Practitioners' Goals for Sevoflurane Minimum Alveolar Concentration at the End of Surgery and the Incidence of Prolonged Extubations: A Prospective and Observational Study. Cureus 2024; 16:e63371. [PMID: 39070308 PMCID: PMC11283767 DOI: 10.7759/cureus.63371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/27/2024] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND Prolonged times to tracheal extubation (≥15 minutes from dressing on the patient) are consequential based on their clinical and economic effect. We evaluated the variability among anesthesia practitioners in their goals for the age-adjusted end-tidal minimum alveolar concentration of sevoflurane (MAC) at surgery end and achievement of their goals. METHODS We prospectively studied a cohort of 56 adult patients undergoing general anesthesia with sevoflurane as the sole anesthetic agent, scheduled operating room time of at least 3 hours, and non-prone positioning. At the start of surgical closure, an observer asked the anesthesia practitioner their goal for MAC when the surgical drapes are lowered (i.e., the functional end of surgery for the studied procedures). When the drapes were lowered, the MAC achieved was recorded, and the values were compared. RESULTS The standard deviation of the practitioners' MAC goal was large, 0.199 (N = 56 cases, 95% confidence interval 0.17-0.24), not significantly different from the standard deviation of the MAC achieved of 0.253, P = 0.071. The MAC goal and MAC achieved were correlated pairwise, Pearson r =0.65, P < 0.0001. There was no incremental effect of operating room conversation(s) related to case progress on the association (partial correlation ‑0.01, P = 0.96). Differences among practitioners in the MAC achieved at surgery end were consequential. Specifically, for the N = 12 cases with prolonged extubation, the mean MAC was 0.60 (standard deviation 0.10) versus 0.48 (0.21) among the N = 44 cases without prolonged extubation (P = 0.0070). CONCLUSIONS The standard deviation of the MAC goal among practitioners was sufficiently large to contribute significantly to the variability in the MAC achieved at the end of surgery. We confirmed prospectively that the age-adjusted end-tidal MAC at the end of surgery matters clinically and economically because differences of 0.60 versus 0.48 were associated with more prolonged extubations. Our novel finding is that the MAC achieved ≥0.60 were caused in part by the anesthesia practitioners' stated MAC goals when surgical closures started.
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Affiliation(s)
| | | | - Richard H Epstein
- Anesthesiology, University of Miami Miller School of Medicine, Miami, USA
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2
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Luo Z, Yin E, Yan Y, Zhao S, Xie L, Shen H, Zeng LL, Wang L, Hu D. Sleep deprivation changes frequency-specific functional organization of the resting human brain. Brain Res Bull 2024; 210:110925. [PMID: 38493835 DOI: 10.1016/j.brainresbull.2024.110925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/13/2024] [Accepted: 03/10/2024] [Indexed: 03/19/2024]
Abstract
Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies have widely explored the temporal connection changes in the human brain following long-term sleep deprivation (SD). However, the frequency-specific topological properties of sleep-deprived functional networks remain virtually unclear. In this study, thirty-seven healthy male subjects underwent resting-state fMRI during rested wakefulness (RW) and after 36 hours of SD, and we examined frequency-specific spectral connection changes (0.01-0.08 Hz, interval = 0.01 Hz) caused by SD. First, we conducted a multivariate pattern analysis combining linear SVM classifiers with a robust feature selection algorithm, and the results revealed that accuracies of 74.29%-84.29% could be achieved in the classification between RW and SD states in leave-one-out cross-validation at different frequency bands, moreover, the spectral connection at the lowest and highest frequency bands exhibited higher discriminative power. Connection involving the cingulo-opercular network increased most, while connection involving the default-mode network decreased most following SD. Then we performed a graph-theoretic analysis and observed reduced low-frequency modularity and high-frequency global efficiency in the SD state. Moreover, hub regions, which were primarily situated in the cerebellum and the cingulo-opercular network after SD, exhibited high discriminative power in the aforementioned classification consistently. The findings may indicate the frequency-dependent effects of SD on the functional network topology and its efficiency of information exchange, providing new insights into the impact of SD on the human brain.
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Affiliation(s)
- Zhiguo Luo
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China; College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Erwei Yin
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China.
| | - Ye Yan
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Shaokai Zhao
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Liang Xie
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Hui Shen
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Lubin Wang
- The Brain Science Center, Beijing Institute of Basic Medical Sciences, Beijing 102206, China
| | - Dewen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China.
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3
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Gervais C, Boucher LP, Villar GM, Lee U, Duclos C. A scoping review for building a criticality-based conceptual framework of altered states of consciousness. Front Syst Neurosci 2023; 17:1085902. [PMID: 37304151 PMCID: PMC10248073 DOI: 10.3389/fnsys.2023.1085902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 05/08/2023] [Indexed: 06/13/2023] Open
Abstract
The healthy conscious brain is thought to operate near a critical state, reflecting optimal information processing and high susceptibility to external stimuli. Conversely, deviations from the critical state are hypothesized to give rise to altered states of consciousness (ASC). Measures of criticality could therefore be an effective way of establishing the conscious state of an individual. Furthermore, characterizing the direction of a deviation from criticality may enable the development of treatment strategies for pathological ASC. The aim of this scoping review is to assess the current evidence supporting the criticality hypothesis, and the use of criticality as a conceptual framework for ASC. Using the PRISMA guidelines, Web of Science and PubMed were searched from inception to February 7th 2022 to find articles relating to measures of criticality across ASC. N = 427 independent papers were initially found on the subject. N = 378 were excluded because they were either: not related to criticality; not related to consciousness; not presenting results from a primary study; presenting model data. N = 49 independent papers were included in the present research, separated in 7 sub-categories of ASC: disorders of consciousness (DOC) (n = 5); sleep (n = 13); anesthesia (n = 18); epilepsy (n = 12); psychedelics and shamanic state of consciousness (n = 4); delirium (n = 1); meditative state (n = 2). Each category included articles suggesting a deviation of the critical state. While most studies were only able to identify a deviation from criticality without being certain of its direction, the preliminary consensus arising from the literature is that non-rapid eye movement (NREM) sleep reflects a subcritical state, epileptic seizures reflect a supercritical state, and psychedelics are closer to the critical state than normal consciousness. This scoping review suggests that, though the literature is limited and methodologically inhomogeneous, ASC are characterized by a deviation from criticality, though its direction is not clearly reported in a majority of studies. Criticality could become, with more extensive research, an effective and objective way to characterize ASC, and help identify therapeutic avenues to improve criticality in pathological brain states. Furthermore, we suggest how anesthesia and psychedelics could potentially be used as neuromodulation techniques to restore criticality in DOC.
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Affiliation(s)
- Charles Gervais
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
| | - Louis-Philippe Boucher
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
- Department of Neuroscience, Université de Montréal, Montréal, QC, Canada
| | - Guillermo Martinez Villar
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
- Department of Biomedical Sciences, Université de Montréal, Montréal, QC, Canada
| | - UnCheol Lee
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Catherine Duclos
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
- Department of Neuroscience, Université de Montréal, Montréal, QC, Canada
- Department of Anesthesiology and Pain Medicine, Université de Montréal, Montréal, QC, Canada
- CIFAR Azrieli Global Scholars Program, Toronto, ON, Canada
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4
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Gilmore‐Bykovskyi A, Griffin JM, Mueller KD, Parnia S, Kolanowski A. Toward harmonization of strategies for investigating lucidity in AD/ADRD: A preliminary research framework. Alzheimers Dement 2023; 19:343-352. [PMID: 35757902 PMCID: PMC9792622 DOI: 10.1002/alz.12709] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 05/11/2022] [Accepted: 05/12/2022] [Indexed: 01/25/2023]
Abstract
Episodes of lucidity (ELs) in Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD), have garnered increasing attention as an important area of research. Efforts to study lucidity suffer from a lack of clear definitional criteria, inconsistent conceptualization, and diverse approaches to operationalizing features of these events. To advance systematic investigation of ELs in AD/ADRD, there is a need for clarity and precision in labeling event attributes, markers, and specific measurement strategies that enable operational harmonization across distinct approaches to investigating the relatively broad and nascent phenomenon. To that end, we propose a preliminary research framework to guide harmonization of approaches to investigating ELs in AD/ADRD. Our goal is to provide an initial schematic that encourages uniform labeling of operational decisions about ELs.
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Affiliation(s)
- Andrea Gilmore‐Bykovskyi
- Department of Emergency Medicine, University of Wisconsin‐Madison School of Medicine & Public HealthMadisonWisconsinUSA
- UW Center for Health Disparities ResearchMadisonWisconsinUSA
| | - Joan M. Griffin
- Division of Health Care Delivery ResearchMayo ClinicRochesterMinnesotaUSA
- Kern Center for the Science of Health Care DeliveryMayo ClinicRochesterMinnesotaUSA
| | - Kimberly D. Mueller
- University of Wisconsin‐Madison Department of Communication Sciences and DisordersMadisonWisconsinUSA
- Division of GeriatricsDepartment of MedicineUniversity of Wisconsin‐Madison School of Medicine & Public HealthMadisonWisconsinUSA
| | - Sam Parnia
- NYU Langone Medical CenterNew York CityNew YorkUSA
| | - Ann Kolanowski
- Penn State Ross and Carol Nese College of NursingState CollegePennsylvaniaUSA
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5
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Crofts JJ, Forrester M, Coombes S, O'Dea RD. Structure-function clustering in weighted brain networks. Sci Rep 2022; 12:16793. [PMID: 36202837 PMCID: PMC9537289 DOI: 10.1038/s41598-022-19994-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 09/07/2022] [Indexed: 11/09/2022] Open
Abstract
Functional networks, which typically describe patterns of activity taking place across the cerebral cortex, are widely studied in neuroscience. The dynamical features of these networks, and in particular their deviation from the relatively static structural network, are thought to be key to higher brain function. The interactions between such structural networks and emergent function, and the multimodal neuroimaging approaches and common analysis according to frequency band motivate a multilayer network approach. However, many such investigations rely on arbitrary threshold choices that convert dense, weighted networks to sparse, binary structures. Here, we generalise a measure of multiplex clustering to describe weighted multiplexes with arbitrarily-many layers. Moreover, we extend a recently-developed measure of structure-function clustering (that describes the disparity between anatomical connectivity and functional networks) to the weighted case. To demonstrate its utility we combine human connectome data with simulated neural activity and bifurcation analysis. Our results indicate that this new measure can extract neurologically relevant features not readily apparent in analogous single-layer analyses. In particular, we are able to deduce dynamical regimes under which multistable patterns of neural activity emerge. Importantly, these findings suggest a role for brain operation just beyond criticality to promote cognitive flexibility.
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Affiliation(s)
- Jonathan J Crofts
- Department of Physics and Mathematics, Nottingham Trent University, Nottingham, NG11 8NS, UK
| | - Michael Forrester
- School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK.
| | - Stephen Coombes
- School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Reuben D O'Dea
- School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
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Mashour GA, Pal D, Brown EN. Prefrontal cortex as a key node in arousal circuitry. Trends Neurosci 2022; 45:722-732. [PMID: 35995629 PMCID: PMC9492635 DOI: 10.1016/j.tins.2022.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 07/02/2022] [Accepted: 07/31/2022] [Indexed: 10/15/2022]
Abstract
The role of the prefrontal cortex (PFC) in the mechanism of consciousness is a matter of active debate. Most theoretical and empirical investigations have focused on whether the PFC is critical for the content of consciousness (i.e., the qualitative aspects of conscious experience). However, there is emerging evidence that, in addition to its well-established roles in cognition, the PFC is a key regulator of the level of consciousness (i.e., the global state of arousal). In this opinion article we review recent data supporting the hypothesis that the medial PFC is a critical node in arousal-promoting networks.
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Affiliation(s)
- George A Mashour
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA; Department of Pharmacology, University of Michigan, Ann Arbor, MI, USA; Center for Consciousness Science, University of Michigan, Ann Arbor, MI, USA; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA; Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, USA.
| | - Dinesh Pal
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA; Center for Consciousness Science, University of Michigan, Ann Arbor, MI, USA; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA; Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, USA; Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Emery N Brown
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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7
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Kim M, Harris RE, DaSilva AF, Lee U. Explosive Synchronization-Based Brain Modulation Reduces Hypersensitivity in the Brain Network: A Computational Model Study. Front Comput Neurosci 2022; 16:815099. [PMID: 35311218 PMCID: PMC8927545 DOI: 10.3389/fncom.2022.815099] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 01/18/2022] [Indexed: 11/29/2022] Open
Abstract
Fibromyalgia (FM) is a chronic pain condition that is characterized by hypersensitivity to multimodal sensory stimuli, widespread pain, and fatigue. We have previously proposed explosive synchronization (ES), a phenomenon wherein a small perturbation to a network can lead to an abrupt state transition, as a potential mechanism of the hypersensitive FM brain. Therefore, we hypothesized that converting a brain network from ES to general synchronization (GS) may reduce the hypersensitivity of FM brain. To find an effective brain network modulation to convert ES into GS, we constructed a large-scale brain network model near criticality (i.e., an optimally balanced state between order and disorders), which reflects brain dynamics in conscious wakefulness, and adjusted two parameters: local structural connectivity and signal randomness of target brain regions. The network sensitivity to global stimuli was compared between the brain networks before and after the modulation. We found that only increasing the local connectivity of hubs (nodes with intense connections) changes ES to GS, reducing the sensitivity, whereas other types of modulation such as decreasing local connectivity, increasing and decreasing signal randomness are not effective. This study would help to develop a network mechanism-based brain modulation method to reduce the hypersensitivity in FM.
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Affiliation(s)
- MinKyung Kim
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Richard E. Harris
- Chronic Pain and Fatigue Research Center, Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
| | - Alexandre F. DaSilva
- Headache & Orofacial Pain Effort Laboratory, Biologic & Materials Sciences Department, University of Michigan School of Dentistry, Ann Arbor, MI, United States
| | - UnCheol Lee
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States
- *Correspondence: UnCheol Lee,
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8
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Abstract
Background: The wakeful brain can easily access and coordinate a large repertoire of different states—dynamics suggestive of “criticality.” Anesthesia causes loss of criticality at the level of electroencephalogram waveforms, but the criticality of brain network connectivity is less well studied. The authors hypothesized that propofol anesthesia is associated with abrupt and divergent changes in brain network connectivity for different frequencies and time scales—characteristic of a phase transition, a signature of loss of criticality. Methods: As part of a previously reported study, 16 volunteers were given propofol in slowly increasing brain concentrations, and their behavioral responsiveness was assessed. The network dynamics from 31-channel electroencephalogram data were calculated from 1 to 20 Hz using four phase and envelope amplitude–based functional connectivity metrics that covered a wide range of time scales from milliseconds to minutes. The authors calculated network global efficiency, clustering coefficient, and statistical complexity (using the Jensen–Shannon divergence) for each functional connectivity metric and compared their findings with those from an in silico Kuramoto network model. Results: The transition to anesthesia was associated with critical slowing and then abrupt profound decreases in global network efficiency of 2 Hz power envelope metrics (from mean ± SD of 0.64 ± 0.15 to 0.29 ± 0.28 absolute value, P < 0.001, for medium; and from 0.47 ± 0.13 to 0.24 ± 0.21, P < 0.001, for long time scales) but with an increase in global network efficiency for 10 Hz weighted phase lag index (from 0.30 ± 0.20 to 0.72 ± 0.06, P < 0.001). Network complexity decreased for both the 10 Hz hypersynchronous (0.44 ± 0.13 to 0.23 ± 0.08, P < 0.001), and the 2 Hz asynchronous (0.73 ± 0.08 to 0.40 ± 0.13, P < 0.001) network states. These patterns of network coupling were consistent with those of the Kuramoto model of an order–disorder phase transition. Conclusions: Around loss of behavioral responsiveness, a small increase in propofol concentrations caused a collapse of long time scale power envelope connectivity and an increase in 10 Hz phase-based connectivity—suggestive of a brain network phase transition. Temporospatial electroencephalographic analysis of brain network dynamics over a wide range of frequencies and time scales in 16 volunteers receiving slowly increasing concentrations of propofol revealed that transition to unresponsiveness was associated with a sudden rise in alpha frequency network phase synchrony anteriorly, but also a transient surge and then loss of network coupling over long (tens of seconds) time scales. Deep anesthesia was characterized by alpha waveform hypersynchrony and slow-wave power envelope dissynchrony across the whole cortex. These observations suggest that propofol anesthesia is associated with a constellation of changes in network connectivity across frequencies and time scales that are signatures of sharp and sudden transitions in the behavior of networks.
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Neurophysiologic Complexity in Children Increases with Developmental Age and Is Reduced by General Anesthesia. Anesthesiology 2021; 135:813-828. [PMID: 34491305 DOI: 10.1097/aln.0000000000003929] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Neurophysiologic complexity in the cortex has been shown to reflect changes in the level of consciousness in adults but remains incompletely understood in the developing brain. This study aimed to address changes in cortical complexity related to age and anesthetic state transitions. This study tested the hypotheses that cortical complexity would (1) increase with developmental age and (2) decrease during general anesthesia. METHODS This was a single-center, prospective, cross-sectional study of healthy (American Society of Anesthesiologists physical status I or II) children (n = 50) of age 8 to 16 undergoing surgery with general anesthesia at Michigan Medicine. This age range was chosen because it reflects a period of substantial brain network maturation. Whole scalp (16-channel), wireless electroencephalographic data were collected from the preoperative period through the recovery of consciousness. Cortical complexity was measured using the Lempel-Ziv algorithm and analyzed during the baseline, premedication, maintenance of general anesthesia, and clinical recovery periods. The effect of spectral power on Lempel-Ziv complexity was analyzed by comparing the original complexity value with those of surrogate time series generated through phase randomization that preserves power spectrum. RESULTS Baseline spatiotemporal Lempel-Ziv complexity increased with age (yr; slope [95% CI], 0.010 [0.004, 0.016]; P < 0.001); when normalized to account for spectral power, there was no significant age effect on cortical complexity (0.001 [-0.004, 0.005]; P = 0.737). General anesthesia was associated with a significant decrease in spatiotemporal complexity (median [25th, 75th]; baseline, 0.660 [0.620, 0.690] vs. maintenance, 0.459 [0.402, 0.527]; P < 0.001), and spatiotemporal complexity exceeded baseline levels during postoperative recovery (0.704 [0.642, 0.745]; P = 0.009). When normalized, there was a similar reduction in complexity during general anesthesia (baseline, 0.913 [0.887, 0.923] vs. maintenance 0.851 [0.823, 0.877]; P < 0.001), but complexity remained significantly reduced during recovery (0.873 [0.840, 0.902], P < 0.001). CONCLUSIONS Cortical complexity increased with developmental age and decreased during general anesthesia. This association remained significant when controlling for spectral changes during anesthetic-induced perturbations in consciousness but not with developmental age. EDITOR’S PERSPECTIVE
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10
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Franciotti R, Moretti DV, Benussi A, Ferri L, Russo M, Carrarini C, Barbone F, Arnaldi D, Falasca NW, Koch G, Cagnin A, Nobili FM, Babiloni C, Borroni B, Padovani A, Onofrj M, Bonanni L. Cortical network modularity changes along the course of frontotemporal and Alzheimer's dementing diseases. Neurobiol Aging 2021; 110:37-46. [PMID: 34847523 DOI: 10.1016/j.neurobiolaging.2021.10.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/07/2021] [Accepted: 10/26/2021] [Indexed: 12/14/2022]
Abstract
Cortical network modularity underpins cognitive functions, so we hypothesized its progressive derangement along the course of frontotemporal (FTD) and Alzheimer's (AD) dementing diseases. EEG was recorded in 18 FTD, 18 AD, and 20 healthy controls (HC). In the FTD and AD patients, the EEG recordings were performed at the prodromal stage of dementia, at the onset of dementia, and three years after the onset of dementia. HC underwent three EEG recordings at 2-3-year time interval. Information flows underlying EEG activity recorded at electrode pairs were estimated by means of Mutual Information (MI) analysis. The functional organization of the cortical network was modelled by means of the Graph theory analysis on MI adjacency matrices. Graph theory analysis showed that the main hub of HC (Parietal area) was lost in FTD patients at onset of dementia, substituted by provincial hubs in frontal leads. No changes in global network organization were found in AD. Despite a progressive cognitive impairment during the FTD and AD progression, only the FTD patients showed a derangement in the cortical network modularity, possibly due to dysfunctions in frontal functional connectivity.
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Affiliation(s)
- Raffaella Franciotti
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Davide V Moretti
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Alberto Benussi
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Laura Ferri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Mirella Russo
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Claudia Carrarini
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Filomena Barbone
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Dario Arnaldi
- Dipartimento di Neuroscienze (DINOGMI), University of Genova, Genoa, Italy; U.O. Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Nicola W Falasca
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Giacomo Koch
- Non Invasive Brain Stimulation Unit/Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Stroke Unit, Department of Neuroscience, Tor Vergata Policlinic, Rome, Italy
| | | | - Flavio M Nobili
- Dipartimento di Neuroscienze (DINOGMI), University of Genova, Genoa, Italy; U.O. Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer," Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino (FR), Cassino, Italy
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Laura Bonanni
- Department of Medicine and Aging Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
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Roy M, Poria S, Hens C. Assortativity-induced explosive synchronization in a complex neuronal network. Phys Rev E 2021; 103:062307. [PMID: 34271687 DOI: 10.1103/physreve.103.062307] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 05/25/2021] [Indexed: 11/07/2022]
Abstract
In this study, we consider a scale-free network of nonidentical Chialvo neurons, coupled through electrical synapses. For sufficiently strong coupling, the system undergoes a transition from completely out of phase synchronized to phase synchronized state. The principal focus of this study is to investigate the effect of the degree of assortativity over the synchronization transition process. It is observed that, depending on assortativity, bistability between two asymptotically stable states allows one to develop a hysteresis loop which transforms the phase transition from second order to first order. An expansion in the area of hysteresis loop is noticeable with increasing degree-degree correlation in the network. Our study also reveals that effective frequencies of nodes simultaneously go through a continuous or sudden transition to the synchronized state with the corresponding phases. Further, we examine the robustness of the results under the effect of network size and average degree, as well as diverse frequency setup. Finally, we investigate the dynamical mechanism in the process of generating explosive synchronization. We observe a significant impact of lower degree nodes behind such phenomena: in a positive assortative network the low degree nodes delay the synchronization transition.
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Affiliation(s)
- Mousumi Roy
- Department of Applied Mathematics, University of Calcutta, 92, A.P.C. Road, Kolkata 700009, India
| | - Swarup Poria
- Department of Applied Mathematics, University of Calcutta, 92, A.P.C. Road, Kolkata 700009, India
| | - Chittaranjan Hens
- Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108, India
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12
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Huels ER, Kim H, Lee U, Bel-Bahar T, Colmenero AV, Nelson A, Blain-Moraes S, Mashour GA, Harris RE. Neural Correlates of the Shamanic State of Consciousness. Front Hum Neurosci 2021; 15:610466. [PMID: 33815077 PMCID: PMC8012721 DOI: 10.3389/fnhum.2021.610466] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 02/25/2021] [Indexed: 12/12/2022] Open
Abstract
Psychedelics have been recognized as model interventions for studying altered states of consciousness. However, few empirical studies of the shamanic state of consciousness, which is anecdotally similar to the psychedelic state, exist. We investigated the neural correlates of shamanic trance using high-density electroencephalography (EEG) in 24 shamanic practitioners and 24 healthy controls during rest, shamanic drumming, and classical music listening, followed by an assessment of altered states of consciousness. EEG data were used to assess changes in absolute power, connectivity, signal diversity, and criticality, which were correlated with assessment measures. We also compared assessment scores to those of individuals in a previous study under the influence of psychedelics. Shamanic practitioners were significantly different from controls in several domains of altered states of consciousness, with scores comparable to or exceeding that of healthy volunteers under the influence of psychedelics. Practitioners also displayed increased gamma power during drumming that positively correlated with elementary visual alterations. Furthermore, shamanic practitioners had decreased low alpha and increased low beta connectivity during drumming and classical music and decreased neural signal diversity in the gamma band during drumming that inversely correlated with insightfulness. Finally, criticality in practitioners was increased during drumming in the low and high beta and gamma bands, with increases in the low beta band correlating with complex imagery and elementary visual alterations. These findings suggest that psychedelic drug-induced and non-pharmacologic alterations in consciousness have overlapping phenomenal traits but are distinct states of consciousness, as reflected by the unique brain-related changes during shamanic trance compared to previous literature investigating the psychedelic state.
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Affiliation(s)
- Emma R. Huels
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, United States
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan, Ann Arbor, MI, United States
| | - Hyoungkyu Kim
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan, Ann Arbor, MI, United States
| | - UnCheol Lee
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, United States
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan, Ann Arbor, MI, United States
| | - Tarik Bel-Bahar
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, United States
| | - Angelo V. Colmenero
- The Graduate Center, City University of New York, New York, NY, United States
| | - Amanda Nelson
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
| | - Stefanie Blain-Moraes
- School of Physical and Occupational Therapy, McGill University, Montreal, QC, Canada
| | - George A. Mashour
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, United States
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan, Ann Arbor, MI, United States
| | - Richard E. Harris
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, United States
- Chronic Pain and Fatigue Research Center, Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
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13
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Bonanni L, Moretti D, Benussi A, Ferri L, Russo M, Carrarini C, Barbone F, Arnaldi D, Falasca NW, Koch G, Cagnin A, Nobili F, Babiloni C, Borroni B, Padovani A, Onofrj M, Franciotti R. Hyperconnectivity in Dementia Is Early and Focal and Wanes with Progression. Cereb Cortex 2020; 31:97-105. [DOI: 10.1093/cercor/bhaa209] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/19/2020] [Accepted: 07/08/2020] [Indexed: 12/14/2022] Open
Abstract
Abstract
We investigated in a longitudinal multicenter cohort study functional cortical connectivity changes along the course of frontotemporal dementia (FTD) and Alzheimer’s disease (AD) from the prodromal stage of the diseases.
Electroencephalography (EEG) was recorded in 18 FTD and 18 AD patients at the prodromal stage of dementia, at dementia onset, and 3 years after dementia onset. Twenty healthy controls (HC) underwent EEG recordings at the same time interval as the patients.
Mutual information (MI) analysis measured the strength of functional network connectivity.
FTD and AD patients showed greater MI at the prodromal stage of dementia (FTD vs. HC P = 2 × 10−8; AD vs. HC P = 4 × 10–3). Local connectivity was higher in left and right frontal areas of FTD (P = 7 × 10−5 and 0.03) and in left and right posterior areas in AD (P = 3 × 10−5 and 5 × 10−5) versus HC.
We showed cortical hyperconnectivity at the prodromal stage of dementia in areas involved in the specific pathological process of FTD (frontal regions) and AD (posterior regions). Hyperconnectivity disappeared during follow-up, thus suggesting that it is an early electrophysiological feature of dementia, potentially useful to identify prodromal FTD and AD.
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Affiliation(s)
- Laura Bonanni
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
| | - Davide Moretti
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Alzheimer Unit, 25125 Brescia, Italy
| | - Alberto Benussi
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, 25040 Brescia, Italy
| | - Laura Ferri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
| | - Mirella Russo
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
| | - Claudia Carrarini
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
| | - Filomena Barbone
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
| | - Dario Arnaldi
- Dipartimento di Neuroscienze (DINOGMI), University of Genova, 16132 Genoa, Italy
- U.O. Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
| | - Nicola Walter Falasca
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
| | - Giacomo Koch
- Non Invasive Brain Stimulation Unit/Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, 00179 Rome, Italy
| | - Annachiara Cagnin
- Stroke Unit, Department of Neuroscience, Tor Vergata Policlinic, 00184 Rome, Italy
- Department of Neurosciences, University of Padua, 35128 Padova, Italy
| | - Flavio Nobili
- Dipartimento di Neuroscienze (DINOGMI), University of Genova, 16132 Genoa, Italy
- U.O. Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, 00185 Rome, Italy
- Hospital San Raffaele Cassino (FR), 03043 Cassino, Italy
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, 25040 Brescia, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, 25040 Brescia, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
| | - Raffaella Franciotti
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d’Annunzio of Chieti-Pescara, 66100 Chieti, Italy
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14
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Kim M, Lee U. Alpha oscillation, criticality, and responsiveness in complex brain networks. Netw Neurosci 2020; 4:155-173. [PMID: 32043048 PMCID: PMC7006877 DOI: 10.1162/netn_a_00113] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 10/29/2019] [Indexed: 12/05/2022] Open
Abstract
Brains in unconsciousness are characterized by significantly limited responsiveness to stimuli. Even during conscious wakefulness, responsiveness is highly dependent on ongoing brain activity, specifically, of alpha oscillations (∼10 Hz). We hypothesized that the variety of brain responses to external stimuli result from the interaction between state-specific and transient alpha oscillations and stimuli. To justify this hypothesis, we simulated various alpha oscillations in the human brain network, modulating criticality (a balanced state between order and disorder), and investigated specific alpha oscillation properties (instantaneous amplitude, phase, and global synchronization) that induce a large or small response. As a result, we found that the alpha oscillations near a critical state show a more complex and long-lasting response, which is more prominent when stimuli are given to globally desynchronized and low-amplitude oscillations. We also found specific phases of alpha oscillation that barely respond to stimuli, which implies the presence of temporal windows in the alpha cycle for a large or small response. The results explain why brain responses are so variable across conscious and unconscious states and across time windows even during conscious wakefulness, and emphasize the importance of considering ongoing alpha oscillations for effective brain stimulation. Responsiveness of the brain varies depending on the brain states (wakefulness, sleep, anesthesia, and traumatic injuries) and even during wakefulness, resulting in various responses to the same stimulus. What makes those different responses across brain states and even across time windows in conscious state? What is an effective way to obtain the largest response to external stimulus? To answer those questions, we simulated various alpha oscillations (∼10 Hz) in a large-scale brain network and found state-specific alpha oscillation properties that show large or small responsiveness. Notably, the results suggest the presence of temporal windows in alpha cycle that inhibit external information integration and emphasize considering the large/small responsiveness conditions for effective brain stimulation.
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Affiliation(s)
- MinKyung Kim
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - UnCheol Lee
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
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15
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Abstract
Integrated information theory (IIT) describes consciousness as information integrated across highly differentiated but irreducible constituent parts in a system. However, in a complex dynamic system such as the brain, the optimal conditions for large integrated information systems have not been elucidated. In this study, we hypothesized that network criticality, a balanced state between a large variation in functional network configuration and a large constraint on structural network configuration, may be the basis of the emergence of a large Φ¯, a surrogate of integrated information. We also hypothesized that as consciousness diminishes, the brain loses network criticality and Φ¯ decreases. We tested these hypotheses with a large-scale brain network model and high-density electroencephalography (EEG) acquired during various levels of human consciousness under general anesthesia. In the modeling study, maximal criticality coincided with maximal Φ¯. The EEG study demonstrated an explicit relationship between Φ¯, criticality, and level of consciousness. The conscious resting state showed the largest Φ¯ and criticality, whereas the balance between variation and constraint in the brain network broke down as the response rate dwindled. The results suggest network criticality as a necessary condition of a large Φ¯ in the human brain.
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16
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Kalitzin S, Petkov G, Suffczynski P, Grigorovsky V, Bardakjian BL, Lopes da Silva F, Carlen PL. Epilepsy as a manifestation of a multistate network of oscillatory systems. Neurobiol Dis 2019; 130:104488. [DOI: 10.1016/j.nbd.2019.104488] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 06/03/2019] [Accepted: 06/04/2019] [Indexed: 12/18/2022] Open
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17
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Paradoxical lucidity: A potential paradigm shift for the neurobiology and treatment of severe dementias. Alzheimers Dement 2019; 15:1107-1114. [DOI: 10.1016/j.jalz.2019.04.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 03/26/2019] [Accepted: 04/03/2019] [Indexed: 01/17/2023]
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18
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Jalan S, Kumar A, Leyva I. Explosive synchronization in frequency displaced multiplex networks. CHAOS (WOODBURY, N.Y.) 2019; 29:041102. [PMID: 31042936 DOI: 10.1063/1.5092226] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 03/21/2019] [Indexed: 06/09/2023]
Abstract
Motivated by the recent multiplex framework of complex networks, in this work, we investigate if explosive synchronization can be induced in the multiplex network of two layers. Using nonidentical Kuramoto oscillators, we show that a sufficient frequency mismatch between two layers of a multiplex network can lead to explosive inter- and intralayer synchronization due to mutual frustration in the completion of the synchronization processes of the layers, generating a hybrid transition without imposing any specific structure-dynamics correlation.
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Affiliation(s)
- Sarika Jalan
- Complex Systems Lab, Discipline of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, 453552 Indore, India
| | - Anil Kumar
- Complex Systems Lab, Discipline of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, 453552 Indore, India
| | - Inmaculada Leyva
- Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain
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19
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Abstract
The heterogeneity of molecular mechanisms, target neural circuits, and neurophysiologic effects of general anesthetics makes it difficult to develop a reliable and drug-invariant index of general anesthesia. No single brain region or mechanism has been identified as the neural correlate of consciousness, suggesting that consciousness might emerge through complex interactions of spatially and temporally distributed brain functions. The goal of this review article is to introduce the basic concepts of networks and explain why the application of network science to general anesthesia could be a pathway to discover a fundamental mechanism of anesthetic-induced unconsciousness. This article reviews data suggesting that reduced network efficiency, constrained network repertoires, and changes in cortical dynamics create inhospitable conditions for information processing and transfer, which lead to unconsciousness. This review proposes that network science is not just a useful tool but a necessary theoretical framework and method to uncover common principles of anesthetic-induced unconsciousness.
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Affiliation(s)
- UnCheol Lee
- From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan
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20
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Eagleman SL, Drover DR. Calculations of consciousness: electroencephalography analyses to determine anesthetic depth. Curr Opin Anaesthesiol 2018; 31:431-438. [PMID: 29847364 DOI: 10.1097/aco.0000000000000618] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
PURPOSE OF REVIEW Electroencephalography (EEG) was introduced into anesthesia practice in the 1990s as a tool to titrate anesthetic depth. However, limitations in current analysis techniques have called into question whether these techniques improve standard of care, or instead call for improved, more ubiquitously applicable measures to assess anesthetic transitions and depth. This review highlights emerging analytical approaches and techniques from neuroscience research that have the potential to better capture anesthetic transitions to provide better measurements of anesthetic depth. RECENT FINDINGS Since the introduction of electroencephalography, neuroscientists, engineers, mathematicians, and clinicians have all been developing new ways of analyzing continuous electrical signals. Collaborations between these fields have proliferated several analytical techniques that demonstrate how anesthetics affect brain dynamics and conscious transitions. Here, we review techniques in the following categories: network science, integration and information, nonlinear dynamics, and artificial intelligence. SUMMARY Up-and-coming techniques have the potential to better clinically define and characterize altered consciousness time points. Such new techniques used alongside traditional measures have the potential to improve depth of anesthesia measurements and enhance an understanding of how the brain is affected by anesthetic agents. However, new measures will be needed to be tested for robustness in real-world environments and on diverse experimental protocols.
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Affiliation(s)
- Sarah L Eagleman
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, California, USA
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21
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Kim H, Moon JY, Mashour GA, Lee U. Mechanisms of hysteresis in human brain networks during transitions of consciousness and unconsciousness: Theoretical principles and empirical evidence. PLoS Comput Biol 2018; 14:e1006424. [PMID: 30161118 PMCID: PMC6135517 DOI: 10.1371/journal.pcbi.1006424] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 09/12/2018] [Accepted: 08/08/2018] [Indexed: 11/18/2022] Open
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. Hysteresis, characterized by distinct forward and reverse phase transitions, is ubiquitous in nature. For example, there are distinct temperatures for water freezing and ice melting. Similarly, it has been found that state transitions related to consciousness exhibit hysteresis. In particular, the concentration of general anesthetics required to achieve loss of consciousness is significantly higher than the concentration at which consciousness is regained. However, it is unknown whether this is trivially reducible to the pharmacology of these drugs or if it is something related to brain function itself. In this study, we took a novel, network-based approach and hypothesized that the hysteresis observed during anesthetic state transitions shares the same underlying mechanism as that observed in non-biological networks. Our computational modeling, analytic study, and high-density human EEG analysis suggest that various hysteresis phenomena during loss and recovery of consciousness can be explained in principled ways by generic network features. Identifying these network mechanisms of hysteresis in the brain also provides a unified framework for understanding the radically different conscious state transitions associated with sleep, anesthesia, and disorders of consciousness.
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Affiliation(s)
- Hyoungkyu Kim
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States of America
| | - Joon-Young Moon
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States of America
| | - George A. Mashour
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States of America
| | - UnCheol Lee
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States of America
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States of America
- * E-mail:
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22
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Avalos-Gaytán V, Almendral JA, Leyva I, Battiston F, Nicosia V, Latora V, Boccaletti S. Emergent explosive synchronization in adaptive complex networks. Phys Rev E 2018; 97:042301. [PMID: 29758636 DOI: 10.1103/physreve.97.042301] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Indexed: 06/08/2023]
Abstract
Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.
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Affiliation(s)
- Vanesa Avalos-Gaytán
- Research Center in Applied Mathematics, Universidad Autónoma de Coahuila, Saltillo, Coahuila 25115, Mexico
| | - Juan A Almendral
- Center for Biomedical Technology, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain and Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain
| | - I Leyva
- Center for Biomedical Technology, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain and Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain
| | - F Battiston
- School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom
| | - V Nicosia
- School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom
| | - V Latora
- School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom
| | - S Boccaletti
- CNR-Institute of Complex Systems, Via Madonna del Piano, 10, 50019 Sesto Fiorentino, Florence, Italy and Embassy of Italy in Israel, Trade Tower, 25 Hamered St., 68125 Tel Aviv, Israel
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23
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Mashour GA, Hudetz AG. Neural Correlates of Unconsciousness in Large-Scale Brain Networks. Trends Neurosci 2018; 41:150-160. [PMID: 29409683 PMCID: PMC5835202 DOI: 10.1016/j.tins.2018.01.003] [Citation(s) in RCA: 97] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2017] [Revised: 12/12/2017] [Accepted: 01/09/2018] [Indexed: 12/21/2022]
Abstract
The biological basis of consciousness is one of the most challenging and fundamental questions in 21st century science. A related pursuit aims to identify the neural correlates and causes of unconsciousness. We review current trends in the investigation of physiological, pharmacological, and pathological states of unconsciousness at the level of large-scale functional brain networks. We focus on the roles of brain connectivity, repertoire, graph-theoretical techniques, and neural dynamics in understanding the functional brain disconnections and reduced complexity that appear to characterize these states. Persistent questions in the field, such as distinguishing true correlates, linking neural scales, and understanding differential recovery patterns, are also addressed.
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Affiliation(s)
- George A Mashour
- Neuroscience Graduate Program, Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, 1500 East Medical Center Drive, Ann Arbor, MI 48109, USA.
| | - Anthony G Hudetz
- Neuroscience Graduate Program, Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, 1500 East Medical Center Drive, Ann Arbor, MI 48109, USA
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24
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Garcia PS, Rothman DL, Fitzpatrick SM. Waking Up to a New Model for Studying Neural Systems: What Emergence from Unconscious States Can Reveal about Brain Organization. Front Syst Neurosci 2017; 11:78. [PMID: 29089871 PMCID: PMC5651010 DOI: 10.3389/fnsys.2017.00078] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 10/03/2017] [Indexed: 12/28/2022] Open
Affiliation(s)
- Paul S Garcia
- Department of Anesthesiology, Emory University, Atlanta, GA, United States.,Anesthesiology and Research Divisions, Atlanta VA Medical Center, Atlanta, GA, United States
| | - Douglas L Rothman
- Department of Biomedical Engineering, Radiology and Biomedical Imaging, Yale University, New Haven, CT, United States
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