1
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Kreuzer M, García PS, Gutierrez R, Purdon PL. For EEG-Guided Anesthesia, We Have to Go Beyond the Index. Anesth Analg 2024; 139:e21-e22. [PMID: 38885144 DOI: 10.1213/ane.0000000000007098] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Affiliation(s)
- Matthias Kreuzer
- Department of Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Munich, Germany,
| | - Paul S García
- Department of Anesthesiology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Rodrigo Gutierrez
- Department of Anesthesia and Perioperative Medicine, University of Chile, Santiago, Chile
| | - Patrick L Purdon
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, California
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2
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Das P, He M, Purdon PL. A dynamic generative model can extract interpretable oscillatory components from multichannel neurophysiological recordings. eLife 2024; 13:RP97107. [PMID: 39146208 PMCID: PMC11326773 DOI: 10.7554/elife.97107] [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] [Indexed: 08/17/2024] Open
Abstract
Modern neurophysiological recordings are performed using multichannel sensor arrays that are able to record activity in an increasingly high number of channels numbering in the 100s to 1000s. Often, underlying lower-dimensional patterns of activity are responsible for the observed dynamics, but these representations are difficult to reliably identify using existing methods that attempt to summarize multivariate relationships in a post hoc manner from univariate analyses or using current blind source separation methods. While such methods can reveal appealing patterns of activity, determining the number of components to include, assessing their statistical significance, and interpreting them requires extensive manual intervention and subjective judgment in practice. These difficulties with component selection and interpretation occur in large part because these methods lack a generative model for the underlying spatio-temporal dynamics. Here, we describe a novel component analysis method anchored by a generative model where each source is described by a bio-physically inspired state-space representation. The parameters governing this representation readily capture the oscillatory temporal dynamics of the components, so we refer to it as oscillation component analysis. These parameters - the oscillatory properties, the component mixing weights at the sensors, and the number of oscillations - all are inferred in a data-driven fashion within a Bayesian framework employing an instance of the expectation maximization algorithm. We analyze high-dimensional electroencephalography and magnetoencephalography recordings from human studies to illustrate the potential utility of this method for neuroscience data.
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Affiliation(s)
- Proloy Das
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, United States
| | - Mingjian He
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, United States
- Department of Psychology, Stanford University, Stanford, United States
| | - Patrick L Purdon
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, United States
- Department of Bioengineering, Stanford University, Stanford, United States
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3
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Bomatter P, Paillard J, Garces P, Hipp J, Engemann DA. Machine learning of brain-specific biomarkers from EEG. EBioMedicine 2024; 106:105259. [PMID: 39106531 DOI: 10.1016/j.ebiom.2024.105259] [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: 01/10/2024] [Revised: 07/05/2024] [Accepted: 07/11/2024] [Indexed: 08/09/2024] Open
Abstract
BACKGROUND Electroencephalography (EEG) has a long history as a clinical tool to study brain function, and its potential to derive biomarkers for various applications is far from exhausted. Machine learning (ML) can guide future innovation by harnessing the wealth of complex EEG signals to isolate relevant brain activity. Yet, ML studies in EEG tend to ignore physiological artefacts, which may cause problems for deriving biomarkers specific to the central nervous system (CNS). METHODS We present a framework for conceptualising machine learning from CNS versus peripheral signals measured with EEG. A signal representation based on Morlet wavelets allowed us to define traditional brain activity features (e.g. log power) and alternative inputs used by state-of-the-art ML approaches based on covariance matrices. Using more than 2600 EEG recordings from large public databases (TUAB, TDBRAIN), we studied the impact of peripheral signals and artefact removal techniques on ML models in age and sex prediction analyses. FINDINGS Across benchmarks, basic artefact rejection improved model performance, whereas further removal of peripheral signals using ICA decreased performance. Our analyses revealed that peripheral signals enable age and sex prediction. However, they explained only a fraction of the performance provided by brain signals. INTERPRETATION We show that brain signals and body signals, both present in the EEG, allow for prediction of personal characteristics. While these results may depend on specific applications, our work suggests that great care is needed to separate these signals when the goal is to develop CNS-specific biomarkers using ML. FUNDING All authors have been working for F. Hoffmann-La Roche Ltd.
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Affiliation(s)
- Philipp Bomatter
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Joseph Paillard
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Pilar Garces
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Jörg Hipp
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Denis-Alexander Engemann
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
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4
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Parada FJ, Grasso-Cladera A, Rossi A, Soto-Icaza P, Arenas-Pérez M, Errázuriz MC. Applied human neuroscience: Fostering and designing inclusive environments with the 3E-Cognition perspective. Eur J Neurosci 2024; 60:4148-4168. [PMID: 39001625 DOI: 10.1111/ejn.16463] [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: 01/03/2024] [Revised: 06/17/2024] [Accepted: 06/26/2024] [Indexed: 08/07/2024]
Abstract
The conventional medical paradigm often focuses on deficits and impairments, failing to capture the rich tapestry of experiences and abilities inherent in neurodiversity conditions. In this article, we introduce the 3E-Cognition perspective, offering a paradigm shift by emphasizing the dynamic interplay between the brain, body, and environment in shaping cognitive processes. The perspective fosters a more inclusive and supportive understanding of neurodiversity, with potential applications across various domains such as education, workplace, and healthcare. We begin by introducing the 3E-Cognition principles: embodied, environmentally scaffolded, and enactive. Then, we explore how the 3E-Cognition perspective can be applied to create inclusive environments and experiences for neurodiverse individuals. We provide examples in the realms of education, workplace, and healthcare. In all of these domains, spaces, methodologies, epistemologies, and roles that cater to diverse needs and strengths can be designed using the 3E principles. Finally, we discuss the challenges and benefits of implementing the 3E-Cognition perspective. We focus on the need for technological advancements and research in complex real-world scenarios; we suggest mobile brain/body imaging is a possible solution. We furthermore highlight the importance of recognizing and valuing the diverse manners of experiencing and interacting with the world, the promotion of diverse well-being, and the facilitation of innovation and creativity. Thus, we conclude that the 3E-Cognition perspective offers a groundbreaking approach to understanding and supporting neurodiversity: by embracing the inherent interconnectedness of the brain, body, and environment, we can create a more inclusive and supportive world.
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Affiliation(s)
- Francisco J Parada
- Centro de Estudios en Neurociencia Humana y Neuropsicología (CENHN), Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
- Escuela de Diseño, Facultad de Arquitectura, Arte y Diseño, Universidad Diego Portales, Santiago, Chile, Salvador Sanfuentes 2221, Santiago, Metropolitan, Chile
| | | | - Alejandra Rossi
- Centro de Estudios en Neurociencia Humana y Neuropsicología (CENHN), Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
| | - Patricia Soto-Icaza
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago, Chile
| | - Maritza Arenas-Pérez
- Centro de Estudios en Neurociencia Humana y Neuropsicología (CENHN), Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
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5
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Brenna CTA, Goldstein BI, Zarate CA, Orser BA. Repurposing General Anesthetic Drugs to Treat Depression: A New Frontier for Anesthesiologists in Neuropsychiatric Care. Anesthesiology 2024; 141:222-237. [PMID: 38856663 DOI: 10.1097/aln.0000000000005037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
During the last 100 years, the role of anesthesiologists in psychiatry has focused primarily on facilitating electroconvulsive therapy and mitigating postoperative delirium and other perioperative neurocognitive disorders. The discovery of the rapid and sustained antidepressant properties of ketamine, and early results suggesting that other general anesthetic drugs (including nitrous oxide, propofol, and isoflurane) have antidepressant properties, has positioned anesthesiologists at a new frontier in the treatment of neuropsychiatric disorders. Moreover, shared interest in understanding the biologic underpinnings of anesthetic drugs as psychotropic agents is eroding traditional academic boundaries between anesthesiology and psychiatry. This article presents a brief overview of anesthetic drugs as novel antidepressants and identifies promising future candidates for the treatment of depression. The authors issue a call to action and outline strategies to foster collaborations between anesthesiologists and psychiatrists as they work toward the common goals of repurposing anesthetic drugs as antidepressants and addressing mood disorders in surgical patients.
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Affiliation(s)
- Connor T A Brenna
- Department of Anesthesiology & Pain Medicine and Department of Physiology, University of Toronto, Toronto, Canada; Perioperative Brain Health Centre, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Benjamin I Goldstein
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry and Department of Pharmacology, University of Toronto, Toronto, Canada
| | - Carlos A Zarate
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Beverley A Orser
- Department of Anesthesiology & Pain Medicine and Department of Physiology, University of Toronto, Toronto, Canada; Perioperative Brain Health Centre, Sunnybrook Health Sciences Centre, Toronto, Canada
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6
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Ensel S, Uhrig L, Ozkirli A, Hoffner G, Tasserie J, Dehaene S, Van De Ville D, Jarraya B, Pirondini E. Transient brain activity dynamics discriminate levels of consciousness during anesthesia. Commun Biol 2024; 7:716. [PMID: 38858589 PMCID: PMC11164921 DOI: 10.1038/s42003-024-06335-x] [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: 10/20/2023] [Accepted: 05/15/2024] [Indexed: 06/12/2024] Open
Abstract
The awake mammalian brain is functionally organized in terms of large-scale distributed networks that are constantly interacting. Loss of consciousness might disrupt this temporal organization leaving patients unresponsive. We hypothesize that characterizing brain activity in terms of transient events may provide a signature of consciousness. For this, we analyze temporal dynamics of spatiotemporally overlapping functional networks obtained from fMRI transient activity across different anesthetics and levels of anesthesia. We first show a striking homology in spatial organization of networks between monkeys and humans, indicating cross-species similarities in resting-state fMRI structure. We then track how network organization shifts under different anesthesia conditions in macaque monkeys. While the spatial aspect of the networks is preserved, their temporal dynamics are highly affected by anesthesia. Networks express for longer durations and co-activate in an anesthetic-specific configuration. Additionally, hierarchical brain organization is disrupted with a consciousness-level-signature role of the default mode network. In conclusion, large-scale brain network temporal dynamics capture differences in anesthetic-specific consciousness-level, paving the way towards a clinical translation of these cortical signature.
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Affiliation(s)
- Scott Ensel
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lynn Uhrig
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Department of Anesthesiology and Critical Care, Necker Hospital, AP-HP, Université Paris Cité, Paris, France
| | - Ayberk Ozkirli
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Guylaine Hoffner
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
| | - Jordy Tasserie
- Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Stanislas Dehaene
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Collège de France, Paris, France
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Béchir Jarraya
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Université Paris-Saclay (UVSQ), Saclay, France
- Neuroscience Pole, Foch Hospital, Suresnes, France
| | - Elvira Pirondini
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.
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7
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Das P, He M, Purdon PL. A dynamic generative model can extract interpretable oscillatory components from multichannel neurophysiological recordings. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.26.550594. [PMID: 37546851 PMCID: PMC10402019 DOI: 10.1101/2023.07.26.550594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Modern neurophysiological recordings are performed using multichannel sensor arrays that are able to record activity in an increasingly high number of channels numbering in the 100's to 1000's. Often, underlying lower-dimensional patterns of activity are responsible for the observed dynamics, but these representations are difficult to reliably identify using existing methods that attempt to summarize multivariate relationships in a post-hoc manner from univariate analyses, or using current blind source separation methods. While such methods can reveal appealing patterns of activity, determining the number of components to include, assessing their statistical significance, and interpreting them requires extensive manual intervention and subjective judgement in practice. These difficulties with component selection and interpretation occur in large part because these methods lack a generative model for the underlying spatio-temporal dynamics. Here we describe a novel component analysis method anchored by a generative model where each source is described by a bio-physically inspired state space representation. The parameters governing this representation readily capture the oscillatory temporal dynamics of the components, so we refer to it as Oscillation Component Analysis (OCA). These parameters - the oscillatory properties, the component mixing weights at the sensors, and the number of oscillations - all are inferred in a data-driven fashion within a Bayesian framework employing an instance of the expectation maximization algorithm. We analyze high-dimensional electroencephalography and magnetoencephalography recordings from human studies to illustrate the potential utility of this method for neuroscience data.
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Affiliation(s)
- Proloy Das
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305
| | - Mingjian He
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305
- epartment of Psychology, Stanford University, Stanford, CA 94305
| | - Patrick L. Purdon
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305
- Department of Bioengineering, Stanford University, Stanford, CA 94305
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8
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Thum JA, Malekmohammadi M, Toker D, Sparks H, Alijanpourotaghsara A, Choi JW, Hudson AE, Monti MM, Pouratian N. Globus pallidus externus drives increase in network-wide alpha power with propofol-induced loss-of-consciousness in humans. Cereb Cortex 2024; 34:bhae243. [PMID: 38850214 PMCID: PMC11161864 DOI: 10.1093/cercor/bhae243] [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: 10/19/2023] [Revised: 05/16/2024] [Accepted: 05/29/2024] [Indexed: 06/10/2024] Open
Abstract
States of consciousness are likely mediated by multiple parallel yet interacting cortico-subcortical recurrent networks. Although the mesocircuit model has implicated the pallidocortical circuit as one such network, this circuit has not been extensively evaluated to identify network-level electrophysiological changes related to loss of consciousness (LOC). We characterize changes in the mesocircuit in awake versus propofol-induced LOC in humans by directly simultaneously recording from sensorimotor cortices (S1/M1) and globus pallidus interna and externa (GPi/GPe) in 12 patients with Parkinson disease undergoing deep brain stimulator implantation. Propofol-induced LOC is associated with increases in local power up to 20 Hz in GPi, 35 Hz in GPe, and 100 Hz in S1/M1. LOC is likewise marked by increased pallidocortical alpha synchrony across all nodes, with increased alpha/low beta Granger causal (GC) flow from GPe to all other nodes. In contrast, LOC is associated with decreased network-wide beta coupling and beta GC from M1 to the rest of the network. Results implicate an important and possibly central role of GPe in mediating LOC-related increases in alpha power, supporting a significant role of the GPe in modulating cortico-subcortical circuits for consciousness. Simultaneous LOC-related suppression of beta synchrony highlights that distinct oscillatory frequencies act independently, conveying unique network activity.
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Affiliation(s)
- Jasmine A Thum
- Department of Neurosurgery, University of California Los Angeles, 300 Stein Plaza, Suite 540, Los Angeles, CA 90095, United States
| | - Mahsa Malekmohammadi
- Department of Neurosurgery, University of California Los Angeles, 300 Stein Plaza, Suite 540, Los Angeles, CA 90095, United States
| | - Daniel Toker
- Department of Psychology, University of California, Los Angeles, 6522 Pritzker Hall, Los Angeles, CA 90095, United States
| | - Hiro Sparks
- Department of Neurosurgery, University of California Los Angeles, 300 Stein Plaza, Suite 540, Los Angeles, CA 90095, United States
| | - Amirreza Alijanpourotaghsara
- Department of Neurological Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd MC8855, Dallas, TX 75390, United States
| | - Jeong Woo Choi
- Department of Neurological Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd MC8855, Dallas, TX 75390, United States
| | - Andrew E Hudson
- Department of Anesthesiology, University of California, Los Angeles, 747 Westwood Plaza, Los Angeles, CA 90095, United States
| | - Martin M Monti
- Department of Neurosurgery, University of California Los Angeles, 300 Stein Plaza, Suite 540, Los Angeles, CA 90095, United States
- Department of Psychology, University of California, Los Angeles, 6522 Pritzker Hall, Los Angeles, CA 90095, United States
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd MC8855, Dallas, TX 75390, United States
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9
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Yi R, Cheng S, Zhong F, Luo D, You Y, Yu T, Wang H, Zhou L, Zhang Y. GABAergic neurons of anterior thalamic reticular nucleus regulate states of consciousness in propofol- and isoflurane-mediated general anesthesia. CNS Neurosci Ther 2024; 30:e14782. [PMID: 38828651 PMCID: PMC11145368 DOI: 10.1111/cns.14782] [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: 02/18/2024] [Revised: 04/22/2024] [Accepted: 05/13/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND The thalamus system plays critical roles in the regulation of reversible unconsciousness induced by general anesthetics, especially the arousal stage of general anesthesia (GA). But the function of thalamus in GA-induced loss of consciousness (LOC) is little known. The thalamic reticular nucleus (TRN) is the only GABAergic neurons-composed nucleus in the thalamus, which is composed of parvalbumin (PV) and somatostatin (SST)-expressing GABAergic neurons. The anterior sector of TRN (aTRN) is indicated to participate in the induction of anesthesia, but the roles remain unclear. This study aimed to reveal the role of the aTRN in propofol and isoflurane anesthesia. METHODS We first set up c-Fos straining to monitor the activity variation of aTRNPV and aTRNSST neurons during propofol and isoflurane anesthesia. Subsequently, optogenetic tools were utilized to activate aTRNPV and aTRNSST neurons to elucidate the roles of aTRNPV and aTRNSST neurons in propofol and isoflurane anesthesia. Electroencephalogram (EEG) recordings and behavioral tests were recorded and analyzed. Lastly, chemogenetic activation of the aTRNPV neurons was applied to confirm the function of the aTRN neurons in propofol and isoflurane anesthesia. RESULTS c-Fos straining showed that both aTRNPV and aTRNSST neurons are activated during the LOC period of propofol and isoflurane anesthesia. Optogenetic activation of aTRNPV and aTRNSST neurons promoted isoflurane induction and delayed the recovery of consciousness (ROC) after propofol and isoflurane anesthesia, meanwhile chemogenetic activation of the aTRNPV neurons displayed the similar effects. Moreover, optogenetic and chemogenetic activation of the aTRN neurons resulted in the accumulated burst suppression ratio (BSR) during propofol and isoflurane GA, although they represented different effects on the power distribution of EEG frequency. CONCLUSION Our findings reveal that the aTRN GABAergic neurons play a critical role in promoting the induction of propofol- and isoflurane-mediated GA.
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Affiliation(s)
- Rulan Yi
- Department of AnesthesiologyAffiliated Hospital of Zunyi Medical UniversityZunyiChina
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Shiyu Cheng
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Fuwang Zhong
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Dan Luo
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Ying You
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Tian Yu
- Department of AnesthesiologyAffiliated Hospital of Zunyi Medical UniversityZunyiChina
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Haiying Wang
- Department of AnesthesiologyAffiliated Hospital of Zunyi Medical UniversityZunyiChina
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Liang Zhou
- Department of AnesthesiologyAffiliated Hospital of Zunyi Medical UniversityZunyiChina
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
| | - Yu Zhang
- Department of AnesthesiologyAffiliated Hospital of Zunyi Medical UniversityZunyiChina
- Key Laboratory of Anesthesia and Organ Protection (Zunyi Medical University), Ministry of EducationZunyi Medical UniversityZunyiChina
- Key Laboratory of Brain ScienceZunyi Medical UniversityZunyiChina
- Guizhou Key Laboratory of Anesthesia and Organ ProtectionZunyi Medical UniversityZunyiChina
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10
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Yuan I, Bong CL, Chao JY. Intraoperative pediatric electroencephalography monitoring: an updated review. Korean J Anesthesiol 2024; 77:289-305. [PMID: 38228393 PMCID: PMC11150110 DOI: 10.4097/kja.23843] [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: 11/17/2023] [Revised: 12/05/2023] [Accepted: 01/16/2024] [Indexed: 01/18/2024] Open
Abstract
Intraoperative electroencephalography (EEG) monitoring under pediatric anesthesia has begun to attract increasing interest, driven by the availability of pediatric-specific EEG monitors and the realization that traditional dosing methods based on patient movement or changes in hemodynamic response often lead to imprecise dosing, especially in younger infants who may experience adverse events (e.g., hypotension) due to excess anesthesia. EEG directly measures the effects of anesthetics on the brain, which is the target end-organ responsible for inducing loss of consciousness. Over the past ten years, research on anesthesia and computational neuroscience has improved our understanding of intraoperative pediatric EEG monitoring and expanded the utility of EEG in clinical practice. We now have better insights into neurodevelopmental changes in the developing pediatric brain, functional connectivity, the use of non-proprietary EEG parameters to guide anesthetic dosing, epileptiform EEG changes during induction, EEG changes from spinal/regional anesthesia, EEG discontinuity, and the use of EEG to improve clinical outcomes. This review article summarizes the recent literature on EEG monitoring in perioperative pediatric anesthesia, highlighting several of the topics mentioned above.
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Affiliation(s)
- Ian Yuan
- Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Choon L. Bong
- Department of Pediatric Anesthesia, KK Women’s and Children’s Hospital, Duke-NUS Medical School, Singapore
| | - Jerry Y. Chao
- Department of Anesthesiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA
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11
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Mintz NB, Andrews N, Pan K, Bessette E, Asaad WF, Sherif M, Rubinos C, Mahta A, Girard TD, Reznik ME. Prevalence of clinical electroencephalography findings in stroke patients with delirium. Clin Neurophysiol 2024; 162:229-234. [PMID: 38548493 PMCID: PMC11185045 DOI: 10.1016/j.clinph.2024.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 02/15/2024] [Accepted: 03/06/2024] [Indexed: 05/19/2024]
Abstract
OBJECTIVE Delirium is an acute cognitive disorder associated with multiple electroencephalographic (EEG) abnormalities in non-neurological patients, though specific EEG characteristics in patients with stroke remain unclear. We aimed to compare the prevalence of EEG abnormalities in stroke patients during delirium episodes with periods that did not correspond to delirium. METHODS We retrospectively analyzed clinical EEG reports for stroke patients who received daily delirium assessments as part of a prospective study. We compared the prevalence of EEG features corresponding to patient-days with vs. without delirium, including focal and generalized slowing, and focal and generalized epileptiform abnormalities (EAs). RESULTS Among 58 patients who received EEGs, there were 192 days of both EEG and delirium monitoring (88% [n = 169] corresponding to delirium). Generalized slowing was significantly more prevalent on days with vs. without delirium (96% vs. 57%, p = 0.03), as were bilateral or generalized EAs (38% vs. 13%, p = 0.03). In contrast, focal slowing (53% vs. 74%, p = 0.11) and focal EAs were less prevalent on days with delirium (38% vs. 48%, p = 0.37), though these differences were not statistically significant. CONCLUSIONS We found a higher prevalence of generalized but not focal EEG abnormalities in stroke patients with delirium. SIGNIFICANCE These findings may reinforce the diffuse nature of delirium-associated encephalopathy, even in patients with discrete structural lesions.
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Affiliation(s)
- Noa B Mintz
- Department of Neurology, Brown University, Alpert Medical School, United States
| | - Nicholas Andrews
- Department of Neurology, Brown University, Alpert Medical School, United States
| | - Kelly Pan
- Department of Neurology, Brown University, Alpert Medical School, United States
| | - Eric Bessette
- Department of Neurology, Brown University, Alpert Medical School, United States
| | - Wael F Asaad
- Department of Neurosurgery, Brown University, Alpert Medical School, United States; Department of Neuroscience, Brown University, United States; Carney Institute for Brain Science, Brown University, United States; Norman Prince Neurosciences Institute, Rhode Island Hospital, United States
| | - Mohamed Sherif
- Carney Institute for Brain Science, Brown University, United States; Norman Prince Neurosciences Institute, Rhode Island Hospital, United States; Department of Psychiatry and Human Behavior, Brown University, Alpert Medical School, United States
| | - Clio Rubinos
- Department of Neurology, University of North Carolina School of Medicine, United States
| | - Ali Mahta
- Department of Neurology, Brown University, Alpert Medical School, United States; Department of Neurosurgery, Brown University, Alpert Medical School, United States; Norman Prince Neurosciences Institute, Rhode Island Hospital, United States
| | - Timothy D Girard
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, United States
| | - Michael E Reznik
- Department of Neurology, Brown University, Alpert Medical School, United States; Department of Neurosurgery, Brown University, Alpert Medical School, United States; Carney Institute for Brain Science, Brown University, United States; Norman Prince Neurosciences Institute, Rhode Island Hospital, United States; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, United States.
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12
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Li Z, Wang P, Han L, Hao X, Mi W, Tong L, Liang Z. Age-dependent coupling characteristics of bilateral frontal EEG during desflurane anesthesia. Physiol Meas 2024; 45:055012. [PMID: 38697205 DOI: 10.1088/1361-6579/ad46e0] [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: 01/10/2023] [Accepted: 05/01/2024] [Indexed: 05/04/2024]
Abstract
Objectives.The purpose of this study is to investigate the age dependence of bilateral frontal electroencephalogram (EEG) coupling characteristics, and find potential age-independent depth of anesthesia monitoring indicators for the elderlies.Approach.We recorded bilateral forehead EEG data from 41 patients (ranged in 19-82 years old), and separated into three age groups: 18-40 years (n= 12); 40-65 years (n= 14), >65 years (n= 15). All these patients underwent desflurane maintained general anesthesia (GA). We analyzed the age-related EEG spectra, phase amplitude coupling (PAC), coherence and phase lag index (PLI) of EEG data in the states of awake, GA, and recovery.Main results.The frontal alpha power shows age dependence in the state of GA maintained by desflurane. Modulation index in slow oscillation-alpha and delta-alpha bands showed age dependence and state dependence in varying degrees, the PAC pattern also became less pronounced with increasing age. In the awake state, the coherence in delta, theta and alpha frequency bands were all significantly higher in the >65 years age group than in the 18-40 years age group (p< 0.05 for three frequency bands). The coherence in alpha-band was significantly enhanced in all age groups in GA (p< 0.01) and then decreased in recovery state. Notably, the PLI in the alpha band was able to significantly distinguish the three states of awake, GA and recovery (p< 0.01) and the results of PLI in delta and theta frequency bands had similar changes to those of coherence.Significance.We found the EEG coupling and synchronization between bilateral forehead are age-dependent. The PAC, coherence and PLI portray this age-dependence. The PLI and coherence based on bilateral frontal EEG functional connectivity measures and PAC based on frontal single-channel are closely associated with anesthesia-induced unconsciousness.
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Affiliation(s)
- Ziyang Li
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, People's Republic of China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, People's Republic of China
| | - Peiqi Wang
- Department of Anesthesiology, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, People's Republic of China
| | - Licheng Han
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, People's Republic of China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, People's Republic of China
| | - Xinyu Hao
- Department of Anesthesiology, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, People's Republic of China
| | - Weidong Mi
- Department of Anesthesiology, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, People's Republic of China
| | - Li Tong
- Department of Anesthesiology, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, People's Republic of China
| | - Zhenhu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, People's Republic of China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, People's Republic of China
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13
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Chen X, Cramer SR, Chan DCY, Han X, Zhang N. Sequential deactivation across the thalamus-hippocampus-mPFC pathway during loss of consciousness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.20.594986. [PMID: 38826282 PMCID: PMC11142108 DOI: 10.1101/2024.05.20.594986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
How consciousness is lost in states such as sleep or anesthesia remains a mystery. To gain insight into this phenomenon, we conducted concurrent recordings of electrophysiology signals in the anterior cingulate cortex and whole-brain functional magnetic resonance imaging (fMRI) in rats exposed to graded propofol, undergoing the transition from consciousness to unconsciousness. Our results reveal that upon the loss of consciousness (LOC), as indicated by the loss of righting reflex, there is a sharp increase in low-frequency power of the electrophysiological signal. Additionally, simultaneously measured fMRI signals exhibit a cascade of deactivation across a pathway including the hippocampus, thalamus, and medial prefrontal cortex (mPFC) surrounding the moment of LOC, followed by a broader increase in brain activity across the cortex during sustained unconsciousness. Furthermore, sliding window analysis demonstrates a temporary increase in synchrony of fMRI signals across the hippocampus-thalamus-mPFC pathway preceding LOC. These data suggest that LOC might be triggered by sequential activities in the hippocampus, thalamus and mPFC, while wide-spread activity increases in other cortical regions commonly observed during anesthesia-induced unconsciousness might be a consequence, rather than a cause of LOC. Taken together, our study identifies a cascade of neural events unfolding as the brain transitions into unconsciousness, offering critical insight into the systems-level neural mechanisms underpinning LOC.
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14
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Mashour GA. Anesthesia and the neurobiology of consciousness. Neuron 2024; 112:1553-1567. [PMID: 38579714 PMCID: PMC11098701 DOI: 10.1016/j.neuron.2024.03.002] [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: 02/02/2024] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 04/07/2024]
Abstract
In the 19th century, the discovery of general anesthesia revolutionized medical care. In the 21st century, anesthetics have become indispensable tools to study consciousness. Here, I review key aspects of the relationship between anesthesia and the neurobiology of consciousness, including interfaces of sleep and anesthetic mechanisms, anesthesia and primary sensory processing, the effects of anesthetics on large-scale functional brain networks, and mechanisms of arousal from anesthesia. I discuss the implications of the data derived from the anesthetized state for the science of consciousness and then conclude with outstanding questions, reflections, and future directions.
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Affiliation(s)
- George A Mashour
- Center for Consciousness Science, Department of Anesthesiology, Department of Pharmacology, Neuroscience Graduate Program, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
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15
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Obert DP, Killing D, Happe T, Tamas P, Altunkaya A, Dragovic SZ, Kreuzer M, Schneider G, Fenzl T. Substance specific EEG patterns in mice undergoing slow anesthesia induction. BMC Anesthesiol 2024; 24:167. [PMID: 38702608 PMCID: PMC11067159 DOI: 10.1186/s12871-024-02552-3] [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: 03/06/2024] [Accepted: 04/26/2024] [Indexed: 05/06/2024] Open
Abstract
The exact mechanisms and the neural circuits involved in anesthesia induced unconsciousness are still not fully understood. To elucidate them valid animal models are necessary. Since the most commonly used species in neuroscience are mice, we established a murine model for commonly used anesthetics/sedatives and evaluated the epidural electroencephalographic (EEG) patterns during slow anesthesia induction and emergence. Forty-four mice underwent surgery in which we inserted a central venous catheter and implanted nine intracranial electrodes above the prefrontal, motor, sensory, and visual cortex. After at least one week of recovery, mice were anesthetized either by inhalational sevoflurane or intravenous propofol, ketamine, or dexmedetomidine. We evaluated the loss and return of righting reflex (LORR/RORR) and recorded the electrocorticogram. For spectral analysis we focused on the prefrontal and visual cortex. In addition to analyzing the power spectral density at specific time points we evaluated the changes in the spectral power distribution longitudinally. The median time to LORR after start anesthesia ranged from 1080 [1st quartile: 960; 3rd quartile: 1080]s under sevoflurane anesthesia to 1541 [1455; 1890]s with ketamine. Around LORR sevoflurane as well as propofol induced a decrease in the theta/alpha band and an increase in the beta/gamma band. Dexmedetomidine infusion resulted in a shift towards lower frequencies with an increase in the delta range. Ketamine induced stronger activity in the higher frequencies. Our results showed substance-specific changes in EEG patterns during slow anesthesia induction. These patterns were partially identical to previous observations in humans, but also included significant differences, especially in the low frequencies. Our study emphasizes strengths and limitations of murine models in neuroscience and provides an important basis for future studies investigating complex neurophysiological mechanisms.
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Affiliation(s)
- David P Obert
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts's General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - David Killing
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
| | - Tom Happe
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
| | - Philipp Tamas
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
| | - Alp Altunkaya
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
| | - Srdjan Z Dragovic
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
| | - Matthias Kreuzer
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
| | - Gerhard Schneider
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany
| | - Thomas Fenzl
- School of Medicine and Health, Department of Anesthesiology and Intensive Care, Technical University of Munich, 81675, Munich, Germany.
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Hight D, Ehrhardt A, Lersch F, Luedi MM, Stüber F, Kaiser HA. Lower alpha frequency of intraoperative frontal EEG is associated with postoperative delirium: A secondary propensity-matched analysis. J Clin Anesth 2024; 93:111343. [PMID: 37995609 DOI: 10.1016/j.jclinane.2023.111343] [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: 08/09/2023] [Revised: 10/23/2023] [Accepted: 11/15/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Postoperative delirium (POD) is a serious complication of surgery, especially in the elderly patient population. It has been proposed that decreasing the amount of anesthetics by titrating to an EEG index will lower POD rate, but clear evidence is missing. A strong age-dependent negative correlation has been reported between the peak oscillatory frequency of alpha waves and end-tidal anesthetic concentration, with older patients generating slower alpha frequencies. We hypothesized, that slower alpha oscillations are associated with a higher rate of POD. METHOD Retrospective analysis of patients` data from a prospective observational study in cardiac surgical patients approved by the Bernese Ethics committee. Frontal EEG was recorded during Isoflurane effect-site concentrations of 0.7 to 0.8 and peak alpha frequency was measured at highest power between 6 and 17 Hz. Delirium was assessed by chart review. Demographic and clinical characteristics were compared between POD and non-POD groups. Selection bias was addressed using nearest neighbor propensity score matching (PSM) for best balance. This incorporated 18 variables, whereas patients with missing variable information or without an alpha oscillation were excluded. RESULT Of the 1072 patients in the original study, 828 were included, 73 with POD, 755 without. PSM allowed 328 patients into the final analysis, 67 with, 261 without POD. Before PSM, 8 variables were significantly different between POD and non-POD groups, none thereafter. Mean peak alpha frequency was significantly lower in the POD in contrast to non-POD group before and after matching (7.9 vs 8.9 Hz, 7.9 vs 8.8 Hz respectively, SD 1.3, p < 0.001). CONCLUSION Intraoperative slower frontal peak alpha frequency is independently associated with POD after cardiac surgery and may be a simple intraoperative neurophysiological marker of a vulnerable brain for POD. Further studies are needed to investigate if there is a causal link between alpha frequency and POD.
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Affiliation(s)
- Darren Hight
- Inselspital, Bern University Hospital, University of Bern, Department of Anaesthesiology & Pain Medicine, Bern, Switzerland
| | - Alexander Ehrhardt
- Inselspital, Bern University Hospital, University of Bern, Department of Anaesthesiology & Pain Medicine, Bern, Switzerland; Hirslanden Clinic Aarau, Center for Anaesthesiology and Intensive Care Medicine, Aarau, Switzerland
| | - Friedrich Lersch
- Inselspital, Bern University Hospital, University of Bern, Department of Anaesthesiology & Pain Medicine, Bern, Switzerland
| | - Markus M Luedi
- Inselspital, Bern University Hospital, University of Bern, Department of Anaesthesiology & Pain Medicine, Bern, Switzerland; Department for Anesthesiology, Intensive, Rescue and Pain medicine, Kantonsspital St Gallen, St Gallen, Switzerland
| | - Frank Stüber
- Inselspital, Bern University Hospital, University of Bern, Department of Anaesthesiology & Pain Medicine, Bern, Switzerland
| | - Heiko A Kaiser
- Inselspital, Bern University Hospital, University of Bern, Department of Anaesthesiology & Pain Medicine, Bern, Switzerland; Hirslanden Clinic Aarau, Center for Anaesthesiology and Intensive Care Medicine, Aarau, Switzerland.
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17
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Pollak M, Leroy S, Röhr V, Brown EN, Spies C, Koch S. Electroencephalogram Biomarkers from Anesthesia Induction to Identify Vulnerable Patients at Risk for Postoperative Delirium. Anesthesiology 2024; 140:979-989. [PMID: 38295384 DOI: 10.1097/aln.0000000000004929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
BACKGROUND Postoperative delirium is a common complication in elderly patients undergoing anesthesia. Even though it is increasingly recognized as an important health issue, the early detection of patients at risk for postoperative delirium remains a challenge. This study aims to identify predictors of postoperative delirium by analyzing frontal electroencephalogram at propofol-induced loss of consciousness. METHODS This prospective, observational single-center study included patients older than 70 yr undergoing general anesthesia for a planned surgery. Frontal electroencephalogram was recorded on the day before surgery (baseline) and during anesthesia induction (1, 2, and 15 min after loss of consciousness). Postoperative patients were screened for postoperative delirium twice daily for 5 days. Spectral analysis was performed using the multitaper method. The electroencephalogram spectrum was decomposed in periodic and aperiodic (correlates to asynchronous spectrum wide activity) components. The aperiodic component is characterized by its offset (y intercept) and exponent (the slope of the curve). Computed electroencephalogram parameters were compared between patients who developed postoperative delirium and those who did not. Significant electroencephalogram parameters were included in a binary logistic regression analysis to predict vulnerability for postoperative delirium. RESULTS Of 151 patients, 50 (33%) developed postoperative delirium. At 1 min after loss of consciousness, postoperative delirium patients demonstrated decreased alpha (postoperative delirium: 0.3 μV2 [0.21 to 0.71], no postoperative delirium: 0.55 μV2 [0.36 to 0.74]; P = 0.019] and beta band power [postoperative delirium: 0.27 μV2 [0.12 to 0.38], no postoperative delirium: 0.38 μV2 [0.25 to 0.48]; P = 0.003) and lower spectral edge frequency (postoperative delirium: 10.45 Hz [5.65 to 15.04], no postoperative delirium: 14.56 Hz [9.51 to 16.65]; P = 0.01). At 15 min after loss of consciousness, postoperative delirium patients displayed a decreased aperiodic offset (postoperative delirium: 0.42 μV2 (0.11 to 0.69), no postoperative delirium: 0.62 μV2 [0.37 to 0.79]; P = 0.004). The logistic regression model predicting postoperative delirium vulnerability demonstrated an area under the curve of 0.73 (0.69 to 0.75). CONCLUSIONS The findings suggest that electroencephalogram markers obtained during loss of consciousness at anesthesia induction may serve as electroencephalogram-based biomarkers to identify at an early time patients at risk of developing postoperative delirium. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Marie Pollak
- Department of Anesthesiology and Operative Intensive Care Medicine, Charité University Medicine Berlin, Berlin, Germany
| | - Sophie Leroy
- Department of Anesthesiology and Operative Intensive Care Medicine, Charité University Medicine Berlin, Berlin, Germany
| | - Vera Röhr
- Neurotechnology Group, Technical University Berlin, Berlin, Germany
| | - Emery Neal Brown
- Harvard-MIT Health Sciences and Technology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts; and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Claudia Spies
- Department of Anesthesiology and Operative Intensive Care Medicine, Charité University Medicine Berlin, Berlin, Germany
| | - Susanne Koch
- Department of Anesthesiology and Operative Intensive Care Medicine, Charité University Medicine Berlin, Berlin, Germany; and Department of Anesthesia, University of Southern Denmark, Odense, Denmark
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Liang Z, Tang B, Chang Y, Wang J, Li D, Li X, Wei C. State-related Electroencephalography Microstate Complexity during Propofol- and Esketamine-induced Unconsciousness. Anesthesiology 2024; 140:935-949. [PMID: 38157438 DOI: 10.1097/aln.0000000000004896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
BACKGROUND Identifying the state-related "neural correlates of consciousness" for anesthetics-induced unconsciousness is challenging. Spatiotemporal complexity is a promising tool for investigating consciousness. The authors hypothesized that spatiotemporal complexity may serve as a state-related but not drug-related electroencephalography (EEG) indicator during an unconscious state induced by different anesthetic drugs (e.g., propofol and esketamine). METHODS The authors recorded EEG from patients with unconsciousness induced by propofol (n = 10) and esketamine (n = 10). Both conventional microstate parameters and microstate complexity were analyzed. Spatiotemporal complexity was constructed by microstate sequences and complexity measures. Two different EEG microstate complexities were proposed to quantify the randomness (type I) and complexity (type II) of the EEG microstate series during the time course of the general anesthesia. RESULTS The coverage and occurrence of microstate E (prefrontal pattern) and the duration of microstate B (right frontal pattern) could distinguish the states of preinduction wakefulness, unconsciousness, and recovery under both anesthetics. Type I EEG microstate complexity based on mean information gain significantly increased from awake to unconsciousness state (propofol: from mean ± SD, 1.562 ± 0.059 to 1.672 ± 0.023, P < 0.001; esketamine: 1.599 ± 0.051 to 1.687 ± 0.013, P < 0.001), and significantly decreased from unconsciousness to recovery state (propofol: 1.672 ± 0.023 to 1.537 ± 0.058, P < 0.001; esketamine: 1.687 ± 0.013 to 1.608 ± 0.028, P < 0.001) under both anesthetics. In contrast, type II EEG microstate fluctuation complexity significantly decreased in the unconscious state under both drugs (propofol: from 2.291 ± 0.771 to 0.782 ± 0.163, P < 0.001; esketamine: from 1.645 ± 0.417 to 0.647 ± 0.252, P < 0.001), and then increased in the recovery state (propofol: 0.782 ± 0.163 to 2.446 ± 0.723, P < 0.001; esketamine: 0.647 ± 0.252 to 1.459 ± 0.264, P < 0.001). CONCLUSIONS Both type I and type II EEG microstate complexities are drug independent. Thus, the EEG microstate complexity measures that the authors proposed are promising tools for building state-related neural correlates of consciousness to quantify anesthetic-induced unconsciousness. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Zhenhu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao, China
| | - Bo Tang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao, China
| | - Yu Chang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao, China
| | - Jing Wang
- Department of Anesthesiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Duan Li
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern, Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Changwei Wei
- Department of Anesthesiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
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Wang TC, Li WY, Lai JCY, Kuo TBJ, Yang CCH. Nociception Effect on Frontal Electroencephalogram Waveform and Phase-Amplitude Coupling in Laparoscopic Surgery. Anesth Analg 2024; 138:1070-1080. [PMID: 37428681 DOI: 10.1213/ane.0000000000006609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
BACKGROUND Electroencephalographic pattern changes during anesthesia reflect the nociception-analgesia balance. Alpha dropout, delta arousal, and beta arousal with noxious stimulation have been described during anesthesia; however, data on the reaction of other electroencephalogram signatures toward nociception are scarce. Analyzing the effects of nociception on different electroencephalogram signatures may help us find new nociception markers in anesthesia and understand the neurophysiology of pain in the brain. This study aimed to analyze the electroencephalographic frequency pattern and phase-amplitude coupling change during laparoscopic surgeries. METHODS This study evaluated 34 patients who underwent laparoscopic surgery. The electroencephalogram frequency band power and phase-amplitude coupling of different frequencies were analyzed across 3 stages of laparoscopy: incision, insufflation, and opioid stages. Repeated-measures analysis of variance with a mixed model and the Bonferroni method for multiple comparisons were used to analyze the changes in the electroencephalogram signatures between the preincision and postincision/postinsufflation/postopioid phases. RESULTS During noxious stimulation, the frequency spectrum showed obvious decreases in the alpha power percentage after the incision (mean ± standard error of the mean [SEM], 26.27 ± 0.44 and 24.37 ± 0.66; P < .001) and insufflation stages (26.27 ± 0.44 and 24.40 ± 0.68; P = .002), which recovered after opioid administration. Further phase-amplitude analyses showed that the modulation index (MI) of the delta-alpha coupling decreased after the incision stage (1.83 ± 0.22 and 0.98 ± 0.14 [MI × 10 3 ]; P < .001), continued to be suppressed during the insufflation stage (1.83 ± 0.22 and 1.17 ± 0.15 [MI × 10 3 ]; P = .044), and recovered after opioid administration. CONCLUSIONS Alpha dropout during noxious stimulation is observed in laparoscopic surgeries under sevoflurane. In addition, the modulation index of delta-alpha coupling decreases during noxious stimulation and recovers after the administration of rescue opioids. Phase-amplitude coupling of the electroencephalogram may be a new approach for evaluating the nociception-analgesia balance during anesthesia.
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Affiliation(s)
- Tzu Chun Wang
- From the Department of Anaesthesia, Taitung MacKay Memorial Hospital, Taitung, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wei Yi Li
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jerry Cheng-Yen Lai
- Department of Medical Research, Taitung MacKay Memorial Hospital, Taitung, Taiwan
- Master Program in Biomedicine, College of Science and Engineering, National Taitung University, Taitung, Taiwan
| | - Terry B J Kuo
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Sleep Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
- Tsoutun Psychiatric Center, Ministry of Health and Welfare, Nantou, Taiwan
| | - Cheryl C H Yang
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Sleep Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
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Martin JC, Liley DTJ, Beer CFLA, Davidson AJ. Topographical Features of Pediatric Electroencephalography during High Initial Concentration Sevoflurane for Inhalational Induction of Anesthesia. Anesthesiology 2024; 140:890-905. [PMID: 38207324 DOI: 10.1097/aln.0000000000004902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
BACKGROUND High-density electroencephalographic (EEG) monitoring remains underutilized in clinical anesthesia, despite its obvious utility in unraveling the profound physiologic impact of these agents on central nervous system functioning. In school-aged children, the routine practice of rapid induction with high concentrations of inspiratory sevoflurane is commonplace, given its favorable efficacy and tolerance profile. However, few studies investigate topographic EEG during the critical timepoint coinciding with loss of responsiveness-a key moment for anesthesiologists in their everyday practice. The authors hypothesized that high initial sevoflurane inhalation would better precipitate changes in brain regions due to inhomogeneities in maturation across three different age groups compared with gradual stepwise paradigms utilized by other investigators. Knowledge of these changes may inform strategies for agent titration in everyday clinical settings. METHODS A total of 37 healthy children aged 5 to 10 yr underwent induction with 4% or greater sevoflurane in high-flow oxygen. Perturbations in anesthetic state were investigated in 23 of these children using 64-channel EEG with the Hjorth Laplacian referencing scheme. Topographical maps illustrated absolute, relative, and total band power across three age groups: 5 to 6 yr (n = 7), 7 to 8 yr (n = 8), and 9 to 10 yr (n = 8). RESULTS Spectral analysis revealed a large shift in total power driven by increased delta oscillations. Well-described topographic patterns of anesthesia, e.g., frontal predominance, paradoxical beta excitation, and increased slow activity, were evident in the topographic maps. However, there were no statistically significant age-related changes in spectral power observed in a midline electrode subset between the groups when responsiveness was lost compared to the resting state. CONCLUSIONS High initial concentration sevoflurane induction causes large-scale topographic effects on the pediatric EEG. Within the minute after unresponsiveness, this dosage may perturb EEG activity in children to an extent where age-related differences are not discernible. EDITOR’S PERSPECTIVE
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Affiliation(s)
| | - David T J Liley
- Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Christopher F L A Beer
- Swinburne University of Technology, Faculty of Science, Engineering, and Technology, Australia
| | - Andrew J Davidson
- Department of Anaesthetics, Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Australia
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Shang Z, Jiang Y, Fang P, Zhu W, Guo J, Li L, Liang Y, Zhang S, Ma S, Mei B, Fan Y, Xie Z, Shen Q, Liu X. The Association of Preoperative Diabetes With Postoperative Delirium in Older Patients Undergoing Major Orthopedic Surgery: A Prospective Matched Cohort Study. Anesth Analg 2024; 138:1031-1042. [PMID: 38335150 DOI: 10.1213/ane.0000000000006893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
BACKGROUND Postoperative delirium (POD) is a common form of postoperative brain dysfunction, especially in the elderly. However, its risk factors remain largely to be determined. This study aimed to investigate whether (1) preoperative diabetes is associated with POD after elective orthopedic surgery and (2) intraoperative frontal alpha power is a mediator of the association between preoperative diabetes and POD. METHODS This was a prospective matched cohort study of patients aged 60 years or more, with a preoperative diabetes who underwent elective orthopedic surgery. Nondiabetic patients were matched 1:1 to diabetic patients in terms of age, sex, and type of surgery. Primary outcome was occurrence of POD, assessed using the 3-minute Diagnostic Confusion Assessment Method (3D-CAM) once daily from 6 pm to 8 pm during the postoperative days 1-7 or until discharge. Secondary outcome was the severity of POD which was assessed for all participants using the short form of the CAM-Severity. Frontal electroencephalogram (EEG) was recorded starting before induction of anesthesia and lasting until discharge from the operating room. Intraoperative alpha power was calculated using multitaper spectral analyses. Mediation analysis was used to estimate the proportion of the association between preoperative diabetes and POD that could be explained by intraoperative alpha power. RESULTS A total of 138 pairs of eligible patients successfully matched 1:1. After enrollment, 6 patients in the diabetes group and 4 patients in the nondiabetes group were excluded due to unavailability of raw EEG data. The final analysis included 132 participants with preoperative diabetes and 134 participants without preoperative diabetes, with a median age of 68 years and 72.6% of patients were female. The incidence of POD was 16.7% (22/132) in patients with preoperative diabetes vs 6.0% (8/134) in patients without preoperative diabetes. Preoperative diabetes was associated with increased odds of POD after adjustment of age, sex, body mass index, education level, hypertension, arrhythmia, coronary heart disease, and history of stroke (odds ratio, 3.2; 95% confidence interval [CI], 1.4-8.0; P = .009). The intraoperative alpha power accounted for an estimated 20% (95% CI, 2.6-60%; P = .021) of the association between diabetes and POD. CONCLUSIONS This study suggests that preoperative diabetes is associated with an increased risk of POD in older patients undergoing major orthopedic surgery, and that low intraoperative alpha power partially mediates such association.
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Affiliation(s)
- Zixiang Shang
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Yu Jiang
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Panpan Fang
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Wenjie Zhu
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Jiaxin Guo
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Lili Li
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Yongjie Liang
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Sichen Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, P.R. China
| | - Shenglan Ma
- Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, Hefei, P.R. China
| | - Bin Mei
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Yinguang Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, P.R. China
| | - Zhongcong Xie
- Geriatric Anesthesia Research Unit, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
| | - Qiying Shen
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
| | - Xuesheng Liu
- From the Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China
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Kim YS, Kim J, Park S, Kim KN, Ha Y, Yi S, Shin DA, Kuh SU, Lee CK, Koo BN, Kim SE. Differential effects of sevoflurane and desflurane on frontal intraoperative electroencephalogram dynamics associated with postoperative delirium. J Clin Anesth 2024; 93:111368. [PMID: 38157663 DOI: 10.1016/j.jclinane.2023.111368] [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: 04/16/2023] [Revised: 11/23/2023] [Accepted: 12/18/2023] [Indexed: 01/03/2024]
Abstract
STUDY OBJECTIVE Intraoperative electroencephalogram (EEG) patterns associated with postoperative delirium (POD) development have been studied, but the differences in EEG recordings between sevoflurane- and desflurane-induced anesthesia have not been clarified. We aimed to distinguish the EEG characteristics of sevoflurane and desflurane in relation to POD development. DESIGN AND PATIENTS We collected frontal four-channel EEG data during the maintenance of anesthesia from 148 elderly patients who received sevoflurane (n = 77) or desflurane (n = 71); 30 patients were diagnosed with delirium postoperatively. The patients were divided into four subgroups based on anesthetics and delirium status: sevoflurane delirium (n = 17), sevoflurane non-delirium (n = 60), desflurane delirium (n = 13), and desflurane non-delirium (n = 58). We compared spectral power, coherence, and pairwise phase consistency (PPC) between sevoflurane and desflurane, and between non-delirium and delirium groups for each anesthetic. MAIN RESULTS In patients without POD, the sevoflurane non-delirium group exhibited higher EEG spectral power across 8.5-35 Hz (99.5% CI bootstrap analysis) and higher PPC from alpha to gamma bands (p < 0.005) compared to the desflurane non-delirium group. Conversely, in patients with POD, no significant EEG differences were observed between the sevoflurane and desflurane delirium groups. For the sevoflurane-induced patients, the sevoflurane delirium group had significantly lower power within 7.5-31.5 Hz (99.5% CI bootstrap analysis), reduced coherence over 8.9-23.8 Hz (99.5% CI bootstrap analysis), and lower PPC values in the alpha band (p < 0.005) compared with the sevoflurane non-delirium group. For the desflurane-induced patients, there were no significant differences in the EEG patterns between delirium and non-delirium groups. CONCLUSIONS In normal patients without POD, sevoflurane demonstrates a higher power spectrum and prefrontal connectivity than desflurane. Furthermore, reduced frontal alpha power, coherence, and connectivity of intraoperative EEG could be associated with an increased risk of POD. These intraoperative EEG characteristics associated with POD are more noticeable in sevoflurane-induced anesthesia than in desflurane-induced anesthesia.
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Affiliation(s)
- Yeon-Su Kim
- Department of Applied Artificial Intelligence, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea
| | - Jeongmin Kim
- Department of Anesthesiology and Pain Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Sujung Park
- Department of Anesthesiology and Pain Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Keung Nyun Kim
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
| | - Yoon Ha
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea; POSTECH Biotech Center, Pohang University of Science and Technology, Pohang, Gyeongbuk 37673, Republic of Korea
| | - Seong Yi
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
| | - Dong Ah Shin
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
| | - Sung Uk Kuh
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
| | - Chang Kyu Lee
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
| | - Bon-Nyeo Koo
- Department of Anesthesiology and Pain Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
| | - Seong-Eun Kim
- Department of Applied Artificial Intelligence, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea.
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Liu J, Zhang W, Hu S, Wu C, Dong K, Wei Q, Wang G, Fang J, Zhang D, Lan M, Zhang F, Sun H. Analysis of Amplitude Modulation of EEG Based on Holo-Hilbert Spectrum Analysis During General Anesthesia. IEEE Trans Biomed Eng 2024; 71:1607-1616. [PMID: 38285584 DOI: 10.1109/tbme.2023.3345942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
OBJECTIVE The study aims to investigate the relationship between amplitude modulation (AM) of EEG and anesthesia depth during general anesthesia. METHODS In this study, Holo-Hilbert spectrum analysis (HHSA) was used to decompose the multichannel EEG signals of 15 patients to obtain the spatial distribution of AM in the brain. Subsequently, HHSA was applied to the prefrontal EEG (Fp1) obtained during general anesthesia surgery in 15 and 34 patients, and the α-θ and α-δ regions of feature (ROFs) were defined in Holo-Hilbert spectrum (HHS) and three features were derived to quantify AM in ROFs. RESULTS During anesthetized phase, an anteriorization of the spatial distribution of AMs of α-carrier in brain was observed, as well as AMs of α-θ and α-δ in the EEG of Fp1. The total power ([Formula: see text]), mean carrier frequency ([Formula: see text]) and mean amplitude frequency ([Formula: see text]) of AMs changed during different anesthesia states. CONCLUSION HHSA can effectively analyze the cross-frequency coupling of EEG during anesthesia and the AM features may be applied to anesthesia monitoring. SIGNIFICANCE The study provides a new perspective for the characterization of brain states during general anesthesia, which is of great significance for exploring new features of anesthesia monitoring.
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24
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Madariaga S, Devia C, Penna A, Egaña JI, Lucero V, Ramírez S, Maldonado F, Ganga M, Valls N, Villablanca N, Stamm T, Purdon PL, Gutiérrez R. Effect of Repeated Exposure to Sevoflurane on Electroencephalographic Alpha Oscillation in Pediatric Patients Undergoing Radiation Therapy: A Prospective Observational Study. J Neurosurg Anesthesiol 2024; 36:125-133. [PMID: 37965706 DOI: 10.1097/ana.0000000000000938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 08/25/2023] [Indexed: 11/16/2023]
Abstract
BACKGROUND Pharmacological tolerance is defined as a decrease in the effect of a drug over time, or the need to increase the dose to achieve the same effect. It has not been established whether repeated exposure to sevoflurane induces tolerance in children. METHODS We conducted an observational study in children younger than 6 years of age scheduled for multiple radiotherapy sessions with sevoflurane anesthesia. To evaluate the development of sevoflurane tolerance, we analyzed changes in electroencephalographic spectral power at induction, across sessions. We fitted individual and group-level linear regression models to evaluate the correlation between the outcomes and sessions. In addition, a linear mixed-effect model was used to evaluate the association between radiotherapy sessions and outcomes. RESULTS Eighteen children were included and the median number of radiotherapy sessions per child was 28 (interquartile range: 10 to 33). There was no correlation between induction time and radiotherapy sessions. At the group level, the linear mixed-effect model showed, in a subgroup of patients, that alpha relative power and spectral edge frequency 95 were inversely correlated with the number of anesthesia sessions. Nonetheless, this subgroup did not differ from the other subjects in terms of age, sex, or the total number of radiotherapy sessions. CONCLUSIONS Our results suggest that children undergoing repeated anesthesia exposure for radiotherapy do not develop tolerance to sevoflurane. However, we found that a group of patients exhibited a reduction in the alpha relative power as a function of anesthetic exposure. These results may have implications that justify further studies.
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Affiliation(s)
- Samuel Madariaga
- Centro Nacional de Inteligencia Artificial (CENIA) Chile
- Department of Neuroscience
| | - Christ Devia
- Centro Nacional de Inteligencia Artificial (CENIA) Chile
- Department of Neuroscience
| | - Antonello Penna
- Centro de Investigación Clínica Avanzada (CICA), Faculty of Medicine, University of Chile
- Department of Anesthesiology and Perioperative Medicine, University of Chile
| | - José I Egaña
- Centro Nacional de Inteligencia Artificial (CENIA) Chile
- Department of Anesthesiology and Perioperative Medicine, University of Chile
| | | | | | - Felipe Maldonado
- Department of Anesthesiology and Perioperative Medicine, University of Chile
| | | | | | | | - Tomás Stamm
- Department of Anesthesia, National Cancer Institute
| | - Patrick L Purdon
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Rodrigo Gutiérrez
- Centro de Investigación Clínica Avanzada (CICA), Faculty of Medicine, University of Chile
- Department of Anesthesiology and Perioperative Medicine, University of Chile
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Coronel-Oliveros C, Medel V, Whitaker GA, Astudillo A, Gallagher D, Z-Rivera L, Prado P, El-Deredy W, Orio P, Weinstein A. Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses. Netw Neurosci 2024; 8:275-292. [PMID: 38562297 PMCID: PMC10927308 DOI: 10.1162/netn_a_00352] [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: 06/22/2023] [Accepted: 11/17/2023] [Indexed: 04/04/2024] Open
Abstract
High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.
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Affiliation(s)
- Carlos Coronel-Oliveros
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Global Brain Health Institute (GBHI), University of California, San Francisco (UCSF), San Francisco, CA, USA and Trinity College Dublin, Dublin, Ireland
- Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Universidad de Valparaíso, Valparaíso, Chile
| | - Vicente Medel
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Brain and Mind Centre, The University of Sydney, Sydney, Australia
- Department of Neuroscience, Universidad de Chile, Santiago, Chile
| | - Grace Alma Whitaker
- Advanced Center for Electrical and Electronics Engineering (AC3E), Federico Santa María Technical University, Valparaíso, Chile
- Chair of Acoustics and Haptics, Technische Universität Dresden, Dresden, Germany
| | - Aland Astudillo
- Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Universidad de Valparaíso, Valparaíso, Chile
- Centro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso, Chile
- NICM Health Research Institute, Western Sydney University, Penrith, New South Wales, Australia
| | - David Gallagher
- School of Psychology, Liverpool John Moores University, Liverpool, England
| | - Lucía Z-Rivera
- Advanced Center for Electrical and Electronics Engineering (AC3E), Federico Santa María Technical University, Valparaíso, Chile
| | - Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Wael El-Deredy
- Advanced Center for Electrical and Electronics Engineering (AC3E), Federico Santa María Technical University, Valparaíso, Chile
- Centro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso, Chile
| | - Patricio Orio
- Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Universidad de Valparaíso, Valparaíso, Chile
- Instituto de Neurociencia, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile
| | - Alejandro Weinstein
- Advanced Center for Electrical and Electronics Engineering (AC3E), Federico Santa María Technical University, Valparaíso, Chile
- Centro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso, Chile
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Baron Shahaf D, Shahaf G. Intraoperative EEG-based monitors: are we looking under the lamppost? Curr Opin Anaesthesiol 2024; 37:177-183. [PMID: 38390951 DOI: 10.1097/aco.0000000000001339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
PURPOSE OF REVIEW While electroencephalogram (EEG)-based depth of anesthesia monitors have been in use clinically for decades, there is still a major debate concerning their efficacy for detecting awareness under anesthesia (AUA). Further utilization of these monitors has also been discussed vividly, for example, reduction of postoperative delirium (POD).It seems that with regard to reducing AUA and POD, these monitors might be applicable, under specific anesthetic protocols. But in other settings, such monitoring might be less contributive and may have a 'built-it glass ceiling'.Recent advances in other venues of electrophysiological monitoring might have a strong theoretical rationale, and early supporting results, to offer a breakthrough out of this metaphorical glass ceiling. The purpose of this review is to present this possibility. RECENT FINDINGS Following previous findings, it might be concluded that for some anesthesia protocols, the prevailing depth of anesthesia monitors may prevent incidences of AUA and POD. However, in other settings, which may involve other anesthesia protocols, or specifically for POD - other perioperative causes, they may not. Attention-related processes measured by easy-to-use real-time electrophysiological markers are becoming feasible, also under anesthesia, and might be applicable for more comprehensive prevention of AUA, POD and possibly other perioperative complications. SUMMARY Attention-related monitoring might have a strong theoretical basis for the prevention of AUA, POD, and potentially other distressing postoperative outcomes, such as stroke and postoperative neurocognitive disorder. There seems to be already some initial supporting evidence in this regard.
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Affiliation(s)
- Dana Baron Shahaf
- Department of Anaesthesia, Rambam Healthcare Campus
- Ruth and Bruce Faculty of Medicine, Technion Israel Institute of Technology
| | - Goded Shahaf
- The Applied Neurophysiology Lab, Rambam Healthcare Campus, Haifa, Israel
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Cui Y, Li Y, Li Q, Huang J, Tan X, Zhan CA. Alpha anteriorization and theta posteriorization during deep sleep. J Neurosci Res 2024; 102:e25325. [PMID: 38562056 DOI: 10.1002/jnr.25325] [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: 05/15/2023] [Revised: 03/06/2024] [Accepted: 03/17/2024] [Indexed: 04/04/2024]
Abstract
Brain states (wake, sleep, general anesthesia, etc.) are profoundly associated with the spatiotemporal dynamics of brain oscillations. Previous studies showed that the EEG alpha power shifted from the occipital cortex to the frontal cortex (alpha anteriorization) after being induced into a state of general anesthesia via propofol. The sleep research literature suggests that slow waves and sleep spindles are generated locally and propagated gradually to different brain regions. Since sleep and general anesthesia are conceptualized under the same framework of consciousness, the present study examines whether alpha anteriorization similarly occurs during sleep and how the EEG power in other frequency bands changes during different sleep stages. The results from the analysis of three polysomnography datasets of 234 participants show consistent alpha anteriorization during the sleep stages N2 and N3, beta anteriorization during stage REM, and theta posteriorization during stages N2 and N3. Although it is known that the neural circuits responsible for sleep are not exactly the same for general anesthesia, the findings of alpha anteriorization in this study suggest that, at macro level, the circuits for alpha oscillations are organized in the similar cortical areas. The spatial shifts of EEG power in different frequency bands during sleep may offer meaningful neurophysiological markers for the level of consciousness.
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Affiliation(s)
- Yue Cui
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Yu Li
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Qiqi Li
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Jing Huang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Xiaodan Tan
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Chang'an A Zhan
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
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Bardon AG, Ballesteros JJ, Brincat SL, Roy JE, Mahnke MK, Ishizawa Y, Brown EN, Miller EK. Convergent effects of different anesthetics are due to changes in phase alignment of cortical oscillations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.20.585943. [PMID: 38562734 PMCID: PMC10983946 DOI: 10.1101/2024.03.20.585943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Many different anesthetics cause loss of responsiveness despite having diverse underlying molecular and circuit actions. To explore the convergent effects of these drugs, we examined how ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, and dexmedetomidine, an α2 adrenergic receptor agonist, affected neural oscillations in the prefrontal cortex of nonhuman primates. Previous work has shown that anesthesia increases phase locking of low-frequency local field potential activity across cortex. We observed similar increases with anesthetic doses of ketamine and dexmedetomidine in the ventrolateral and dorsolateral prefrontal cortex, within and across hemispheres. However, the nature of the phase locking varied between regions. We found that oscillatory activity in different prefrontal subregions within each hemisphere became more anti-phase with both drugs. Local analyses within a region suggested that this finding could be explained by broad cortical distance-based effects, such as a large traveling wave. By contrast, homologous areas across hemispheres increased their phase alignment. Our results suggest that the drugs induce strong patterns of cortical phase alignment that are markedly different from those in the awake state, and that these patterns may be a common feature driving loss of responsiveness from different anesthetic drugs.
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Hermann G, Tödt I, Tagliazucchi E, Todtenhaupt IK, Laufs H, von Wegner F. Propofol Reversibly Attenuates Short-Range Microstate Ordering and 20 Hz Microstate Oscillations. Brain Topogr 2024; 37:329-342. [PMID: 38228923 DOI: 10.1007/s10548-023-01023-1] [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: 05/09/2023] [Accepted: 11/18/2023] [Indexed: 01/18/2024]
Abstract
Microstate sequences summarize the changing voltage patterns measured by electroencephalography, using a clustering approach to reduce the high dimensionality of the underlying data. A common approach is to restrict the pattern matching step to local maxima of the global field power (GFP) and to interpolate the microstate fit in between. In this study, we investigate how the anesthetic propofol affects microstate sequence periodicity and predictability, and how these metrics are changed by interpolation. We performed two frequency analyses on microstate sequences, one based on time-lagged mutual information, the other based on Fourier transform methodology, and quantified the effects of interpolation. Resting-state microstate sequences had a 20 Hz frequency peak related to dominant 10 Hz (alpha) rhythms, and the Fourier approach demonstrated that all five microstate classes followed this frequency. The 20 Hz periodicity was reversibly attenuated under moderate propofol sedation, as shown by mutual information and Fourier analysis. Characteristic microstate frequencies could only be observed in non-interpolated microstate sequences and were masked by smoothing effects of interpolation. Information-theoretic analysis revealed faster microstate dynamics and larger entropy rates under propofol, whereas Shannon entropy did not change significantly. In moderate sedation, active information storage decreased for non-interpolated sequences. Signatures of non-equilibrium dynamics were observed in non-interpolated sequences, but no changes were observed between sedation levels. All changes occurred while subjects were able to perform an auditory perception task. In summary, we show that low dose propofol reversibly increases the randomness of microstate sequences and attenuates microstate oscillations without correlation to cognitive task performance. Microstate dynamics between GFP peaks reflect physiological processes that are not accessible in interpolated sequences.
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Affiliation(s)
- Gesine Hermann
- Department of Neurology, Christian-Albrechts University, University Hospital Schleswig Holstein, Arnold-Heller-Strasse 3, 24105, Kiel, Germany
| | - Inken Tödt
- Institute of Sexual Medicine & Forensic Psychiatry and Psychotherapy, Christian-Albrechts University, Schwanenweg 24, 24105, Kiel, Germany
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
| | - Inga Karin Todtenhaupt
- Department of Neurology, Christian-Albrechts University, University Hospital Schleswig Holstein, Arnold-Heller-Strasse 3, 24105, Kiel, Germany
| | - Helmut Laufs
- Department of Neurology, Christian-Albrechts University, University Hospital Schleswig Holstein, Arnold-Heller-Strasse 3, 24105, Kiel, Germany
| | - Frederic von Wegner
- School of Biomedical Sciences, UNSW, Wallace Wurth Building, Kensington, NSW, 2052, Australia.
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30
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Liang Z, Chang Y, Liu X, Cao S, Chen Y, Wang T, Xu J, Li D, Zhang J. Changes in information integration and brain networks during propofol-, dexmedetomidine-, and ketamine-induced unresponsiveness. Br J Anaesth 2024; 132:528-540. [PMID: 38105166 DOI: 10.1016/j.bja.2023.11.033] [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: 09/23/2022] [Revised: 10/18/2023] [Accepted: 11/07/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Information integration and network science are important theories for quantifying consciousness. However, whether these theories propose drug- or conscious state-related changes in EEG during anaesthesia-induced unresponsiveness remains unknown. METHODS A total of 72 participants were randomised to receive i.v. infusion of propofol, dexmedetomidine, or ketamine at a constant infusion rate until loss of responsiveness. High-density EEG was recorded during the consciousness transition from the eye-closed baseline to the unresponsiveness state and then to the recovery of the responsiveness state. Permutation cross mutual information (PCMI) and PCMI-based brain networks in broadband (0.1-45 Hz) and sub-band frequencies were used to analyse drug- and state-related EEG signature changes. RESULTS PCMI and brain networks exhibited state-related changes in certain brain regions and frequency bands. The within-area PCMI of the frontal, parietal, and occipital regions, and the between-area PCMI of the parietal-occipital region (median [inter-quartile ranges]), baseline vs unresponsive were as follows: 0.54 (0.46-0.58) vs 0.46 (0.40-0.50), 0.58 (0.52-0.60) vs 0.48 (0.44-0.53), 0.54 (0.49-0.59) vs 0.47 (0.42-0.52) decreased during anaesthesia for three drugs (P<0.05). Alpha PCMI in the frontal region, and gamma PCMI in the posterior area significantly decreased in the unresponsive state (P<0.05). The frontal, parietal, and occipital nodal clustering coefficients and parietal nodal efficiency decreased in the unresponsive state (P<0.05). The increased normalised path length in delta, theta, and gamma bands indicated impaired global integration (P<0.05). CONCLUSIONS The three anaesthetics caused changes in information integration patterns and network functions. Thus, it is possible to build a quantifying framework for anaesthesia-induced conscious state changes on the EEG scale using PCMI and network science.
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Affiliation(s)
- Zhenhu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, P.R. China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao, P.R. China
| | - Yu Chang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, P.R. China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao, P.R. China
| | - Xiaoge Liu
- Department of Anaesthesiology, Fudan University Shanghai Cancer Center, Shanghai, P.R. China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China
| | - Shumei Cao
- Department of Anaesthesiology, Fudan University Shanghai Cancer Center, Shanghai, P.R. China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China
| | - Yali Chen
- Department of Anaesthesiology, Fudan University Shanghai Cancer Center, Shanghai, P.R. China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China
| | - Tingting Wang
- Department of Anaesthesiology, Huashan Hospital, Fudan University, Shanghai, P.R. China
| | - Jianghui Xu
- Department of Anaesthesiology, Fudan University Shanghai Cancer Center, Shanghai, P.R. China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China
| | - Duan Li
- Center for Consciousness Science, Department of Anaesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Jun Zhang
- Department of Anaesthesiology, Fudan University Shanghai Cancer Center, Shanghai, P.R. China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China.
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31
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Brake N, Duc F, Rokos A, Arseneau F, Shahiri S, Khadra A, Plourde G. A neurophysiological basis for aperiodic EEG and the background spectral trend. Nat Commun 2024; 15:1514. [PMID: 38374047 PMCID: PMC10876973 DOI: 10.1038/s41467-024-45922-8] [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: 09/06/2023] [Accepted: 02/06/2024] [Indexed: 02/21/2024] Open
Abstract
Electroencephalograms (EEGs) display a mixture of rhythmic and broadband fluctuations, the latter manifesting as an apparent 1/f spectral trend. While network oscillations are known to generate rhythmic EEG, the neural basis of broadband EEG remains unexplained. Here, we use biophysical modelling to show that aperiodic neural activity can generate detectable scalp potentials and shape broadband EEG features, but that these aperiodic signals do not significantly perturb brain rhythm quantification. Further model analysis demonstrated that rhythmic EEG signals are profoundly corrupted by shifts in synapse properties. To examine this scenario, we recorded EEGs of human subjects being administered propofol, a general anesthetic and GABA receptor agonist. Drug administration caused broadband EEG changes that quantitatively matched propofol's known effects on GABA receptors. We used our model to correct for these confounding broadband changes, which revealed that delta power, uniquely, increased within seconds of individuals losing consciousness. Altogether, this work details how EEG signals are shaped by neurophysiological factors other than brain rhythms and elucidates how these signals can undermine traditional EEG interpretation.
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Affiliation(s)
- Niklas Brake
- Quantiative Life Sciences PhD Program, McGill University, Montreal, Canada
- Department of Physiology, McGill University, Montreal, Canada
| | - Flavie Duc
- Department of Anesthesia, McGill University, Montreal, Canada
| | - Alexander Rokos
- Department of Anesthesia, McGill University, Montreal, Canada
| | | | - Shiva Shahiri
- School of Nursing, McGill University, Montreal, Canada
| | - Anmar Khadra
- Department of Physiology, McGill University, Montreal, Canada.
| | - Gilles Plourde
- Department of Anesthesia, McGill University, Montreal, Canada.
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32
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Ryalino C, Sahinovic MM, Drost G, Absalom AR. Intraoperative monitoring of the central and peripheral nervous systems: a narrative review. Br J Anaesth 2024; 132:285-299. [PMID: 38114354 DOI: 10.1016/j.bja.2023.11.032] [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: 05/08/2023] [Revised: 11/03/2023] [Accepted: 11/03/2023] [Indexed: 12/21/2023] Open
Abstract
The central and peripheral nervous systems are the primary target organs during anaesthesia. At the time of the inception of the British Journal of Anaesthesia, monitoring of the central nervous system comprised clinical observation, which provided only limited information. During the 100 yr since then, and particularly in the past few decades, significant progress has been made, providing anaesthetists with tools to obtain real-time assessments of cerebral neurophysiology during surgical procedures. In this narrative review article, we discuss the rationale and uses of electroencephalography, evoked potentials, near-infrared spectroscopy, and transcranial Doppler ultrasonography for intraoperative monitoring of the central and peripheral nervous systems.
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Affiliation(s)
- Christopher Ryalino
- Department of Anaesthesiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Marko M Sahinovic
- Department of Anaesthesiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Gea Drost
- Department of Neurology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands; Department of Neurosurgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Anthony R Absalom
- Department of Anaesthesiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.
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33
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Lin FS, Shih PY, Sung CH, Chou WH, Wu CY. Electroencephalographic spectrogram-guided total intravenous anesthesia using dexmedetomidine and propofol prevents unnecessary anesthetic dosing during craniotomy: a propensity score-matched analysis. Korean J Anesthesiol 2024; 77:122-132. [PMID: 37211766 PMCID: PMC10834723 DOI: 10.4097/kja.23118] [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: 02/15/2023] [Revised: 05/03/2023] [Accepted: 05/15/2023] [Indexed: 05/23/2023] Open
Abstract
BACKGROUND The bispectral index (BIS) may be unreliable to gauge anesthetic depth when dexmedetomidine is administered. By comparison, the electroencephalogram (EEG) spectrogram enables the visualization of the brain response during anesthesia and may prevent unnecessary anesthetic consumption. METHODS This retrospective study included 140 adult patients undergoing elective craniotomy who received total intravenous anesthesia using a combination of propofol and dexmedetomidine infusions. Patients were equally matched to the spectrogram group (maintaining the robust EEG alpha power during surgery) or the index group (maintaining the BIS score between 40 and 60 during surgery) based on the propensity score of age and surgical type. The primary outcome was the propofol dose. Secondary outcome was the postoperative neurological profile. RESULTS Patients in the spectrogram group received significantly less propofol (1585 ± 581 vs. 2314 ± 810 mg, P < 0.001). Fewer patients in the spectrogram group exhibited delayed emergence (1.4% vs. 11.4%, P = 0.033). The postoperative delirium profile was similar between the groups (profile P = 0.227). Patients in the spectrogram group exhibited better in-hospital Barthel's index scores changes (admission state: 83.6 ± 27.6 vs. 91.6 ± 17.1; discharge state: 86.4 ± 24.3 vs. 85.1 ± 21.5; group-time interaction P = 0.008). However, the incidence of postoperative neurological complications was similar between the groups. CONCLUSIONS EEG spectrogram-guided anesthesia prevents unnecessary anesthetic consumption during elective craniotomy. This may also prevent delayed emergence and improve postoperative Barthel index scores.
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Affiliation(s)
- Feng-Sheng Lin
- Department of Anesthesiology, National Taiwan University Hospital, Taipei, Taiwan
| | - Po-Yuan Shih
- Department of Anesthesiology, National Taiwan University Hospital, Taipei, Taiwan
| | - Chao-Hsien Sung
- Department of Anesthesiology, Fu Jen Catholic University Hospital, New Taipei City, Taiwan
| | - Wei-Han Chou
- Department of Anesthesiology, National Taiwan University Hospital, Taipei, Taiwan
| | - Chun-Yu Wu
- Department of Anesthesiology, National Taiwan University Hospital Hsinchu Branch, Hsinchu, Taiwan
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Tauber JM, Brincat SL, Stephen EP, Donoghue JA, Kozachkov L, Brown EN, Miller EK. Propofol-mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy. J Cogn Neurosci 2024; 36:394-413. [PMID: 37902596 PMCID: PMC11161138 DOI: 10.1162/jocn_a_02081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
A critical component of anesthesia is the loss of sensory perception. Propofol is the most widely used drug for general anesthesia, but the neural mechanisms of how and when it disrupts sensory processing are not fully understood. We analyzed local field potential and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of nonhuman primates before and during propofol-mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-related synchronization between brain areas in the local field potential of Awake animals. By contrast, propofol-mediated unconsciousness eliminated stimulus-related synchrony and drastically weakened stimulus responses and information in all brain areas except for auditory cortex, where responses and information persisted. However, we found stimuli occurring during spiking Up states triggered weaker spiking responses than in Awake animals in auditory cortex, and little or no spiking responses in higher order areas. These results suggest that propofol's effect on sensory processing is not just because of asynchronous Down states. Rather, both Down states and Up states reflect disrupted dynamics.
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Affiliation(s)
- John M Tauber
- Massachusetts Institute of Technology, Cambridge, MA
| | | | | | | | - Leo Kozachkov
- Massachusetts Institute of Technology, Cambridge, MA
| | - Emery N Brown
- Massachusetts Institute of Technology, Cambridge, MA
- Massachusetts General Hospital, Boston
- Harvard University, Cambridge, MA
| | - Earl K Miller
- Massachusetts Institute of Technology, Cambridge, MA
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Casey CP, Tanabe S, Farahbakhsh ZZ, Parker M, Bo A, White M, Ballweg T, Mcintosh A, Filbey W, Banks MI, Saalmann YB, Pearce RA, Sanders RD. Evaluation of putative signatures of consciousness using specific definitions of responsiveness, connectedness, and consciousness. Br J Anaesth 2024; 132:300-311. [PMID: 37914581 PMCID: PMC10808836 DOI: 10.1016/j.bja.2023.09.031] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/15/2023] [Accepted: 09/25/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND Understanding the neural correlates of consciousness has important ramifications for the theoretical understanding of consciousness and for clinical anaesthesia. A major limitation of prior studies is the use of responsiveness as an index of consciousness. We identified a collection of measures derived from unresponsive subjects and more specifically their association with consciousness (any subjective experience) or connectedness (specific experience of environmental stimuli). METHODS Using published data generated through the UNderstanding Consciousness Connectedness and Intra-Operative Unresponsiveness Study (NCT03284307), we evaluated 10 previously published resting-state EEG-based measures that were derived using unresponsiveness as a proxy for unconsciousness. Measures were tested across dexmedetomidine and propofol sedation and natural sleep. These markers represent the complexity, connectivity, cross-frequency coupling, graph theory, and power spectrum measures. RESULTS Although many of the proposed markers were associated with consciousness per se (reported subjective experience), none were specific to consciousness alone; rather, each was also associated with connectedness (i.e. awareness of the environment). In addition, multiple markers showed no association with consciousness and were associated only with connectedness. Of the markers tested, loss of normalised-symbolic transfer entropy (front to back) was associated with connectedness across all three experimental conditions, whereas the transition from disconnected consciousness to unconsciousness was associated with significant decreases in permutation entropy and spectral exponent (P<0.05 for all conditions). CONCLUSIONS None of the proposed EEG-based neural correlates of unresponsiveness corresponded solely to consciousness, highlighting the need for a more conservative use of the term (un)consciousness when assessing unresponsive participants. CLINICAL TRIAL REGISTRATION NCT03284307.
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Affiliation(s)
- Cameron P Casey
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA.
| | - Sean Tanabe
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Zahra Z Farahbakhsh
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Margaret Parker
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Amber Bo
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Marissa White
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Tyler Ballweg
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Andrew Mcintosh
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - William Filbey
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Matthew I Banks
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Yuri B Saalmann
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Robert A Pearce
- Department of Anesthesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Robert D Sanders
- Specialty of Anaesthetics & NHMRC Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Camperdown, NSW, Australia; Institute of Academic Surgery, Royal Prince Alfred Hospital, Camperdown, NSW, Australia.
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36
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Zhang Q, Lu H, Wang J, Yang T, Bi W, Zeng Y, Yu B. Hierarchical rhythmic propagation of corticothalamic interactions for consciousness: A computational study. Comput Biol Med 2024; 169:107843. [PMID: 38141448 DOI: 10.1016/j.compbiomed.2023.107843] [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: 03/29/2023] [Revised: 11/22/2023] [Accepted: 12/11/2023] [Indexed: 12/25/2023]
Abstract
Clarifying the mechanisms of loss and recovery of consciousness in the brain is a major challenge in neuroscience, and research on the spatiotemporal organization of rhythms at the brain region scale at different levels of consciousness remains scarce. By applying computational neuroscience, an extended corticothalamic network model was developed in this study to simulate the altered states of consciousness induced by different concentration levels of propofol. The cortex area containing oscillation spread from posterior to anterior in four successive time stages, defining four groups of brain regions. A quantitative analysis showed that hierarchical rhythm propagation was mainly due to heterogeneity in the inter-brain region connections. These results indicate that the proposed model is an anatomically data-driven testbed and a simulation platform with millisecond resolution. It facilitates understanding of activity coordination across multiple areas of the conscious brain and the mechanisms of action of anesthetics in terms of brain regions.
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Affiliation(s)
- Qian Zhang
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Han Lu
- Department of Anesthesiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jihang Wang
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Taoyi Yang
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Weida Bi
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Yi Zeng
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China; Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Buwei Yu
- Department of Anesthesiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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Wasilczuk AZ, Rinehart C, Aggarwal A, Stone ME, Mashour GA, Avidan MS, Kelz MB, Proekt A. Hormonal basis of sex differences in anesthetic sensitivity. Proc Natl Acad Sci U S A 2024; 121:e2312913120. [PMID: 38190526 PMCID: PMC10801881 DOI: 10.1073/pnas.2312913120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 11/20/2023] [Indexed: 01/10/2024] Open
Abstract
General anesthesia-a pharmacologically induced reversible state of unconsciousness-enables millions of life-saving procedures. Anesthetics induce unconsciousness in part by impinging upon sexually dimorphic and hormonally sensitive hypothalamic circuits regulating sleep and wakefulness. Thus, we hypothesized that anesthetic sensitivity should be sex-dependent and modulated by sex hormones. Using distinct behavioral measures, we show that at identical brain anesthetic concentrations, female mice are more resistant to volatile anesthetics than males. Anesthetic sensitivity is bidirectionally modulated by testosterone. Castration increases anesthetic resistance. Conversely, testosterone administration acutely increases anesthetic sensitivity. Conversion of testosterone to estradiol by aromatase is partially responsible for this effect. In contrast, oophorectomy has no effect. To identify the neuronal circuits underlying sex differences, we performed whole brain c-Fos activity mapping under anesthesia in male and female mice. Consistent with a key role of the hypothalamus, we found fewer active neurons in the ventral hypothalamic sleep-promoting regions in females than in males. In humans, we demonstrate that females regain consciousness and recover cognition faster than males after identical anesthetic exposures. Remarkably, while behavioral and neurocognitive measures in mice and humans point to increased anesthetic resistance in females, cortical activity fails to show sex differences under anesthesia in either species. Cumulatively, we demonstrate that sex differences in anesthetic sensitivity are evolutionarily conserved and not reflected in conventional electroencephalographic-based measures of anesthetic depth. This covert resistance to anesthesia may explain the higher incidence of unintended awareness under general anesthesia in females.
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Affiliation(s)
- Andrzej Z. Wasilczuk
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Neuroscience of Unconsciousness and Reanimation Research Alliance, Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA19104
| | - Cole Rinehart
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Neuroscience of Unconsciousness and Reanimation Research Alliance, Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
| | - Adeeti Aggarwal
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Neuroscience of Unconsciousness and Reanimation Research Alliance, Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA19104
| | - Martha E. Stone
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Neuroscience of Unconsciousness and Reanimation Research Alliance, Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA19104
| | - George A. Mashour
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI48105
| | - Michael S. Avidan
- Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO63110
| | - Max B. Kelz
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Neuroscience of Unconsciousness and Reanimation Research Alliance, Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA19104
- Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Alex Proekt
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Neuroscience of Unconsciousness and Reanimation Research Alliance, Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA19104
- Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - ReCCognition Study Group
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA19104
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI48105
- Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO63110
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Ostertag J, Engelhard A, Nuttall R, Aydin D, Schneider G, García PS, Hinzmann D, Sleigh JW, Kratzer S, Kreuzer M. Development of Postanesthesia Care Unit Delirium Is Associated with Differences in Aperiodic and Periodic Alpha Parameters of the Electroencephalogram during Emergence from General Anesthesia: Results from a Prospective Observational Cohort Study. Anesthesiology 2024; 140:73-84. [PMID: 37815856 DOI: 10.1097/aln.0000000000004797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/11/2023]
Abstract
BACKGROUND Intraoperative alpha-band power in frontal electrodes may provide helpful information about the balance of hypnosis and analgesia and has been associated with reduced occurrence of delirium in the postanesthesia care unit. Recent studies suggest that narrow-band power computations from neural power spectra can benefit from separating periodic and aperiodic components of the electroencephalogram. This study investigates whether such techniques are more useful in separating patients with and without delirium in the postanesthesia care unit at the group level as opposed to conventional power spectra. METHODS Intraoperative electroencephalography recordings of 32 patients who developed perioperative neurocognitive disorders and 137 patients who did not were considered in this post hoc secondary analysis. The power spectra were calculated using conventional methods and the "fitting oscillations and one over f" algorithm was applied to separate aperiodic and periodic components to see whether the electroencephalography signature is different between groups. RESULTS At the group level, patients who did not develop perioperative neurocognitive disorders presented with significantly higher alpha-band power and a broadband increase in power, allowing a "fair" separation based on conventional power spectra. Within the first third of emergence, the difference in median absolute alpha-band power amounted to 8.53 decibels (area under the receiver operator characteristics curve, 0.74 [0.65; 0.82]), reaching its highest value. In relative terms, the best separation was achieved in the second third of emergence, with a difference in medians of 7.71% (area under the receiver operator characteristics curve, 0.70 [0.61; 0.79]). The area under the receiver operator characteristics curve values were generally lower toward the end of emergence with increasing arousal. CONCLUSIONS Increased alpha-band power during emergence in patients who did not develop perioperative neurocognitive disorders can be traced back to an increase in oscillatory alpha activity and an overall increase in aperiodic broadband power. Although the differences between patients with and without perioperative neurocognitive disorders can be detected relying on traditional methods, the separation of the signal allows a more detailed analysis. This may enable clinicians to detect patients at risk for developing perioperative neurocognitive disorders in the postanesthesia care unit early in the emergence phase. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Julian Ostertag
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
| | - Antonia Engelhard
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
| | - Rachel Nuttall
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
| | - Duygu Aydin
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
| | - Gerhard Schneider
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
| | - Paul S García
- Department of Anesthesiology, Columbia University, New York, New York
| | - Dominik Hinzmann
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
| | - Jamie W Sleigh
- Department of Anesthesiology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Stephan Kratzer
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
| | - Matthias Kreuzer
- Department of Anesthesiology and Intensive Care, Technical University of Munich - School of Medicine, Munich, Germany
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Zhang M, Chen Y, Xu T, Jiang J, Zhang D, Huang H, Kurth CD, Yuan I, Wang R, Liu J, Zhu T, Zhou C. γ-Aminobutyric Acid-Ergic Development Contributes to the Enhancement of Electroencephalogram Slow-Delta Oscillations Under Volatile Anesthesia in Neonatal Rats. Anesth Analg 2024; 138:198-209. [PMID: 36753442 DOI: 10.1213/ane.0000000000006396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
BACKGROUND General anesthetics (eg, propofol and volatile anesthetics) enhance the slow-delta oscillations of the cortical electroencephalogram (EEG), which partly results from the enhancement of (γ-aminobutyric acid [GABA]) γ-aminobutyric acid-ergic (GABAergic) transmission. There is a GABAergic excitatory-inhibitory shift during postnatal development. Whether general anesthetics can enhance slow-delta oscillations in the immature brain has not yet been unequivocally determined. METHODS Perforated patch-clamp recording was used to confirm the reversal potential of GABAergic currents throughout GABAergic development in acute brain slices of neonatal rats. The power density of the electrocorticogram and the minimum alveolar concentrations (MAC) of isoflurane and/or sevoflurane were measured in P4-P21 rats. Then, the effects of bumetanide, an inhibitor of the Na + -K + -2Cl - cotransporter (NKCC1) and K + -Cl - cotransporter (KCC2) knockdown on the potency of volatile anesthetics and the power density of the EEG were determined in vivo. RESULTS Reversal potential of GABAergic currents were gradually hyperpolarized from P4 to P21 in cortical pyramidal neurons. Bumetanide enhanced the hypnotic effects of volatile anesthetics at P5 (for MAC LORR , isoflurane: 0.63% ± 0.07% vs 0.81% ± 0.05%, 95% confidence interval [CI], -0.257 to -0.103, P < .001; sevoflurane: 1.46% ± 0.12% vs 1.66% ± 0.09%, 95% CI, -0.319 to -0.081, P < .001); while knockdown of KCC2 weakened their hypnotic effects at P21 in rats (for MAC LORR , isoflurane: 0.58% ± 0.05% to 0.77% ± 0.20%, 95% CI, 0.013-0.357, P = .003; sevoflurane: 1.17% ± 0.04% to 1.33% ± 0.04%, 95% CI, 0.078-0.244, P < .001). For cortical EEG, slow-delta oscillations were the predominant components of the EEG spectrum in neonatal rats. Isoflurane and/or sevoflurane suppressed the power density of slow-delta oscillations rather than enhancement of it until GABAergic maturity. Enhancement of slow-delta oscillations under volatile anesthetics was simulated by preinjection of bumetanide at P5 (isoflurane: slow-delta changed ratio from -0.31 ± 0.22 to 1.57 ± 1.15, 95% CI, 0.67-3.08, P = .007; sevoflurane: slow-delta changed ratio from -0.46 ± 0.25 to 0.95 ± 0.97, 95% CI, 0.38-2.45, P = .014); and suppressed by KCC2-siRNA at P21 (isoflurane: slow-delta changed ratio from 16.13 ± 5.69 to 3.98 ± 2.35, 95% CI, -18.50 to -5.80, P = .002; sevoflurane: slow-delta changed ratio from 0.13 ± 2.82 to 3.23 ± 2.49, 95% CI, 3.02-10.79, P = .003). CONCLUSIONS Enhancement of cortical EEG slow-delta oscillations by volatile anesthetics may require mature GABAergic inhibitory transmission during neonatal development.
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Affiliation(s)
- Mingyue Zhang
- From the Department of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
- Laboratory of Anesthesia and Critical Care Medicine, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yali Chen
- From the Department of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
- Laboratory of Anesthesia and Critical Care Medicine, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
| | - Ting Xu
- Department of Anesthesiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingyao Jiang
- From the Department of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
- Laboratory of Anesthesia and Critical Care Medicine, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
| | - Donghang Zhang
- From the Department of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
- Laboratory of Anesthesia and Critical Care Medicine, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
| | - Han Huang
- Department of Anesthesiology, West China Second Hospital of Sichuan University, Chengdu, China
| | - Charles D Kurth
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Ian Yuan
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Rurong Wang
- From the Department of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
| | - Jin Liu
- From the Department of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
- Laboratory of Anesthesia and Critical Care Medicine, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
| | - Tao Zhu
- From the Department of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
| | - Cheng Zhou
- Laboratory of Anesthesia and Critical Care Medicine, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital of Sichuan University, Chengdu, China
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Dragovic S, Schneider G, García PS, Hinzmann D, Sleigh J, Kratzer S, Kreuzer M. Predictors of Low Risk for Delirium during Anesthesia Emergence. Anesthesiology 2023; 139:757-768. [PMID: 37616326 DOI: 10.1097/aln.0000000000004754] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
BACKGROUND Processed electroencephalography (EEG) is used to monitor the level of anesthesia, and it has shown the potential to predict the occurrence of delirium. While emergence trajectories of relative EEG band power identified post hoc show promising results in predicting a risk for a delirium, they are not easily transferable into an online predictive application. This article describes a low-resource and easily applicable method to differentiate between patients at high risk and low risk for delirium, with patients at low risk expected to show decreasing EEG power during emergence. METHODS This study includes data from 169 patients (median age, 61 yr [49, 73]) who underwent surgery with general anesthesia maintained with propofol, sevoflurane, or desflurane. The data were derived from a previously published study. The investigators chose a single frontal channel, calculated the total and spectral band power from the EEG and calculated a linear regression model to observe the parameters' change during anesthesia emergence, described as slope. The slope of total power and single band power was correlated with the occurrence of delirium. RESULTS Of 169 patients, 32 (19%) showed delirium. Patients whose total EEG power diminished the most during emergence were less likely to screen positive for delirium in the postanesthesia care unit. A positive slope in total power and band power evaluated by using a regression model was associated with a higher risk ratio (total, 2.83 [95% CI, 1.46 to 5.51]; alpha/beta band, 7.79 [95% CI, 2.24 to 27.09]) for delirium. Furthermore, a negative slope in multiple bands during emergence was specific for patients without delirium and allowed definition of a test for patients at low risk. CONCLUSIONS This study developed an easily applicable exploratory method to analyze a single frontal EEG channel and to identify patterns specific for patients at low risk for delirium. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Srdjan Dragovic
- Department for Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany
| | - Gerhard Schneider
- Department for Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany
| | - Paul S García
- Department of Anesthesiology, Columbia University, New York, New York
| | - Dominik Hinzmann
- Department for Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jamie Sleigh
- Waikato Clinical Campus, University of Auckland, Auckland, New Zealand
| | - Stephan Kratzer
- Department for Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany; and Hessing Clinic for Anesthesiology, Intensive Care and Pain Medicine, Augsburg, Germany
| | - Matthias Kreuzer
- Department for Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany
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Santa Cruz Mercado LA, Lee JM, Liu R, Deng H, Johnson JJ, Chen AL, He M, Chung ER, Bharadwaj KM, Houle TT, Purdon PL, Liu CA. Age-Dependent Electroencephalogram Features in Infants Under Spinal Anesthesia Appear to Mirror Physiologic Sleep in the Developing Brain: A Prospective Observational Study. Anesth Analg 2023; 137:1241-1249. [PMID: 36881544 DOI: 10.1213/ane.0000000000006410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
BACKGROUND Infants under spinal anesthesia appear to be sedated despite the absence of systemic sedative medications. In this prospective observational study, we investigated the electroencephalogram (EEG) of infants under spinal anesthesia and hypothesized that we would observe EEG features similar to those seen during sleep. METHODS We computed the EEG power spectra and spectrograms of 34 infants undergoing infraumbilical surgeries under spinal anesthesia (median age 11.5 weeks postmenstrual age, range 38-65 weeks postmenstrual age). Spectrograms were visually scored for episodes of EEG discontinuity or spindle activity. We characterized the relationship between EEG discontinuity or spindles and gestational age, postmenstrual age, or chronological age using logistic regression analyses. RESULTS The predominant EEG patterns observed in infants under spinal anesthesia were slow oscillations, spindles, and EEG discontinuities. The presence of spindles, observed starting at about 49 weeks postmenstrual age, was best described by postmenstrual age ( P =.002) and was more likely with increasing postmenstrual age. The presence of EEG discontinuities, best described by gestational age ( P = .015), was more likely with decreasing gestational age. These age-related changes in the presence of spindles and EEG discontinuities in infants under spinal anesthesia generally corresponded to developmental changes in the sleep EEG. CONCLUSIONS This work illustrates 2 separate key age-dependent transitions in EEG dynamics during infant spinal anesthesia that may reflect the maturation of underlying brain circuits: (1) diminishing discontinuities with increasing gestational age and (2) the appearance of spindles with increasing postmenstrual age. The similarity of these age-dependent transitions under spinal anesthesia with transitions in the developing brain during physiological sleep supports a sleep-related mechanism for the apparent sedation observed during infant spinal anesthesia.
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Affiliation(s)
- Laura A Santa Cruz Mercado
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Johanna M Lee
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Ran Liu
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Hao Deng
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Jasmine J Johnson
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Andrew L Chen
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Mingjian He
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Evan R Chung
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Kishore M Bharadwaj
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Timothy T Houle
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Patrick L Purdon
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Chang A Liu
- From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
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Zhang Y, Wang Y, Cheng H, Yan F, Li D, Song D, Wang Q, Huang L. EEG spectral slope: A reliable indicator for continuous evaluation of consciousness levels during propofol anesthesia. Neuroimage 2023; 283:120426. [PMID: 37898378 DOI: 10.1016/j.neuroimage.2023.120426] [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: 07/11/2023] [Revised: 10/17/2023] [Accepted: 10/25/2023] [Indexed: 10/30/2023] Open
Abstract
The level of consciousness undergoes continuous alterations during anesthesia. Prior to the onset of propofol-induced complete unconsciousness, degraded levels of behavioral responsiveness can be observed. However, a reliable index to monitor altered consciousness levels during anesthesia has not been sufficiently investigated. In this study, we obtained 60-channel EEG data from 24 healthy participants during an ultra-slow propofol infusion protocol starting with an initial concentration of 1 μg/ml and a stepwise increase of 0.2 μg/ml in concentration. Consecutive auditory stimuli were delivered every 5 to 6 s, and the response time to the stimuli was used to assess the responsiveness levels. We calculated the spectral slope in a time-resolved manner by extracting 5-second EEG segments at each auditory stimulus and estimated their correlation with the corresponding response time. Our results demonstrated that during slow propofol infusion, the response time to external stimuli increased, while the EEG spectral slope, fitted at 15-45 Hz, became steeper, and a significant negative correlation was observed between them. Moreover, the spectral slope further steepened at deeper anesthetic levels and became flatter during anesthesia recovery. We verified these findings using an external dataset. Additionally, we found that the spectral slope of frontal electrodes over the prefrontal lobe had the best performance in predicting the response time. Overall, this study used a time-resolved analysis to suggest that the EEG spectral slope could reliably track continuously altered consciousness levels during propofol anesthesia. Furthermore, the frontal spectral slope may be a promising index for clinical monitoring of anesthesia depth.
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Affiliation(s)
- Yun Zhang
- School of Life Science and Technology, Xidian University, No.2 TaiBai South Road, Xi'an 710061, China
| | - Yubo Wang
- School of Life Science and Technology, Xidian University, No.2 TaiBai South Road, Xi'an 710061, China
| | - Huanhuan Cheng
- School of Life Science and Technology, Xidian University, No.2 TaiBai South Road, Xi'an 710061, China
| | - Fei Yan
- Department of Anesthesiology & Center for Brain Science, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 Yanta West Road, Xi'an 710061, China
| | - Dingning Li
- School of Life Science and Technology, Xidian University, No.2 TaiBai South Road, Xi'an 710061, China
| | - Dawei Song
- Department of Anesthesiology & Center for Brain Science, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 Yanta West Road, Xi'an 710061, China
| | - Qiang Wang
- Department of Anesthesiology & Center for Brain Science, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 Yanta West Road, Xi'an 710061, China.
| | - Liyu Huang
- School of Life Science and Technology, Xidian University, No.2 TaiBai South Road, Xi'an 710061, China.
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Kinoshita H, Saito J, Kushikata T, Oyama T, Takekawa D, Hashiba E, Sawa T, Hirota K. The Perioperative Frontal Relative Ratio of the Alpha Power of Electroencephalography for Predicting Postoperative Delirium After Highly Invasive Surgery: A Prospective Observational Study. Anesth Analg 2023; 137:1279-1288. [PMID: 36917508 DOI: 10.1213/ane.0000000000006424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/15/2023]
Abstract
BACKGROUND We investigated the associations between postoperative delirium (POD) and both the relative ratio of the alpha (α)-power of electroencephalography (EEG) and inflammatory markers in a prospective, single-center observational study. METHODS We enrolled 84 patients who underwent radical cancer surgeries with reconstruction for esophageal cancer, oral floor cancer, or pharyngeal cancer under total intravenous anesthesia. We collected the perioperative EEG data and the perioperative data of the inflammatory markers, including neutrophil gelatinase-associated lipocalin, presepsin, procalcitonin, C-reactive protein, and the neutrophil-lymphocyte ratio (NLR). The existence of POD was evaluated based on the Intensive Care Delirium Screening Checklist. We compared the time-dependent changes in the relative ratio of the EEG α-power and inflammatory markers between the patients with and without POD. RESULTS Four of the 84 patients were excluded from the analysis. Of the remaining 80 patients, 25 developed POD and the other 55 did not. The relative ratio of the α-power at baseline was significantly lower in the POD group than the non-POD group (0.18 ± 0.08 vs 0.28 ± 0.11, P < .001). A time-dependent decline in the relative ratio of α-power in the EEG during surgery was observed in both groups. There were significant differences between the POD and non-POD groups in the baseline, 3-h, 6-h, and 9-h values of the relative ratio of α-power. The preoperative NLR of the POD group was significantly higher than that of the non-POD group (2.88 ± 1.04 vs 2.22 ± 1.00, P < .001), but other intraoperative inflammatory markers were comparable between the groups. Two multivariable logistic regression models demonstrated that the relative ratio of the α-power at baseline was significantly associated with POD. CONCLUSIONS Intraoperative frontal relative ratios of the α-power of EEG were associated with POD in patients who underwent radical cancer surgery. Intraoperative EEG monitoring could be a simple and more useful tool for predicting the development of postoperative delirium than measuring perioperative acute inflammatory markers. A lower relative ratio of α-power might be an effective marker for vulnerability of brain and ultimately for the development of POD.
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Affiliation(s)
- Hirotaka Kinoshita
- From the Department of Anesthesiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Junichi Saito
- From the Department of Anesthesiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Tetsuya Kushikata
- From the Department of Anesthesiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Tasuku Oyama
- From the Department of Anesthesiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Daiki Takekawa
- From the Department of Anesthesiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Eiji Hashiba
- Division of Intensive Care, Hirosaki University Medical Hospital, Hirosaki, Japan
| | - Teiji Sawa
- Department of Anesthesiology, School of Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Kazuyoshi Hirota
- From the Department of Anesthesiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
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Simpson BK, Rangwani R, Abbasi A, Chung JM, Reed CM, Gulati T. Disturbed laterality of non-rapid eye movement sleep oscillations in post-stroke human sleep: a pilot study. Front Neurol 2023; 14:1243575. [PMID: 38099067 PMCID: PMC10719949 DOI: 10.3389/fneur.2023.1243575] [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: 06/26/2023] [Accepted: 11/08/2023] [Indexed: 12/17/2023] Open
Abstract
Sleep is known to promote recovery post-stroke. However, there is a paucity of data profiling sleep oscillations in the post-stroke human brain. Recent rodent work showed that resurgence of physiologic spindles coupled to sleep slow oscillations (SOs) and concomitant decrease in pathological delta (δ) waves is associated with sustained motor performance gains during stroke recovery. The goal of this study was to evaluate bilaterality of non-rapid eye movement (NREM) sleep-oscillations (namely SOs, δ-waves, spindles, and their nesting) in post-stroke patients vs. healthy control subjects. We analyzed NREM-marked electroencephalography (EEG) data in hospitalized stroke-patients (n = 5) and healthy subjects (n = 3). We used a laterality index to evaluate symmetry of NREM oscillations across hemispheres. We found that stroke subjects had pronounced asymmetry in the oscillations, with a predominance of SOs, δ-waves, spindles, and nested spindles in affected hemisphere, when compared to the healthy subjects. Recent preclinical work classified SO-nested spindles as restorative post-stroke and δ-wave-nested spindles as pathological. We found that the ratio of SO-nested spindles laterality index to δ-wave-nested spindles laterality index was lower in stroke subjects. Using linear mixed models (which included random effects of concurrent pharmacologic drugs), we found large and medium effect size for δ-wave nested spindle and SO-nested spindle, respectively. Our results in this pilot study indicate that considering laterality index of NREM oscillations might be a useful metric for assessing recovery post-stroke and that factoring in pharmacologic drugs may be important when targeting sleep modulation for neurorehabilitation post-stroke.
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Affiliation(s)
- Benjamin K. Simpson
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Rohit Rangwani
- Department of Biomedical Sciences, Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Bioengineering Graduate Program, Department of Bioengineering, Henry Samueli School of Engineering, University of California, Los Angeles, Los Angeles, CA, United States
| | - Aamir Abbasi
- Department of Biomedical Sciences, Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Jeffrey M. Chung
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Chrystal M. Reed
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Tanuj Gulati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Biomedical Sciences, Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Bioengineering Graduate Program, Department of Bioengineering, Henry Samueli School of Engineering, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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45
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Qin X, Chen X, Wang B, Zhao X, Tang Y, Yao L, Liang Z, He J, Li X. EEG Changes during Propofol Anesthesia Induction in Vegetative State Patients Undergoing Spinal Cord Stimulation Implantation Surgery. Brain Sci 2023; 13:1608. [PMID: 38002567 PMCID: PMC10669685 DOI: 10.3390/brainsci13111608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/07/2023] [Accepted: 11/17/2023] [Indexed: 11/26/2023] Open
Abstract
OBJECTIVE To compare the EEG changes in vegetative state (VS) patients and non-craniotomy, non-vegetative state (NVS) patients during general anesthesia with low-dose propofol and to find whether it affects the arousal rate of VS patients. METHODS Seven vegetative state patients (VS group: five with traumatic brain injury, two with ischemic-hypoxic VS) and five non-craniotomy, non-vegetative state patients (NVS group) treated in the Department of Neurosurgery, Peking University International Hospital from January to May 2022 were selected. All patients were induced with 0.5 mg/kg propofol, and the Bispectral Index (BIS) changes within 5 min after administration were observed. Raw EEG signals and perioperative EEG signals were collected and analyzed using EEGLAB in the MATLAB software environment, time-frequency spectrums were calculated, and EEG changes were analyzed using power spectrums. RESULTS There was no significant difference in the general data before surgery between the two groups (p > 0.05); the BIS reduction in the VS group was significantly greater than that in the NVS group at 1 min, 2 min, 3 min, 4 min, and 5 min after 0.5 mg/kg propofol induction (p < 0.05). Time-frequency spectrum analysis showed the following: prominent α band energy around 10 Hz and decreased high-frequency energy in the NVS group, decreased high-frequency energy and main energy concentrated below 10 Hz in traumatic brain injury VS patients, higher energy in the 10-20 Hz band in ischemic-hypoxic VS patients. The power spectrum showed that the brain electrical energy of the NVS group was weakened R5 min after anesthesia induction compared with 5 min before induction, mainly concentrated in the small wave peak after 10 Hz, i.e., the α band peak; the energy of traumatic brain injury VS patients was weakened after anesthesia induction, but no α band peak appeared; and in ischemic-hypoxic VS patients, there was no significant change in low-frequency energy after anesthesia induction, high-frequency energy was significantly weakened, and a clear α band peak appeared slightly after 10 Hz. Three months after the operation, follow-up visits were made to the VS group patients who had undergone SCS surgery. One patient with traumatic brain injury VS was diagnosed with MCS-, one patient with ischemic-hypoxic VS had increased their CRS-R score by 1 point, and the remaining five patients had no change in their CRS scores. CONCLUSIONS Low doses of propofol cause great differences in the EEG of different types of VS patients, which may be the unique response of damaged nerve cell residual function to propofol, and these weak responses may also be the basis of brain recovery.
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Affiliation(s)
- Xuewei Qin
- Department of Anesthesiology, Peking University International Hospital, Beijing 102206, China; (X.Q.); (X.Z.)
| | - Xuanling Chen
- Department of Anesthesiology, Peking University International Hospital, Beijing 102206, China; (X.Q.); (X.Z.)
| | - Bo Wang
- Department of Anesthesiology, Peking University International Hospital, Beijing 102206, China; (X.Q.); (X.Z.)
| | - Xin Zhao
- Department of Anesthesiology, Peking University International Hospital, Beijing 102206, China; (X.Q.); (X.Z.)
| | - Yi Tang
- Department of Anesthesiology, Peking University International Hospital, Beijing 102206, China; (X.Q.); (X.Z.)
| | - Lan Yao
- Department of Anesthesiology, Peking University International Hospital, Beijing 102206, China; (X.Q.); (X.Z.)
| | - Zhenhu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;
| | - Jianghong He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China;
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China;
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875, China
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Zelmann R, Paulk AC, Tian F, Balanza Villegas GA, Dezha Peralta J, Crocker B, Cosgrove GR, Richardson RM, Williams ZM, Dougherty DD, Purdon PL, Cash SS. Differential cortical network engagement during states of un/consciousness in humans. Neuron 2023; 111:3479-3495.e6. [PMID: 37659409 PMCID: PMC10843836 DOI: 10.1016/j.neuron.2023.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 06/13/2023] [Accepted: 08/08/2023] [Indexed: 09/04/2023]
Abstract
What happens in the human brain when we are unconscious? Despite substantial work, we are still unsure which brain regions are involved and how they are impacted when consciousness is disrupted. Using intracranial recordings and direct electrical stimulation, we mapped global, network, and regional involvement during wake vs. arousable unconsciousness (sleep) vs. non-arousable unconsciousness (propofol-induced general anesthesia). Information integration and complex processing we`re reduced, while variability increased in any type of unconscious state. These changes were more pronounced during anesthesia than sleep and involved different cortical engagement. During sleep, changes were mostly uniformly distributed across the brain, whereas during anesthesia, the prefrontal cortex was the most disrupted, suggesting that the lack of arousability during anesthesia results not from just altered overall physiology but from a disconnection between the prefrontal and other brain areas. These findings provide direct evidence for different neural dynamics during loss of consciousness compared with loss of arousability.
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Affiliation(s)
- Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA.
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Fangyun Tian
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick L Purdon
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
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Jin X, Liang Z, Wen X, Wang Y, Bai Y, Xia X, He J, Sleigh J, Li X. The Characteristics of Electroencephalogram Signatures in Minimally Conscious State Patients Induced by General Anesthesia. IEEE Trans Biomed Eng 2023; 70:3239-3247. [PMID: 37335799 DOI: 10.1109/tbme.2023.3287203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
OBJECTIVE General anesthesia (GA) is necessary for surgery, even for patients in a minimally conscious state (MCS). The characteristics of the electroencephalogram (EEG) signatures of the MCS patients under GA are still unclear. METHODS The EEG during GA were recorded from 10 MCS patients undergoing spinal cord stimulation surgery. The power spectrum, phase-amplitude coupling (PAC), the diversity of connectivity, and the functional network were investigated. Long term recovery was assessed by the Coma Recovery Scale-Revised at one year after the surgery, and the characteristics of the patients with good or bad prognosis status were compared. RESULTS For the four MCS patients with good prognostic recovery, slow oscillation (0.1-1 Hz) and the alpha band (8-12 Hz) in the frontal areas increased during the maintenance of a surgical state of anesthesia (MOSSA), and "peak-max" and "trough-max" patterns emerged in frontal and parietal areas. During MOSSA, the six MCS patients with bad prognosis demonstrated: increased modulation index, reduced diversity of connectivity (from mean±SD of 0.877 ± 0.003 to 0.776 ± 0.003, p < 0.001), reduced function connectivity significantly in theta band (from mean±SD of 1.032 ± 0.043 to 0.589 ± 0.036, p < 0.001, in prefrontal-frontal; and from mean±SD of 0.989 ± 0.043 to 0.684 ± 0.036, p < 0.001, in frontal-parietal) and reduced local and global efficiency of the network in delta band. CONCLUSIONS A bad prognosis in MCS patients is associated with signs of impaired thalamocortical and cortico-cortical connectivity - as indicated by inability to produce inter-frequency coupling and phase synchronization. These indices may have a role in predicting the long-term recovery of MCS patients.
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Simpson BK, Rangwani R, Abbasi A, Chung JM, Reed CM, Gulati T. Disturbed laterality of non-rapid eye movement sleep oscillations in post-stroke human sleep: a pilot study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.01.23289359. [PMID: 37205348 PMCID: PMC10187327 DOI: 10.1101/2023.05.01.23289359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Sleep is known to promote recovery post-stroke. However, there is a paucity of data profiling sleep oscillations post-stroke in the human brain. Recent rodent work showed that resurgence of physiologic spindles coupled to sleep slow oscillations(SOs) and concomitant decrease in pathological delta(δ) waves is associated with sustained motor performance gains during stroke recovery. The goal of this study was to evaluate bilaterality of non-rapid eye movement (NREM) sleep-oscillations (namely SOs, δ-waves, spindles and their nesting) in post-stroke patients versus healthy control subjects. We analyzed NREM-marked electroencephalography (EEG) data in hospitalized stroke-patients (n=5) and healthy subjects (n=3) from an open-sourced dataset. We used a laterality index to evaluate symmetry of NREM oscillations across hemispheres. We found that stroke subjects had pronounced asymmetry in the oscillations, with a predominance of SOs, δ-waves, spindles and nested spindles in one hemisphere, when compared to the healthy subjects. Recent preclinical work classified SO-nested spindles as restorative post-stroke and δ-wave-nested spindles as pathological. We found that the ratio of SO-nested spindles laterality index to δ-wave-nested spindles laterality index was lower in stroke subjects. Using linear mixed models (which included random effects of concurrent pharmacologic drugs), we found large and medium effect size for δ-wave nested spindle and SO-nested spindle, respectively. Our results indicate considering laterality index of NREM oscillations might be a useful metric for assessing recovery post-stroke and that factoring in pharmacologic drugs may be important when targeting sleep modulation for neurorehabilitation post-stroke.
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Affiliation(s)
| | - Rohit Rangwani
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA
- Bioengineering Graduate Program, Department of Bioengineering, Henry Samueli School of Engineering, University of California - Los Angeles, Los Angeles, CA
| | - Aamir Abbasi
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jeffrey M Chung
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Chrystal M Reed
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Tanuj Gulati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA
- Bioengineering Graduate Program, Department of Bioengineering, Henry Samueli School of Engineering, University of California - Los Angeles, Los Angeles, CA
- Department of Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA
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49
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Király B, Domonkos A, Jelitai M, Lopes-Dos-Santos V, Martínez-Bellver S, Kocsis B, Schlingloff D, Joshi A, Salib M, Fiáth R, Barthó P, Ulbert I, Freund TF, Viney TJ, Dupret D, Varga V, Hangya B. The medial septum controls hippocampal supra-theta oscillations. Nat Commun 2023; 14:6159. [PMID: 37816713 PMCID: PMC10564782 DOI: 10.1038/s41467-023-41746-0] [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: 07/27/2022] [Accepted: 09/15/2023] [Indexed: 10/12/2023] Open
Abstract
Hippocampal theta oscillations orchestrate faster beta-to-gamma oscillations facilitating the segmentation of neural representations during navigation and episodic memory. Supra-theta rhythms of hippocampal CA1 are coordinated by local interactions as well as inputs from the entorhinal cortex (EC) and CA3 inputs. However, theta-nested gamma-band activity in the medial septum (MS) suggests that the MS may control supra-theta CA1 oscillations. To address this, we performed multi-electrode recordings of MS and CA1 activity in rodents and found that MS neuron firing showed strong phase-coupling to theta-nested supra-theta episodes and predicted changes in CA1 beta-to-gamma oscillations on a cycle-by-cycle basis. Unique coupling patterns of anatomically defined MS cell types suggested that indirect MS-to-CA1 pathways via the EC and CA3 mediate distinct CA1 gamma-band oscillations. Optogenetic activation of MS parvalbumin-expressing neurons elicited theta-nested beta-to-gamma oscillations in CA1. Thus, the MS orchestrates hippocampal network activity at multiple temporal scales to mediate memory encoding and retrieval.
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Affiliation(s)
- Bálint Király
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary
- Department of Biological Physics, Institute of Physics, Eötvös Loránd University, Budapest, Hungary
| | - Andor Domonkos
- Subcortical Modulation Research Group, Institute of Experimental Medicine, Budapest, Hungary
| | - Márta Jelitai
- Subcortical Modulation Research Group, Institute of Experimental Medicine, Budapest, Hungary
| | - Vítor Lopes-Dos-Santos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Sergio Martínez-Bellver
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary
- Department of Anatomy and Human Embryology, Faculty of Medicine and Odontology, University of Valencia, Valencia, Spain
| | - Barnabás Kocsis
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Dániel Schlingloff
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary
| | - Abhilasha Joshi
- Department of Pharmacology, University of Oxford, Oxford, UK
| | - Minas Salib
- Department of Pharmacology, University of Oxford, Oxford, UK
| | - Richárd Fiáth
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Péter Barthó
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - István Ulbert
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Tamás F Freund
- Laboratory of Cerebral Cortex Research, Institute of Experimental Medicine, Budapest, Hungary
| | - Tim J Viney
- Department of Pharmacology, University of Oxford, Oxford, UK
| | - David Dupret
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Viktor Varga
- Subcortical Modulation Research Group, Institute of Experimental Medicine, Budapest, Hungary
| | - Balázs Hangya
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary.
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Chakravarty S, Donoghue J, Waite AS, Mahnke M, Garwood IC, Gallo S, Miller EK, Brown EN. Closed-loop control of anesthetic state in nonhuman primates. PNAS NEXUS 2023; 2:pgad293. [PMID: 37920551 PMCID: PMC10619513 DOI: 10.1093/pnasnexus/pgad293] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 08/13/2023] [Accepted: 08/22/2023] [Indexed: 11/04/2023]
Abstract
Research in human volunteers and surgical patients has shown that unconsciousness under general anesthesia can be reliably tracked using real-time electroencephalogram processing. Hence, a closed-loop anesthesia delivery (CLAD) system that maintains precisely specified levels of unconsciousness is feasible and would greatly aid intraoperative patient management. The US Federal Drug Administration has approved no CLAD system for human use due partly to a lack of testing in appropriate animal models. To address this key roadblock, we implement a nonhuman primate (NHP) CLAD system that controls the level of unconsciousness using the anesthetic propofol. The key system components are a local field potential (LFP) recording system; propofol pharmacokinetics and pharmacodynamic models; the control variable (LFP power between 20 and 30 Hz), a programmable infusion system and a linear quadratic integral controller. Our CLAD system accurately controlled the level of unconsciousness along two different 125-min dynamic target trajectories for 18 h and 45 min in nine experiments in two NHPs. System performance measures were comparable or superior to those in previous CLAD reports. We demonstrate that an NHP CLAD system can reliably and accurately control in real-time unconsciousness maintained by anesthesia. Our findings establish critical steps for CLAD systems' design and testing prior to human testing.
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Affiliation(s)
- Sourish Chakravarty
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jacob Donoghue
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA 02139, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Ayan S Waite
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Meredith Mahnke
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Indie C Garwood
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA 02139, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Sebastian Gallo
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Emery N Brown
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA 02139, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
- Institute for Medical Engineering and Sciences, MIT, Cambridge, MA 02139, USA
- Department of Anaesthesia, Harvard Medical School, Boston, MA 02115, USA
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