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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: 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: 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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52
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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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53
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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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54
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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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55
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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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56
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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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57
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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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58
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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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59
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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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60
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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: 1.5] [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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63
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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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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: 4.0] [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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69
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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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70
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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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71
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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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72
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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: 0.5] [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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73
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Gutiérrez R, Purdon PL. Phase-amplitude coupling during maintenance of general anaesthesia: towards a better understanding of anaesthetic-induced brain dynamics in children. Br J Anaesth 2023; 131:439-442. [PMID: 37611972 DOI: 10.1016/j.bja.2023.06.030] [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: 04/07/2023] [Revised: 05/30/2023] [Accepted: 06/02/2023] [Indexed: 08/25/2023] Open
Abstract
Electroencephalogram signatures associated with anaesthetic-induced loss of consciousness have been widely described in adult populations. A recent study helps verify our understanding of brain dynamics induced by anaesthetics in a paediatric population by describing a specific pattern in terms of an interaction of the phase of delta oscillations and the amplitude of alpha oscillations. This feature has potential translational implications for optimising future monitoring technologies.
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Affiliation(s)
- Rodrigo Gutiérrez
- Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Patrick L Purdon
- Department of Anaesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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74
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Fehrlin ES, Hight D, Kaiser HA, Luedi MM, Huber M, Zubler F, Lersch F. A Pilot Investigation Evaluating Relative Changes in Fronto-Occipital Alpha and Beta Spectral Power as Measurement of Anesthesia Hypnotic Depth. Anesth Analg 2023; 137:656-664. [PMID: 36961823 PMCID: PMC10408731 DOI: 10.1213/ane.0000000000006398] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2022] [Indexed: 03/25/2023]
Abstract
BACKGROUND Other than clinical observation of a patient's vegetative response to nociception, monitoring the hypnotic component of general anesthesia (GA) and unconsciousness relies on electroencephalography (EEG)-based indices. These indices exclusively based on frontal EEG activity neglect an important observation. One of the main hallmarks of transitions from wakefulness to GA is a shift in alpha oscillations (7.5-12.5 Hz activity) from occipital brain regions toward anterior brain regions ("alpha anteriorization"). Monitoring the degree of this alpha anteriorization may help to guide induction and maintenance of hypnotic depth and prevent intraoperative awareness. However, the occipital region of the brain is completely disregarded and occipital alpha as characteristic of wakefulness and its posterior-to-anterior shift during induction are missed. Here, we propose an application of Narcotrend's reduced power alpha beta (RPAB) index, originally developed to monitor differences in hemispheric perfusion, for determining the ratio of alpha and beta activity in the anterior-posterior axis. METHODS Perioperative EEG data of 32 patients undergoing GA in the ophthalmic surgery department of Bern University Hospital were retrospectively analyzed. EEG was recorded with the Narcotrend® monitor using a frontal (Fp1-Fp2) and a posterior (T9-Oz) bipolar derivation with reference electrode over A2. The RPAB index was computed between both bipolar signals, defining the fronto-occipital RPAB (FO-RPAB). FO-RPAB was analyzed during wakefulness, GA maintenance, and emergence, as well as before and after the intraoperative administration of a ketamine bolus. FO-RPAB was compared with a classical quantitative EEG measure-the spectral edge frequency 95% (SEF-95). RESULTS A significant shift of the FO-RPAB was observed during both induction of and emergence from GA ( P < .001). Interestingly, the additional administration of ketamine during GA did not lead to a significant change in FO-RPAB ( P = 0.81). In contrast, a significant increase in the SEF-95 in the frontal channel was observed during the 10-minute period after ketamine administration ( P < .001). CONCLUSIONS FO-RPAB appears to qualify as a marker of unconsciousness, reflecting physiological fronto-occipital activity differences during GA. In contrast to frontal SEF-95, it is not disturbed by additional administration of ketamine for analgesia.
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Affiliation(s)
- Eloy S. Fehrlin
- From the Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Darren Hight
- From the Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Heiko A. Kaiser
- From the Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Sleep-Wake-Epilepsy-Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Markus M. Luedi
- From the Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Markus Huber
- From the Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Frédéric Zubler
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Friedrich Lersch
- From the Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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75
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Müller EJ, Munn BR, Redinbaugh MJ, Lizier J, Breakspear M, Saalmann YB, Shine JM. The non-specific matrix thalamus facilitates the cortical information processing modes relevant for conscious awareness. Cell Rep 2023; 42:112844. [PMID: 37498741 DOI: 10.1016/j.celrep.2023.112844] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 04/25/2023] [Accepted: 07/06/2023] [Indexed: 07/29/2023] Open
Abstract
The neurobiological mechanisms of arousal and anesthesia remain poorly understood. Recent evidence highlights the key role of interactions between the cerebral cortex and the diffusely projecting matrix thalamic nuclei. Here, we interrogate these processes in a whole-brain corticothalamic neural mass model endowed with targeted and diffusely projecting thalamocortical nuclei inferred from empirical data. This model captures key features seen in propofol anesthesia, including diminished network integration, lowered state diversity, impaired susceptibility to perturbation, and decreased corticocortical coherence. Collectively, these signatures reflect a suppression of information transfer across the cerebral cortex. We recover these signatures of conscious arousal by selectively stimulating the matrix thalamus, recapitulating empirical results in macaque, as well as wake-like information processing states that reflect the thalamic modulation of large-scale cortical attractor dynamics. Our results highlight the role of matrix thalamocortical projections in shaping many features of complex cortical dynamics to facilitate the unique communication states supporting conscious awareness.
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Affiliation(s)
- Eli J Müller
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia; Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia; School of Computer Science, The University of Sydney, Sydney, NSW, Australia.
| | - Brandon R Munn
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia; Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia
| | | | - Joseph Lizier
- Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia; School of Computer Science, The University of Sydney, Sydney, NSW, Australia
| | | | - Yuri B Saalmann
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA; Wisconsin National Primate Research Centre, Madison, WI, USA
| | - James M Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia; Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia
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76
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Amorim E, Zheng WL, Jing J, Ghassemi MM, Lee JW, Wu O, Herman ST, Pang T, Sivaraju A, Gaspard N, Hirsch L, Ruijter BJ, Tjepkema-Cloostermans MC, Hofmeijer J, van Putten MJAM, Westover MB. Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest. Neurology 2023; 101:e940-e952. [PMID: 37414565 PMCID: PMC10501085 DOI: 10.1212/wnl.0000000000207537] [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] [Received: 10/11/2022] [Accepted: 05/04/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest. METHODS Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months. RESULTS One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery. DISCUSSION Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.
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Affiliation(s)
- Edilberto Amorim
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands.
| | - Wei-Long Zheng
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Jin Jing
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Mohammad M Ghassemi
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Jong Woo Lee
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Ona Wu
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Susan T Herman
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Trudy Pang
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Adithya Sivaraju
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Nicolas Gaspard
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Lawrence Hirsch
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Barry J Ruijter
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Marleen C Tjepkema-Cloostermans
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Jeannette Hofmeijer
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Michel J A M van Putten
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - M Brandon Westover
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
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Frohlich J, Crone JS, Mediano PAM, Toker D, Bor D. Editorial: Dissociations between neural activity and conscious state: a key to understanding consciousness. Front Hum Neurosci 2023; 17:1256168. [PMID: 37600551 PMCID: PMC10433896 DOI: 10.3389/fnhum.2023.1256168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 07/20/2023] [Indexed: 08/22/2023] Open
Affiliation(s)
- Joel Frohlich
- Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tuebingen, Tuebingen, Germany
- Institute for Advanced Consciousness Studies, Santa Monica, CA, United States
| | - Julia S. Crone
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
| | - Pedro A. M. Mediano
- Department of Computing, Imperial College London, London, United Kingdom
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Daniel Toker
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Daniel Bor
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
- Department of Psychology, Queen Mary University of London, London, United Kingdom
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McCulloch TJ, Sanders RD. Depth of anaesthesia monitoring: time to reject the index? Br J Anaesth 2023; 131:196-199. [PMID: 37198033 DOI: 10.1016/j.bja.2023.04.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 05/19/2023] Open
Abstract
Depth of anaesthesia monitors can fail to detect consciousness under anaesthesia, primarily because they rely on the frontal EEG, which does not arise from a neural correlate of consciousness. A study published in a previous issue of the British Journal of Anaesthesia showed that indices produced by the different commercial monitors can give highly discordant results when analysing changes in the frontal EEG. Anaesthetists could benefit from routinely assessing the raw EEG and its spectrogram, rather than relying solely on an index produced by a depth of anaesthesia monitor.
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Affiliation(s)
- Timothy J McCulloch
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney Local Health District, Sydney, NSW, Australia.
| | - Robert D Sanders
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney Local Health District, Sydney, NSW, Australia; Institute of Academic Surgery, Royal Prince Alfred Hospital, Sydney Local Health District, Sydney, NSW, Australia; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia
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Valli K, Radek L, Kallionpää RE, Scheinin A, Långsjö J, Kaisti K, Kantonen O, Korhonen J, Vahlberg T, Revonsuo A, Scheinin H. Subjective experiences during dexmedetomidine- or propofol-induced unresponsiveness and non-rapid eye movement sleep in healthy male subjects. Br J Anaesth 2023; 131:348-359. [PMID: 37268445 PMCID: PMC10375502 DOI: 10.1016/j.bja.2023.04.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 04/06/2023] [Accepted: 04/12/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND Anaesthetic-induced unresponsiveness and non-rapid eye movement (NREM) sleep share common neural pathways and neurophysiological features. We hypothesised that these states bear resemblance also at the experiential level. METHODS We compared, in a within-subject design, the prevalence and content of experiences in reports obtained after anaesthetic-induced unresponsiveness and NREM sleep. Healthy males (N=39) received dexmedetomidine (n=20) or propofol (n=19) in stepwise doses to induce unresponsiveness. Those rousable were interviewed and left unstimulated, and the procedure was repeated. Finally, the anaesthetic dose was increased 50%, and the participants were interviewed after recovery. The same participants (N=37) were also later interviewed after NREM sleep awakenings. RESULTS Most subjects were rousable, with no difference between anaesthetic agents (P=0.480). Lower drug plasma concentrations were associated with being rousable for both dexmedetomidine (P=0.007) and propofol (P=0.002) but not with recall of experiences in either drug group (dexmedetomidine: P=0.543; propofol: P=0.460). Of the 76 and 73 interviews performed after anaesthetic-induced unresponsiveness and NREM sleep, 69.7% and 64.4% included experiences, respectively. Recall did not differ between anaesthetic-induced unresponsiveness and NREM sleep (P=0.581), or between dexmedetomidine and propofol in any of the three awakening rounds (P>0.05). Disconnected dream-like experiences (62.3% vs 51.1%; P=0.418) and memory incorporation of the research setting (88.7% vs 78.7%; P=0.204) were equally often present in anaesthesia and sleep interviews, respectively, whereas awareness, signifying connected consciousness, was rarely reported in either state. CONCLUSIONS Anaesthetic-induced unresponsiveness and NREM sleep are characterised by disconnected conscious experiences with corresponding recall frequencies and content. CLINICAL TRIAL REGISTRATION Clinical trial registration. This study was part of a larger study registered at ClinicalTrials.gov (NCT01889004).
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Affiliation(s)
- Katja Valli
- Department of Psychology and Speech-Language Pathology, Turku Brain and Mind Center, University of Turku, Turku, Finland; Department of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland; Department of Cognitive Neuroscience and Philosophy, School of Bioscience, University of Skövde, Skövde, Sweden.
| | - Linda Radek
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Roosa E Kallionpää
- Department of Psychology and Speech-Language Pathology, Turku Brain and Mind Center, University of Turku, Turku, Finland; Department of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland
| | - Annalotta Scheinin
- Department of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland; Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Jaakko Långsjö
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland; Department of Intensive Care, Tampere University Hospital, Tampere, Finland
| | - Kaike Kaisti
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland; Department of Anesthesiology and Intensive Care, Oulu University Hospital, Oulu, Finland
| | - Oskari Kantonen
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Jarno Korhonen
- Department of Psychology and Speech-Language Pathology, Turku Brain and Mind Center, University of Turku, Turku, Finland
| | - Tero Vahlberg
- Institute of Clinical Medicine, Biostatistics, University of Turku and Turku University Hospital, Turku, Finland
| | - Antti Revonsuo
- Department of Psychology and Speech-Language Pathology, Turku Brain and Mind Center, University of Turku, Turku, Finland; Department of Cognitive Neuroscience and Philosophy, School of Bioscience, University of Skövde, Skövde, Sweden
| | - Harry Scheinin
- Department of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland; Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland; Institute of Biomedicine and Unit of Clinical Pharmacology, University of Turku and Turku University Hospital, Turku, Finland
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Zhang X, Li A, Wang S, Wang T, Liu T, Wang Y, Fu J, Zhao G, Yang Q, Dong H. Differences in the EEG Power Spectrum and Cross-Frequency Coupling Patterns between Young and Elderly Patients during Sevoflurane Anesthesia. Brain Sci 2023; 13:1149. [PMID: 37626505 PMCID: PMC10452117 DOI: 10.3390/brainsci13081149] [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: 05/24/2023] [Revised: 07/23/2023] [Accepted: 07/28/2023] [Indexed: 08/27/2023] Open
Abstract
Electroencephalography (EEG) is widely used for monitoring the depth of anesthesia in surgical patients. Distinguishing age-related EEG features under general anesthesia will help to optimize anesthetic depth monitoring during surgery for elderly patients. This retrospective cohort study included 41 patients aged from 18 to 79 years undergoing noncardiac surgery under general anesthesia. We compared the power spectral signatures and phase-amplitude coupling patterns of the young and elderly groups under baseline and surgical anesthetic depth. General anesthesia by sevoflurane significantly increased the spectral power of delta, theta, alpha, and beta bands and strengthened the cross-frequency coupling both in young and elderly patients. However, the variation in EEG power spectral density and the modulation of alpha amplitudes on delta phases was relatively weaker in elderly patients. In conclusion, the EEG under general anesthesia using sevoflurane exhibited similar dynamic features between young and elderly patients, and the weakened alteration of spectral power and cross-frequency coupling patterns could be utilized to precisely quantify the depth of anesthesia in elderly patients.
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Affiliation(s)
- Xinxin Zhang
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
| | - Ao Li
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
- Anesthesia and Operation Center, The First Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Sa Wang
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
| | - Tingting Wang
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
| | - Tiantian Liu
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
| | - Yonghui Wang
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
| | - Jingwen Fu
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
| | - Guangchao Zhao
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
| | - Qianzi Yang
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
- Department of Anesthesiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Hailong Dong
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an 710000, China; (X.Z.); (A.L.); (S.W.); (T.W.); (T.L.); (Y.W.); (J.F.); (G.Z.)
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Soplata AE, Adam E, Brown EN, Purdon PL, McCarthy MM, Kopell N. Rapid thalamocortical network switching mediated by cortical synchronization underlies propofol-induced EEG signatures: a biophysical model. J Neurophysiol 2023; 130:86-103. [PMID: 37314079 PMCID: PMC10312318 DOI: 10.1152/jn.00068.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 06/08/2023] [Accepted: 06/08/2023] [Indexed: 06/15/2023] Open
Abstract
Propofol-mediated unconsciousness elicits strong alpha/low-beta and slow oscillations in the electroencephalogram (EEG) of patients. As anesthetic dose increases, the EEG signal changes in ways that give clues to the level of unconsciousness; the network mechanisms of these changes are only partially understood. Here, we construct a biophysical thalamocortical network involving brain stem influences that reproduces transitions in dynamics seen in the EEG involving the evolution of the power and frequency of alpha/low-beta and slow rhythm, as well as their interactions. Our model suggests that propofol engages thalamic spindle and cortical sleep mechanisms to elicit persistent alpha/low-beta and slow rhythms, respectively. The thalamocortical network fluctuates between two mutually exclusive states on the timescale of seconds. One state is characterized by continuous alpha/low-beta-frequency spiking in thalamus (C-state), whereas in the other, thalamic alpha spiking is interrupted by periods of co-occurring thalamic and cortical silence (I-state). In the I-state, alpha colocalizes to the peak of the slow oscillation; in the C-state, there is a variable relationship between an alpha/beta rhythm and the slow oscillation. The C-state predominates near loss of consciousness; with increasing dose, the proportion of time spent in the I-state increases, recapitulating EEG phenomenology. Cortical synchrony drives the switch to the I-state by changing the nature of the thalamocortical feedback. Brain stem influence on the strength of thalamocortical feedback mediates the amount of cortical synchrony. Our model implicates loss of low-beta, cortical synchrony, and coordinated thalamocortical silent periods as contributing to the unconscious state.NEW & NOTEWORTHY GABAergic anesthetics induce alpha/low-beta and slow oscillations in the EEG, which interact in dose-dependent ways. We constructed a thalamocortical model to investigate how these interdependent oscillations change with propofol dose. We find two dynamic states of thalamocortical coordination, which change on the timescale of seconds and dose-dependently mirror known changes in EEG. Thalamocortical feedback determines the oscillatory coupling and power seen in each state, and this is primarily driven by cortical synchrony and brain stem neuromodulation.
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Affiliation(s)
- Austin E Soplata
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States
| | - Elie Adam
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
| | - Emery N Brown
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
| | - Patrick L Purdon
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Michelle M McCarthy
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States
| | - Nancy Kopell
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States
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82
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Shine JM, Lewis LD, Garrett DD, Hwang K. The impact of the human thalamus on brain-wide information processing. Nat Rev Neurosci 2023; 24:416-430. [PMID: 37237103 DOI: 10.1038/s41583-023-00701-0] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2023] [Indexed: 05/28/2023]
Abstract
The thalamus is a small, bilateral structure in the diencephalon that integrates signals from many areas of the CNS. This critical anatomical position allows the thalamus to influence whole-brain activity and adaptive behaviour. However, traditional research paradigms have struggled to attribute specific functions to the thalamus, and it has remained understudied in the human neuroimaging literature. Recent advances in analytical techniques and increased accessibility to large, high-quality data sets have brought forth a series of studies and findings that (re-)establish the thalamus as a core region of interest in human cognitive neuroscience, a field that otherwise remains cortico-centric. In this Perspective, we argue that using whole-brain neuroimaging approaches to investigate the thalamus and its interaction with the rest of the brain is key for understanding systems-level control of information processing. To this end, we highlight the role of the thalamus in shaping a range of functional signatures, including evoked activity, interregional connectivity, network topology and neuronal variability, both at rest and during the performance of cognitive tasks.
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Affiliation(s)
- James M Shine
- Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Douglas D Garrett
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Kai Hwang
- Cognitive Control Collaborative, Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, IA, USA.
- Department of Psychiatry, The University of Iowa, Iowa City, IA, USA.
- Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, USA.
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83
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Berger M, Ryu D, Reese M, McGuigan S, Evered LA, Price CC, Scott DA, Westover MB, Eckenhoff R, Bonanni L, Sweeney A, Babiloni C. A Real-Time Neurophysiologic Stress Test for the Aging Brain: Novel Perioperative and ICU Applications of EEG in Older Surgical Patients. Neurotherapeutics 2023; 20:975-1000. [PMID: 37436580 PMCID: PMC10457272 DOI: 10.1007/s13311-023-01401-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/29/2023] [Indexed: 07/13/2023] Open
Abstract
As of 2022, individuals age 65 and older represent approximately 10% of the global population [1], and older adults make up more than one third of anesthesia and surgical cases in developed countries [2, 3]. With approximately > 234 million major surgical procedures performed annually worldwide [4], this suggests that > 70 million surgeries are performed on older adults across the globe each year. The most common postoperative complications seen in these older surgical patients are perioperative neurocognitive disorders including postoperative delirium, which are associated with an increased risk for mortality [5], greater economic burden [6, 7], and greater risk for developing long-term cognitive decline [8] such as Alzheimer's disease and/or related dementias (ADRD). Thus, anesthesia, surgery, and postoperative hospitalization have been viewed as a biological "stress test" for the aging brain, in which postoperative delirium indicates a failed stress test and consequent risk for later cognitive decline (see Fig. 3). Further, it has been hypothesized that interventions that prevent postoperative delirium might reduce the risk of long-term cognitive decline. Recent advances suggest that rather than waiting for the development of postoperative delirium to indicate whether a patient "passed" or "failed" this stress test, the status of the brain can be monitored in real-time via electroencephalography (EEG) in the perioperative period. Beyond the traditional intraoperative use of EEG monitoring for anesthetic titration, perioperative EEG may be a viable tool for identifying waveforms indicative of reduced brain integrity and potential risk for postoperative delirium and long-term cognitive decline. In principle, research incorporating routine perioperative EEG monitoring may provide insight into neuronal patterns of dysfunction associated with risk of postoperative delirium, long-term cognitive decline, or even specific types of aging-related neurodegenerative disease pathology. This research would accelerate our understanding of which waveforms or neuronal patterns necessitate diagnostic workup and intervention in the perioperative period, which could potentially reduce postoperative delirium and/or dementia risk. Thus, here we present recommendations for the use of perioperative EEG as a "predictor" of delirium and perioperative cognitive decline in older surgical patients.
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Affiliation(s)
- Miles Berger
- Department of Anesthesiology, Duke University Medical Center, Duke South Orange Zone Room 4315B, Box 3094, Durham, NC, 27710, USA.
- Duke Aging Center, Duke University Medical Center, Durham, NC, USA.
- Duke/UNC Alzheimer's Disease Research Center, Duke University Medical Center, Durham, NC, USA.
| | - David Ryu
- School of Medicine, Duke University, Durham, NC, USA
| | - Melody Reese
- Department of Anesthesiology, Duke University Medical Center, Duke South Orange Zone Room 4315B, Box 3094, Durham, NC, 27710, USA
- Duke Aging Center, Duke University Medical Center, Durham, NC, USA
| | - Steven McGuigan
- Department of Anaesthesia and Acute Pain Medicine, St Vincent's Hospital, Melbourne, VIC, Australia
- Department of Critical Care, School of Medicine, University of Melbourne, Melbourne, Australia
| | - Lisbeth A Evered
- Department of Anaesthesia and Acute Pain Medicine, St Vincent's Hospital, Melbourne, VIC, Australia
- Department of Critical Care, School of Medicine, University of Melbourne, Melbourne, Australia
- Weill Cornell Medicine, New York, NY, USA
| | - Catherine C Price
- Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - David A Scott
- Department of Anaesthesia and Acute Pain Medicine, St Vincent's Hospital, Melbourne, VIC, Australia
- Department of Critical Care, School of Medicine, University of Melbourne, Melbourne, Australia
| | - M Brandon Westover
- Department of Neurology, Beth Israel Deaconess Hospital, Boston, MA, USA
| | - Roderic Eckenhoff
- Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura Bonanni
- Department of Medicine and Aging Sciences, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Aoife Sweeney
- School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
- San Raffaele of Cassino, Cassino, FR, Italy
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84
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Fard RS, Ziaei N, Yousefi A. Latent Dynamical Model to Characterize Brain Network-Level Rhythmic Dynamics. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38083516 DOI: 10.1109/embc40787.2023.10340730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Characterizing network-level rhythmic dynamics over multiple spatio-temporal scales can significantly advance our understanding of brain cognitive function and information processing. In this research, we propose a new switching state space model called latent dynamical coherence model or briefly LDCM. In the LDCM, we develop model inference and parameter estimation solutions that facilitate studying network-level rhythmic dynamics at scales. In the proposed framework, we incorporate both continuous and discrete state processes, helping us to capture dynamics of functional connectivity at various rates, such as slow, rapid, or a combination of both. We then demonstrate an application of our model in characterizing circuit dynamics of the anesthetic state in a sample data set, recorded from a patient under anesthesia using 64-channel EEG over the course of two hours.
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85
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Tauber JM, Brincat SL, Stephen EP, Donaghue JA, Kozachkov L, Brown EN, Miller EK. Propofol Mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.25.546463. [PMID: 37425684 PMCID: PMC10327085 DOI: 10.1101/2023.06.25.546463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
A critical component of anesthesia is the loss 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 (LFP) and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of non-human primates before and during propofol mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-induced coherence between brain areas in the LFP of awake animals. By contrast, propofol mediated unconsciousness eliminated stimulus-induced coherence 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 due to asynchronous down states. Rather, both Down states and Up states reflect disrupted dynamics.
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Affiliation(s)
- John M. Tauber
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Scott L. Brincat
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Emily P. Stephen
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
| | - Jacob A. Donaghue
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Leo Kozachkov
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Emery N. Brown
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - Earl K. Miller
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
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86
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Pelentritou A, Nguissi NAN, Iten M, Haenggi M, Zubler F, Rossetti AO, De Lucia M. The effect of sedation and time after cardiac arrest on coma outcome prognostication based on EEG power spectra. Brain Commun 2023; 5:fcad190. [PMID: 37469860 PMCID: PMC10353761 DOI: 10.1093/braincomms/fcad190] [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: 12/01/2022] [Revised: 05/11/2023] [Accepted: 06/27/2023] [Indexed: 07/21/2023] Open
Abstract
Early prognostication of long-term outcome of comatose patients after cardiac arrest remains challenging. Electroencephalography-based power spectra after cardiac arrest have been shown to help with the identification of patients with favourable outcome during the first day of coma. Here, we aim at comparing the power spectra prognostic value during the first and second day after coma onset following cardiac arrest and to investigate the impact of sedation on prognostication. In this cohort observational study, we included comatose patients (N = 91) after cardiac arrest for whom resting-state electroencephalography was collected on the first and second day after cardiac arrest in four Swiss hospitals. We evaluated whether the average power spectra values at 4.6-15.2 Hz were predictive of patients' outcome based on the best cerebral performance category score at 3 months, with scores ranging from 1 to 5 and dichotomized as favourable (1-2) and unfavourable (3-5). We assessed the effect of sedation and its interaction with the electroencephalography-based power spectra on patient outcome prediction through a generalized linear mixed model. Power spectra values provided 100% positive predictive value (95% confidence intervals: 0.81-1.00) on the first day of coma, with correctly predicted 18 out of 45 favourable outcome patients. On the second day, power spectra values were not predictive of patients' outcome (positive predictive value: 0.46, 95% confidence intervals: 0.19-0.75). On the first day, we did not find evidence of any significant contribution of sedative infusion rates to the patient outcome prediction (P > 0.05). Comatose patients' outcome prediction based on electroencephalographic power spectra is higher on the first compared with the second day after cardiac arrest. Sedation does not appear to impact patient outcome prediction.
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Affiliation(s)
| | | | - Manuela Iten
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Matthias Haenggi
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Frederic Zubler
- Department of Neurology, Spitalzentrum Biel, University of Bern, 2501 Biel, Switzerland
| | - Andrea O Rossetti
- Department of Clinical Neurosciences, University Hospital (CHUV) & University of Lausanne, 1011 Lausanne, Switzerland
| | - Marzia De Lucia
- Correspondence to: Marzia De Lucia, Laboratoire de Recherche en Neuroimagerie (LREN), Centre Hospitalier Universitaire Vaudois (CHUV), MP16 05 559, Chemin de Mont-Paisible 16, Lausanne 1010, Switzerland. E-mail:
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87
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Maschke C, Duclos C, Owen AM, Jerbi K, Blain-Moraes S. Aperiodic brain activity and response to anesthesia vary in disorders of consciousness. Neuroimage 2023; 275:120154. [PMID: 37209758 DOI: 10.1016/j.neuroimage.2023.120154] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/28/2023] [Accepted: 05/02/2023] [Indexed: 05/22/2023] Open
Abstract
In the human electroencephalogram (EEG), oscillatory power peaks co-exist with non-oscillatory, aperiodic activity. Although EEG analysis has traditionally focused exclusively on oscillatory power, recent investigations have shown that the aperiodic EEG component can distinguish conscious wakefulness from sleep and anesthetic-induced unconsciousness. This study investigates the aperiodic EEG component of individuals in a disorder of consciousness (DOC); how it changes in response to exposure to anesthesia; and how it relates to the brain's information richness and criticality. High-density EEG was recorded from 43 individuals in a DOC, with 16 of these individuals undergoing a protocol of propofol anesthesia. The aperiodic component was defined by the spectral slope of the power spectral density. Our results demonstrate that the EEG aperiodic component is more informative about the participants' level of consciousness than the oscillatory component, especially for patients that suffered from a stroke. Importantly, the pharmacologically induced change in the spectral slope from 30-45 Hz positively correlated with individual's pre-anesthetic level of consciousness. The pharmacologically induced loss of information-richness and criticality was associated with individual's pre-anesthetic aperiodic component. During exposure to anesthesia, the aperiodic component was correlated with 3-month recovery status for individuals with DOC. The aperiodic EEG component has been historically neglected; this research highlights the necessity of considering this measure for the assessment of individuals in DOC and future research that seeks to understand the neurophysiological underpinnings of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Canada
| | - Catherine Duclos
- Hôpital du Sacré-Cœur de Montréal, Centre intégré universitaire de Santé et de Services Sociaux du Nord-de-l'île-de-Montréal, Montréal, Québec Canada; Department of Anesthesiology and Pain Medicine, Université de Montréal, Montréal, Québec Canada
| | - Adrian M Owen
- Department of Physiology and Pharmacology, Western University, London, Ontario, Canada; Western Institute for Neuroscience, Western University, London, Ontario, Canada; Department of Psychology, Western University, London, Ontario, Canada
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada; MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada; Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, Québec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada; School of Physical and Occupational Therapy, McGill University, Montreal, Canada.
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88
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Zakaria L, Desowska A, Berde CB, Cornelissen L. Electroencephalographic delta and alpha oscillations reveal phase-amplitude coupling in paediatric patients undergoing sevoflurane-based general anaesthesia. Br J Anaesth 2023; 130:595-602. [PMID: 36922266 DOI: 10.1016/j.bja.2023.01.025] [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: 09/19/2022] [Revised: 01/03/2023] [Accepted: 01/28/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND Sevoflurane-induced anaesthesia generates frontal alpha oscillations as early as 6 months of age, whereas strong delta oscillations are present at birth. In adults, delta oscillations and alpha oscillations are coupled: the phase of delta waves modulates the amplitude of alpha oscillations in a phenomenon known as phase-amplitude coupling. We hypothesise that delta-alpha phase-amplitude coupling exists in young children and is a feature of sevoflurane-based general anaesthesia distinct from emergence after anaesthesia. METHODS Electroencephalographic data from 31 paediatric patients aged 10 months to 3 yr undergoing elective surgery with sevoflurane-based anaesthesia were analysed retrospectively. Delta-alpha phase-amplitude coupling was evaluated during maintenance of anaesthesia and during emergence. RESULTS Delta-alpha phase-amplitude coupling was observed in the study population. Strength of phase-amplitude coupling, represented by the delta-alpha mean amplitude vector, was greater during general anaesthesia than during emergence (Wilcoxon paired signed-rank test, Z=3.107, P=0.002). Frontal alpha amplitude during anaesthesia was not uniformly distributed across all delta phases. During general anaesthesia, alpha power was restricted to the positive phase of the delta wave (omnibus circular uniformity, general anaesthesia: P<0.001, mean phase: 114º; 99% confidence interval: 90º-139º; emergence: P=0.35, mean phase 181º, 99% confidence interval: 110º-253º). CONCLUSIONS Sevoflurane-based anaesthesia is associated with delta-alpha phase-amplitude coupling in paediatric patients. These findings improve our understanding of cortical dynamics in children undergoing general anaesthesia, which might improve paediatric intraoperative depth of anaesthesia monitoring techniques.
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Affiliation(s)
- Luai Zakaria
- Department of Anesthesiology, Perioperative & Pain Medicine, Brigham & Women's Hospital, Boston, USA; Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Adela Desowska
- Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Charles B Berde
- Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Laura Cornelissen
- Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA.
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89
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Liang Z, Wang X, Yu Z, Tong Y, Li X, Ma Y, Guo H. Age-dependent neurovascular coupling characteristics in children and adults during general anesthesia. BIOMEDICAL OPTICS EXPRESS 2023; 14:2240-2259. [PMID: 37206124 PMCID: PMC10191645 DOI: 10.1364/boe.482127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 04/06/2023] [Accepted: 04/11/2023] [Indexed: 05/21/2023]
Abstract
General anesthesia is an indispensable procedure in clinical practice. Anesthetic drugs induce dramatic changes in neuronal activity and cerebral metabolism. However, the age-related changes in neurophysiology and hemodynamics during general anesthesia remain unclear. Therefore, the objective of this study was to explore the neurovascular coupling between neurophysiology and hemodynamics in children and adults during general anesthesia. We analyzed frontal electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals recorded from children (6-12 years old, n = 17) and adults (18-60 years old, n = 25) during propofol-induced and sevoflurane-maintained general anesthesia. The neurovascular coupling was evaluated in wakefulness, maintenance of a surgical state of anesthesia (MOSSA), and recovery by using correlation, coherence and Granger-causality (GC) between the EEG indices [EEG power in different bands and permutation entropy (PE)], and hemodynamic responses the oxyhemoglobin (Δ[HbO]) and deoxy-hemoglobin (Δ[Hb]) from fNIRS in the frequency band in 0.01-0.1 Hz. The PE and Δ[Hb] performed well in distinguishing the anesthesia state (p > 0.001). The correlation between PE and Δ[Hb] was higher than those of other indices in the two age groups. The coherence significantly increased during MOSSA (p < 0.05) compared with wakefulness, and the coherences between theta, alpha and gamma, and hemodynamic activities of children are significantly stronger than that of adults' bands. The GC from neuronal activities to hemodynamic responses decreased during MOSSA, and can better distinguish anesthesia state in adults. Propofol-induced and sevoflurane-maintained combination exhibited age-dependent neuronal activities, hemodynamics, and neurovascular coupling, which suggests the need for separate rules for children's and adults' brain states monitoring during general anesthesia.
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Affiliation(s)
- Zhenhu Liang
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, China
| | - Xin Wang
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, China
| | - Zhenyang Yu
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, China
| | - Yunjie Tong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Xiaoli Li
- Center for Cognition and Neuroergonomics, Beijing Normal University (Zhuhai), Zhuhai, Guangdong, 519087, China
| | - Yaqun Ma
- Department of Anesthesiology, the Seventh Medical Center to Chinese PLA General Hospital, Beijing, 100700, China
| | - Hang Guo
- Department of Anesthesiology, the Seventh Medical Center to Chinese PLA General Hospital, Beijing, 100700, China
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90
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Sakai DM, Trenholme HN, Torpy FJ, Craig HA, Reed RA. Evaluation of the electroencephalogram in awake, sedated, and anesthetized dogs. Res Vet Sci 2023; 159:66-71. [PMID: 37087922 DOI: 10.1016/j.rvsc.2023.04.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/08/2023] [Accepted: 04/15/2023] [Indexed: 04/25/2023]
Abstract
Sedation and anesthesia alter the raw electroencephalogram (EEG). Interpretation of the EEG is facilitated by measuring the patient state index (PSI), visual inspection of density spectral arrays (DSA), and power density analysis of the delta (0.1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta plus gamma (12-40 Hz) frequency bands. Baseline data were recorded in six male intact Beagles before sedation with intravenous acepromazine (0.03 mg/kg) and hydromorphone (0.1 mg/kg). Anesthesia was induced and maintained for five minutes with intravenous propofol (1.5 mg/kg over five seconds followed by 12 mg/kg/h). Additional propofol (0.5-1.0 mg/kg and up to 16.7 mg/kg/h) was administered within this time frame if the PSI was above 50. The effects of sedation and anesthesia were evaluated with a mixed-effect model followed by Dunnett's test (alpha = 0.05). The average baseline PSI (95% confidence interval) was 93.0 (91.4-94.6) and decreased on sedation [88.7 (86.0-91.3); p = 0.039] and anesthesia [44.5 (40.8-48.2); p < 0.001]. The awake DSA showed dense power in all bands. The power density decreased with sedation. During anesthesia, the power density was reduced in frequencies above 12 Hz. The baseline power density on the delta, theta, alpha, and beta plus gamma bands was higher than sedation (p < 0.007). Compared to baseline, anesthesia had lower power on delta, and beta plus gamma bands (p < 0.002). The interpretation in awake, sedated, and anesthetized dogs of the EEG can be facilitated by processing and generating PSI and DSA.
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Affiliation(s)
- Daniel M Sakai
- Department of Small Animal Medicine and Surgery, College of Veterinary Medicine, University of Georgia, 2200 College Station Road, Athens, GA 30605, USA.
| | - H Nicole Trenholme
- Department of Large Animal Medicine, College of Veterinary Medicine, University of Georgia, 2200 College Station Road, Athens, GA 30605, USA
| | - Frederick J Torpy
- Department of Small Animal Medicine and Surgery, College of Veterinary Medicine, University of Georgia, 2200 College Station Road, Athens, GA 30605, USA
| | - Hannah A Craig
- Department of Small Animal Medicine and Surgery, College of Veterinary Medicine, University of Georgia, 2200 College Station Road, Athens, GA 30605, USA
| | - Rachel A Reed
- Department of Large Animal Medicine, College of Veterinary Medicine, University of Georgia, 2200 College Station Road, Athens, GA 30605, USA
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91
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Obata Y, Yamada T, Akiyama K, Sawa T. Time-trend analysis of the center frequency of the intrinsic mode function from the Hilbert-Huang transform of electroencephalography during general anesthesia: a retrospective observational study. BMC Anesthesiol 2023; 23:125. [PMID: 37059989 PMCID: PMC10105429 DOI: 10.1186/s12871-023-02082-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 04/06/2023] [Indexed: 04/16/2023] Open
Abstract
BACKGROUND Anesthesiologists are required to maintain an optimal depth of anesthesia during general anesthesia, and several electroencephalogram (EEG) processing methods have been developed and approved for clinical use to evaluate anesthesia depth. Recently, the Hilbert-Huang transform (HHT) was introduced to analyze nonlinear and nonstationary data. In this study, we assessed whether the changes in EEG characteristics during general anesthesia that are analyzed by the HHT are useful for monitoring the depth of anesthesia. METHODS This retrospective observational study enrolled patients who underwent propofol anesthesia. Raw EEG signals were obtained from a monitor through a previously developed software application. We developed an HHT analyzer to decompose the EEG signal into six intrinsic mode functions (IMFs) and estimated the instantaneous frequencies (HHT_IF) for each IMF. Changes over time in the raw EEG waves and parameters such as HHT_IF, BIS, spectral edge frequency 95 (SEF95), and electromyogram parameter (EMGlow) were assessed, and a Gaussian process regression model was created to assess the association between BIS and HHT_IF. RESULTS We analyzed EEG signals from 30 patients. The beta oscillation frequency range (13-25 Hz) was detected in IMF1 and IMF2 during the awake state, then after loss of consciousness, the frequency decreased and alpha oscillation (8-12 Hz) was detected in IMF2. At the emergence phase, the frequency increased and beta oscillations were detected in IMF1, IMF2, and IMF3. BIS and EMGlow changed significantly during the induction and emergence phases, whereas SEF95 showed a wide variability and no significant changes during the induction phase. The root mean square error between the observed BIS values and the values predicted by a Gaussian process regression model ranged from 4.69 to 9.68. CONCLUSIONS We applied the HHT to EEG analyses during propofol anesthesia. The instantaneous frequency in IMF1 and IMF2 identified changes in EEG characteristics during induction and emergence from general anesthesia. Moreover, the HHT_IF in IMF2 showed strong associations with BIS and was suitable for depicting the alpha oscillation. Our study suggests that the HHT is useful for monitoring the depth of anesthesia.
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Affiliation(s)
- Yurie Obata
- Department of Anesthesiology, Yodogawa Christian Hospital, 1-7-50 Kunijima, Higashiyodogawaku, 533-0024, Osaka, Japan.
| | - Tomomi Yamada
- Department of Anesthesiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Koichi Akiyama
- Department of Anesthesiology, Kindai University, Osaka, Japan
| | - Teiji Sawa
- Department of Anesthesiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
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92
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Hutcheon EA, Vakorin VA, Nunes A, Ribary U, Ferguson S, Claydon VE, Doesburg SM. Associations between spontaneous electroencephalogram oscillations and oxygen saturation across normobaric and hypobaric hypoxia. Hum Brain Mapp 2023; 44:2345-2364. [PMID: 36715216 PMCID: PMC10028628 DOI: 10.1002/hbm.26214] [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: 05/10/2022] [Revised: 12/12/2022] [Accepted: 01/09/2023] [Indexed: 01/31/2023] Open
Abstract
High-altitude indoctrination (HAI) trains individuals to recognize symptoms of hypoxia by simulating high-altitude conditions using normobaric (NH) or hypobaric (HH) hypoxia. Previous studies suggest that despite equivalent inspired oxygen levels, physiological differences could exist between these conditions. In particular, differences in neurophysiological responses to these conditions are not clear. Our study aimed to investigate correlations between oxygen saturation (SpO2 ) and neural responses in NH and HH. We recorded 5-min of resting-state eyes-open electroencephalogram (EEG) and SpO2 during control, NH, and HH conditions from 13 participants. We applied a multivariate framework to characterize correlations between SpO2 and EEG measures (spectral power and multiscale entropy [MSE]), within each participant and at the group level. Participants were desaturating during the first 150 s of NH versus steadily desaturated in HH. We considered the entire time interval, first and second half intervals, separately. All the conditions were characterized by statistically significant participant-specific patterns of EEG-SpO2 correlations. However, at the group level, the desaturation period expressed a robust pattern of these correlations across frequencies and brain locations. Specifically, the first 150 s of NH during desaturation differed significantly from the other conditions with negative absolute alpha power-SpO2 correlations and positive MSE-SpO2 correlations. Once steadily desaturated, NH and HH had no significant differences in EEG-SpO2 correlations. Our findings indicate that the desaturating phase of hypoxia is a critical period in HAI courses, which would require developing strategies for mitigating the hypoxic stimulus in a real-world situation.
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Affiliation(s)
- Evan A Hutcheon
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Vasily A Vakorin
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Adonay Nunes
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
- Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Urs Ribary
- Department of Psychology, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Sherri Ferguson
- Environmental Physiology and Medicine Unit, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Victoria E Claydon
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Sam M Doesburg
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
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93
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Azuma S, Asamoto M, Hattori K, Otsuji M, Uchida K, Yamada Y. Quantitative relationship between anteriorization of alpha oscillations and level of general anesthesia. J Clin Monit Comput 2023; 37:609-618. [PMID: 36316519 DOI: 10.1007/s10877-022-00932-z] [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: 07/25/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022]
Abstract
A typical electroencephalogram (EEG) change induced by general anesthesia is anteriorization-disappearance of occipital alpha oscillations followed by the development of frontal alpha oscillations. Investigating the quantitative relationship between such a specific EEG change and the level of anesthesia has academic and clinical importance. We quantified the degree of anteriorization and investigated its detailed relationship with the level of anesthesia. We acquired 21-electrode EEG data and bispectral index (BIS) values of 50 patients undergoing surgery from before anesthesia induction until after patient arousal. For each epoch of a 10.24-s window with 1-s offsets, we calculated frontal alpha power [Formula: see text], occipital alpha power [Formula: see text], and their difference [Formula: see text] to quantify anteriorization. We calculated Spearman's rank correlation coefficients between these values and the BIS value. We used locally weighted regression to estimate [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] at each BIS value. Thirty-six patients (26 females and 10 males aged 24-85 years) were analyzed. The 95% confidence intervals for the mean of Fisher transformations of Spearman's rank correlation coefficients between [Formula: see text], [Formula: see text], and [Formula: see text] and BIS value were [- 0.68, - 0.26], [0.02, 0.62], and [- 1.11, - 0.91], respectively. The change in [Formula: see text] and [Formula: see text] with BIS value showed different patterns by the type of anesthetic agent, whereas that in [Formula: see text] was more consistent with smaller individual variance. Anteriorization, quantified by the difference between frontal and occipital alpha powers, continuously developed in conjunction with general anesthesia. Quantifying anteriorization may provide an objective indicator of the level of anesthesia.
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Affiliation(s)
- Seiichi Azuma
- Department of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan
- Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Masaaki Asamoto
- Department of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan.
| | - Kohshi Hattori
- Department of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan
- Department of Anesthesiology, Center Hospital of the National Center for Global Health and Medicine, Tokyo, Japan
| | - Mikiya Otsuji
- Department of Anesthesiology, Tokyo Teishin Hospital, Tokyo, Japan
| | - Kanji Uchida
- Department of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan
| | - Yoshitsugu Yamada
- Department of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan
- Department of Anesthesiology, International University of Health and Welfare Mita Hospital, Tokyo, Japan
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94
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Tian F, Lewis LD, Zhou DW, Balanza GA, Paulk AC, Zelmann R, Peled N, Soper D, Santa Cruz Mercado LA, Peterfreund RA, Aglio LS, Eskandar EN, Cosgrove GR, Williams ZM, Richardson RM, Brown EN, Akeju O, Cash SS, Purdon PL. Characterizing brain dynamics during ketamine-induced dissociation and subsequent interactions with propofol using human intracranial neurophysiology. Nat Commun 2023; 14:1748. [PMID: 36991011 PMCID: PMC10060225 DOI: 10.1038/s41467-023-37463-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 03/17/2023] [Indexed: 03/31/2023] Open
Abstract
Ketamine produces antidepressant effects in patients with treatment-resistant depression, but its usefulness is limited by its psychotropic side effects. Ketamine is thought to act via NMDA receptors and HCN1 channels to produce brain oscillations that are related to these effects. Using human intracranial recordings, we found that ketamine produces gamma oscillations in prefrontal cortex and hippocampus, structures previously implicated in ketamine's antidepressant effects, and a 3 Hz oscillation in posteromedial cortex, previously proposed as a mechanism for its dissociative effects. We analyzed oscillatory changes after subsequent propofol administration, whose GABAergic activity antagonizes ketamine's NMDA-mediated disinhibition, alongside a shared HCN1 inhibitory effect, to identify dynamics attributable to NMDA-mediated disinhibition versus HCN1 inhibition. Our results suggest that ketamine engages different neural circuits in distinct frequency-dependent patterns of activity to produce its antidepressant and dissociative sensory effects. These insights may help guide the development of brain dynamic biomarkers and novel therapeutics for depression.
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Affiliation(s)
- Fangyun Tian
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Department of Radiology, MGH/HST Martinos Center for Biomedical Imaging and Harvard Medical School, Boston, MA, USA
- Institute for Medical Engineering and Sciences, Department of Electrical Engineering and Computer Science, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - David W Zhou
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Gustavo A Balanza
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Noam Peled
- Department of Radiology, MGH/HST Martinos Center for Biomedical Imaging and Harvard Medical School, Boston, MA, USA
| | - Daniel Soper
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Laura A Santa Cruz Mercado
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert A Peterfreund
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Linda S Aglio
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Emad N Eskandar
- Department of Neurological Surgery, Albert Einstein College of Medicine, Bronx, NY, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Emery N Brown
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Oluwaseun Akeju
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick L Purdon
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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95
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Yuechen Z, Shaosong X, Zhouxing Z, Fuli G, Wei H. A summary of the current diagnostic methods for, and exploration of the value of microRNAs as biomarkers in, sepsis-associated encephalopathy. Front Neurosci 2023; 17:1125888. [PMID: 37008225 PMCID: PMC10060640 DOI: 10.3389/fnins.2023.1125888] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/02/2023] [Indexed: 03/18/2023] Open
Abstract
Sepsis-associated encephalopathy (SAE) is an acute neurological deficit caused by severe sepsis without signs of direct brain infection, characterized by the systemic inflammation and disturbance of the blood-brain barrier. SAE is associated with a poor prognosis and high mortality in patients with sepsis. Survivors may exhibit long-term or permanent sequelae, including behavioral changes, cognitive impairment, and decreased quality of life. Early detection of SAE can help ameliorate long-term sequelae and reduce mortality. Half of the patients with sepsis suffer from SAE in the intensive care unit, but its physiopathological mechanism remains unknown. Therefore, the diagnosis of SAE remains a challenge. The current clinical diagnosis of SAE is a diagnosis of exclusion; this makes the process complex and time-consuming and delays early intervention by clinicians. Furthermore, the scoring scales and laboratory indicators involved have many problems, including insufficient specificity or sensitivity. Thus, a new biomarker with excellent sensitivity and specificity is urgently needed to guide the diagnosis of SAE. MicroRNAs have attracted attention as putative diagnostic and therapeutic targets for neurodegenerative diseases. They exist in various body fluids and are highly stable. Based on the outstanding performance of microRNAs as biomarkers for other neurodegenerative diseases, it is reasonable to infer that microRNAs will be excellent biomarkers for SAE. This review explores the current diagnostic methods for sepsis-associated encephalopathy (SAE). We also explore the role that microRNAs could play in SAE diagnosis and if they can be used to make the SAE diagnosis faster and more specific. We believe that our review makes a significant contribution to the literature because it summarizes some of the important diagnostic methods for SAE, highlighting their advantages and disadvantages in clinical use, and could benefit the field as it highlights the potential of miRNAs as SAE diagnostic markers.
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Affiliation(s)
| | - Xi Shaosong
- Department of Critical Care Medicine, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | | | | | - Hu Wei
- Department of Critical Care Medicine, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
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96
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Weiner VS, Zhou DW, Kahali P, Stephen EP, Peterfreund RA, Aglio LS, Szabo MD, Eskandar EN, Salazar-Gomez AF, Sampson AL, Cash SS, Brown EN, Purdon PL. Propofol disrupts alpha dynamics in functionally distinct thalamocortical networks during loss of consciousness. Proc Natl Acad Sci U S A 2023; 120:e2207831120. [PMID: 36897972 PMCID: PMC10089159 DOI: 10.1073/pnas.2207831120] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 01/14/2023] [Indexed: 03/12/2023] Open
Abstract
During propofol-induced general anesthesia, alpha rhythms measured using electroencephalography undergo a striking shift from posterior to anterior, termed anteriorization, where the ubiquitous waking alpha is lost and a frontal alpha emerges. The functional significance of alpha anteriorization and the precise brain regions contributing to the phenomenon are a mystery. While posterior alpha is thought to be generated by thalamocortical circuits connecting nuclei of the sensory thalamus with their cortical partners, the thalamic origins of the propofol-induced alpha remain poorly understood. Here, we used human intracranial recordings to identify regions in sensory cortices where propofol attenuates a coherent alpha network, distinct from those in the frontal cortex where it amplifies coherent alpha and beta activities. We then performed diffusion tractography between these identified regions and individual thalamic nuclei to show that the opposing dynamics of anteriorization occur within two distinct thalamocortical networks. We found that propofol disrupted a posterior alpha network structurally connected with nuclei in the sensory and sensory associational regions of the thalamus. At the same time, propofol induced a coherent alpha oscillation within prefrontal cortical areas that were connected with thalamic nuclei involved in cognition, such as the mediodorsal nucleus. The cortical and thalamic anatomy involved, as well as their known functional roles, suggests multiple means by which propofol dismantles sensory and cognitive processes to achieve loss of consciousness.
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Affiliation(s)
- Veronica S. Weiner
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA02139
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA02139
| | - David W. Zhou
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA02139
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA02139
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
- Center for Neurotechnology and Recovery, Department of Neurology, Massachusetts General Hospital, Boston, MA02114
| | - Pegah Kahali
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA02139
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
| | - Emily P. Stephen
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Robert A. Peterfreund
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
- Harvard Medical School, Boston, MA02115
| | - Linda S. Aglio
- Harvard Medical School, Boston, MA02115
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Boston, MA02115
| | - Michele D. Szabo
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
| | - Emad N. Eskandar
- Harvard Medical School, Boston, MA02115
- Department of Neurological Surgery, Massachusetts General Hospital, Boston, MA02114
| | - Andrés F. Salazar-Gomez
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
| | - Aaron L. Sampson
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
| | - Sydney S. Cash
- Center for Neurotechnology and Recovery, Department of Neurology, Massachusetts General Hospital, Boston, MA02114
- Harvard Medical School, Boston, MA02115
| | - Emery N. Brown
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA02139
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA02139
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
- Harvard Medical School, Boston, MA02115
- Division of Health Sciences and Technology, Harvard Medical School/Massachusetts Institute of Technology, Cambridge, MA02139
- Institute of Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Patrick L. Purdon
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA02114
- Harvard Medical School, Boston, MA02115
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97
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Xu C, Li H, Gao J, Li L, He F, Yu J, Ling Y, Gao J, Li J, Melloni L, Luo B, Ding N. Statistical learning in patients in the minimally conscious state. Cereb Cortex 2023; 33:2507-2516. [PMID: 35670595 DOI: 10.1093/cercor/bhac222] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/08/2022] [Accepted: 05/10/2022] [Indexed: 12/22/2022] Open
Abstract
When listening to speech, cortical activity can track mentally constructed linguistic units such as words, phrases, and sentences. Recent studies have also shown that the neural responses to mentally constructed linguistic units can predict the outcome of patients with disorders of consciousness (DoC). In healthy individuals, cortical tracking of linguistic units can be driven by both long-term linguistic knowledge and online learning of the transitional probability between syllables. Here, we investigated whether statistical learning could occur in patients in the minimally conscious state (MCS) and patients emerged from the MCS (EMCS) using electroencephalography (EEG). In Experiment 1, we presented to participants an isochronous sequence of syllables, which were composed of either 4 real disyllabic words or 4 reversed disyllabic words. An inter-trial phase coherence analysis revealed that the patient groups showed similar word tracking responses to real and reversed words. In Experiment 2, we presented trisyllabic artificial words that were defined by the transitional probability between words, and a significant word-rate EEG response was observed for MCS patients. These results suggested that statistical learning can occur with a minimal conscious level. The residual statistical learning ability in MCS patients could potentially be harnessed to induce neural plasticity.
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Affiliation(s)
- Chuan Xu
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Hangcheng Li
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Jiaxin Gao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
- Research Center for Advanced Artificial Intelligence Theory, Zhejiang Lab, Hangzhou 311121, China
| | - Lingling Li
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Fangping He
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Jie Yu
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Yi Ling
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Jian Gao
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Jingqi Li
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Lucia Melloni
- New York University Comprehensive Epilepsy Center, 223 34th Street, New York, NY 10016, USA
| | - Benyan Luo
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Nai Ding
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
- Research Center for Advanced Artificial Intelligence Theory, Zhejiang Lab, Hangzhou 311121, China
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98
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Hight D, Kreuzer M, Ugen G, Schuller P, Stüber F, Sleigh J, Kaiser HA. Five commercial 'depth of anaesthesia' monitors provide discordant clinical recommendations in response to identical emergence-like EEG signals. Br J Anaesth 2023; 130:536-545. [PMID: 36894408 DOI: 10.1016/j.bja.2022.12.026] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 12/16/2022] [Accepted: 12/18/2022] [Indexed: 03/09/2023] Open
Abstract
BACKGROUND 'Depth of anaesthesia' monitors claim to measure hypnotic depth during general anaesthesia from the EEG, and clinicians could reasonably expect agreement between monitors if presented with the same EEG signal. We took 52 EEG signals showing intraoperative patterns of diminished anaesthesia, similar to those that occur during emergence (after surgery) and subjected them to analysis by five commercially available monitors. METHODS We compared five monitors (BIS, Entropy-SE, Narcotrend, qCON, and Sedline) to see if index values remained within, or moved out of, each monitors' recommended index range for general anaesthesia for at least 2 min during a period of supposed lighter anaesthesia, as observed by changes in the EEG spectrogram obtained in a previous study. RESULTS Of the 52 cases, 27 (52%) had at least one monitor warning of potentially inadequate hypnosis (index above range) and 16 of the 52 cases (31%) had at least one monitor signifying excessive hypnotic depth (index below clinical range). Of the 52 cases, only 16 (31%) showed concordance between all five monitors. Nineteen cases (36%) had one monitor discordant compared with the remaining four, and 17 cases (33%) had two monitors in disagreement with the remaining three. CONCLUSIONS Many clinical providers still rely on index values and manufacturer's recommended ranges for titration decision making. That two-thirds of cases showed discordant recommendations given identical EEG data, and that one-third signified excessive hypnotic depth where the EEG would suggest a lighter hypnotic state, emphasizes the importance of personalised EEG interpretation as an essential clinical skill.
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Affiliation(s)
- Darren Hight
- Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
| | - Matthias Kreuzer
- Department of Anesthesiology and Intensive Care Medicine, Technical University of Munich, School of Medicine, Munich, Germany
| | - Gesar Ugen
- Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Peter Schuller
- Department of Anaesthesia, Cairns Hospital, Cairns, QLD, Australia
| | - Frank Stüber
- Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Jamie Sleigh
- Department of Anaesthesia, Waikato Clinical School, University of Auckland, Hamilton, New Zealand
| | - Heiko A Kaiser
- Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland; Centre for Anaesthesiology and Intensive Care Medicine, Hirslanden Klinik Aarau, Hirslanden Group, Aarau, Switzerland
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Lendner JD, Harler U, Daume J, Engel AK, Zöllner C, Schneider TR, Fischer M. Oscillatory and aperiodic neuronal activity in working memory following anesthesia. Clin Neurophysiol 2023; 150:79-88. [PMID: 37028144 DOI: 10.1016/j.clinph.2023.03.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 02/07/2023] [Accepted: 03/02/2023] [Indexed: 03/28/2023]
Abstract
OBJECTIVE Anesthesia and surgery are associated with cognitive impairment, particularly memory deficits. So far, electroencephalography markers of perioperative memory function remain scarce. METHODS We included male patients >60 years scheduled for prostatectomy under general anesthesia. We obtained neuropsychological assessments and a visual match-to-sample working memory task with simultaneous 62-channel scalp electroencephalography 1 day before and 2 to 3 days after surgery. RESULTS Twenty-six patients completed both pre- and postoperative sessions. Compared with preoperative performance, verbal learning deteriorated after anesthesia (California Verbal Learning Test total recall; t25 = -3.25, p = 0.015, d = -0.902), while visual working memory performance showed a dissociation between match and mismatch accuracy (match*session F1,25 = 3.866, p = 0.060). Better verbal learning was associated with an increase of aperiodic brain activity (total recall r = 0.66, p = 0.029, learning slope r = 0.66, p = 0.015), whereas visual working memory accuracy was tracked by oscillatory theta/alpha (7 - 9 Hz), low beta (14 - 18 Hz) and high beta/gamma (34 - 38 Hz) activity (matches: p < 0.001, mismatches: p = 0.022). CONCLUSIONS Oscillatory and aperiodic brain activity in scalp electroencephalography track distinct features of perioperative memory function. SIGNIFICANCE Aperiodic activity provides a potential electroencephalographic biomarker to identify patients at risk for postoperative cognitive impairments.
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100
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Choe M, Jin SH, Kim JS, Chung CK. Propofol anesthesia-induced spatiotemporal changes in cortical activity with loss of external and internal awareness: An electrocorticography study. Clin Neurophysiol 2023; 149:51-60. [PMID: 36898318 DOI: 10.1016/j.clinph.2023.01.020] [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: 07/27/2022] [Revised: 01/12/2023] [Accepted: 01/29/2023] [Indexed: 02/17/2023]
Abstract
OBJECTIVE To understand the underlying mechanism of consciousness, investigating spatiotemporal changes in the cortical activity during the induction phase of unconsciousness is important. Loss of consciousness induced by general anesthesia is not necessarily accompanied by a uniform inhibition of all cortical activities. We hypothesized that cortical regions involved in internal awareness would be suppressed after disruption of cortical regions involved in external awareness. Thus, we investigated temporal changes in cortex during induction of unconsciousness. METHODS We recorded electrocorticography data of 16 epilepsy patients and investigated power spectral changes during induction phase from awake state to unconsciousness. Temporal changes were assessed at 1) the start point and 2) the interval of normalized time between start and end of power change (Δ tnormalized). RESULTS We found that the power increased at frequencies < 46 Hz, and decreased in range of 62-150 Hz, in global channels. In temporal changes of power change, superior parietal lobule and dorsolateral prefrontal cortex started to change early, but the changes were completed over a prolonged interval, whereas angular gyrus and associative visual cortex showed a delayed change and rapid completion. CONCLUSIONS Loss of consciousness induced by general anesthesia results first from disrupted communication between self and external world, followed by disrupted communication within self, with decreased activities of superior parietal lobule and dorsolateral prefrontal cortex, and later, attenuated activities of angular gyrus. SIGNIFICANCE Our findings provided neurophysiological evidence for the temporal changes in consciousness components induced by general anesthesia.
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Affiliation(s)
- Mikyung Choe
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Seung-Hyun Jin
- Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - June Sic Kim
- The Research Institute of Basic Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Chun Kee Chung
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea; Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Neurosurgery, Seoul National University Hospital, Seoul, Republic of Korea.
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