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Rhee SH, Kweon YS, Won DO, Lee SW, Seo KS. Identification of an effective and safe bolus dose and lockout time for patient-controlled sedation (PCS) using dexmedetomidine in dental treatments: a randomized clinical trial. J Dent Anesth Pain Med 2024; 24:19-35. [PMID: 38362260 PMCID: PMC10864709 DOI: 10.17245/jdapm.2024.24.1.19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 01/18/2024] [Accepted: 01/25/2024] [Indexed: 02/17/2024] Open
Abstract
Background This study investigated a safe and effective bolus dose and lockout time for patient-controlled sedation (PCS) with dexmedetomidine for dental treatments. The depth of sedation, vital signs, and patient satisfaction were investigated to demonstrate safety. Methods Thirty patients requiring dental scaling were enrolled and randomly divided into three groups based on bolus doses and lockout times: group 1 (low dose group, bolus dose 0.05 µg/kg, 1-minute lockout time), group 2 (middle dose group, 0.1 µg/kg, 1-minute), and group 3 (high dose group, 0.2 µg/kg, 3-minute) (n = 10 each). ECG, pulse, oxygen saturation, blood pressure, end-tidal CO2, respiratory rate, and bispectral index scores (BIS) were measured and recorded. The study was conducted in two stages: the first involved sedation without dental treatment and the second included sedation with dental scaling. Patients were instructed to press the drug demand button every 10 s, and the process of falling asleep and waking up was repeated 1-5 times. In the second stage, during dental scaling, patients were instructed to press the drug demand button. Loss of responsiveness (LOR) was defined as failure to respond to auditory stimuli six times, determining sleep onset. Patient and dentist satisfaction were assessed before and after experimentation. Results Thirty patients (22 males) participated in the study. Scaling was performed in 29 patients after excluding one who experienced dizziness during the first stage. The average number of drug administrations until first LOR was significantly lower in group 3 (2.8 times) than groups 1 and 2 (8.0 and 6.5 times, respectively). The time taken to reach the LOR showed no difference between groups. During the second stage, the average time required to reach the LOR during scaling was 583.4 seconds. The effect site concentrations (Ce) was significantly lower in group 1 than groups 2 and 3. In the participant survey on PCS, 8/10 in group 3 reported partial memory loss, whereas 17/20 in groups 1 and 2 recalled the procedure fully or partially. Conclusion PCS with dexmedetomidine can provide a rapid onset of sedation, safe vital sign management, and minimal side effects, thus facilitating smooth dental sedation.
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Affiliation(s)
- Seung-Hyun Rhee
- Department of Dental Anesthesiology, School of Dentistry, Seoul National University, Seoul, Republic of Korea
| | - Young-Seok Kweon
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Dong-Ok Won
- Department of Artificial Intelligence Convergence, Hallym University, Chuncheon, Republic of Korea
| | - Seong-Whan Lee
- Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea
| | - Kwang-Suk Seo
- Department of Dental Anesthesiology, School of Dentistry, Seoul National University, Seoul, Republic of Korea
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2
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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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3
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Tagliabue S, Lindner C, da Prat IC, Sanchez-Guerrero A, Serra I, Kacprzak M, Maruccia F, Silva OM, Weigel UM, de Nadal M, Poca MA, Durduran T. Comparison of cerebral metabolic rate of oxygen, blood flow, and bispectral index under general anesthesia. NEUROPHOTONICS 2023; 10:015006. [PMID: 36911206 PMCID: PMC9993084 DOI: 10.1117/1.nph.10.1.015006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
SIGNIFICANCE The optical measurement of cerebral oxygen metabolism was evaluated. AIM Compare optically derived cerebral signals to the electroencephalographic bispectral index (BIS) sensors to monitor propofol-induced anesthesia during surgery. APPROACH Relative cerebral metabolic rate of oxygen ( rCMRO 2 ) and blood flow (rCBF) were measured by time-resolved and diffuse correlation spectroscopies. Changes were tested against the relative BIS (rBIS) ones. The synchronism in the changes was also assessed by the R-Pearson correlation. RESULTS In 23 measurements, optically derived signals showed significant changes in agreement with rBIS: during propofol induction, rBIS decreased by 67% [interquartile ranges (IQR) 62% to 71%], rCMRO 2 by 33% (IQR 18% to 46%), and rCBF by 28% (IQR 10% to 37%). During recovery, a significant increase was observed for rBIS (48%, IQR 38% to 55%), rCMRO 2 (29%, IQR 17% to 39%), and rCBF (30%, IQR 10% to 44%). The significance and direction of the changes subject-by-subject were tested: the coupling between the rBIS, rCMRO 2 , and rCBF was witnessed in the majority of the cases (14/18 and 12/18 for rCBF and 19/21 and 13/18 for rCMRO 2 in the initial and final part, respectively). These changes were also correlated in time ( R > 0.69 to R = 1 , p - values < 0.05 ). CONCLUSIONS Optics can reliably monitor rCMRO 2 in such conditions.
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Affiliation(s)
- Susanna Tagliabue
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Claus Lindner
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | | | - Angela Sanchez-Guerrero
- Vall d’Hebron University Hospital Research Institute, Neurotraumatology and Neurosurgery Research Unit, Barcelona, Spain
| | - Isabel Serra
- Centre de Recerca Matemàtica, Bellaterra, Spain
- Barcelona Supercomputing Center—Centre Nacional de Supercomputació, Spain
| | - Michał Kacprzak
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Nalecz Institute of Biocybernetics and Biomedical Engineering PAS, Warsaw, Poland
| | - Federica Maruccia
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Vall d’Hebron University Hospital Research Institute, Neurotraumatology and Neurosurgery Research Unit, Barcelona, Spain
| | - Olga Martinez Silva
- Vall d’Hebron University Hospital, Department of Anesthesiology, Barcelona, Spain
| | - Udo M. Weigel
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
- HemoPhotonics S.L., Mediterranean Technology Park, Barcelona, Spain
| | - Miriam de Nadal
- Vall d’Hebron University Hospital, Department of Anesthesiology, Barcelona, Spain
- Universidad Autònoma de Barcelona, Plaça Cívica, Barcelona, Spain
| | - Maria A. Poca
- Vall d’Hebron University Hospital Research Institute, Neurotraumatology and Neurosurgery Research Unit, Barcelona, Spain
- Universidad Autònoma de Barcelona, Plaça Cívica, Barcelona, Spain
- Vall d’Hebron University Hospital, Department of Neurosurgery, Barcelona, Spain
| | - Turgut Durduran
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
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4
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Bak S, Jeong Y, Yeu M, Jeong J. Brain-computer interface to predict impulse buying behavior using functional near-infrared spectroscopy. Sci Rep 2022; 12:18024. [PMID: 36289356 PMCID: PMC9606125 DOI: 10.1038/s41598-022-22653-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/18/2022] [Indexed: 01/24/2023] Open
Abstract
As the rate of vaccination against COVID-19 is increasing, demand for overseas travel is also increasing. Despite people's preference for duty-free shopping, previous studies reported that duty-free shopping increases impulse buying behavior. There are also self-reported tools to measure their impulse buying behavior, but it has the disadvantage of relying on the human memory and perception. Therefore, we propose a Brain-Computer Interface (BCI)-based brain signal processing methodology to supplement these limitations and to reduce ambiguity and conjecture of data. To achieve this goal, we focused on the brain's prefrontal cortex (PFC) activity, which supervises human decision-making and is closely related to impulse buying behavior. The PFC activation is observed by recording signals using a functional near-infrared spectroscopy (fNIRS) while inducing impulse buying behavior in virtual computing environments. We found that impulse buying behaviors were not only higher in online duty-free shops than in online regular stores, but the fNIRS signals were also different on the two sites. We also achieved an average accuracy of 93.78% in detecting impulse buying patterns using a support vector machine. These results were identical to the people's self-reported responses. This study provides evidence as a potential biomarker for detecting impulse buying behavior with fNIRS.
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Affiliation(s)
- SuJin Bak
- grid.222754.40000 0001 0840 2678Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841 South Korea
| | - Yunjoo Jeong
- grid.222754.40000 0001 0840 2678Center for Research in Marketing in School of Business at Korea University, Seoul, 02841 South Korea
| | - Minsun Yeu
- grid.267370.70000 0004 0533 4667College of Business Administration, University of Ulsan, Ulsan, 44610 South Korea
| | - Jichai Jeong
- grid.222754.40000 0001 0840 2678Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841 South Korea
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5
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Di Flumeri G, Ronca V, Giorgi A, Vozzi A, Aricò P, Sciaraffa N, Zeng H, Dai G, Kong W, Babiloni F, Borghini G. EEG-Based Index for Timely Detecting User's Drowsiness Occurrence in Automotive Applications. Front Hum Neurosci 2022; 16:866118. [PMID: 35669201 PMCID: PMC9164820 DOI: 10.3389/fnhum.2022.866118] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
Human errors are widely considered among the major causes of road accidents. Furthermore, it is estimated that more than 90% of vehicle crashes causing fatal and permanent injuries are directly related to mental tiredness, fatigue, and drowsiness of the drivers. In particular, driving drowsiness is recognized as a crucial aspect in the context of road safety, since drowsy drivers can suddenly lose control of the car. Moreover, the driving drowsiness episodes mostly appear suddenly without any prior behavioral evidence. The present study aimed at characterizing the onset of drowsiness in car drivers by means of a multimodal neurophysiological approach to develop a synthetic electroencephalographic (EEG)-based index, able to detect drowsy events. The study involved 19 participants in a simulated scenario structured in a sequence of driving tasks under different situations and traffic conditions. The experimental conditions were designed to induce prominent mental drowsiness in the final part. The EEG-based index, so-called “MDrow index”, was developed and validated to detect the driving drowsiness of the participants. The MDrow index was derived from the Global Field Power calculated in the Alpha EEG frequency band over the parietal brain sites. The results demonstrated the reliability of the proposed MDrow index in detecting the driving drowsiness experienced by the participants, resulting also more sensitive and timely sensible with respect to more conventional autonomic parameters, such as the EyeBlinks Rate and the Heart Rate Variability, and to subjective measurements (self-reports).
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Affiliation(s)
- Gianluca Di Flumeri
- Laboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.,BrainSigns srl, Rome, Italy
| | - Vincenzo Ronca
- BrainSigns srl, Rome, Italy.,Department of Anatomical, Histological, Forensic and Orthopedic Sciences, Sapienza University of Rome, Rome, Italy
| | - Andrea Giorgi
- BrainSigns srl, Rome, Italy.,Department of Anatomical, Histological, Forensic and Orthopedic Sciences, Sapienza University of Rome, Rome, Italy
| | - Alessia Vozzi
- BrainSigns srl, Rome, Italy.,Department of Anatomical, Histological, Forensic and Orthopedic Sciences, Sapienza University of Rome, Rome, Italy
| | - Pietro Aricò
- Laboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.,BrainSigns srl, Rome, Italy
| | | | - Hong Zeng
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China
| | - Guojun Dai
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China
| | - Wanzeng Kong
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China
| | - Fabio Babiloni
- Laboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.,BrainSigns srl, Rome, Italy.,School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China
| | - Gianluca Borghini
- Laboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.,BrainSigns srl, Rome, Italy
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6
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Yeung MK, Chu VW. Viewing neurovascular coupling through the lens of combined EEG-fNIRS: A systematic review of current methods. Psychophysiology 2022; 59:e14054. [PMID: 35357703 DOI: 10.1111/psyp.14054] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/01/2022] [Accepted: 03/08/2022] [Indexed: 12/25/2022]
Abstract
Neurovascular coupling is a key physiological mechanism that occurs in the healthy human brain, and understanding this process has implications for understanding the aging and neuropsychiatric populations. Combined electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has emerged as a promising, noninvasive tool for probing neurovascular interactions in humans. However, the utility of this approach critically depends on the methodological quality used for multimodal integration. Despite a growing number of combined EEG-fNIRS applications reported in recent years, the methodological rigor of past studies remains unclear, limiting the accurate interpretation of reported findings and hindering the translational application of this multimodal approach. To fill this knowledge gap, we critically evaluated various methodological aspects of previous combined EEG-fNIRS studies performed in healthy individuals. A literature search was conducted using PubMed and PsycINFO on June 28, 2021. Studies involving concurrent EEG and fNIRS measurements in awake and healthy individuals were selected. After screening and eligibility assessment, 96 studies were included in the methodological evaluation. Specifically, we critically reviewed various aspects of participant sampling, experimental design, signal acquisition, data preprocessing, outcome selection, data analysis, and results presentation reported in these studies. Altogether, we identified several notable strengths and limitations of the existing EEG-fNIRS literature. In light of these limitations and the features of combined EEG-fNIRS, recommendations are made to improve and standardize research practices to facilitate the use of combined EEG-fNIRS when studying healthy neurovascular coupling processes and alterations in neurovascular coupling among various populations.
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Affiliation(s)
- Michael K Yeung
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Vivian W Chu
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
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7
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Meng M, Dai L, She Q, Ma Y, Kong W. Crossing time windows optimization based on mutual information for hybrid BCI. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:7919-7935. [PMID: 34814281 DOI: 10.3934/mbe.2021392] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Hybrid EEG-fNIRS brain-computer interface (HBCI) is widely employed to enhance BCI performance. EEG and fNIRS signals are combined to increase the dimensionality of the information. Time windows are used to select EEG and fNIRS singles synchronously. However, it ignores that specific modal signals have their own characteristics, when the task is stimulated, the information between the modalities will mismatch at the moment, which has a significant impact on the classification performance. Here we propose a novel crossing time windows optimization for mental arithmetic (MA) based BCI. The EEG and fNIRS signals were segmented separately by sliding time windows. Then crossing time windows (CTW) were combined with each one segment from EEG and fNIRS selected independently. Furthermore, EEG and fNIRS features were extracted using Filter Bank Common Spatial Pattern (FBCSP) and statistical methods from each sample. Mutual information was calculated for FBCSP and statistical features to characterize the discrimination of crossing time windows, and the optimal window would be selected based on the largest mutual information. Finally, a sparse structured framework of Fisher Lasso feature selection (FLFS) was designed to select the joint features, and conventional Linear Discriminant Analysis (LDA) was employed to perform classification. We used proposed method for a MA dataset. The classification accuracy of the proposed method is 92.52 ± 5.38% and higher than other methods, which shows the rationality and superiority of the proposed method.
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Affiliation(s)
- Ming Meng
- Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
| | - Luyang Dai
- Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Qingshan She
- Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
| | - Yuliang Ma
- Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
| | - Wanzeng Kong
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
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9
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Cheremushkin EA, Petrenko NE, Dorokhov VB. [Sleep and neurophysiological correlates of consciousness activation upon awakening]. Zh Nevrol Psikhiatr Im S S Korsakova 2021; 121:14-18. [PMID: 34078854 DOI: 10.17116/jnevro202112104214] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The authors discuss modern ideas about the neurophysiological mechanisms of awakening from sleep and the results of own EEG studies of the spatio-temporal dynamics of the activity of the cerebral hemispheres using the own experimental model for studying consciousness in the sleep-wake paradigm. This model is based on continuous execution of a monotonous psychomotor test performed lying down with eyes closed and allows observing several short-term sleep episodes during a 1-hour experiment, followed by spontaneous awakening and restoration of the psychomotor test. A necessary condition for the restoration of activity during spontaneous awakening is the emergence of the EEG alpha rhythm, the parameters of which determine the effectiveness of the restoration of the psychomotor test and, accordingly, the achievement of a certain level of consciousness, and therefore can be considered as a neurophysiological correlate of consciousness activation upon awakening. The considered experimental model of consciousness can be useful for analyzing the neurophysiological mechanisms of consciousness activation in patients with chronic impairments of consciousness and for searching for effective methods for the rehabilitation of such patients.
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Affiliation(s)
- E A Cheremushkin
- Institute of Higher Nervous Activity and Neurophysiology, Moscow, Russia
| | - N E Petrenko
- Institute of Higher Nervous Activity and Neurophysiology, Moscow, Russia
| | - V B Dorokhov
- Institute of Higher Nervous Activity and Neurophysiology, Moscow, Russia
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10
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Sattin D, Duran D, Visintini S, Schiaffi E, Panzica F, Carozzi C, Rossi Sebastiano D, Visani E, Tobaldini E, Carandina A, Citterio V, Magnani FG, Cacciatore M, Orena E, Montano N, Caldiroli D, Franceschetti S, Picozzi M, Matilde L. Analyzing the Loss and the Recovery of Consciousness: Functional Connectivity Patterns and Changes in Heart Rate Variability During Propofol-Induced Anesthesia. Front Syst Neurosci 2021; 15:652080. [PMID: 33889078 PMCID: PMC8055941 DOI: 10.3389/fnsys.2021.652080] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 03/15/2021] [Indexed: 11/13/2022] Open
Abstract
The analysis of the central and the autonomic nervous systems (CNS, ANS) activities during general anesthesia (GA) provides fundamental information for the study of neural processes that support alterations of the consciousness level. In the present pilot study, we analyzed EEG signals and the heart rate (HR) variability (HRV) in a sample of 11 patients undergoing spinal surgery to investigate their CNS and ANS activities during GA obtained with propofol administration. Data were analyzed during different stages of GA: baseline, the first period of anesthetic induction, the period before the loss of consciousness, the first period after propofol discontinuation, and the period before the recovery of consciousness (ROC). In EEG spectral analysis, we found a decrease in posterior alpha and beta power in all cortical areas observed, except the occipital ones, and an increase in delta power, mainly during the induction phase. In EEG connectivity analysis, we found a significant increase of local efficiency index in alpha and delta bands between baseline and loss of consciousness as well as between baseline and ROC in delta band only and a significant reduction of the characteristic path length in alpha band between the baseline and ROC. Moreover, connectivity results showed that in the alpha band there was mainly a progressive increase in the number and in the strength of incoming connections in the frontal region, while in the beta band the parietal region showed mainly a significant increase in the number and in the strength of outcoming connections values. The HRV analysis showed that the induction of anesthesia with propofol was associated with a progressive decrease in complexity and a consequent increase in the regularity indexes and that the anesthetic procedure determined bradycardia which was accompanied by an increase in cardiac sympathetic modulation and a decrease in cardiac parasympathetic modulation during the induction. Overall, the results of this pilot study showed as propofol-induced anesthesia caused modifications on EEG signal, leading to a "rebalance" between long and short-range cortical connections, and had a direct effect on the cardiac system. Our data suggest interesting perspectives for the interactions between the central and autonomic nervous systems for the modulation of the consciousness level.
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Affiliation(s)
- Davide Sattin
- Neurology, Public Health, Disability Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
- Clinical and Experimental Medicine and Medical Humanities-PhD Program, Insubria University, Varese, Italy
| | - Dunja Duran
- Clinical and Experimental Epileptology Division, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Sergio Visintini
- Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Elena Schiaffi
- Neurophysiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Ferruccio Panzica
- Clinical Engineering Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Carla Carozzi
- Department of Anaesthesia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | | | - Elisa Visani
- Clinical and Experimental Epileptology Division, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Eleonora Tobaldini
- Department of Internal Medicine, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Angelica Carandina
- Department of Internal Medicine, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Valeria Citterio
- Department of Internal Medicine, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Francesca Giulia Magnani
- Neurology, Public Health, Disability Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Martina Cacciatore
- Neurology, Public Health, Disability Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Eleonora Orena
- Department of Anaesthesia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Nicola Montano
- Department of Internal Medicine, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Dario Caldiroli
- Department of Anaesthesia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Silvana Franceschetti
- Neurophysiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Mario Picozzi
- Center for Clinical Ethics, Biotechnology and Life Sciences Department, Insubria University, Varese, Italy
| | - Leonardi Matilde
- Neurology, Public Health, Disability Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
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11
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Kratzer S, Schneider M, Obert DP, Schneider G, García PS, Kreuzer M. Age-Related EEG Features of Bursting Activity During Anesthetic-Induced Burst Suppression. Front Syst Neurosci 2020; 14:599962. [PMID: 33343307 PMCID: PMC7744408 DOI: 10.3389/fnsys.2020.599962] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 11/09/2020] [Indexed: 12/19/2022] Open
Abstract
Electroencephalographic (EEG) Burst Suppression (BSUPP) is a discontinuous pattern characterized by episodes of low voltage disrupted by bursts of cortical synaptic activity. It can occur while delivering high-dose anesthesia. Current research suggests an association between BSUPP and the occurrence of postoperative delirium in the post-anesthesia care unit (PACU) and beyond. We investigated burst micro-architecture to further understand how age influences the neurophysiology of this pharmacologically-induced state. We analyzed a subset of EEG recordings (n = 102) taken from a larger data set previously published. We selected the initial burst that followed a visually identified “silent second,” i.e., at least 1 s of iso-electricity of the EEG during propofol induction. We derived the (normalized) power spectral density [(n)PSD], the alpha band power, the maximum amplitude, the maximum slope of the EEG as well as the permutation entropy (PeEn) for the first 1.5 s of the initial burst of each patient. In the old patients >65 years, we observed significantly lower (p < 0.001) EEG power in the 1–15 Hz range. In general, their EEG contained a significantly higher amount of faster oscillations (>15 Hz). Alpha band power (p < 0.001), EEG amplitude (p = 0.001), and maximum EEG slope (p = 0.045) all significantly decreased with age, whereas PeEn increased (p = 0.008). Hence, we can describe an age-related change in features during EEG burst suppression. Sub-group analysis revealed no change in results based on pre-medication. These EEG changes add knowledge to the impact of age on cortical synaptic activity. In addition to a reduction in EEG amplitude, age-associated burst features can complicate the identification of excessive anesthetic administration in patients under general anesthesia. Knowledge of these neurophysiologic changes may not only improve anesthesia care through improved detection of burst suppression but might also provide insight into changes in neuronal network organization in patients at risk for age-related neurocognitive problems.
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Affiliation(s)
- Stephan Kratzer
- Department of Anesthesiology and Intensive Care Medicine, School of Medicine, Technical University Munich, Munich, Germany
| | - Michael Schneider
- Department of Anesthesiology and Intensive Care Medicine, School of Medicine, Technical University Munich, Munich, Germany
| | - David P Obert
- Department of Anesthesiology and Intensive Care Medicine, School of Medicine, Technical University Munich, Munich, Germany
| | - Gerhard Schneider
- Department of Anesthesiology and Intensive Care Medicine, School of Medicine, Technical University Munich, Munich, Germany
| | - Paul S García
- Department of Anesthesiology, Columbia University, New York, NY, United States
| | - Matthias Kreuzer
- Department of Anesthesiology and Intensive Care Medicine, School of Medicine, Technical University Munich, Munich, Germany
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12
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Jovellar DB, Doudet DJ. fMRI in Non-human Primate: A Review on Factors That Can Affect Interpretation and Dynamic Causal Modeling Application. Front Neurosci 2019; 13:973. [PMID: 31619951 PMCID: PMC6759819 DOI: 10.3389/fnins.2019.00973] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 08/30/2019] [Indexed: 11/13/2022] Open
Abstract
Dynamic causal modeling (DCM)-a framework for inferring hidden neuronal states from brain activity measurements (e. g., fMRI) and their context-dependent modulation-was developed for human neuroimaging, and has not been optimized for non-human primate (NHP) studies, which are usually done under anesthesia. Animal neuroimaging studies offer the potential to improve effective connectivity modeling using DCM through combining functional imaging with invasive procedures such as in vivo optogenetic or electrical stimulation. Employing a Bayesian approach, model parameters are estimated based on prior knowledge of conditions that might be related to neural and BOLD dynamics (e.g., requires empirical knowledge about the range of plausible parameter values). As such, we address the following questions in this review: What factors need to be considered when applying DCM to NHP data? What differences in functional networks, cerebrovascular architecture and physiology exist between human and NHPs that are relevant for DCM application? How do anesthetics affect vascular physiology, BOLD contrast, and neural dynamics-particularly, effective communication within, and between networks? Considering the factors that are relevant for DCM application to NHP neuroimaging, we propose a strategy for modeling effective connectivity under anesthesia using an integrated physiologic-stochastic DCM (IPS-DCM).
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Affiliation(s)
- D Blair Jovellar
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada.,Center of Neurology, Hertie Institute for Clinical Brain Research, University Hospital, Tuebingen, Germany
| | - Doris J Doudet
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
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13
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Alteration of coupling between brain and heart induced by sedation with propofol and midazolam. PLoS One 2019; 14:e0219238. [PMID: 31314775 PMCID: PMC6636731 DOI: 10.1371/journal.pone.0219238] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Accepted: 06/20/2019] [Indexed: 11/19/2022] Open
Abstract
For a comprehensive understanding of the nervous system, several previous studies have examined the network connections between the brain and the heart in diverse conditions. In this study, we identified coupling between the brain and the heart along the continuum of sedation levels, but not in discrete sedation levels (e. g., wakefulness, conscious sedation, and deep sedation). To identify coupling between the brain and the heart during sedation, we induced several depths of sedation using patient-controlled sedation with propofol and midazolam. We performed electroencephalogram (EEG) spectral analysis and extracted the instantaneous heart rate (HR) from the electrocardiogram (ECG). EEG spectral power dynamics and mean HR were compared along the continuum of sedation levels. We found that EEG sigma power was the parameter most sensitive to changes in the sedation level and was correlated with the mean HR under the effect of sedative agents. Moreover, we calculated the Granger causality (GC) value to quantify brain-heart coupling at each sedation level. Additionally, the GC analysis revealed noticeably different strengths and directions of causality among different sedation levels. In all the sedation levels, GC values from the brain to the heart (GCb→h) were higher than GC values from the heart to the brain (GCh→b). Moreover, the mean GCb→h increased as the sedation became deeper, resulting in higher GCb→h values in deep sedation (1.97 ± 0.18 in propofol, 2.02 ± 0.15 in midazolam) than in pre-sedation (1.71 ± 0.13 in propofol, 1.75 ± 0.11 in midazolam; p < 0.001). These results show that coupling between brain and heart activities becomes stronger as sedation becomes deeper, and that this coupling is more attributable to the brain-heart direction than to the heart-brain direction. These findings provide a better understanding of the relationship between the brain and the heart under specific conditions, namely, different sedation states.
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14
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Cascella M, Bimonte S, Muzio MR. Towards a better understanding of anesthesia emergence mechanisms: Research and clinical implications. World J Methodol 2018; 8:9-16. [PMID: 30345225 PMCID: PMC6189114 DOI: 10.5662/wjm.v8.i2.9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 08/09/2018] [Accepted: 08/26/2018] [Indexed: 02/06/2023] Open
Abstract
Emergence from anesthesia (AE) is the ending stage of anesthesia featuring the transition from unconsciousness to complete wakefulness and recovery of consciousness (RoC). A wide range of undesirable complications, including coughing, respiratory/cardiovascular events, and mental status changes such as emergence delirium, and delayed RoC, may occur during this critical phase. In general anesthesia processes, induction and AE represent a neurobiological example of “hysteresis”. Indeed, AE mechanisms should not be simply considered as reverse events of those occurring in the induction phase. Anesthesia-induced loss of consciousness (LoC) and AE until RoC are quite distinct phenomena with, in part, a distinct neurobiology. Althoughanaesthetics produce LoC mostly by affecting cortical connectivity, arousal processes at the end of anesthesia are triggered by structures deep in the brain, rather than being induced within the neocortex. This work aimed to provide an overview on AE processes research, in terms of mechanisms, and EEG findings. Because most of the research in this field concerns preclinical investigations, translational suggestions and research perspectives are proposed. However, little is known about the relationship between AE neurobiology, and potential complications occurring during the emergence, and after the RoC. Thus, another scope of this review is to underline why a better understanding of AE mechanisms could have significant clinical implications, such as improving the patients’ quality of recovery, and avoiding early and late postoperative complications.
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Affiliation(s)
- Marco Cascella
- Division of Anesthesia and Pain Management, Department of Supportive Care, Istituto Nazionale Tumori “Fondazione G. Pascale” - IRCSS, Naples 80131, Italy
| | - Sabrina Bimonte
- Division of Anesthesia and Pain Management, Department of Supportive Care, Istituto Nazionale Tumori “Fondazione G. Pascale” - IRCSS, Naples 80131, Italy
| | - Maria Rosaria Muzio
- Division of Infantile Neuropsychiatry, UOMI-Maternal and Infant Health, ASL NA3 SUD Torre del Greco, Naples 80059, Italy
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Rupawala M, Dehghani H, Lucas SJE, Tino P, Cruse D. Shining a Light on Awareness: A Review of Functional Near-Infrared Spectroscopy for Prolonged Disorders of Consciousness. Front Neurol 2018; 9:350. [PMID: 29872420 PMCID: PMC5972220 DOI: 10.3389/fneur.2018.00350] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/30/2018] [Indexed: 12/19/2022] Open
Abstract
Qualitative clinical assessments of the recovery of awareness after severe brain injury require an assessor to differentiate purposeful behavior from spontaneous behavior. As many such behaviors are minimal and inconsistent, behavioral assessments are susceptible to diagnostic errors. Advanced neuroimaging tools can bypass behavioral responsiveness and reveal evidence of covert awareness and cognition within the brains of some patients, thus providing a means for more accurate diagnoses, more accurate prognoses, and, in some instances, facilitated communication. The majority of reports to date have employed the neuroimaging methods of functional magnetic resonance imaging, positron emission tomography, and electroencephalography (EEG). However, each neuroimaging method has its own advantages and disadvantages (e.g., signal resolution, accessibility, etc.). Here, we describe a burgeoning technique of non-invasive optical neuroimaging—functional near-infrared spectroscopy (fNIRS)—and review its potential to address the clinical challenges of prolonged disorders of consciousness. We also outline the potential for simultaneous EEG to complement the fNIRS signal and suggest the future directions of research that are required in order to realize its clinical potential.
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Affiliation(s)
- Mohammed Rupawala
- Centre for Doctoral Training in Physical Sciences for Health, University of Birmingham, Birmingham, United Kingdom
| | - Hamid Dehghani
- Centre for Doctoral Training in Physical Sciences for Health, University of Birmingham, Birmingham, United Kingdom.,School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Samuel J E Lucas
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Peter Tino
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Damian Cruse
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
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