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Nilsen AS, Arena A, Storm JF. Exploring effects of anesthesia on complexity, differentiation, and integrated information in rat EEG. Neurosci Conscious 2024; 2024:niae021. [PMID: 38757120 PMCID: PMC11097907 DOI: 10.1093/nc/niae021] [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: 07/11/2023] [Revised: 04/09/2024] [Accepted: 04/29/2024] [Indexed: 05/18/2024] Open
Abstract
To investigate mechanisms underlying loss of consciousness, it is important to extend methods established in humans to rodents as well. Perturbational complexity index (PCI) is a promising metric of "capacity for consciousness" and is based on a perturbational approach that allows inferring a system's capacity for causal integration and differentiation of information. These properties have been proposed as necessary for conscious systems. Measures based on spontaneous electroencephalography recordings, however, may be more practical for certain clinical purposes and may better reflect ongoing dynamics. Here, we compare PCI (using electrical stimulation for perturbing cortical activity) to several spontaneous electroencephalography-based measures of signal diversity and integrated information in rats undergoing propofol, sevoflurane, and ketamine anesthesia. We find that, along with PCI, the spontaneous electroencephalography-based measures, Lempel-Ziv complexity (LZ) and geometric integrated information (ΦG), were best able to distinguish between awake and propofol and sevoflurane anesthesia. However, PCI was anti-correlated with spontaneous measures of integrated information, which generally increased during propofol and sevoflurane anesthesia, contrary to expectations. Together with an observed divergence in network properties estimated from directed functional connectivity (current results) and effective connectivity (earlier results), the perturbation-based results seem to suggest that anesthesia disrupts global cortico-cortical information transfer, whereas spontaneous activity suggests the opposite. We speculate that these seemingly diverging results may be because of suppressed encoding specificity of information or driving subcortical projections from, e.g., the thalamus. We conclude that certain perturbation-based measures (PCI) and spontaneous measures (LZ and ΦG) may be complementary and mutually informative when studying altered states of consciousness.
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Affiliation(s)
- André Sevenius Nilsen
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Sognsvannsveien 9, Oslo 0372, Norway
| | - Alessandro Arena
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Sognsvannsveien 9, Oslo 0372, Norway
| | - Johan F Storm
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Sognsvannsveien 9, Oslo 0372, Norway
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Kuruvilla A, Sadle CJ, Mutchnick I, Karia S, Sah J, Stilp R, Dashti S, Karakas C. Super-selective Wada test for pre-surgical leg motor function assessment: A case report. Childs Nerv Syst 2024; 40:1631-1636. [PMID: 38285223 DOI: 10.1007/s00381-024-06302-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/24/2024] [Indexed: 01/30/2024]
Abstract
INTRODUCTION Wada test is well-known to assess lateralization of memory and language functions; however, super-selective Wada (ss-Wada) to evaluate motor leg function is rare. We present a ss-Wada test within the anterior cerebral artery (ACA) to assess the motor function of the leg. METHODS Retrospective chart review. RESULTS Comprehensive phase-I/II surgical evaluation revealed an ictal focus around the left post-central gyrus with immediate involvement around the left para-central regions. To avoid potential right leg motor dysfunction with the surgery, the patient underwent a ss-Wada procedure. Angiography revealed bilateral ACAs were supplied by the left A1 segment. Super-selective microcatheter injection of amobarbital into the left ACA was performed to avoid cross-filling the contralateral ACA. The ss-Wada test confirmed no right leg motor impairment. Afterward, a craniotomy with direct cortical stimulation confirmed that the left-sided ictal/peri-ictal zone had no clear leg motor function. The patient underwent disconnection of that region and remained seizure-free at 10-month post-op follow-up without any motor or sensory deficits in the right limbs. CONCLUSION This case demonstrates the proof of concept for ss-Wada in assessing lower extremity motor function. The ss-Wada procedure accurately predicted no motor deficits in the right leg, consistent with preserved motor function post-surgery.
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Affiliation(s)
- Alexander Kuruvilla
- Division of Pediatric Neurology, Department of Neurology, University of Louisville School of Medicine, 615 S Preston Street, 2nd floor, Louisville, KY, 40202, USA
| | - Charles J Sadle
- Division of Pediatric Neurology, Department of Neurology, University of Louisville School of Medicine, 615 S Preston Street, 2nd floor, Louisville, KY, 40202, USA
| | - Ian Mutchnick
- Department of Neurological Surgery, University of Louisville School of Medicine, Louisville, KY, 40202, USA
- Norton Children's Neuroscience Institute and Children's Hospital, Louisville, KY, 40202, USA
| | - Samir Karia
- Division of Pediatric Neurology, Department of Neurology, University of Louisville School of Medicine, 615 S Preston Street, 2nd floor, Louisville, KY, 40202, USA
- Norton Children's Neuroscience Institute and Children's Hospital, Louisville, KY, 40202, USA
| | - Jeetendra Sah
- Division of Pediatric Neurology, Department of Neurology, University of Louisville School of Medicine, 615 S Preston Street, 2nd floor, Louisville, KY, 40202, USA
- Norton Children's Neuroscience Institute and Children's Hospital, Louisville, KY, 40202, USA
| | - Rebecca Stilp
- Norton Children's Neuroscience Institute and Children's Hospital, Louisville, KY, 40202, USA
| | - Shervin Dashti
- Norton Children's Neuroscience Institute and Children's Hospital, Louisville, KY, 40202, USA
- Department of Neurosurgery, Billings Clinic, Billings, MT, 59101, USA
| | - Cemal Karakas
- Division of Pediatric Neurology, Department of Neurology, University of Louisville School of Medicine, 615 S Preston Street, 2nd floor, Louisville, KY, 40202, USA.
- Norton Children's Neuroscience Institute and Children's Hospital, Louisville, KY, 40202, USA.
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Vrijdag XCE, Hallum LE, Tonks EI, van Waart H, Mitchell SJ, Sleigh JW. Support-vector classification of low-dose nitrous oxide administration with multi-channel EEG power spectra. J Clin Monit Comput 2024; 38:363-371. [PMID: 37440117 PMCID: PMC10995006 DOI: 10.1007/s10877-023-01054-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 06/25/2023] [Indexed: 07/14/2023]
Abstract
Support-vector machines (SVMs) can potentially improve patient monitoring during nitrous oxide anaesthesia. By elucidating the effects of low-dose nitrous oxide on the power spectra of multi-channel EEG recordings, we quantified the degree to which these effects generalise across participants. In this single-blind, cross-over study, 32-channel EEG was recorded from 12 healthy participants exposed to 0, 20, 30 and 40% end-tidal nitrous oxide. Features of the delta-, theta-, alpha- and beta-band power were used within a 12-fold, participant-wise cross-validation framework to train and test two SVMs: (1) binary SVM classifying EEG during 0 or 40% exposure (chance = 50%); (2) multi-class SVM classifying EEG during 0, 20, 30 or 40% exposure (chance = 25%). Both the binary (accuracy 92%) and the multi-class (accuracy 52%) SVMs classified EEG recordings at rates significantly better than chance (p < 0.001 and p = 0.01, respectively). To determine the relative importance of frequency band features for classification accuracy, we systematically removed features before re-training and re-testing the SVMs. This showed the relative importance of decreased delta power and the frontal region. SVM classification identified that the most important effects of nitrous oxide were found in the delta band in the frontal electrodes that was consistent between participants. Furthermore, support-vector classification of nitrous oxide dosage is a promising method that might be used to improve patient monitoring during nitrous oxide anaesthesia.
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Affiliation(s)
- Xavier C E Vrijdag
- Department of Anaesthesiology, School of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
| | - Luke E Hallum
- Department of Mechanical and Mechatronics Engineering, University of Auckland, Auckland, 1142, New Zealand
| | - Emma I Tonks
- Department of Mechanical and Mechatronics Engineering, University of Auckland, Auckland, 1142, New Zealand
| | - Hanna van Waart
- Department of Anaesthesiology, School of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand
| | - Simon J Mitchell
- Department of Anaesthesiology, School of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand
- Department of Anaesthesia, Auckland City Hospital, Auckland, 1023, New Zealand
| | - Jamie W Sleigh
- Department of Anaesthesiology, School of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand
- Department of Anaesthesia, Waikato Hospital, Hamilton, 3240, New Zealand
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Hönigsperger C, Storm JF, Arena A. Laminar evoked responses in mouse somatosensory cortex suggest a special role for deep layers in cortical complexity. Eur J Neurosci 2024; 59:752-770. [PMID: 37586411 DOI: 10.1111/ejn.16108] [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: 12/13/2022] [Revised: 07/03/2023] [Accepted: 07/20/2023] [Indexed: 08/18/2023]
Abstract
It has been suggested that consciousness is closely related to the complexity of the brain. The perturbational complexity index (PCI) has been used in humans and rodents to distinguish conscious from unconscious states based on the global cortical responses (recorded by electroencephalography, EEG) to local cortical stimulation (CS). However, it is unclear how different cortical layers respond to CS and contribute to the resulting intra- and inter-areal cortical connectivity and PCI. A detailed investigation of the local dynamics is needed to understand the basis for PCI. We hypothesized that the complexity level of global cortical responses (PCI) correlates with layer-specific activity and connectivity. We tested this idea by measuring global cortical dynamics and layer-specific activity in the somatosensory cortex (S1) of mice, combining cortical electrical stimulation in deep motor cortex, global electrocorticography (ECoG) and local laminar recordings from layers 1-6 in S1, during wakefulness and general anaesthesia (sevoflurane). We found that the transition from wake to sevoflurane anaesthesia correlated with a drop in both the global and local PCI (PCIst ) values (complexity). This was accompanied by a local decrease in neural firing rate, spike-field coherence and long-range functional connectivity specific to deep layers (L5, L6). Our results suggest that deep cortical layers are mechanistically important for changes in PCI and thereby for changes in the state of consciousness.
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Affiliation(s)
| | - Johan F Storm
- Department of Molecular Medicine, University of Oslo, Oslo, Norway
| | - Alessandro Arena
- Department of Molecular Medicine, University of Oslo, Oslo, Norway
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Kentar M, Díaz-Peregrino R, Trenado C, Sánchez-Porras R, San-Juan D, Ramírez-Cuapio FL, Holzwarth N, Maier-Hein L, Woitzik J, Santos E. Spatial and temporal frequency band changes during infarct induction, infarct progression, and spreading depolarizations in the gyrencephalic brain. Front Neurosci 2022; 16:1025967. [PMID: 36570832 PMCID: PMC9769704 DOI: 10.3389/fnins.2022.1025967] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/18/2022] [Indexed: 12/07/2022] Open
Abstract
Aim To describe the spatial and temporal electrocorticographic (ECoG) changes after middle cerebral artery occlusion (MCAo), including those caused by spreading depolarization (SD) in the pig brain. Methods The left middle cerebral arteries (MCAs) were clipped in six pigs. The clipping procedure lasted between 8 and 12 min, achieving a permanent occlusion (MCAo). Five-contact ECoG stripes were placed bilaterally over the frontoparietal cortices corresponding to the irrigation territory of the MCA and anterior cerebral artery (ACA). ECoG recordings were performed around 24 h: 1 h before and 23 h after the MCAo, and SDs were quantified. Five-minute ECoG signal segments were sampled before, 5 min, and 4, 8, and 12 h after cerebral artery occlusion and before, during, and after the negative direct current shift of the SDs. The power spectrum of the signals was decomposed into delta, theta, alpha, beta, and gamma bands. Descriptive statistics, Wilcoxon matched-pairs signed-rank tests, and Friedman tests were performed. Results Electrodes close to the MCAo showed instant decay in all frequency bands and SD onset during the first 5 h. Electrodes far from the MCAo exhibited immediate loss of fast frequencies and progressive decline of slow frequencies with an increased SD incidence between 6 and 14 h. After 8 h, the ACA electrode reported a secondary reduction of all frequency bands except gamma and high SD incidence within 12-17 h. During the SD, all electrodes showed a decline in all frequency bands. After SD passage, frequency band recovery was impaired only in MCA electrodes. Conclusion ECoG can identify infarct progression and secondary brain injury. Severe disturbances in all the frequency bands are generated in the cortices where the SDs are passing by.
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Affiliation(s)
- Modar Kentar
- Department of Neurosurgery, University Hospital Heidelberg, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Roberto Díaz-Peregrino
- Department of Neurosurgery, University Hospital Heidelberg, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Carlos Trenado
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Renán Sánchez-Porras
- Department of Neurosurgery, Evangelisches Krankenhaus, Carl-von-Ossietzky University, Oldenburg, Germany
| | - Daniel San-Juan
- Epilepsy Clinic, National Institute of Neurology and Neurosurgery, Manuel Velasco Suárez, Mexico City, Mexico
| | - F. Leonardo Ramírez-Cuapio
- Department of Neurosurgery, University Hospital Heidelberg, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Niklas Holzwarth
- Division of Intelligent Medical Systems, German Cancer Research Center, Heidelberg, Germany
| | - Lena Maier-Hein
- Division of Intelligent Medical Systems, German Cancer Research Center, Heidelberg, Germany
| | - Johannes Woitzik
- Department of Neurosurgery, Evangelisches Krankenhaus, Carl-von-Ossietzky University, Oldenburg, Germany
| | - Edgar Santos
- Department of Neurosurgery, University Hospital Heidelberg, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany,Department of Neurosurgery, Evangelisches Krankenhaus, Carl-von-Ossietzky University, Oldenburg, Germany,*Correspondence: Edgar Santos,
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Alsafy I, Diykh M. Developing a robust model to predict depth of anesthesia from single channel EEG signal. Phys Eng Sci Med 2022; 45:793-808. [PMID: 35790625 PMCID: PMC9448694 DOI: 10.1007/s13246-022-01145-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/20/2022] [Indexed: 11/29/2022]
Abstract
Monitoring depth of anaesthesia (DoA) from electroencephalograph (EEG) signals is an ongoing challenge for anaesthesiologists. In this study, we propose an intelligence model that predicts the DoA from a single channel electroencephalograph (EEG) signal. A segmentation technique based on a sliding window is employed to partition EEG signals. Hierarchical dispersion entropy (HDE) is applied to each EEG segment. A set of features is extracted from each EEG segment. The extracted features are investigated using a community graph detection approach (CGDA), and the most relevant features are selected to trace the DoA. The proposed model, based on HDE coupled with CGDA, is evaluated in term of BIS index using several statistical metrics such Q-Q plot, regression, and correlation coefficients. In addition, the proposed model is evaluated against the BIS index in the case of the poor signal quality. The results demonstrated that the proposed model showed an earlier reaction compared with the BIS index when patient’s state transits from deep anaesthesia to moderate anaesthesia in the case of poor signal quality. The highest Pearson correlation coefficient obtained by the proposed is 0.96.
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Affiliation(s)
- Iman Alsafy
- College of Education for Pure Sciences, University of Thi-Qar, Nasiriyah, Iraq
| | - Mohammed Diykh
- College of Education for Pure Sciences, University of Thi-Qar, Nasiriyah, Iraq. .,USQ College, University of Southern Queensland, Toowoomba, QLD, 4350, Australia. .,Information and Communication Technology Research Group, Scientific Research Centre, Al-Ayen University, Nasiriyah, Iraq.
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Searching in the wrong place: Might consciousness reside in the brainstem? Behav Brain Sci 2022; 45:e46. [PMID: 35319425 DOI: 10.1017/s0140525x21001928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Doubtless, the conscious brain integrates masses of information. But declaring that consciousness simply "emerges" when enough has accumulated, doesn't really explain how first person experience is implemented by neurons. Moreover, empirical observations challenge integrated information theory's (IIT) reliance on thalamo-cortical interactions as the information integrator. More likely, the cortex streams processed information to a still-enigmatic consciousness generator, one perhaps located in the brainstem.
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Han Y, Ziebell P, Riccio A, Halder S. Two sides of the same coin: adaptation of BCIs to internal states with user-centered design and electrophysiological features. BRAIN-COMPUTER INTERFACES 2022. [DOI: 10.1080/2326263x.2022.2041294] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Yiyuan Han
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK
| | - Philipp Ziebell
- Institute of Psychology, University of Würzburg, Würzburg, Germany
| | - Angela Riccio
- Neuroelectrical Imaging and Brain Computer Interface Laboratory,Fondazione Santa Lucia, Irccs, Rome, Italy
| | - Sebastian Halder
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK
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Baron M, Devor M. Might pain be experienced in the brainstem rather than in the cerebral cortex? Behav Brain Res 2022; 427:113861. [DOI: 10.1016/j.bbr.2022.113861] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/09/2022] [Accepted: 03/23/2022] [Indexed: 11/02/2022]
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Huggins JE, Krusienski D, Vansteensel MJ, Valeriani D, Thelen A, Stavisky S, Norton JJS, Nijholt A, Müller-Putz G, Kosmyna N, Korczowski L, Kapeller C, Herff C, Halder S, Guger C, Grosse-Wentrup M, Gaunt R, Dusang AN, Clisson P, Chavarriaga R, Anderson CW, Allison BZ, Aksenova T, Aarnoutse E. Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier. BRAIN-COMPUTER INTERFACES 2022; 9:69-101. [PMID: 36908334 PMCID: PMC9997957 DOI: 10.1080/2326263x.2021.2009654] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 11/15/2021] [Indexed: 12/11/2022]
Abstract
The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.
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Affiliation(s)
- Jane E Huggins
- Department of Physical Medicine and Rehabilitation, Department of Biomedical Engineering, Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, United States 325 East Eisenhower, Room 3017; Ann Arbor, Michigan 48108-5744, 734-936-7177
| | - Dean Krusienski
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23219
| | - Mariska J Vansteensel
- UMC Utrecht Brain Center, Dept of Neurosurgery, University Medical Center Utrecht, The Netherlands
| | | | - Antonia Thelen
- eemagine Medical Imaging Solutions GmbH, Berlin, Germany
| | | | - James J S Norton
- National Center for Adaptive Neurotechnologies, US Department of Veterans Affairs, 113 Holland Ave, Albany, NY 12208
| | - Anton Nijholt
- Faculty EEMCS, University of Twente, Enschede, The Netherlands
| | - Gernot Müller-Putz
- Institute of Neural Engineering, GrazBCI Lab, Graz University of Technology, Stremayrgasse 16/4, 8010 Graz, Austria
| | - Nataliya Kosmyna
- Massachusetts Institute of Technology (MIT), Media Lab, E14-548, Cambridge, MA 02139, Unites States
| | | | | | - Christian Herff
- School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Christoph Guger
- g.tec medical engineering GmbH/Guger Technologies OG, Austria, Sierningstrasse 14, 4521 Schiedlberg, Austria, +43725122240-0
| | - Moritz Grosse-Wentrup
- Research Group Neuroinformatics, Faculty of Computer Science, Vienna Cognitive Science Hub, Data Science @ Uni Vienna University of Vienna
| | - Robert Gaunt
- Rehab Neural Engineering Labs, Department of Physical Medicine and Rehabilitation, Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA, 3520 5th Ave, Suite 300, Pittsburgh, PA 15213, 412-383-1426
| | - Aliceson Nicole Dusang
- Department of Electrical and Computer Engineering, School of Engineering, Brown University, Carney Institute for Brain Science, Brown University, Providence, RI
- Department of Veterans Affairs Medical Center, Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence, RI
- Center for Neurotechnology and Neurorecovery, Neurology, Massachusetts General Hospital, Boston, MA
| | | | - Ricardo Chavarriaga
- IEEE Standards Association Industry Connections group on neurotechnologies for brain-machine interface, Center for Artificial Intelligence, School of Engineering, ZHAW-Zurich University of Applied Sciences, Switzerland, Switzerland
| | - Charles W Anderson
- Department of Computer Science, Molecular, Cellular and Integrative Neurosience Program, Colorado State University, Fort Collins, CO 80523
| | - Brendan Z Allison
- Dept. of Cognitive Science, Mail Code 0515, University of California at San Diego, La Jolla, United States, 619-534-9754
| | - Tetiana Aksenova
- University Grenoble Alpes, CEA, LETI, Clinatec, Grenoble 38000, France
| | - Erik Aarnoutse
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
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Grady FS, Boes AD, Geerling JC. A Century Searching for the Neurons Necessary for Wakefulness. Front Neurosci 2022; 16:930514. [PMID: 35928009 PMCID: PMC9344068 DOI: 10.3389/fnins.2022.930514] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/15/2022] [Indexed: 11/25/2022] Open
Abstract
Wakefulness is necessary for consciousness, and impaired wakefulness is a symptom of many diseases. The neural circuits that maintain wakefulness remain incompletely understood, as do the mechanisms of impaired consciousness in many patients. In contrast to the influential concept of a diffuse "reticular activating system," the past century of neuroscience research has identified a focal region of the upper brainstem that, when damaged, causes coma. This region contains diverse neuronal populations with different axonal projections, neurotransmitters, and genetic identities. Activating some of these populations promotes wakefulness, but it remains unclear which specific neurons are necessary for sustaining consciousness. In parallel, pharmacological evidence has indicated a role for special neurotransmitters, including hypocretin/orexin, histamine, norepinephrine, serotonin, dopamine, adenosine and acetylcholine. However, genetically targeted experiments have indicated that none of these neurotransmitters or the neurons producing them are individually necessary for maintaining wakefulness. In this review, we emphasize the need to determine the specific subset of brainstem neurons necessary for maintaining arousal. Accomplishing this will enable more precise mapping of wakefulness circuitry, which will be useful in developing therapies for patients with coma and other disorders of arousal.
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Affiliation(s)
- Fillan S Grady
- Geerling Laboratory, Department of Neurology, Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, United States
| | - Aaron D Boes
- Boes Laboratory, Departments of Pediatrics, Neurology, and Psychiatry, The University of Iowa, Iowa City, IA, United States
| | - Joel C Geerling
- Geerling Laboratory, Department of Neurology, Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, United States
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