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Mondino A, González J, Li D, Mateos D, Osorio L, Cavelli M, Castro-Nin JP, Serantes D, Costa A, Vanini G, Mashour GA, Torterolo P. Urethane anaesthesia exhibits neurophysiological correlates of unconsciousness and is distinct from sleep. Eur J Neurosci 2024; 59:483-501. [PMID: 35545450 DOI: 10.1111/ejn.15690] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 04/13/2022] [Accepted: 05/06/2022] [Indexed: 11/27/2022]
Abstract
Urethane is a general anaesthetic widely used in animal research. The state of urethane anaesthesia is unique because it alternates between macroscopically distinct electrographic states: a slow-wave state that resembles non-rapid eye movement (NREM) sleep and an activated state with features of both REM sleep and wakefulness. Although it is assumed that urethane produces unconsciousness, this has been questioned because of states of cortical activation during drug exposure. Furthermore, the similarities and differences between urethane anaesthesia and physiological sleep are still unclear. In this study, we recorded the electroencephalogram (EEG) and electromyogram in chronically prepared rats during natural sleep-wake states and during urethane anaesthesia. We subsequently analysed the power, coherence, directed connectivity and complexity of brain oscillations and found that EEG under urethane anaesthesia has clear signatures of unconsciousness, with similarities to other general anaesthetics. In addition, the EEG profile under urethane is different in comparison with natural sleep states. These results suggest that consciousness is disrupted during urethane. Furthermore, despite similarities that have led others to conclude that urethane is a model of sleep, the electrocortical traits of depressed and activated states during urethane anaesthesia differ from physiological sleep states.
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Affiliation(s)
- Alejandra Mondino
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
| | - Joaquín González
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
| | - Duan Li
- Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan, USA
- Center for Consciousness Science, University of Michigan, Ann Arbor, Michigan, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, USA
| | - Diego Mateos
- Institute of Applied Mathematics of the Coast-CONICET-UNL, CCT CONICET, Santa Fe, Argentina
- Faculty of Science and Technology, Autonomous University of Entre Ríos, Parana, Argentina
| | - Lucía Osorio
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
| | - Matías Cavelli
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
- Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, USA
| | - Juan Pedro Castro-Nin
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
| | - Diego Serantes
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
| | - Alicia Costa
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
| | - Giancarlo Vanini
- Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan, USA
- Center for Consciousness Science, University of Michigan, Ann Arbor, Michigan, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, USA
| | - George A Mashour
- Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan, USA
- Center for Consciousness Science, University of Michigan, Ann Arbor, Michigan, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, USA
| | - Pablo Torterolo
- Department of Physiology, Faculty of Medicine, University of the Republic, Montevideo, Uruguay
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Fuentes N, Garcia A, Guevara R, Orofino R, Mateos DM. Complexity of Brain Dynamics as a Correlate of Consciousness in Anaesthetized Monkeys. Neuroinformatics 2022; 20:1041-1054. [PMID: 35511398 DOI: 10.1007/s12021-022-09586-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2022] [Indexed: 12/31/2022]
Abstract
The use of anaesthesia is a fundamental tool in the investigation of consciousness. Anesthesia procedures allow to investigate different states of consciousness from sedation to deep anesthesia within controlled scenarios. In this study we use information quantifiers to measure the complexity of electrocorticogram recordings in monkeys. We apply these metrics to compare different stages of general anesthesia for evaluating consciousness in several anesthesia protocols. We find that the complexity of brain activity can be used as a correlate of consciousness. For two of the anaesthetics used, propofol and medetomidine, we find that the anaesthetised state is accompanied by a reduction in the complexity of brain activity. On the other hand we observe that use of ketamine produces an increase in complexity measurements. We relate this observation with increase activity within certain brain regions associated with the ketamine used doses. Our measurements indicate that complexity of brain activity is a good indicator for a general evaluation of different levels of consciousness awareness, both in anesthetized and non anesthetizes states.
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Affiliation(s)
- Nicolas Fuentes
- Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Alexis Garcia
- Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Ramón Guevara
- Department of Physics and Astronomy, University of Padua, Padua, Italy
| | - Roberto Orofino
- Hospital de Ninos Pedro de Elizalde, Buenos Aires, Argentina.,Hospital Español, La Plata, Argentina
| | - Diego M Mateos
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina. .,Facultad de Ciencia y Tecnología. Universidad Autónoma de Entre Ríos (UADER), Oro Verde, Entre Ríos, Argentina. .,Instituto de Matemática Aplicada del Litoral (IMAL-CONICET-UNL), CCT CONICET, Santa Fé, Argentina.
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3
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Power Spectrum and Connectivity Analysis in EEG Recording during Attention and Creativity Performance in Children. NEUROSCI 2022. [DOI: 10.3390/neurosci3020025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Abstract
The present research aims at examining the power spectrum and exploring functional brain connectivity/disconnectivity during concentration performance, as measured by the d2 test of attention and creativity as measured by the CREA test in typically developing children. To this end, we examined brain connectivity by using phase synchrony (i.e., phase locking index (PLI) over the EEG signals acquired by the Emotiv EPOC neuroheadset in 15 children aged 9- to 12-years. Besides, as a complement, a power spectrum analysis of the acquired signals was performed. Our results indicated that, during d2 Test performance there was an increase in global gamma phase synchronization and there was a global alpha and theta band desynchronization. Conversely, during CREA task, power spectrum analysis showed a significant increase in the delta, beta, theta, and gamma bands. Connectivity analysis revealed marked synchronization in theta, alpha, and gamma. These findings are consistent with other neuroscience research indicating that multiple brain mechanisms are indeed involved in creativity. In addition, these results have important implications for the assessment of attention functions and creativity in clinical and research settings, as well as for neurofeedback interventions in children with typical and atypical development.
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Sarasso S, Casali AG, Casarotto S, Rosanova M, Sinigaglia C, Massimini M. Consciousness and complexity: a consilience of evidence. Neurosci Conscious 2021; 2021:niab023. [PMID: 38496724 PMCID: PMC10941977 DOI: 10.1093/nc/niab023] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 06/19/2021] [Accepted: 07/29/2021] [Indexed: 03/19/2024] Open
Abstract
Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.
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Affiliation(s)
- Simone Sarasso
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
| | - Adenauer Girardi Casali
- Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo, Sao Jose dos Campos, 12247-014, Brazil
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan 20148, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
| | | | - Marcello Massimini
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan 20148, Italy
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Fernandez-Leon JA, Acosta G. A heuristic perspective on non-variational free energy modulation at the sleep-like edge. Biosystems 2021; 208:104466. [PMID: 34246689 DOI: 10.1016/j.biosystems.2021.104466] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 06/03/2021] [Accepted: 06/21/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND The variational Free Energy Principle (FEP) establishes that a neural system minimizes a free energy function of their internal state through environmental sensing entailing beliefs about hidden states in their environment. PROBLEM Because sensations are drastically reduced during sleep, it is still unclear how a self-organizing neural network can modulate free energy during sleep transitions. GOAL To address this issue, we study how network's state-dependent changes in energy, entropy and free energy connect with changes at the synaptic level in the absence of sensing during a sleep-like transition. APPROACH We use simulations of a physically plausible, environmentally isolated neuronal network that self-organize after inducing a thalamic input to show that the reduction of non-variational free energy depends sensitively upon thalamic input at a slow, rhythmic Poisson (delta) frequency due to spike timing dependent plasticity. METHODS We define a non-variational free energy in terms of the relative difference between the energy and entropy of the network from the initial distribution (prior to activity dependent plasticity) to the nonequilibrium steady-state distribution (after plasticity). We repeated the analysis under different levels of thalamic drive - as defined by the number of cortical neurons in receipt of thalamic input. RESULTS Entraining slow activity with thalamic input induces a transition from a gamma (awake-like state) to a delta (sleep-like state) mode of activity, which can be characterized through a modulation of network's energy and entropy (non-variational free energy) of the ensuing dynamics. The self-organizing response to low and high thalamic drive also showed characteristic differences in the spectrum of frequency content due to spike timing dependent plasticity. CONCLUSIONS The modulation of this non-variational free energy in a network that self-organizes, seems to be an organizational network principle. This could open a window to new empirically testable hypotheses about state changes in a neural network.
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Affiliation(s)
- Jose A Fernandez-Leon
- Neurology, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, 02115, USA; Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA.
| | - Gerardo Acosta
- INTELYMEC-CIFICEN (UNCPBA-CICPBA-CONICET), Olavarría, B7400JWI, Argentina
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Frohlich J, Toker D, Monti MM. Consciousness among delta waves: a paradox? Brain 2021; 144:2257-2277. [PMID: 33693596 DOI: 10.1093/brain/awab095] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 02/12/2021] [Accepted: 02/25/2021] [Indexed: 01/29/2023] Open
Abstract
A common observation in EEG research is that consciousness vanishes with the appearance of delta (1 - 4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are very frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalised epileptic seizures, and disorders of consciousness such as coma and vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the "down states" or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and nonconvulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalogram or MEG signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.
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Affiliation(s)
- Joel Frohlich
- Department of Psychology, University of California Los Angeles, 3423 Franz Hall, Los Angeles, California 90095, USA
| | - Daniel Toker
- Department of Psychology, University of California Los Angeles, 3423 Franz Hall, Los Angeles, California 90095, USA
| | - Martin M Monti
- Department of Psychology, University of California Los Angeles, 3423 Franz Hall, Los Angeles, California 90095, USA.,Department of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90095, USA
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Guevara R, Mateos DM, Pérez Velázquez JL. Consciousness as an Emergent Phenomenon: A Tale of Different Levels of Description. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E921. [PMID: 33286690 PMCID: PMC7597170 DOI: 10.3390/e22090921] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 08/15/2020] [Accepted: 08/19/2020] [Indexed: 01/17/2023]
Abstract
One of the biggest queries in cognitive sciences is the emergence of consciousness from matter. Modern neurobiological theories of consciousness propose that conscious experience is the result of interactions between large-scale neuronal networks in the brain, traditionally described within the realm of classical physics. Here, we propose a generalized connectionist framework in which the emergence of "conscious networks" is not exclusive of large brain areas, but can be identified in subcellular networks exhibiting nontrivial quantum phenomena. The essential feature of such networks is the existence of strong correlations in the system (classical or quantum coherence) and the presence of an optimal point at which the system's complexity and energy dissipation are maximized, whereas free-energy is minimized. This is expressed either by maximization of the information content in large scale functional networks or by achieving optimal efficiency through the quantum Goldilock effect.
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Affiliation(s)
- Ramón Guevara
- Integrative Neuroscience and Cognition Centre (INCC UMR8002), University of Paris and CNRS, 75270 Paris, France
- Department of Physics and Astronomy, University of Padova, 35131 Padova, Italy
| | - Diego M. Mateos
- Department of Science and Technology, Universidad Autónoma de Entre Ríos, Paraná 3100, Argentina;
- Instituto de Matemática Aplicada del Litoral (IMAL-CONICET-UNL), Santa Fe 3000, Argentina
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8
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On the emergence of cognition: from catalytic closure to neuroglial closure. J Biol Phys 2020; 46:95-119. [PMID: 32130568 DOI: 10.1007/s10867-020-09543-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 02/12/2020] [Indexed: 10/24/2022] Open
Abstract
In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called "life"-due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions-it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.
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Perez Velazquez JL, Mateos DM, Guevara Erra R. On a Simple General Principle of Brain Organization. Front Neurosci 2019; 13:1106. [PMID: 31680839 PMCID: PMC6804438 DOI: 10.3389/fnins.2019.01106] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 10/01/2019] [Indexed: 12/27/2022] Open
Abstract
A possible framework to characterize nervous system dynamics and its organization in conscious and unconscious states is introduced, derived from a high level perspective on the coordinated activity of brain cell ensembles. Some questions are best addressable in a global framework and here we build on past observations about the structure of configurations of brain networks in conscious and unconscious states and about neurophysiological results. Aiming to bind some results together into some sort of coherence with a central theme, the scenario that emerges underscores the crucial importance of the creation and dissipation of energy gradients in brain cellular ensembles resulting in maximization of the configurations in the functional connectivity among those networks that favor conscious awareness and healthy conditions. These considerations are then applied to indicate approaches that can be used to improve neuropathological syndromes.
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Affiliation(s)
| | - Diego M. Mateos
- Instituto de Matemática Aplicada del Litoral–CONICET–UNL, CCT CONICET, Santa Fe, Argentina
- Facultad de Ciencia y Tecnología, Universidad Autónoma de Entre Ríos, Entre Ríos, Argentina
| | - Ramon Guevara Erra
- Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Sorbonne Paris Cité, Paris, France
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Structural transition in the collective behavior of cognitive agents. Sci Rep 2019; 9:12477. [PMID: 31462661 PMCID: PMC6713784 DOI: 10.1038/s41598-019-48638-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 08/09/2019] [Indexed: 11/16/2022] Open
Abstract
Living organisms process information to interact and adapt to their surroundings with the goal of finding food, mating, or averting hazards. The structure of their environment has profound repercussions through both selecting their internal architecture and also inducing adaptive responses to environmental cues and stimuli. Adaptive collective behavior underpinned by specialized optimization strategies is ubiquitous in the natural world. We develop a minimal model of agents that explore their environment by means of sampling trajectories. The spatial information stored in the sampling trajectories is our minimal definition of a cognitive map. We find that, as cognitive agents build and update their internal, cognitive representation of the causal structure of their environment, complex patterns emerge in the system, where the onset of pattern formation relates to the spatial overlap of cognitive maps. Exchange of information among the agents leads to an order-disorder transition. As a result of the spontaneous breaking of translational symmetry, a Goldstone mode emerges, which points at a collective mechanism of information transfer among cognitive organisms. These findings may be generally applicable to the design of decentralized, artificial-intelligence swarm systems.
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