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Curic D, Ashby DM, McGirr A, Davidsen J. Existence of multiple transitions of the critical state due to anesthetics. Nat Commun 2024; 15:7025. [PMID: 39147749 PMCID: PMC11327335 DOI: 10.1038/s41467-024-51399-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 08/05/2024] [Indexed: 08/17/2024] Open
Abstract
Scale-free statistics of coordinated neuronal activity, suggesting a universal operating mechanism across spatio-temporal scales, have been proposed as a necessary condition of healthy resting-state brain activity. Recent studies have focused on anesthetic agents to induce distinct neural states in which consciousness is altered to understand the importance of critical dynamics. However, variation in experimental techniques, species, and anesthetics, have made comparisons across studies difficult. Here we conduct a survey of several common anesthetics (isoflurane, pentobarbital, ketamine) at multiple dosages, using calcium wide-field optical imaging of the mouse cortex. We show that while low-dose anesthesia largely preserves scale-free statistics, surgical plane anesthesia induces multiple dynamical modes, most of which do not maintain critical avalanche dynamics. Our findings indicate multiple pathways away from default critical dynamics associated with quiet wakefulness, not only reflecting differences between these common anesthetics but also showing significant variations in individual responses. This is suggestive of a non-trivial relationship between criticality and the underlying state of the subject.
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Affiliation(s)
- Davor Curic
- Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.
| | - Donovan M Ashby
- Department of Psychiatry, University of Calgary, Calgary, AB, T2N 1N4, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
- Mathison Centre for Mental Health Research and Education, Calgary, AB, Canada
| | - Alexander McGirr
- Department of Psychiatry, University of Calgary, Calgary, AB, T2N 1N4, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
- Mathison Centre for Mental Health Research and Education, Calgary, AB, Canada
| | - Jörn Davidsen
- Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
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2
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Maschke C, O'Byrne J, Colombo MA, Boly M, Gosseries O, Laureys S, Rosanova M, Jerbi K, Blain-Moraes S. Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity. Commun Biol 2024; 7:946. [PMID: 39103539 DOI: 10.1038/s42003-024-06613-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 07/22/2024] [Indexed: 08/07/2024] Open
Abstract
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, all participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams), enabling an experimental dissociation between unresponsiveness and unconsciousness. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects' PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
| | - Jordan O'Byrne
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, QC, Canada
| | | | - Melanie Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, WI, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du cerveau, CHU of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- CERVO Brain Research Centre, Laval University, Laval, QC, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, QC, Canada
- Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, QC, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada.
- School of Physical and Occupational Therapy, McGill University, Montreal, QC, Canada.
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3
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Hubbell JAE, Muir WW, Gorenberg E, Hopster K. A review of equine anesthetic induction: Are all equine anesthetic inductions "crash" inductions? J Equine Vet Sci 2024; 139:105130. [PMID: 38879096 DOI: 10.1016/j.jevs.2024.105130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 05/29/2024] [Accepted: 06/12/2024] [Indexed: 06/29/2024]
Abstract
Horses are the most challenging of the common companion animals to anesthetize. Induction of anesthesia in the horse is complicated by the fact that it is accompanied by a transition from a conscious standing position to uncconconscious recumbency. The purpose of this article is to review the literature on induction of anesthesia with a focus on the behavioral and physiologic/pharmacodynamic responses and the actions and interactions of the drugs administered to induce anesthesia in the healthy adult horse with the goal of increasing consistency and predictability.
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Affiliation(s)
| | - William W Muir
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, Tennessee, USA
| | - Emma Gorenberg
- School of Veterinary Medicine, University of Pennsylvania. Kennett Square, PA, USA
| | - Klaus Hopster
- School of Veterinary Medicine, University of Pennsylvania. Kennett Square, PA, USA
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4
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Prince JB, Davis HL, Tan J, Muller-Townsend K, Markovic S, Lewis DMG, Hastie B, Thompson MB, Drummond PD, Fujiyama H, Sohrabi HR. Cognitive and neuroscientific perspectives of healthy ageing. Neurosci Biobehav Rev 2024; 161:105649. [PMID: 38579902 DOI: 10.1016/j.neubiorev.2024.105649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 03/17/2024] [Accepted: 03/30/2024] [Indexed: 04/07/2024]
Abstract
With dementia incidence projected to escalate significantly within the next 25 years, the United Nations declared 2021-2030 the Decade of Healthy Ageing, emphasising cognition as a crucial element. As a leading discipline in cognition and ageing research, psychology is well-equipped to offer insights for translational research, clinical practice, and policy-making. In this comprehensive review, we discuss the current state of knowledge on age-related changes in cognition and psychological health. We discuss cognitive changes during ageing, including (a) heterogeneity in the rate, trajectory, and characteristics of decline experienced by older adults, (b) the role of cognitive reserve in age-related cognitive decline, and (c) the potential for cognitive training to slow this decline. We also examine ageing and cognition through multiple theoretical perspectives. We highlight critical unresolved issues, such as the disparate implications of subjective versus objective measures of cognitive decline and the insufficient evaluation of cognitive training programs. We suggest future research directions, and emphasise interdisciplinary collaboration to create a more comprehensive understanding of the factors that modulate cognitive ageing.
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Affiliation(s)
- Jon B Prince
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia.
| | - Helen L Davis
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Jane Tan
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Katrina Muller-Townsend
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Shaun Markovic
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; Discipline of Psychology, Counselling and Criminology, Edith Cowan University, WA, Australia
| | - David M G Lewis
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | | | - Matthew B Thompson
- School of Psychology, Murdoch University, WA, Australia; Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, WA, Australia
| | - Peter D Drummond
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Hakuei Fujiyama
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, WA, Australia
| | - Hamid R Sohrabi
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, WA, Australia; Department of Biomedical Sciences, Macquarie University, NSW, Australia.
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5
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Mashour GA. Anesthesia and the neurobiology of consciousness. Neuron 2024; 112:1553-1567. [PMID: 38579714 PMCID: PMC11098701 DOI: 10.1016/j.neuron.2024.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 04/07/2024]
Abstract
In the 19th century, the discovery of general anesthesia revolutionized medical care. In the 21st century, anesthetics have become indispensable tools to study consciousness. Here, I review key aspects of the relationship between anesthesia and the neurobiology of consciousness, including interfaces of sleep and anesthetic mechanisms, anesthesia and primary sensory processing, the effects of anesthetics on large-scale functional brain networks, and mechanisms of arousal from anesthesia. I discuss the implications of the data derived from the anesthetized state for the science of consciousness and then conclude with outstanding questions, reflections, and future directions.
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Affiliation(s)
- George A Mashour
- Center for Consciousness Science, Department of Anesthesiology, Department of Pharmacology, Neuroscience Graduate Program, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
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Maschke C, O'Byrne J, Colombo MA, Boly M, Gosseries O, Laureys S, Rosanova M, Jerbi K, Blain-Moraes S. Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564247. [PMID: 37994368 PMCID: PMC10664178 DOI: 10.1101/2023.10.26.564247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects' PCI (i.e., PCImax) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
| | - Jordan O'Byrne
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
| | | | - Melanie Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du cerveau, CHU of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- CERVO Brain Research Centre, Laval University, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
- Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, Québec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- School of Physical and Occupational Therapy, McGill University, Montreal, Canada
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7
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Garel N, Drury J, Thibault Lévesque J, Goyette N, Lehmann A, Looper K, Erritzoe D, Dames S, Turecki G, Rej S, Richard-Devantoy S, Greenway KT. The Montreal model: an integrative biomedical-psychedelic approach to ketamine for severe treatment-resistant depression. Front Psychiatry 2023; 14:1268832. [PMID: 37795512 PMCID: PMC10546328 DOI: 10.3389/fpsyt.2023.1268832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 08/30/2023] [Indexed: 10/06/2023] Open
Abstract
Background Subanesthetic ketamine has accumulated meta-analytic evidence for rapid antidepressant effects in treatment-resistant depression (TRD), resulting in both excitement and debate. Many unanswered questions surround ketamine's mechanisms of action and its integration into real-world psychiatric care, resulting in diverse utilizations that variously resemble electroconvulsive therapy, conventional antidepressants, or serotonergic psychedelics. There is thus an unmet need for clinical approaches to ketamine that are tailored to its unique therapeutic properties. Methods This article presents the Montreal model, a comprehensive biopsychosocial approach to ketamine for severe TRD refined over 6 years in public healthcare settings. To contextualize its development, we review the evidence for ketamine as a biomedical and as a psychedelic treatment of depression, emphasizing each perspectives' strengths, weaknesses, and distinct methods of utilization. We then describe the key clinical experiences and research findings that shaped the model's various components, which are presented in detail. Results The Montreal model, as implemented in a recent randomized clinical trial, aims to synergistically pair ketamine infusions with conventional and psychedelic biopsychosocial care. Ketamine is broadly conceptualized as a brief intervention that can produce windows of opportunity for enhanced psychiatric care, as well as powerful occasions for psychological growth. The model combines structured psychiatric care and concomitant psychotherapy with six ketamine infusions, administered with psychedelic-inspired nonpharmacological adjuncts including rolling preparative and integrative psychological support. Discussion Our integrative model aims to bridge the biomedical-psychedelic divide to offer a feasible, flexible, and standardized approach to ketamine for TRD. Our learnings from developing and implementing this psychedelic-inspired model for severe, real-world patients in two academic hospitals may offer valuable insights for the ongoing roll-out of a range of psychedelic therapies. Further research is needed to assess the Montreal model's effectiveness and hypothesized psychological mechanisms.
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Affiliation(s)
- Nicolas Garel
- Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC, Canada
| | - Jessica Drury
- Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC, Canada
| | | | - Nathalie Goyette
- McGill Group for Suicide Studies, Douglas Mental Health Research Institute, Montreal, QC, Canada
| | - Alexandre Lehmann
- International Laboratory for Brain, Music and Sound Research, Montreal, QC, Canada
- Department of Otolaryngology, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Karl Looper
- Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC, Canada
- Jewish General Hospital, Lady Davis Institute for Medical Research, Montreal, QC, Canada
| | - David Erritzoe
- Division of Psychiatry, Department of Brain Sciences, Centres for Neuropsychopharmacology and Psychedelic Research, Imperial College London, London, United Kingdom
| | - Shannon Dames
- Health Sciences and Human Services, Vancouver Island University, Nanaimo, BC, Canada
| | - Gustavo Turecki
- Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC, Canada
- McGill Group for Suicide Studies, Douglas Mental Health Research Institute, Montreal, QC, Canada
| | - Soham Rej
- Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC, Canada
- Jewish General Hospital, Lady Davis Institute for Medical Research, Montreal, QC, Canada
- Geri-PARTy Research Group, Jewish General Hospital, Montreal, QC, Canada
| | - Stephane Richard-Devantoy
- Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC, Canada
- McGill Group for Suicide Studies, Douglas Mental Health Research Institute, Montreal, QC, Canada
| | - Kyle T. Greenway
- Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC, Canada
- Jewish General Hospital, Lady Davis Institute for Medical Research, Montreal, QC, Canada
- Division of Psychiatry, Department of Brain Sciences, Centres for Neuropsychopharmacology and Psychedelic Research, Imperial College London, London, United Kingdom
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8
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González J, Cavelli M, Tort ABL, Torterolo P, Rubido N. Sleep disrupts complex spiking dynamics in the neocortex and hippocampus. PLoS One 2023; 18:e0290146. [PMID: 37590234 PMCID: PMC10434889 DOI: 10.1371/journal.pone.0290146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 08/02/2023] [Indexed: 08/19/2023] Open
Abstract
Neuronal interactions give rise to complex dynamics in cortical networks, often described in terms of the diversity of activity patterns observed in a neural signal. Interestingly, the complexity of spontaneous electroencephalographic signals decreases during slow-wave sleep (SWS); however, the underlying neural mechanisms remain elusive. Here, we analyse in-vivo recordings from neocortical and hippocampal neuronal populations in rats and show that the complexity decrease is due to the emergence of synchronous neuronal DOWN states. Namely, we find that DOWN states during SWS force the population activity to be more recurrent, deterministic, and less random than during REM sleep or wakefulness, which, in turn, leads to less complex field recordings. Importantly, when we exclude DOWN states from the analysis, the recordings during wakefulness and sleep become indistinguishable: the spiking activity in all the states collapses to a common scaling. We complement these results by implementing a critical branching model of the cortex, which shows that inducing DOWN states to only a percentage of neurons is enough to generate a decrease in complexity that replicates SWS.
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Affiliation(s)
- Joaquín González
- Departamento de Fisiología de Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Matias Cavelli
- Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Adriano B. L. Tort
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Pablo Torterolo
- Departamento de Fisiología de Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Nicolás Rubido
- University of Aberdeen, King’s College, Institute for Complex Systems and Mathematical Biology, Aberdeen, United Kingdom
- Instituto de Física, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay
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9
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Varley TF, Pope M, Puxeddu MG, Faskowitz J, Sporns O. Partial entropy decomposition reveals higher-order information structures in human brain activity. Proc Natl Acad Sci U S A 2023; 120:e2300888120. [PMID: 37467265 PMCID: PMC10372615 DOI: 10.1073/pnas.2300888120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 06/06/2023] [Indexed: 07/21/2023] Open
Abstract
The standard approach to modeling the human brain as a complex system is with a network, where the basic unit of interaction is a pairwise link between two brain regions. While powerful, this approach is limited by the inability to assess higher-order interactions involving three or more elements directly. In this work, we explore a method for capturing higher-order dependencies in multivariate data: the partial entropy decomposition (PED). Our approach decomposes the joint entropy of the whole system into a set of nonnegative atoms that describe the redundant, unique, and synergistic interactions that compose the system's structure. PED gives insight into the mathematics of functional connectivity and its limitation. When applied to resting-state fMRI data, we find robust evidence of higher-order synergies that are largely invisible to standard functional connectivity analyses. Our approach can also be localized in time, allowing a frame-by-frame analysis of how the distributions of redundancies and synergies change over the course of a recording. We find that different ensembles of regions can transiently change from being redundancy-dominated to synergy-dominated and that the temporal pattern is structured in time. These results provide strong evidence that there exists a large space of unexplored structures in human brain data that have been largely missed by a focus on bivariate network connectivity models. This synergistic structure is dynamic in time and likely will illuminate interesting links between brain and behavior. Beyond brain-specific application, the PED provides a very general approach for understanding higher-order structures in a variety of complex systems.
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Affiliation(s)
- Thomas F. Varley
- School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN47405
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN47405
| | - Maria Pope
- School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN47405
- Program in Neuroscience, Indiana University, Bloomington, IN47405
| | - Maria Grazia Puxeddu
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN47405
| | - Joshua Faskowitz
- School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN47405
- Program in Neuroscience, Indiana University, Bloomington, IN47405
| | - Olaf Sporns
- School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN47405
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN47405
- Program in Neuroscience, Indiana University, Bloomington, IN47405
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10
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Martínez‐Cañada P, Perez‐Valero E, Minguillon J, Pelayo F, López‐Gordo MA, Morillas C. Combining aperiodic 1/f slopes and brain simulation: An EEG/MEG proxy marker of excitation/inhibition imbalance in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12477. [PMID: 37662693 PMCID: PMC10474329 DOI: 10.1002/dad2.12477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 07/27/2023] [Accepted: 08/08/2023] [Indexed: 09/05/2023]
Abstract
INTRODUCTION Accumulation and interaction of amyloid-beta (Aβ) and tau proteins during progression of Alzheimer's disease (AD) are shown to tilt neuronal circuits away from balanced excitation/inhibition (E/I). Current available techniques for noninvasive interrogation of E/I in the intact human brain, for example, magnetic resonance spectroscopy (MRS), are highly restrictive (i.e., limited spatial extent), have low temporal and spatial resolution and suffer from the limited ability to distinguish accurately between different neurotransmitters complicating its interpretation. As such, these methods alone offer an incomplete explanation of E/I. Recently, the aperiodic component of neural power spectrum, often referred to in the literature as the '1/f slope', has been described as a promising and scalable biomarker that can track disruptions in E/I potentially underlying a spectrum of clinical conditions, such as autism, schizophrenia, or epilepsy, as well as developmental E/I changes as seen in aging. METHODS Using 1/f slopes from resting-state spectral data and computational modeling, we developed a new method for inferring E/I alterations in AD. RESULTS We tested our method on recent freely and publicly available electroencephalography (EEG) and magnetoencephalography (MEG) datasets of patients with AD or prodromal disease and demonstrated the method's potential for uncovering regional patterns of abnormal excitatory and inhibitory parameters. DISCUSSION Our results provide a general framework for investigating circuit-level disorders in AD and developing therapeutic interventions that aim to restore the balance between excitation and inhibition.
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Affiliation(s)
- Pablo Martínez‐Cañada
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
| | - Eduardo Perez‐Valero
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
| | - Jesus Minguillon
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
- Department of Signal TheoryTelematics and CommunicationsUniversity of GranadaGranadaSpain
| | - Francisco Pelayo
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
| | - Miguel A. López‐Gordo
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
- Department of Signal TheoryTelematics and CommunicationsUniversity of GranadaGranadaSpain
| | - Christian Morillas
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
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11
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Gervais C, Boucher LP, Villar GM, Lee U, Duclos C. A scoping review for building a criticality-based conceptual framework of altered states of consciousness. Front Syst Neurosci 2023; 17:1085902. [PMID: 37304151 PMCID: PMC10248073 DOI: 10.3389/fnsys.2023.1085902] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 05/08/2023] [Indexed: 06/13/2023] Open
Abstract
The healthy conscious brain is thought to operate near a critical state, reflecting optimal information processing and high susceptibility to external stimuli. Conversely, deviations from the critical state are hypothesized to give rise to altered states of consciousness (ASC). Measures of criticality could therefore be an effective way of establishing the conscious state of an individual. Furthermore, characterizing the direction of a deviation from criticality may enable the development of treatment strategies for pathological ASC. The aim of this scoping review is to assess the current evidence supporting the criticality hypothesis, and the use of criticality as a conceptual framework for ASC. Using the PRISMA guidelines, Web of Science and PubMed were searched from inception to February 7th 2022 to find articles relating to measures of criticality across ASC. N = 427 independent papers were initially found on the subject. N = 378 were excluded because they were either: not related to criticality; not related to consciousness; not presenting results from a primary study; presenting model data. N = 49 independent papers were included in the present research, separated in 7 sub-categories of ASC: disorders of consciousness (DOC) (n = 5); sleep (n = 13); anesthesia (n = 18); epilepsy (n = 12); psychedelics and shamanic state of consciousness (n = 4); delirium (n = 1); meditative state (n = 2). Each category included articles suggesting a deviation of the critical state. While most studies were only able to identify a deviation from criticality without being certain of its direction, the preliminary consensus arising from the literature is that non-rapid eye movement (NREM) sleep reflects a subcritical state, epileptic seizures reflect a supercritical state, and psychedelics are closer to the critical state than normal consciousness. This scoping review suggests that, though the literature is limited and methodologically inhomogeneous, ASC are characterized by a deviation from criticality, though its direction is not clearly reported in a majority of studies. Criticality could become, with more extensive research, an effective and objective way to characterize ASC, and help identify therapeutic avenues to improve criticality in pathological brain states. Furthermore, we suggest how anesthesia and psychedelics could potentially be used as neuromodulation techniques to restore criticality in DOC.
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Affiliation(s)
- Charles Gervais
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
| | - Louis-Philippe Boucher
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
- Department of Neuroscience, Université de Montréal, Montréal, QC, Canada
| | - Guillermo Martinez Villar
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
- Department of Biomedical Sciences, Université de Montréal, Montréal, QC, Canada
| | - UnCheol Lee
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Catherine Duclos
- Centre for Advanced Research in Sleep Medicine & Integrated Trauma Centre, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montréal, QC, Canada
- Department of Neuroscience, Université de Montréal, Montréal, QC, Canada
- Department of Anesthesiology and Pain Medicine, Université de Montréal, Montréal, QC, Canada
- CIFAR Azrieli Global Scholars Program, Toronto, ON, Canada
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12
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Nanda A, Johnson GW, Mu Y, Ahrens MB, Chang C, Englot DJ, Breakspear M, Rubinov M. Time-resolved correlation of distributed brain activity tracks E-I balance and accounts for diverse scale-free phenomena. Cell Rep 2023; 42:112254. [PMID: 36966391 PMCID: PMC10518034 DOI: 10.1016/j.celrep.2023.112254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 12/22/2022] [Accepted: 02/28/2023] [Indexed: 03/27/2023] Open
Abstract
Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile these explanations across species and modalities. First, we link estimates of excitation-inhibition (E-I) balance with time-resolved correlation of distributed brain activity. Second, we develop an unbiased method for sampling time series constrained by this time-resolved correlation. Third, we use this method to show that estimates of E-I balance account for diverse scale-free phenomena without need to attribute additional function or importance to these phenomena. Collectively, our results simplify existing explanations of scale-free brain activity and provide stringent tests on future theories that seek to transcend these explanations.
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Affiliation(s)
- Aditya Nanda
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Yu Mu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Catie Chang
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA; Department of Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA; Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Michael Breakspear
- School of Psychology, University of Newcastle, Callaghan, NSW 2308, Australia; School of Medicine and Public Health, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Mikail Rubinov
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Department of Computer Science, Vanderbilt University, Nashville, TN 37235, USA.
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13
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Varley TF, Pope M, Faskowitz J, Sporns O. Multivariate information theory uncovers synergistic subsystems of the human cerebral cortex. Commun Biol 2023; 6:451. [PMID: 37095282 PMCID: PMC10125999 DOI: 10.1038/s42003-023-04843-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 04/14/2023] [Indexed: 04/26/2023] Open
Abstract
One of the most well-established tools for modeling the brain is the functional connectivity network, which is constructed from pairs of interacting brain regions. While powerful, the network model is limited by the restriction that only pairwise dependencies are considered and potentially higher-order structures are missed. Here, we explore how multivariate information theory reveals higher-order dependencies in the human brain. We begin with a mathematical analysis of the O-information, showing analytically and numerically how it is related to previously established information theoretic measures of complexity. We then apply the O-information to brain data, showing that synergistic subsystems are widespread in the human brain. Highly synergistic subsystems typically sit between canonical functional networks, and may serve an integrative role. We then use simulated annealing to find maximally synergistic subsystems, finding that such systems typically comprise ≈10 brain regions, recruited from multiple canonical brain systems. Though ubiquitous, highly synergistic subsystems are invisible when considering pairwise functional connectivity, suggesting that higher-order dependencies form a kind of shadow structure that has been unrecognized by established network-based analyses. We assert that higher-order interactions in the brain represent an under-explored space that, accessible with tools of multivariate information theory, may offer novel scientific insights.
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Affiliation(s)
- Thomas F Varley
- School of Informatics, Computing & Engineering, Indiana University, Bloomington, IN, 47405, USA.
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, 47405, USA.
| | - Maria Pope
- School of Informatics, Computing & Engineering, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Joshua Faskowitz
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Olaf Sporns
- School of Informatics, Computing & Engineering, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
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14
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Varley TF. Decomposing past and future: Integrated information decomposition based on shared probability mass exclusions. PLoS One 2023; 18:e0282950. [PMID: 36952508 PMCID: PMC10035902 DOI: 10.1371/journal.pone.0282950] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 02/27/2023] [Indexed: 03/25/2023] Open
Abstract
A core feature of complex systems is that the interactions between elements in the present causally constrain their own futures, and the futures of other elements as the system evolves through time. To fully model all of these interactions (between elements, as well as ensembles of elements), it is possible to decompose the total information flowing from past to future into a set of non-overlapping temporal interactions that describe all the different modes by which information can be stored, transferred, or modified. To achieve this, I propose a novel information-theoretic measure of temporal dependency (Iτsx) based on the logic of local probability mass exclusions. This integrated information decomposition can reveal emergent and higher-order interactions within the dynamics of a system, as well as refining existing measures. To demonstrate the utility of this framework, I apply the decomposition to spontaneous spiking activity recorded from dissociated neural cultures of rat cerebral cortex to show how different modes of information processing are distributed over the system. Furthermore, being a localizable analysis, Iτsx can provide insight into the computational structure of single moments. I explore the time-resolved computational structure of neuronal avalanches and find that different types of information atoms have distinct profiles over the course of an avalanche, with the majority of non-trivial information dynamics happening before the first half of the cascade is completed. These analyses allow us to move beyond the historical focus on single measures of dependency such as information transfer or information integration, and explore a panoply of different relationships between elements (and groups of elements) in complex systems.
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Affiliation(s)
- Thomas F. Varley
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States of America
- School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States of America
- * E-mail:
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15
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From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans. Transl Psychiatry 2022; 12:467. [PMID: 36344497 PMCID: PMC9640647 DOI: 10.1038/s41398-022-02218-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 08/22/2022] [Accepted: 10/06/2022] [Indexed: 11/09/2022] Open
Abstract
Brain function is a product of the balance between excitatory and inhibitory (E/I) brain activity. Variation in the regulation of this activity is thought to give rise to normal variation in human traits, and disruptions are thought to potentially underlie a spectrum of neuropsychiatric conditions (e.g., Autism, Schizophrenia, Downs' Syndrome, intellectual disability). Hypotheses related to E/I dysfunction have the potential to provide cross-diagnostic explanations and to combine genetic and neurological evidence that exists within and between psychiatric conditions. However, the hypothesis has been difficult to test because: (1) it lacks specificity-an E/I dysfunction could pertain to any level in the neural system- neurotransmitters, single neurons/receptors, local networks of neurons, or global brain balance - most researchers do not define the level at which they are examining E/I function; (2) We lack validated methods for assessing E/I function at any of these neural levels in humans. As a result, it has not been possible to reliably or robustly test the E/I hypothesis of psychiatric disorders in a large cohort or longitudinal patient studies. Currently available, in vivo markers of E/I in humans either carry significant risks (e.g., deep brain electrode recordings or using Positron Emission Tomography (PET) with radioactive tracers) and/or are highly restrictive (e.g., limited spatial extent for Transcranial Magnetic Stimulation (TMS) and Magnetic Resonance Spectroscopy (MRS). More recently, a range of novel Electroencephalography (EEG) features has been described, which could serve as proxy markers for E/I at a given level of inference. Thus, in this perspective review, we survey the theories and experimental evidence underlying 6 novel EEG markers and their biological underpinnings at a specific neural level. These cheap-to-record and scalable proxy markers may offer clinical utility for identifying subgroups within and between diagnostic categories, thus directing more tailored sub-grouping and, therefore, treatment strategies. However, we argue that studies in clinical populations are premature. To maximize the potential of prospective EEG markers, we first need to understand the link between underlying E/I mechanisms and measurement techniques.
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16
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Tian Y, Tan Z, Hou H, Li G, Cheng A, Qiu Y, Weng K, Chen C, Sun P. Theoretical foundations of studying criticality in the brain. Netw Neurosci 2022; 6:1148-1185. [PMID: 38800464 PMCID: PMC11117095 DOI: 10.1162/netn_a_00269] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 07/12/2022] [Indexed: 05/29/2024] Open
Abstract
Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information-processing capacities in the brain. While considerable evidence generally supports this hypothesis, nonnegligible controversies persist regarding the ubiquity of criticality in neural dynamics and its role in information processing. Validity issues frequently arise during identifying potential brain criticality from empirical data. Moreover, the functional benefits implied by brain criticality are frequently misconceived or unduly generalized. These problems stem from the nontriviality and immaturity of the physical theories that analytically derive brain criticality and the statistic techniques that estimate brain criticality from empirical data. To help solve these problems, we present a systematic review and reformulate the foundations of studying brain criticality, that is, ordinary criticality (OC), quasi-criticality (qC), self-organized criticality (SOC), and self-organized quasi-criticality (SOqC), using the terminology of neuroscience. We offer accessible explanations of the physical theories and statistical techniques of brain criticality, providing step-by-step derivations to characterize neural dynamics as a physical system with avalanches. We summarize error-prone details and existing limitations in brain criticality analysis and suggest possible solutions. Moreover, we present a forward-looking perspective on how optimizing the foundations of studying brain criticality can deepen our understanding of various neuroscience questions.
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Affiliation(s)
- Yang Tian
- Department of Psychology & Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China
- Laboratory of Advanced Computing and Storage, Central Research Institute, 2012 Laboratories, Huawei Technologies Co. Ltd., Beijing, China
| | - Zeren Tan
- Institute for Interdisciplinary Information Science, Tsinghua University, Beijing, China
| | - Hedong Hou
- UFR de Mathématiques, Université de Paris, Paris, France
| | - Guoqi Li
- Institute of Automation, Chinese Academy of Science, Beijing, China
- University of Chinese Academy of Science, Beijing, China
| | - Aohua Cheng
- Tsien Excellence in Engineering Program, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Yike Qiu
- Tsien Excellence in Engineering Program, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Kangyu Weng
- Tsien Excellence in Engineering Program, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Chun Chen
- Department of Psychology & Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China
| | - Pei Sun
- Department of Psychology & Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China
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17
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Abstract
A complex system is often associated with emergence of new phenomena from the interactions between the system's components. General anesthesia reduces brain complexity and so inhibits the emergence of consciousness. An understanding of complexity is necessary for the interpretation of brain monitoring algorithms. Complexity indices capture the "difficulty" of understanding brain activity over time and/or space. Complexity-entropy plots reveal the types of complexity indices and their balance of randomness and structure. Lempel-Ziv complexity is a common index of temporal complexity for single-channel electroencephalogram containing both power spectral and nonlinear effects, revealed by phase-randomized surrogate data. Computing spatial complexities involves forming a connectivity matrix and calculating the complexity of connectivity patterns. Spatiotemporal complexity can be estimated in multiple ways including temporal or spatial concatenation, estimation of state switching, or integrated information. This article illustrates the concept and application of various complexities by providing working examples; a website with interactive demonstrations has also been created.
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18
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Walter N, Hinterberger T. Self-organized criticality as a framework for consciousness: A review study. Front Psychol 2022; 13:911620. [PMID: 35911009 PMCID: PMC9336647 DOI: 10.3389/fpsyg.2022.911620] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 06/29/2022] [Indexed: 01/04/2023] Open
Abstract
Objective No current model of consciousness is univocally accepted on either theoretical or empirical grounds, and the need for a solid unifying framework is evident. Special attention has been given to the premise that self-organized criticality (SOC) is a fundamental property of neural system. SOC provides a competitive model to describe the physical mechanisms underlying spontaneous brain activity, and thus, critical dynamics were proposed as general gauges of information processing representing a strong candidate for a surrogate measure of consciousness. As SOC could be a neurodynamical framework, which may be able to bring together existing theories and experimental evidence, the purpose of this work was to provide a comprehensive overview of progress of research on SOC in association with consciousness. Methods A comprehensive search of publications on consciousness and SOC published between 1998 and 2021 was conducted. The Web of Science database was searched, and annual number of publications and citations, type of articles, and applied methods were determined. Results A total of 71 publications were identified. The annual number of citations steadily increased over the years. Original articles comprised 50.7% and reviews/theoretical articles 43.6%. Sixteen studies reported on human data and in seven studies data were recorded in animals. Computational models were utilized in n = 12 studies. EcoG data were assessed in n = 4 articles, fMRI in n = 4 studies, and EEG/MEG in n = 10 studies. Notably, different analytical tools were applied in the EEG/MEG studies to assess a surrogate measure of criticality such as the detrended fluctuation analysis, the pair correlation function, parameters from the neuronal avalanche analysis and the spectral exponent. Conclusion Recent studies pointed out agreements of critical dynamics with the current most influencing theories in the field of consciousness research, the global workspace theory and the integrated information theory. Thus, the framework of SOC as a neurodynamical parameter for consciousness seems promising. However, identified experimental work was small in numbers, and a heterogeneity of applied analytical tools as a surrogate measure of criticality was observable, which limits the generalizability of findings.
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19
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Gonzalez J, Mateos D, Cavelli M, Mondino A, Pascovich C, Torterolo P, Rubido N. Low frequency oscillations drive EEG’s complexity changes during wakefulness and sleep. Neuroscience 2022; 494:1-11. [DOI: 10.1016/j.neuroscience.2022.04.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 11/30/2022]
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20
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Vrijdag XCE, van Waart H, Pullon RM, Sames C, Mitchell SJ, Sleigh JW. EEG functional connectivity is sensitive for nitrogen narcosis at 608 kPa. Sci Rep 2022; 12:4880. [PMID: 35318392 PMCID: PMC8940999 DOI: 10.1038/s41598-022-08869-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 03/14/2022] [Indexed: 12/21/2022] Open
Abstract
Divers commonly breathe air, containing nitrogen. Nitrogen under hyperbaric conditions is a narcotic gas. In dives beyond a notional threshold of 30 m depth (405 kPa) this can cause cognitive impairment, culminating in accidents due to poor decision making. Helium is known to have no narcotic effect. This study explored potential approaches to developing an electroencephalogram (EEG) functional connectivity metric to measure narcosis produced by nitrogen at hyperbaric pressures. Twelve human participants (five female) breathed air and heliox (in random order) at 284 and 608 kPa while recording 32-channel EEG and psychometric function. The degree of spatial functional connectivity, estimated using mutual information, was summarized with global efficiency. Air-breathing at 608 kPa (experienced as mild narcosis) caused a 35% increase in global efficiency compared to surface air-breathing (mean increase = 0.17, 95% CI [0.09–0.25], p = 0.001). Air-breathing at 284 kPa trended in a similar direction. Functional connectivity was modestly associated with psychometric impairment (mixed-effects model r2 = 0.60, receiver-operating-characteristic area, 0.67 [0.51–0.84], p = 0.02). Heliox breathing did not cause a significant change in functional connectivity. In conclusion, functional connectivity increased during hyperbaric air-breathing in a dose-dependent manner, but not while heliox-breathing. This suggests sensitivity to nitrogen narcosis specifically.
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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.
| | - Hanna van Waart
- Department of Anaesthesiology, School of Medicine, University of Auckland, Private bag 92019, Auckland, 1142, New Zealand
| | - Rebecca M Pullon
- 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
| | - Chris Sames
- Slark Hyperbaric Unit, Waitemata District Health Board, Auckland, 0610, New Zealand
| | - Simon J Mitchell
- Department of Anaesthesiology, School of Medicine, University of Auckland, Private bag 92019, Auckland, 1142, New Zealand.,Slark Hyperbaric Unit, Waitemata District Health Board, Auckland, 0610, 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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21
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Varley TF, Sporns O. Network Analysis of Time Series: Novel Approaches to Network Neuroscience. Front Neurosci 2022; 15:787068. [PMID: 35221887 PMCID: PMC8874015 DOI: 10.3389/fnins.2021.787068] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/20/2021] [Indexed: 12/12/2022] Open
Abstract
In the last two decades, there has been an explosion of interest in modeling the brain as a network, where nodes correspond variously to brain regions or neurons, and edges correspond to structural or statistical dependencies between them. This kind of network construction, which preserves spatial, or structural, information while collapsing across time, has become broadly known as "network neuroscience." In this work, we provide an alternative application of network science to neural data: network-based analysis of non-linear time series and review applications of these methods to neural data. Instead of preserving spatial information and collapsing across time, network analysis of time series does the reverse: it collapses spatial information, instead preserving temporally extended dynamics, typically corresponding to evolution through some kind of phase/state-space. This allows researchers to infer a, possibly low-dimensional, "intrinsic manifold" from empirical brain data. We will discuss three methods of constructing networks from nonlinear time series, and how to interpret them in the context of neural data: recurrence networks, visibility networks, and ordinal partition networks. By capturing typically continuous, non-linear dynamics in the form of discrete networks, we show how techniques from network science, non-linear dynamics, and information theory can extract meaningful information distinct from what is normally accessible in standard network neuroscience approaches.
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Affiliation(s)
- Thomas F. Varley
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States
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22
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Xin Y, Bai T, Zhang T, Chen Y, Wang K, Yu S, Liu N, Tian Y. Electroconvulsive therapy modulates critical brain dynamics in major depressive disorder patients. Brain Stimul 2022; 15:214-225. [DOI: 10.1016/j.brs.2021.12.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/03/2021] [Accepted: 12/20/2021] [Indexed: 01/04/2023] Open
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23
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Garwood IC, Chakravarty S, Donoghue J, Mahnke M, Kahali P, Chamadia S, Akeju O, Miller EK, Brown EN. A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque local field potentials and human electroencephalograms. PLoS Comput Biol 2021; 17:e1009280. [PMID: 34407069 PMCID: PMC8405019 DOI: 10.1371/journal.pcbi.1009280] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 08/30/2021] [Accepted: 07/15/2021] [Indexed: 11/18/2022] Open
Abstract
Ketamine is an NMDA receptor antagonist commonly used to maintain general anesthesia. At anesthetic doses, ketamine causes high power gamma (25-50 Hz) oscillations alternating with slow-delta (0.1-4 Hz) oscillations. These dynamics are readily observed in local field potentials (LFPs) of non-human primates (NHPs) and electroencephalogram (EEG) recordings from human subjects. However, a detailed statistical analysis of these dynamics has not been reported. We characterize ketamine's neural dynamics using a hidden Markov model (HMM). The HMM observations are sequences of spectral power in seven canonical frequency bands between 0 to 50 Hz, where power is averaged within each band and scaled between 0 and 1. We model the observations as realizations of multivariate beta probability distributions that depend on a discrete-valued latent state process whose state transitions obey Markov dynamics. Using an expectation-maximization algorithm, we fit this beta-HMM to LFP recordings from 2 NHPs, and separately, to EEG recordings from 9 human subjects who received anesthetic doses of ketamine. Our beta-HMM framework provides a useful tool for experimental data analysis. Together, the estimated beta-HMM parameters and optimal state trajectory revealed an alternating pattern of states characterized primarily by gamma and slow-delta activities. The mean duration of the gamma activity was 2.2s([1.7,2.8]s) and 1.2s([0.9,1.5]s) for the two NHPs, and 2.5s([1.7,3.6]s) for the human subjects. The mean duration of the slow-delta activity was 1.6s([1.2,2.0]s) and 1.0s([0.8,1.2]s) for the two NHPs, and 1.8s([1.3,2.4]s) for the human subjects. Our characterizations of the alternating gamma slow-delta activities revealed five sub-states that show regular sequential transitions. These quantitative insights can inform the development of rhythm-generating neuronal circuit models that give mechanistic insights into this phenomenon and how ketamine produces altered states of arousal.
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Affiliation(s)
- Indie C. Garwood
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Sourish Chakravarty
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Jacob Donoghue
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Meredith Mahnke
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Pegah Kahali
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Shubham Chamadia
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Oluwaseun Akeju
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Earl K. Miller
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Emery N. Brown
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
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Varley TF, Denny V, Sporns O, Patania A. Topological analysis of differential effects of ketamine and propofol anaesthesia on brain dynamics. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201971. [PMID: 34168888 PMCID: PMC8220281 DOI: 10.1098/rsos.201971] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 05/21/2021] [Indexed: 05/07/2023]
Abstract
Research has found that the vividness of conscious experience is related to brain dynamics. Despite both being anaesthetics, propofol and ketamine produce different subjective states: we explore the different effects of these two anaesthetics on the structure of dynamic attractors reconstructed from electrophysiological activity recorded from cerebral cortex of two macaques. We used two methods: the first embeds the recordings in a continuous high-dimensional manifold on which we use topological data analysis to infer the presence of higher-order dynamics. The second reconstruction, an ordinal partition network embedding, allows us to create a discrete state-transition network, which is amenable to information-theoretic analysis and contains rich information about state-transition dynamics. We find that the awake condition generally had the 'richest' structure, visiting the most states, the presence of pronounced higher-order structures, and the least deterministic dynamics. By contrast, the propofol condition had the most dissimilar dynamics, transitioning to a more impoverished, constrained, low-structure regime. The ketamine condition, interestingly, seemed to combine aspects of both: while it was generally less complex than the awake condition, it remained well above propofol in almost all measures. These results provide deeper and more comprehensive insights than what is typically gained by using point-measures of complexity.
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Affiliation(s)
- Thomas F. Varley
- Psychological & Brain Sciences, Indiana University, Bloomington, IN 47401, USA
- School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN 47401, USA
| | - Vanessa Denny
- Psychological & Brain Sciences, Indiana University, Bloomington, IN 47401, USA
| | - Olaf Sporns
- Psychological & Brain Sciences, Indiana University, Bloomington, IN 47401, USA
- Indiana University Network Sciences Institute (IUNI), Bloomington, IN 47401, USA
| | - Alice Patania
- Indiana University Network Sciences Institute (IUNI), Bloomington, IN 47401, USA
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