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Murray CH, Frohlich J, Haggarty CJ, Tare I, Lee R, de Wit H. Neural complexity is increased after low doses of LSD, but not moderate to high doses of oral THC or methamphetamine. Neuropsychopharmacology 2024; 49:1120-1128. [PMID: 38287172 PMCID: PMC11109226 DOI: 10.1038/s41386-024-01809-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 01/07/2024] [Accepted: 01/17/2024] [Indexed: 01/31/2024]
Abstract
Neural complexity correlates with one's level of consciousness. During coma, anesthesia, and sleep, complexity is reduced. During altered states, including after lysergic acid diethylamide (LSD), complexity is increased. In the present analysis, we examined whether low doses of LSD (13 and 26 µg) were sufficient to increase neural complexity in the absence of altered states of consciousness. In addition, neural complexity was assessed after doses of two other drugs that significantly altered consciousness and mood: delta-9-tetrahydrocannabinol (THC; 7.5 and 15 mg) and methamphetamine (MA; 10 and 20 mg). In three separate studies (N = 73; 21, LSD; 23, THC; 29, MA), healthy volunteers received placebo or drug in a within-subjects design over three laboratory visits. During anticipated peak drug effects, resting state electroencephalography (EEG) recorded Limpel-Ziv complexity and spectral power. LSD, but not THC or MA, dose-dependently increased neural complexity. LSD also reduced delta and theta power. THC reduced, and MA increased, alpha power, primarily in frontal regions. Neural complexity was not associated with any subjective drug effect; however, LSD-induced reductions in delta and theta were associated with elation, and THC-induced reductions in alpha were associated with altered states. These data inform relationships between neural complexity, spectral power, and subjective states, demonstrating that increased neural complexity is not necessary or sufficient for altered states of consciousness. Future studies should address whether greater complexity after low doses of LSD is related to cognitive, behavioral, or therapeutic outcomes, and further examine the role of alpha desynchronization in mediating altered states of consciousness.
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Affiliation(s)
- Conor H Murray
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, Chicago, IL, 60637, USA.
- Department of Psychiatry and Biobehavioral Sciences, University of Los Angeles, California, 760 Westwood Plaza, Los Angeles, CA, 90024, USA.
| | - Joel Frohlich
- Institute for Neuromodulation and Neurotechnology, University of Tübingen, Otfried-Müller-Straße 45, 72076, Tübingen, Germany
- Institute for Advanced Consciousness Studies, Santa Monica, California; 2811 Wilshire Blvd # 510, Santa Monica, CA, 90403, USA
| | - Connor J Haggarty
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, Chicago, IL, 60637, USA
| | - Ilaria Tare
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, Chicago, IL, 60637, USA
| | - Royce Lee
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, Chicago, IL, 60637, USA
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, Chicago, IL, 60637, USA
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Montupil J, Cardone P, Staquet C, Bonhomme A, Defresne A, Martial C, Alnagger NL, Gosseries O, Bonhomme V. The nature of consciousness in anaesthesia. BJA OPEN 2023; 8:100224. [PMID: 37780201 PMCID: PMC10539891 DOI: 10.1016/j.bjao.2023.100224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 08/28/2023] [Indexed: 10/03/2023]
Abstract
Neuroscientists agree on the value of locating the source of consciousness within the brain. Anaesthesiologists are no exception, and have their own operational definition of consciousness based on phenomenological observations during anaesthesia. The full functional correlates of consciousness are yet to be precisely identified, however rapidly evolving progress in this scientific domain has yielded several theories that attempt to model the generation of consciousness. They have received variable support from experimental observations, including those involving anaesthesia and its ability to reversibly modulate different aspects of consciousness. Aside from the interest in a better understanding of the mechanisms of consciousness, exploring the functional tenets of the phenomenological consciousness states of general anaesthesia has the potential to ultimately improve patient management. It could facilitate the design of specific monitoring devices and approaches, aiming at reliably detecting each of the possible states of consciousness during an anaesthetic procedure, including total absence of mental content (unconsciousness), and internal awareness (sensation of self and internal thoughts) with or without conscious perception of the environment (connected or disconnected consciousness, respectively). Indeed, it must be noted that unresponsiveness is not sufficient to infer absence of connectedness or even absence of consciousness. This narrative review presents the current knowledge in this field from a system-level, underlining the contribution of anaesthesia studies in supporting theories of consciousness, and proposing directions for future research.
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Affiliation(s)
- Javier Montupil
- Anesthesia and Perioperative Neuroscience Laboratory, Liege, Belgium
- Department of Anesthesia and Intensive Care Medicine, Liege, Belgium
- University Department of Anesthesia and Intensive Care Medicine, Citadelle Regional Hospital, Liege, Belgium
| | - Paolo Cardone
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liege University, Liege, Belgium
- Centre du Cerveau, Liege University Hospital, Liege, Belgium
| | - Cécile Staquet
- Anesthesia and Perioperative Neuroscience Laboratory, Liege, Belgium
- Department of Anesthesia and Intensive Care Medicine, Liege, Belgium
| | - Arthur Bonhomme
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liege University, Liege, Belgium
| | - Aline Defresne
- Anesthesia and Perioperative Neuroscience Laboratory, Liege, Belgium
- Department of Anesthesia and Intensive Care Medicine, Liege, Belgium
- University Department of Anesthesia and Intensive Care Medicine, Citadelle Regional Hospital, Liege, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liege University, Liege, Belgium
- Centre du Cerveau, Liege University Hospital, Liege, Belgium
| | - Naji L.N. Alnagger
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liege University, Liege, Belgium
- Centre du Cerveau, Liege University Hospital, Liege, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liege University, Liege, Belgium
- Centre du Cerveau, Liege University Hospital, Liege, Belgium
| | - Vincent Bonhomme
- Anesthesia and Perioperative Neuroscience Laboratory, Liege, Belgium
- Department of Anesthesia and Intensive Care Medicine, Liege, Belgium
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Luppi AI, Vohryzek J, Kringelbach ML, Mediano PAM, Craig MM, Adapa R, Carhart-Harris RL, Roseman L, Pappas I, Peattie ARD, Manktelow AE, Sahakian BJ, Finoia P, Williams GB, Allanson J, Pickard JD, Menon DK, Atasoy S, Stamatakis EA. Distributed harmonic patterns of structure-function dependence orchestrate human consciousness. Commun Biol 2023; 6:117. [PMID: 36709401 PMCID: PMC9884288 DOI: 10.1038/s42003-023-04474-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 01/11/2023] [Indexed: 01/29/2023] Open
Abstract
A central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function. Here we decompose functional MRI signals from pathological and pharmacologically-induced perturbations of consciousness into distributed patterns of structure-function dependence across scales: the harmonic modes of the human structural connectome. We show that structure-function coupling is a generalisable indicator of consciousness that is under bi-directional neuromodulatory control. We find increased structure-function coupling across scales during loss of consciousness, whether due to anaesthesia or brain injury, capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness. The opposite harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure and correlating with physiological and subjective scores. Overall, connectome harmonic decomposition reveals how neuromodulation and the network architecture of the human connectome jointly shape consciousness and distributed functional activation across scales.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK.
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, CB2 1SB, UK.
| | - Jakub Vohryzek
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, 08005, Spain
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
- Department of Computing, Imperial College London, London, W12 0NN, UK
| | - Michael M Craig
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Ram Adapa
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Robin L Carhart-Harris
- Center for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
- Psychedelics Division - Neuroscape, Department of Neurology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Leor Roseman
- Center for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
| | - Ioannis Pappas
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Alexander R D Peattie
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Anne E Manktelow
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Barbara J Sahakian
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Psychiatry, MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - John D Pickard
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Selen Atasoy
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
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4
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Complementary roles of neural synchrony and complexity for indexing consciousness and chances of surviving in acute coma. Neuroimage 2021; 245:118638. [PMID: 34624502 DOI: 10.1016/j.neuroimage.2021.118638] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 09/28/2021] [Accepted: 10/05/2021] [Indexed: 11/23/2022] Open
Abstract
An open challenge in consciousness research is understanding how neural functions are altered by pathological loss of consciousness. To maintain consciousness, the brain needs synchronized communication of information across brain regions, and sufficient complexity in neural activity. Coordination of brain activity, typically indexed through measures of neural synchrony, has been shown to decrease when consciousness is lost and to reflect the clinical state of patients with disorders of consciousness. Moreover, when consciousness is lost, neural activity loses complexity, while the levels of neural noise, indexed by the slope of the electroencephalography (EEG) spectral exponent decrease. Although these properties have been well investigated in resting state activity, it remains unknown whether the sensory processing network, which has been shown to be preserved in coma, suffers from a loss of synchronization or information content. Here, we focused on acute coma and hypothesized that neural synchrony in response to auditory stimuli would reflect coma severity, while complexity, or neural noise, would reflect the presence or loss of consciousness. Results showed that neural synchrony of EEG signals was stronger for survivors than non-survivors and predictive of patients' outcome, but indistinguishable between survivors and healthy controls. Measures of neural complexity and neural noise were not informative of patients' outcome and had high or low values for patients compared to controls. Our results suggest different roles for neural synchrony and complexity in acute coma. Synchrony represents a precondition for consciousness, while complexity needs an equilibrium between high or low values to support conscious cognition.
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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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6
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Luppi AI, Cain J, Spindler LRB, Górska UJ, Toker D, Hudson AE, Brown EN, Diringer MN, Stevens RD, Massimini M, Monti MM, Stamatakis EA, Boly M. Mechanisms Underlying Disorders of Consciousness: Bridging Gaps to Move Toward an Integrated Translational Science. Neurocrit Care 2021; 35:37-54. [PMID: 34236622 PMCID: PMC8266690 DOI: 10.1007/s12028-021-01281-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 05/17/2021] [Indexed: 01/08/2023]
Abstract
AIM In order to successfully detect, classify, prognosticate, and develop targeted therapies for patients with disorders of consciousness (DOC), it is crucial to improve our mechanistic understanding of how severe brain injuries result in these disorders. METHODS To address this need, the Curing Coma Campaign convened a Mechanisms Sub-Group of the Coma Science Work Group (CSWG), aiming to identify the most pressing knowledge gaps and the most promising approaches to bridge them. RESULTS We identified a key conceptual gap in the need to differentiate the neural mechanisms of consciousness per se, from those underpinning connectedness to the environment and behavioral responsiveness. Further, we characterised three fundamental gaps in DOC research: (1) a lack of mechanistic integration between structural brain damage and abnormal brain function in DOC; (2) a lack of translational bridges between micro- and macro-scale neural phenomena; and (3) an incomplete exploration of possible synergies between data-driven and theory-driven approaches. CONCLUSION In this white paper, we discuss research priorities that would enable us to begin to close these knowledge gaps. We propose that a fundamental step towards this goal will be to combine translational, multi-scale, and multimodal data, with new biomarkers, theory-driven approaches, and computational models, to produce an integrated account of neural mechanisms in DOC. Importantly, we envision that reciprocal interaction between domains will establish a "virtuous cycle," leading towards a critical vantage point of integrated knowledge that will enable the advancement of the scientific understanding of DOC and consequently, an improvement of clinical practice.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Joshua Cain
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Lennart R B Spindler
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Urszula J Górska
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA.
| | - Daniel Toker
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrew E Hudson
- Department of Anesthesia and Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Emery N Brown
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael N Diringer
- Department of Neurology and Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology and Neurosurgery, and Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Marcello Massimini
- Dipartimento di Scienze Biomediche e Cliniche "L. Sacco", Università Degli Studi Di Milano, Milan, Italy
- Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Martin M Monti
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
- Brain Injury Research Center, Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Melanie Boly
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
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7
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Luppi AI, Carhart-Harris RL, Roseman L, Pappas I, Menon DK, Stamatakis EA. LSD alters dynamic integration and segregation in the human brain. Neuroimage 2021; 227:117653. [PMID: 33338615 PMCID: PMC7896102 DOI: 10.1016/j.neuroimage.2020.117653] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 11/26/2020] [Accepted: 12/04/2020] [Indexed: 01/08/2023] Open
Abstract
Investigating changes in brain function induced by mind-altering substances such as LSD is a powerful method for interrogating and understanding how mind interfaces with brain, by connecting novel psychological phenomena with their neurobiological correlates. LSD is known to increase measures of brain complexity, potentially reflecting a neurobiological correlate of the especially rich phenomenological content of psychedelic-induced experiences. Yet although the subjective stream of consciousness is a constant ebb and flow, no studies to date have investigated how LSD influences the dynamics of functional connectivity in the human brain. Focusing on the two fundamental network properties of integration and segregation, here we combined graph theory and dynamic functional connectivity from resting-state functional MRI to examine time-resolved effects of LSD on brain networks properties and subjective experiences. Our main finding is that the effects of LSD on brain function and subjective experience are non-uniform in time: LSD makes globally segregated sub-states of dynamic functional connectivity more complex, and weakens the relationship between functional and anatomical connectivity. On a regional level, LSD reduces functional connectivity of the anterior medial prefrontal cortex, specifically during states of high segregation. Time-specific effects were correlated with different aspects of subjective experiences; in particular, ego dissolution was predicted by increased small-world organisation during a state of high global integration. These results reveal a more nuanced, temporally-specific picture of altered brain connectivity and complexity under psychedelics than has previously been reported.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, United Kingdom; Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, United Kingdom.
| | - Robin L Carhart-Harris
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London W12 0NN, United Kingdom
| | - Leor Roseman
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London W12 0NN, United Kingdom
| | - Ioannis Pappas
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, United Kingdom; Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, United Kingdom; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
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8
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Keilholz S, Maltbie E, Zhang X, Yousefi B, Pan WJ, Xu N, Nezafati M, LaGrow TJ, Guo Y. Relationship Between Basic Properties of BOLD Fluctuations and Calculated Metrics of Complexity in the Human Connectome Project. Front Neurosci 2020; 14:550923. [PMID: 33041756 PMCID: PMC7522447 DOI: 10.3389/fnins.2020.550923] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 08/13/2020] [Indexed: 12/14/2022] Open
Abstract
Resting state functional MRI (rs-fMRI) creates a rich four-dimensional data set that can be analyzed in a variety of ways. As more researchers come to view the brain as a complex dynamical system, tools are increasingly being drawn from other fields to characterize the complexity of the brain's activity. However, given that the signal measured with rs-fMRI arises from the hemodynamic response to neural activity, the extent to which complexity metrics reflect neural complexity as compared to signal properties related to image quality remains unknown. To provide some insight into this question, correlation dimension, approximate entropy and Lyapunov exponent were calculated for different rs-fMRI scans from the same subject to examine their reliability. The metrics of complexity were then compared to several properties of the rs-fMRI signal from each brain area to determine if basic signal features could explain differences in the complexity metrics. Differences in complexity across brain areas were highly reliable and were closely linked to differences in the frequency profiles of the rs-fMRI signal. The spatial distributions of the complexity and frequency metrics suggest that they are both influenced by location-dependent signal properties that can obscure changes related to neural activity.
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Affiliation(s)
- Shella Keilholz
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Eric Maltbie
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Xiaodi Zhang
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Behnaz Yousefi
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Nan Xu
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Maysam Nezafati
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Theodore J LaGrow
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Ying Guo
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States
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9
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Luppi AI, Craig MM, Pappas I, Finoia P, Williams GB, Allanson J, Pickard JD, Owen AM, Naci L, Menon DK, Stamatakis EA. Consciousness-specific dynamic interactions of brain integration and functional diversity. Nat Commun 2019; 10:4616. [PMID: 31601811 PMCID: PMC6787094 DOI: 10.1038/s41467-019-12658-9] [Citation(s) in RCA: 123] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 09/16/2019] [Indexed: 12/26/2022] Open
Abstract
Prominent theories of consciousness emphasise different aspects of neurobiology, such as the integration and diversity of information processing within the brain. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from awake volunteers, propofol-anaesthetised volunteers, and patients with disorders of consciousness, in order to identify consciousness-specific patterns of brain function. We demonstrate that cortical networks are especially affected by loss of consciousness during temporal states of high integration, exhibiting reduced functional diversity and compromised informational capacity, whereas thalamo-cortical functional disconnections emerge during states of higher segregation. Spatially, posterior regions of the brain’s default mode network exhibit reductions in both functional diversity and integration with the rest of the brain during unconsciousness. These results show that human consciousness relies on spatio-temporal interactions between brain integration and functional diversity, whose breakdown may represent a generalisable biomarker of loss of consciousness, with potential relevance for clinical practice. How do diversity (entropy) and integration of activity across brain regions interact to support consciousness? Here the authors show that anaesthetised individuals and patients with disorders of consciousness exhibit overlapping reductions in both diversity and integration in the brain’s default mode network.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK
| | - Michael M Craig
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK
| | - Ioannis Pappas
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Helen Wills Neuroscience Institute, 210 Barker Hall, University of California - Berkeley, 94720, Berkeley, CA, USA
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), CB2 0QQ, Cambridge, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK
| | - John D Pickard
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), CB2 0QQ, Cambridge, UK
| | - Adrian M Owen
- The Brain and Mind Institute, Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario, London, ON, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Lloyd Building, Trinity College Dublin, Dublin, Dublin 2, Ireland
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.,Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), CB2 0QQ, Cambridge, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK. .,Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Rd, CB2 0SP, Cambridge, UK.
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10
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Abstract
Background: The aim of the present study was to assess the upper information content bound of positron emission tomography (PET) images, by means of the information capacity (IC). Methods: The Geant4 Application for the Tomographic Emission (GATE) Monte Carlo (MC) package was used, and reconstructed images were obtained by using the software for tomographic image reconstruction (STIR). The case study for the assessment of the information content was the General Electric (GE) Discovery-ST PET scanner. A thin-film plane source aluminum (Al) foil, coated with a thin layer of silica and with a 18F-fludeoxyglucose (FDG) bath distribution of 1 MBq was used. The influence of the (a) maximum likelihood estimation-ordered subsets-maximum a posteriori probability-one step late (MLE-OS-MAP-OSL) algorithm, using various subsets (1 to 21) and iterations (1 to 20) and (b) different scintillating crystals on PET scanner’s performance, was examined. The study was focused on the noise equivalent quanta (NEQ) and on the single index IC. Images of configurations by using different crystals were obtained after the commonly used 2-dimensional filtered back projection (FBP2D), 3-dimensional filtered back projection re-projection (FPB3DRP) and the (MLE)-OS-MAP-OSL algorithms. Results: Results shown that the images obtained with one subset and various iterations provided maximum NEQ values, however with a steep drop-off after 0.045 cycles/mm. The single index IC data were maximized for the range of 8–20 iterations and three subsets. The PET scanner configuration incorporating lutetium orthoaluminate perovskite (LuAP) crystals provided the highest NEQ values in 2D FBP for spatial frequencies higher than 0.028 cycles/mm. Bismuth germanium oxide (BGO) shows clear dominance against all other examined crystals across the spatial frequency range, in both 3D FBP and OS-MAP-OSL. The particular PET scanner provided optimum IC values using FBP3DRP and BGO crystals (2.4829 bits/mm2). Conclusions: The upper bound of the image information content of PET scanners can be fully characterized and further improved by investigating the imaging chain components through MC methods.
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