1
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Northoff G, Zilio F, Zhang J. Beyond task response-Pre-stimulus activity modulates contents of consciousness. Phys Life Rev 2024; 49:19-37. [PMID: 38492473 DOI: 10.1016/j.plrev.2024.03.002] [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: 02/28/2024] [Accepted: 03/03/2024] [Indexed: 03/18/2024]
Abstract
The current discussion on the neural correlates of the contents of consciousness (NCCc) focuses mainly on the post-stimulus period of task-related activity. This neglects the substantial impact of the spontaneous or ongoing activity of the brain as manifest in pre-stimulus activity. Does the interaction of pre- and post-stimulus activity shape the contents of consciousness? Addressing this gap in our knowledge, we review and converge two recent lines of findings, that is, pre-stimulus alpha power and pre- and post-stimulus alpha trial-to-trial variability (TTV). The data show that pre-stimulus alpha power modulates post-stimulus activity including specifically the subjective features of conscious contents like confidence and vividness. At the same time, alpha pre-stimulus variability shapes post-stimulus TTV reduction including the associated contents of consciousness. We propose that non-additive rather than merely additive interaction of the internal pre-stimulus activity with the external stimulus in the alpha band is key for contents to become conscious. This is mediated by mechanisms on different levels including neurophysiological, neurocomputational, neurodynamic, neuropsychological and neurophenomenal levels. Overall, considering the interplay of pre-stimulus intrinsic and post-stimulus extrinsic activity across wider timescales, not just evoked responses in the post-stimulus period, is critical for identifying neural correlates of consciousness. This is well in line with both processing and especially the Temporo-spatial theory of consciousness (TTC).
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Affiliation(s)
- Georg Northoff
- University of Ottawa, Institute of Mental Health Research at the Royal Ottawa Hospital, Ottawa, Canada.
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua, Padua, Italy
| | - Jianfeng Zhang
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China.
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2
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Chis-Ciure R, Melloni L, Northoff G. A measure centrality index for systematic empirical comparison of consciousness theories. Neurosci Biobehav Rev 2024; 161:105670. [PMID: 38615851 DOI: 10.1016/j.neubiorev.2024.105670] [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: 02/03/2024] [Revised: 03/15/2024] [Accepted: 04/08/2024] [Indexed: 04/16/2024]
Abstract
Consciousness science is marred by disparate constructs and methodologies, making it challenging to systematically compare theories. This foundational crisis casts doubts on the scientific character of the field itself. Addressing it, we propose a framework for systematically comparing consciousness theories by introducing a novel inter-theory classification interface, the Measure Centrality Index (MCI). Recognizing its gradient distribution, the MCI assesses the degree of importance a specific empirical measure has for a given consciousness theory. We apply the MCI to probe how the empirical measures of the Global Neuronal Workspace Theory (GNW), Integrated Information Theory (IIT), and Temporospatial Theory of Consciousness (TTC) would fare within the context of the other two. We demonstrate that direct comparison of IIT, GNW, and TTC is meaningful and valid for some measures like Lempel-Ziv Complexity (LZC), Autocorrelation Window (ACW), and possibly Mutual Information (MI). In contrast, it is problematic for others like the anatomical and physiological neural correlates of consciousness (NCC) due to their MCI-based differential weightings within the structure of the theories. In sum, we introduce and provide proof-of-principle of a novel systematic method for direct inter-theory empirical comparisons, thereby addressing isolated evolution of theories and confirmatory bias issues in the state-of-the-art neuroscience of consciousness.
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Affiliation(s)
- Robert Chis-Ciure
- New York University (NYU), New York, USA; International Center for Neuroscience and Ethics (CINET), Tatiana Foundation, Madrid, Spain; Wolfram Physics Project, USA.
| | - Lucia Melloni
- Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
| | - Georg Northoff
- University of Ottawa, Institute of Mental Health Research at the Royal Ottawa Hospital, Ottawa, Canada
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3
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Ricci V, Maina G, Martinotti G. The Loss of Spatiality and Temporality in Twilight Consciousness: The Emergence of Exogenous Psychosis Induced by Novel Psychoactive Substances. Psychopathology 2024; 57:248-258. [PMID: 38631303 DOI: 10.1159/000536076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 12/29/2023] [Indexed: 04/19/2024]
Abstract
BACKGROUND The state of twilight consciousness is marked by a focused narrowing of awareness, maintaining vigilance and attention while simultaneously experiencing perceptual shifts in the surrounding environment. It is crucial to recognize that this twilight state represents not just a contraction but also an expansion of conscious experience. SUMMARY Substances of abuse, particularly new psychoactive substances, play a significant role in inducing this twilight state. They achieve this by deconstructing essential components of consciousness, such as the perception of time and space. KEY MESSAGE This paper aimed to explore the phenomenon of the twilight state of consciousness and shed light on how new psychoactive substances can alter the perception of time and space during this twilight phase, potentially triggering exogenous psychosis. This comprehensive inquiry employs a phenomenological approach to the study of consciousness, recognizing it as the primary tool for ascribing significance to this intricate yet often overlooked aspect of psychopathology.
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Affiliation(s)
- Valerio Ricci
- San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Giuseppe Maina
- San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
- Department of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Giovanni Martinotti
- Department of Neurosciences, Imaging and Clinical Sciences, Università Degli Studi G. D'Annunzio Chieti-Pescara, Chieti, Italy
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4
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Riddle J, Schooler JW. Hierarchical consciousness: the Nested Observer Windows model. Neurosci Conscious 2024; 2024:niae010. [PMID: 38504828 PMCID: PMC10949963 DOI: 10.1093/nc/niae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/31/2024] [Accepted: 02/26/2024] [Indexed: 03/21/2024] Open
Abstract
Foremost in our experience is the intuition that we possess a unified conscious experience. However, many observations run counter to this intuition: we experience paralyzing indecision when faced with two appealing behavioral choices, we simultaneously hold contradictory beliefs, and the content of our thought is often characterized by an internal debate. Here, we propose the Nested Observer Windows (NOW) Model, a framework for hierarchical consciousness wherein information processed across many spatiotemporal scales of the brain feeds into subjective experience. The model likens the mind to a hierarchy of nested mosaic tiles-where an image is composed of mosaic tiles, and each of these tiles is itself an image composed of mosaic tiles. Unitary consciousness exists at the apex of this nested hierarchy where perceptual constructs become fully integrated and complex behaviors are initiated via abstract commands. We define an observer window as a spatially and temporally constrained system within which information is integrated, e.g. in functional brain regions and neurons. Three principles from the signal analysis of electrical activity describe the nested hierarchy and generate testable predictions. First, nested observer windows disseminate information across spatiotemporal scales with cross-frequency coupling. Second, observer windows are characterized by a high degree of internal synchrony (with zero phase lag). Third, observer windows at the same spatiotemporal level share information with each other through coherence (with non-zero phase lag). The theoretical framework of the NOW Model accounts for a wide range of subjective experiences and a novel approach for integrating prominent theories of consciousness.
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Affiliation(s)
- Justin Riddle
- Department of Psychology, Florida State University, 1107 W Call St, Tallahassee, FL 32304, USA
| | - Jonathan W Schooler
- Department of Psychological & Brain Sciences, University of California, Santa Barbara, Psychological & Brain Sciences, Santa Barbara, CA 93106, USA
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5
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Miao J, Tantawi M, Alizadeh M, Thalheimer S, Vedaei F, Romo V, Mohamed FB, Wu C. Characteristic dynamic functional connectivity during sevoflurane-induced general anesthesia. Sci Rep 2023; 13:21014. [PMID: 38030651 PMCID: PMC10687074 DOI: 10.1038/s41598-023-43832-1] [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: 03/03/2023] [Accepted: 09/28/2023] [Indexed: 12/01/2023] Open
Abstract
General anesthesia (GA) during surgery is commonly maintained by inhalational sevoflurane. Previous resting state functional MRI (rs-fMRI) studies have demonstrated suppressed functional connectivity (FC) of the entire brain networks, especially the default mode networks, transitioning from the awake to GA condition. However, accuracy and reliability were limited by previous administration methods (e.g. face mask) and short rs-fMRI scans. Therefore, in this study, a clinical scenario of epilepsy patients undergoing laser interstitial thermal therapy was leveraged to acquire 15 min of rs-fMRI while under general endotracheal anesthesia to maximize the accuracy of sevoflurane level. Nine recruited patients had fMRI acquired during awake and under GA, of which seven were included in both static and dynamic FC analyses. Group independent component analysis and a sliding-window method followed by k-means clustering were applied to identify four dynamic brain states, which characterized subtypes of FC patterns. Our results showed that a low-FC brain state was characteristic of the GA condition as a single featuring state during the entire rs-fMRI session; In contrast, the awake condition exhibited frequent fluctuations between three distinct brain states, one of which was a highly synchronized brain state not seen in GA. In conclusion, our study revealed remarkable dynamic connectivity changes from awake to GA condition and demonstrated the advantages of dynamic FC analysis for future studies in the assessments of the effects of GA on brain functional activities.
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Affiliation(s)
- Jingya Miao
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA.
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA.
| | - Mohamed Tantawi
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Mahdi Alizadeh
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sara Thalheimer
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Faezeh Vedaei
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Victor Romo
- Department of Anesthesia, Thomas Jefferson University, Philadelphia, PA, USA
| | - Feroze B Mohamed
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Chengyuan Wu
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
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6
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Mehrotra D, Dubé L. Accounting for multiscale processing in adaptive real-world decision-making via the hippocampus. Front Neurosci 2023; 17:1200842. [PMID: 37732307 PMCID: PMC10508350 DOI: 10.3389/fnins.2023.1200842] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 08/25/2023] [Indexed: 09/22/2023] Open
Abstract
For adaptive real-time behavior in real-world contexts, the brain needs to allow past information over multiple timescales to influence current processing for making choices that create the best outcome as a person goes about making choices in their everyday life. The neuroeconomics literature on value-based decision-making has formalized such choice through reinforcement learning models for two extreme strategies. These strategies are model-free (MF), which is an automatic, stimulus-response type of action, and model-based (MB), which bases choice on cognitive representations of the world and causal inference on environment-behavior structure. The emphasis of examining the neural substrates of value-based decision making has been on the striatum and prefrontal regions, especially with regards to the "here and now" decision-making. Yet, such a dichotomy does not embrace all the dynamic complexity involved. In addition, despite robust research on the role of the hippocampus in memory and spatial learning, its contribution to value-based decision making is just starting to be explored. This paper aims to better appreciate the role of the hippocampus in decision-making and advance the successor representation (SR) as a candidate mechanism for encoding state representations in the hippocampus, separate from reward representations. To this end, we review research that relates hippocampal sequences to SR models showing that the implementation of such sequences in reinforcement learning agents improves their performance. This also enables the agents to perform multiscale temporal processing in a biologically plausible manner. Altogether, we articulate a framework to advance current striatal and prefrontal-focused decision making to better account for multiscale mechanisms underlying various real-world time-related concepts such as the self that cumulates over a person's life course.
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Affiliation(s)
- Dhruv Mehrotra
- Integrated Program in Neuroscience, McGill University, Montréal, QC, Canada
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Laurette Dubé
- Desautels Faculty of Management, McGill University, Montréal, QC, Canada
- McGill Center for the Convergence of Health and Economics, McGill University, Montréal, QC, Canada
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7
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Zilio F, Gomez-Pilar J, Chaudhary U, Fogel S, Fomina T, Synofzik M, Schöls L, Cao S, Zhang J, Huang Z, Birbaumer N, Northoff G. Altered brain dynamics index levels of arousal in complete locked-in syndrome. Commun Biol 2023; 6:757. [PMID: 37474587 PMCID: PMC10359418 DOI: 10.1038/s42003-023-05109-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 07/06/2023] [Indexed: 07/22/2023] Open
Abstract
Complete locked-in syndrome (CLIS) resulting from late-stage amyotrophic lateral sclerosis (ALS) is characterised by loss of motor function and eye movements. The absence of behavioural indicators of consciousness makes the search for neuronal correlates as possible biomarkers clinically and ethically urgent. EEG-based measures of brain dynamics such as power-law exponent (PLE) and Lempel-Ziv complexity (LZC) have been shown to have explanatory power for consciousness and may provide such neuronal indices for patients with CLIS. Here, we validated PLE and LZC (calculated in a dynamic way) as benchmarks of a wide range of arousal states across different reference states of consciousness (e.g., awake, sleep stages, ketamine, sevoflurane). We show a tendency toward high PLE and low LZC, with high intra-subject fluctuations and inter-subject variability in a cohort of CLIS patients with values graded along different arousal states as in our reference data sets. In conclusion, changes in brain dynamics indicate altered arousal in CLIS. Specifically, PLE and LZC are potentially relevant biomarkers to identify or diagnose the arousal level in CLIS and to determine the optimal time point for treatment, including communication attempts.
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Affiliation(s)
- Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy.
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Ujwal Chaudhary
- BrainPortal Technologies GmbH, Mannheim, Germany
- ALS Voice gGmbH, Mössingen, Germany
| | - Stuart Fogel
- School of Psychology, University of Ottawa, Ottawa, Canada
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
| | - Tatiana Fomina
- Department for Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Ludger Schöls
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Shumei Cao
- Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Jun Zhang
- Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Zirui Huang
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Niels Birbaumer
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
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8
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Buccellato A, Çatal Y, Bisiacchi P, Zang D, Zilio F, Wang Z, Qi Z, Zheng R, Xu Z, Wu X, Del Felice A, Mao Y, Northoff G. Probing Intrinsic Neural Timescales in EEG with an Information-Theory Inspired Approach: Permutation Entropy Time Delay Estimation (PE-TD). ENTROPY (BASEL, SWITZERLAND) 2023; 25:1086. [PMID: 37510033 PMCID: PMC10378026 DOI: 10.3390/e25071086] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/10/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023]
Abstract
Time delays are a signature of many physical systems, including the brain, and considerably shape their dynamics; moreover, they play a key role in consciousness, as postulated by the temporo-spatial theory of consciousness (TTC). However, they are often not known a priori and need to be estimated from time series. In this study, we propose the use of permutation entropy (PE) to estimate time delays from neural time series as a more robust alternative to the widely used autocorrelation window (ACW). In the first part, we demonstrate the validity of this approach on synthetic neural data, and we show its resistance to regimes of nonstationarity in time series. Mirroring yet another example of comparable behavior between different nonlinear systems, permutation entropy-time delay estimation (PE-TD) is also able to measure intrinsic neural timescales (INTs) (temporal windows of neural activity at rest) from hd-EEG human data; additionally, this replication extends to the abnormal prolongation of INT values in disorders of consciousness (DoCs). Surprisingly, the correlation between ACW-0 and PE-TD decreases in a state-dependent manner when consciousness is lost, hinting at potential different regimes of nonstationarity and nonlinearity in conscious/unconscious states, consistent with many current theoretical frameworks on consciousness. In summary, we demonstrate the validity of PE-TD as a tool to extract relevant time scales from neural data; furthermore, given the divergence between ACW and PE-TD specific to DoC subjects, we hint at its potential use for the characterization of conscious states.
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Affiliation(s)
- Andrea Buccellato
- Padova Neuroscience Center, University of Padova, Via Orus 2/B, 35129 Padova, Italy
- Department of General Psychology, University of Padova, Via Venezia, 8, 35131 Padova, Italy
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, ON K1Z 7K4, Canada
| | - Patrizia Bisiacchi
- Padova Neuroscience Center, University of Padova, Via Orus 2/B, 35129 Padova, Italy
- Department of General Psychology, University of Padova, Via Venezia, 8, 35131 Padova, Italy
| | - Di Zang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Neurosurgical Institute, Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Piazza Capitaniato, 3, 35139 Padova, Italy
| | - Zhe Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Neurosurgical Institute, Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Neurosurgical Institute, Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Ruizhe Zheng
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Neurosurgical Institute, Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Zeyu Xu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Neurosurgical Institute, Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Xuehai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Neurosurgical Institute, Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Alessandra Del Felice
- Padova Neuroscience Center, University of Padova, Via Orus 2/B, 35129 Padova, Italy
- Department of Neuroscience, Section of Neurology, University of Padova, Via Belzoni, 160, 35121 Padova, Italy
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Neurosurgical Institute, Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, ON K1Z 7K4, Canada
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou 310013, China
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310013, China
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9
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Northoff G, Klar P, Bein M, Safron A. As without, so within: how the brain's temporo-spatial alignment to the environment shapes consciousness. Interface Focus 2023; 13:20220076. [PMID: 37065263 PMCID: PMC10102730 DOI: 10.1098/rsfs.2022.0076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/02/2023] [Indexed: 04/18/2023] Open
Abstract
Consciousness is constituted by a structure that includes contents as foreground and the environment as background. This structural relation between the experiential foreground and background presupposes a relationship between the brain and the environment, often neglected in theories of consciousness. The temporo-spatial theory of consciousness addresses the brain-environment relation by a concept labelled 'temporo-spatial alignment'. Briefly, temporo-spatial alignment refers to the brain's neuronal activity's interaction with and adaption to interoceptive bodily and exteroceptive environmental stimuli, including their symmetry as key for consciousness. Combining theory and empirical data, this article attempts to demonstrate the yet unclear neuro-phenomenal mechanisms of temporo-spatial alignment. First, we suggest three neuronal layers of the brain's temporo-spatial alignment to the environment. These neuronal layers span across a continuum from longer to shorter timescales. (i) The background layer comprises longer and more powerful timescales mediating topographic-dynamic similarities between different subjects' brains. (ii) The intermediate layer includes a mixture of medium-scaled timescales allowing for stochastic matching between environmental inputs and neuronal activity through the brain's intrinsic neuronal timescales and temporal receptive windows. (iii) The foreground layer comprises shorter and less powerful timescales for neuronal entrainment of stimuli temporal onset through neuronal phase shifting and resetting. Second, we elaborate on how the three neuronal layers of temporo-spatial alignment correspond to their respective phenomenal layers of consciousness. (i) The inter-subjectively shared contextual background of consciousness. (ii) An intermediate layer that mediates the relationship between different contents of consciousness. (iii) A foreground layer that includes specific fast-changing contents of consciousness. Overall, temporo-spatial alignment may provide a mechanism whose different neuronal layers modulate corresponding phenomenal layers of consciousness. Temporo-spatial alignment can provide a bridging principle for linking physical-energetic (free energy), dynamic (symmetry), neuronal (three layers of distinct time-space scales) and phenomenal (form featured by background-intermediate-foreground) mechanisms of consciousness.
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Affiliation(s)
- Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, TheRoyal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada K1Z 7K4
- Mental Health Centre, Zhejiang University School of Medicine, Hangzhou 310053, People's Republic of China
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310053, People's Republic of China
| | - Philipp Klar
- Medical Faculty, C. & O. Vogt-Institute for Brain Research, Heinrich Heine University of Düsseldorf, 40225 Düsseldorf, Germany
| | - Magnus Bein
- Department of Biology and Department of Psychiatry, McGill University, Quebec, Canada H3A 0G4
| | - Adam Safron
- Center for Psychedelic and Consciousness Research, Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA
- Institute for Advanced Consciousness Studies, Santa Monica, CA 90403, USA
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10
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Yurchenko SB. A systematic approach to brain dynamics: cognitive evolution theory of consciousness. Cogn Neurodyn 2023; 17:575-603. [PMID: 37265655 PMCID: PMC10229528 DOI: 10.1007/s11571-022-09863-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/29/2022] [Accepted: 07/21/2022] [Indexed: 12/18/2022] Open
Abstract
The brain integrates volition, cognition, and consciousness seamlessly over three hierarchical (scale-dependent) levels of neural activity for their emergence: a causal or 'hard' level, a computational (unconscious) or 'soft' level, and a phenomenal (conscious) or 'psyche' level respectively. The cognitive evolution theory (CET) is based on three general prerequisites: physicalism, dynamism, and emergentism, which entail five consequences about the nature of consciousness: discreteness, passivity, uniqueness, integrity, and graduation. CET starts from the assumption that brains should have primarily evolved as volitional subsystems of organisms, not as prediction machines. This emphasizes the dynamical nature of consciousness in terms of critical dynamics to account for metastability, avalanches, and self-organized criticality of brain processes, then coupling it with volition and cognition in a framework unified over the levels. Consciousness emerges near critical points, and unfolds as a discrete stream of momentary states, each volitionally driven from oldest subcortical arousal systems. The stream is the brain's way of making a difference via predictive (Bayesian) processing. Its objective observables could be complexity measures reflecting levels of consciousness and its dynamical coherency to reveal how much knowledge (information gain) the brain acquires over the stream. CET also proposes a quantitative classification of both disorders of consciousness and mental disorders within that unified framework.
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11
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Klar P, Çatal Y, Langner R, Huang Z, Northoff G. Scale-free dynamics in the core-periphery topography and task alignment decline from conscious to unconscious states. Commun Biol 2023; 6:499. [PMID: 37161021 PMCID: PMC10170069 DOI: 10.1038/s42003-023-04879-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 04/26/2023] [Indexed: 05/11/2023] Open
Abstract
Scale-free physiological processes are ubiquitous in the human organism. Resting-state functional MRI studies observed the loss of scale-free dynamics under anesthesia. In contrast, the modulation of scale-free dynamics during task-related activity remains an open question. We investigate scale-free dynamics in the cerebral cortex's unimodal periphery and transmodal core topography in rest and task states during three conscious levels (awake, sedation, and anesthesia) complemented by computational modelling (Stuart-Landau model). The empirical findings demonstrate that the loss of the brain's intrinsic scale-free dynamics in the core-periphery topography during anesthesia, where pink noise transforms into white noise, disrupts the brain's neuronal alignment with the task's temporal structure. The computational model shows that the stimuli's scale-free dynamics, namely pink noise distinguishes from brown and white noise, also modulate task-related activity. Together, we provide evidence for two mechanisms of consciousness, temporo-spatial nestedness and alignment, suggested by the Temporo-Spatial Theory of Consciousness (TTC).
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Affiliation(s)
- Philipp Klar
- Medical Faculty, C. & O. Vogt-Institute for Brain Research, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany.
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, ON, K1Z 7K4, Canada
| | - Robert Langner
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Zirui Huang
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, ON, K1Z 7K4, Canada
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Tianmu Road 305, Hangzhou, Zhejiang Province, 310013, China
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12
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Zhang J, Liu DQ, Qian S, Qu X, Zhang P, Ding N, Zang YF. The neural correlates of amplitude of low-frequency fluctuation: a multimodal resting-state MEG and fMRI-EEG study. Cereb Cortex 2023; 33:1119-1129. [PMID: 35332917 DOI: 10.1093/cercor/bhac124] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 02/28/2022] [Accepted: 03/01/2022] [Indexed: 11/13/2022] Open
Abstract
The amplitude of low-frequency fluctuation (ALFF) describes the regional intensity of spontaneous blood-oxygen-level-dependent signal in resting-state functional magnetic resonance imaging (fMRI). How the fMRI-ALFF relates to the amplitude in electrophysiological signals remains unclear. We here aimed to investigate the neural correlates of fMRI-ALFF by comparing the spatial difference of amplitude between the eyes-closed (EC) and eyes-open (EO) states from fMRI and magnetoencephalography (MEG), respectively. By synthesizing MEG signal into amplitude-based envelope time course, we first investigated 2 types of amplitude in MEG, meaning the amplitude of neural activities from delta to gamma (i.e. MEG-amplitude) and the amplitude of their low-frequency modulation at the fMRI range (i.e. MEG-ALFF). We observed that the MEG-ALFF in EC was increased at parietal sensors, ranging from alpha to beta; whereas the MEG-amplitude in EC was increased at the occipital sensors in alpha. Source-level analysis revealed that the increased MEG-ALFF in the sensorimotor cortex overlapped with the most reliable EC-EO differences observed in fMRI at slow-3 (0.073-0.198 Hz), and these differences were more significant after global mean standardization. Taken together, our results support that (i) the amplitude at 2 timescales in MEG reflect distinct physiological information and that (ii) the fMRI-ALFF may relate to the ALFF in neural activity.
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Affiliation(s)
- Jianfeng Zhang
- Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, Guangdong Province 518055, China.,College of Psychology, Shenzhen University, Shenzhen 518055, China
| | - Dong-Qiang Liu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China
| | - Shufang Qian
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China
| | - Xiujuan Qu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China
| | - Peiwen Zhang
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China
| | - Nai Ding
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China.,Zhejiang Lab, Hangzhou 311121, China
| | - Yu-Feng Zang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, China.,TMS center, Deqing Hospital of Hangzhou Normal University, Deqing, Zhejiang 313200, China.,Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou 311121, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou 311121, China
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13
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Poorganji M, Zomorrodi R, Zrenner C, Bansal A, Hawco C, Hill AT, Hadas I, Rajji TK, Chen R, Zrenner B, Voineskos D, Blumberger DM, Daskalakis ZJ. Pre-Stimulus Power but Not Phase Predicts Prefrontal Cortical Excitability in TMS-EEG. BIOSENSORS 2023; 13:220. [PMID: 36831986 PMCID: PMC9953459 DOI: 10.3390/bios13020220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/10/2023] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
The cortical response to transcranial magnetic stimulation (TMS) has notable inter-trial variability. One source of this variability can be the influence of the phase and power of pre-stimulus neuronal oscillations on single-trial TMS responses. Here, we investigate the effect of brain oscillatory activity on TMS response in 49 distinct healthy participants (64 datasets) who had received single-pulse TMS over the left dorsolateral prefrontal cortex. Across all frequency bands of theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz), there was no significant effect of pre-TMS phase on single-trial cortical evoked activity. After high-powered oscillations, whether followed by a TMS pulse or not, the subsequent activity was larger than after low-powered oscillations. We further defined a measure, corrected_effect, to enable us to investigate brain responses to the TMS pulse disentangled from the power of ongoing (spontaneous) oscillations. The corrected_effect was significantly different from zero (meaningful added effect of TMS) only in theta and beta bands. Our results suggest that brain state prior to stimulation might play some role in shaping the subsequent TMS-EEG response. Specifically, our findings indicate that the power of ongoing oscillatory activity, but not phase, can influence brain responses to TMS. Aligning the TMS pulse with specific power thresholds of an EEG signal might therefore reduce variability in neurophysiological measurements and also has the potential to facilitate more robust therapeutic effects of stimulation.
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Affiliation(s)
- Mohsen Poorganji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute for Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Aiyush Bansal
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Colin Hawco
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Aron T. Hill
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC 3125, Australia
| | - Itay Hadas
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093-0603, USA
| | - Tarek K. Rajji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Robert Chen
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Brigitte Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Daphne Voineskos
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Daniel M. Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Zafiris J. Daskalakis
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093-0603, USA
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14
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Klar P, Çatal Y, Langner R, Huang Z, Northoff G. Scale-free dynamics of core-periphery topography. Hum Brain Mapp 2022; 44:1997-2017. [PMID: 36579661 PMCID: PMC9980897 DOI: 10.1002/hbm.26187] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 11/15/2022] [Accepted: 12/11/2022] [Indexed: 12/30/2022] Open
Abstract
The human brain's cerebral cortex exhibits a topographic division into higher-order transmodal core and lower-order unimodal periphery regions. While timescales between the core and periphery region diverge, features of their power spectra, especially scale-free dynamics during resting-state and their mdulation in task states, remain unclear. To answer this question, we investigated the ~1/f-like pink noise manifestation of scale-free dynamics in the core-periphery topography during rest and task states applying infra-slow inter-trial intervals up to 1 min falling inside the BOLD's infra-slow frequency band. The results demonstrate (1) higher resting-state power-law exponent (PLE) in the core compared to the periphery region; (2) significant PLE increases in task across the core and periphery regions; and (3) task-related PLE increases likely followed the task's atypically low event rates, namely the task's periodicity (inter-trial interval = 52-60 s; 0.016-0.019 Hz). A computational model and a replication dataset that used similar infra-slow inter-trial intervals provide further support for our main findings. Altogether, the results show that scale-free dynamics differentiate core and periphery regions in the resting-state and mediate task-related effects.
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Affiliation(s)
- Philipp Klar
- Medical Faculty, C. & O. Vogt‐Institute for Brain ResearchHeinrich Heine University of DüsseldorfDüsseldorfGermany
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of MedicineUniversity of OttawaOttawaOntarioCanada
| | - Robert Langner
- Institute of Systems NeuroscienceHeinrich Heine University DusseldorfDusseldorfGermany,Institute of Neuroscience and MedicineBrain & Behaviour (INM‐7), Research Centre JülichJülichGermany
| | - Zirui Huang
- Department of AnesthesiologyUniversity of Michigan Medical SchoolAnn ArborMichiganUSA,Center for Consciousness ScienceUniversity of Michigan Medical SchoolAnn ArborMichiganUSA
| | - Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of MedicineUniversity of OttawaOttawaOntarioCanada,Centre for Cognition and Brain DisordersHangzhou Normal UniversityHangzhouZhejiangChina
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15
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Coppola P, Allanson J, Naci L, Adapa R, Finoia P, Williams GB, Pickard JD, Owen AM, Menon DK, Stamatakis EA. The complexity of the stream of consciousness. Commun Biol 2022; 5:1173. [PMID: 36329176 PMCID: PMC9633704 DOI: 10.1038/s42003-022-04109-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 10/10/2022] [Indexed: 11/06/2022] Open
Abstract
Typical consciousness can be defined as an individual-specific stream of experiences. Modern consciousness research on dynamic functional connectivity uses clustering techniques to create common bases on which to compare different individuals. We propose an alternative approach by combining modern theories of consciousness and insights arising from phenomenology and dynamical systems theory. This approach enables a representation of an individual's connectivity dynamics in an intrinsically-defined, individual-specific landscape. Given the wealth of evidence relating functional connectivity to experiential states, we assume this landscape is a proxy measure of an individual's stream of consciousness. By investigating the properties of this landscape in individuals in different states of consciousness, we show that consciousness is associated with short term transitions that are less predictable, quicker, but, on average, more constant. We also show that temporally-specific connectivity states are less easily describable by network patterns that are distant in time, suggesting a richer space of possible states. We show that the cortex, cerebellum and subcortex all display consciousness-relevant dynamics and discuss the implication of our results in forming a point of contact between dynamical systems interpretations and phenomenology.
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Affiliation(s)
- Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Cambridge, UK
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| | - Ram Adapa
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - John D Pickard
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Adrian M Owen
- The Brain and Mind Institute, Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario, London, ON, Canada
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
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16
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Signorelli CM, Boils JD, Tagliazucchi E, Jarraya B, Deco G. From Brain-Body Function to Conscious Interactions. Neurosci Biobehav Rev 2022; 141:104833. [PMID: 36037978 DOI: 10.1016/j.neubiorev.2022.104833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/06/2022] [Accepted: 08/18/2022] [Indexed: 11/15/2022]
Abstract
In this review, we discuss empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience. First, we motivate the discussion through evidence regarding the dynamic brain. Second, we review different brain-body couplings associated with conscious experience and its potential role in driving brain dynamics. Third, we introduce the machinery of multilayer networks to account for several types of interactions in brain-body systems. Then, a multilayer structure consists of two main generalizations: a formal semantic to study biological systems, and an integrative account for several signatures and models of consciousness. Finally, under this framework, we define composition of layers to account for entangled features of brain-body systems related to conscious experience. As such, a multilayer mathematical framework is highly integrative and thus may be more complete than other models. In this short review, we discuss a variety of empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience.
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Affiliation(s)
- Camilo Miguel Signorelli
- Department of Computer Science, University of Oxford, Oxford, 7 Parks Rd, OxfordOX1 3QG, United Kingdom; Physiology of Cognition, GIGA-CRC In Vivo Imaging, Allée du 6 Août, 8 (B30), 4000 Sart Tilman, University of Liège, Belgium; Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France; Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain.
| | - Joaquín Díaz Boils
- Universidad Internacional de La Rioja, Avda La Paz, 137, Logroño, La Rioja, Spain
| | - Enzo Tagliazucchi
- Physics Department, University of Buenos Aires, Buenos Aires, Argentina
| | - Bechir Jarraya
- Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France
| | - Gustavo Deco
- Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
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17
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Northoff G, Vatansever D, Scalabrini A, Stamatakis EA. Ongoing Brain Activity and Its Role in Cognition: Dual versus Baseline Models. Neuroscientist 2022:10738584221081752. [PMID: 35611670 DOI: 10.1177/10738584221081752] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
What is the role of the brain's ongoing activity for cognition? The predominant perspectives associate ongoing brain activity with resting state, the default-mode network (DMN), and internally oriented mentation. This triad is often contrasted with task states, non-DMN brain networks, and externally oriented mentation, together comprising a "dual model" of brain and cognition. In opposition to this duality, however, we propose that ongoing brain activity serves as a neuronal baseline; this builds upon Raichle's original search for the default mode of brain function that extended beyond the canonical default-mode brain regions. That entails what we refer to as the "baseline model." Akin to an internal biological clock for the rest of the organism, the ongoing brain activity may serve as an internal point of reference or standard by providing a shared neural code for the brain's rest as well as task states, including their associated cognition. Such shared neural code is manifest in the spatiotemporal organization of the brain's ongoing activity, including its global signal topography and dynamics like intrinsic neural timescales. We conclude that recent empirical evidence supports a baseline model over the dual model; the ongoing activity provides a global shared neural code that allows integrating the brain's rest and task states, its DMN and non-DMN, and internally and externally oriented cognition.
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18
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Wainio-Theberge S, Wolff A, Gomez-Pilar J, Zhang J, Northoff G. Variability and task-responsiveness of electrophysiological dynamics: scale-free stability and oscillatory flexibility. Neuroimage 2022; 256:119245. [PMID: 35477021 DOI: 10.1016/j.neuroimage.2022.119245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 04/17/2022] [Accepted: 04/22/2022] [Indexed: 11/18/2022] Open
Abstract
Cortical oscillations and scale-free neural activity are thought to influence a variety of cognitive functions, but their differential relationships to neural stability and flexibility has never been investigated. Based on the existing literature, we hypothesize that scale-free and oscillatory processes in the brain exhibit different trade-offs between stability and flexibility; specifically, cortical oscillations may reflect variable, task-responsive aspects of brain activity, while scale-free activity is proposed to reflect a more stable and task-unresponsive aspect. We test this hypothesis using data from two large-scale MEG studies (HCP: n = 89; CamCAN: n = 195), operationalizing stability and flexibility by task-responsiveness and spontaneous intra-subject variability in resting state. We demonstrate that the power-law exponent of scale-free activity is a highly stable parameter, which responds little to external cognitive demands and shows minimal spontaneous fluctuations over time. In contrast, oscillatory power, particularly in the alpha range (8-13 Hz), responds strongly to tasks and exhibits comparatively large spontaneous fluctuations over time. In sum, our data support differential roles for oscillatory and scale-free activity in the brain with respect to neural stability and flexibility. This result carries implications for criticality-based theories of scale-free activity, state-trait models of variability, and homeostatic views of the brain with regulated variables vs. effectors.
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Affiliation(s)
- Soren Wainio-Theberge
- Mind, Brain Imaging, and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre, University of Ottawa, 1145 Carling Avenue, Rm. 6435, Ottawa, ON K1Z 7K4, Canada; Integrated Program in Neuroscience, McGill University, Montréal, QC, Canada.
| | - Annemarie Wolff
- Mind, Brain Imaging, and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre, University of Ottawa, 1145 Carling Avenue, Rm. 6435, Ottawa, ON K1Z 7K4, Canada
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, Valladolid 47011, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain
| | - Jianfeng Zhang
- Mental Health Centre/7th Hospital, Zhejiang University School of Medicine, Tianmu Road 305, Hangzhou, Zhejiang 310013, China; College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China
| | - Georg Northoff
- Mind, Brain Imaging, and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre, University of Ottawa, 1145 Carling Avenue, Rm. 6435, Ottawa, ON K1Z 7K4, Canada; Mental Health Centre/7th Hospital, Zhejiang University School of Medicine, Tianmu Road 305, Hangzhou, Zhejiang 310013, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang 311121, China.
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19
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Northoff G, Smith D. The subjectivity of self and its ontology: From the world–brain relation to the point of view in the world. THEORY & PSYCHOLOGY 2022. [DOI: 10.1177/09593543221080120] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The search for the subjective nature of our self is intensely debated in philosophy and neuroscience. However, despite all progress, the subjectivity of self and how it fits into the seemingly objective world remains elusive. Drawing on recent empirical data, we show how the self is shaped by the brain’s scale-free activity, that is, long-range temporal correlation (LRTC) and the world’s ecological context. We assume that the scale-free LRTC of the world–brain relation provides the ontological basis for the point of view as the foundation of subjectivity within the world. We conclude that the temporal, that is, scale-free based point of view through the world–brain relation provides the ontologically necessary a posteriori condition for the subjectivity of self on a deeper neuro-ecological level. This extends phenomenological concepts like subjectivity and world beyond both Heidegger’s fundamental ontology and Sartre’s phenomenological ontology: it complements their subjectivity-based ontologies with a truly world-based ontology.
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Affiliation(s)
- Georg Northoff
- University of Ottawa
- Royal Ottawa Mental Health Centre and University of Ottawa
- Zhejiang University School of Medicine
- Hangzhou Normal University
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20
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Northoff G, Zilio F. Temporo-spatial Theory of Consciousness (TTC) - Bridging the gap of neuronal activity and phenomenal states. Behav Brain Res 2022; 424:113788. [PMID: 35149122 DOI: 10.1016/j.bbr.2022.113788] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 02/04/2022] [Accepted: 02/04/2022] [Indexed: 01/22/2023]
Abstract
Consciousness and its neural mechanisms remain a mystery. Current neuroscientific theories focus predominantly on the external input/stimulus and the associated stimulus-related activity during conscious contents. Despite all progress, we encounter two gaps: (i) a gap between spontaneous and stimulus-related activity; (ii) a gap between neuronal and phenomenal features. A novel, different, and unique approach, Temporo-spatial theory of consciousness (TTC) aims to bridge both gaps. The TTC focuses on the brain's spontaneous activity and how its spatial topography and temporal dynamic shape stimulus-related activity and resurface in the corresponding spatial and temporal features of consciousness, i.e., 'common currency'. The TTC introduces four temporo-spatial mechanisms: expansion, globalization, alignment, and nestedness. These are associated with distinct dimensions of consciousness including phenomenal content, access, form/structure, and level/state, respectively. Following up on the first introduction of the TTC in 2017, we review updates, further develop these temporo-spatial mechanisms, and postulate specific neurophenomenal hypotheses. We conclude that the TTC offers a viable approach for (i) linking spontaneous and stimulus-related activity in conscious states; (ii) determining specific neuronal and neurophenomenal mechanisms for the distinct dimensions of consciousness; (iii) an integrative and unifying framework of different neuroscientific theories of consciousness; and (iv) offers novel empirically grounded conceptual assumptions about the biological and ontological nature of consciousness and its relation to the brain.
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Affiliation(s)
- Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China; Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua, Padua, Italy.
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21
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Ibarra Chaoul A, Siegel M. Cortical correlation structure of aperiodic neuronal population activity. Neuroimage 2021; 245:118672. [PMID: 34715318 PMCID: PMC8752963 DOI: 10.1016/j.neuroimage.2021.118672] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 10/12/2021] [Accepted: 10/20/2021] [Indexed: 11/02/2022] Open
Abstract
Electrophysiological population signals contain oscillatory and non-oscillatory aperiodic (1/frequency-like) components. So far research has largely focused on oscillatory activity, and only recently, interest in aperiodic population activity has gained momentum. Accordingly, while the cortical correlation structure of oscillatory population activity has been characterized, little is known about the correlation of aperiodic neuronal activity. To address this, we investigated aperiodic neuronal population activity in the human brain using resting-state magnetoencephalography (MEG). We combined source-analysis, signal orthogonalization and irregular-resampling auto-spectral analysis (IRASA) to systematically characterize the cortical distribution and correlation of aperiodic neuronal activity. We found that aperiodic population activity is robustly correlated across the cortex and that this correlation is spatially well structured. Furthermore, we found that the cortical correlation structure of aperiodic activity is similar but distinct from the correlation structure of oscillatory neuronal activity. Anterior cortical regions showed the strongest differences between oscillatory and aperiodic correlation patterns. Our results suggest that correlations of aperiodic population activity serve as robust markers of cortical network interactions. Furthermore, our results show that aperiodic and oscillatory signal components provide non-redundant information about large-scale neuronal correlations. This may reflect at least partly distinct neuronal mechanisms underlying and reflected by oscillatory and aperiodic neuronal population activity.
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Affiliation(s)
- Andrea Ibarra Chaoul
- Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen, Otfried-Müller-Str. 25, Tübingen 72076, Germany; Centre for Integrative Neuroscience, University of Tübingen, Otfried-Müller-Str. 25, Tübingen 72076, Germany; MEG Center, University of Tübingen, Otfried-Müller-Str. 47, Tübingen 72076, Germany; IMPRS for Cognitive and Systems Neuroscience, University of Tübingen, Otfried-Müller-Str. 27, Tübingen 72076, Germany.
| | - Markus Siegel
- Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen, Otfried-Müller-Str. 25, Tübingen 72076, Germany; Centre for Integrative Neuroscience, University of Tübingen, Otfried-Müller-Str. 25, Tübingen 72076, Germany; MEG Center, University of Tübingen, Otfried-Müller-Str. 47, Tübingen 72076, Germany.
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22
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Golkowski D, Willnecker R, Rösler J, Ranft A, Schneider G, Jordan D, Ilg R. Dynamic Patterns of Global Brain Communication Differentiate Conscious From Unconscious Patients After Severe Brain Injury. Front Syst Neurosci 2021; 15:625919. [PMID: 34566586 PMCID: PMC8458756 DOI: 10.3389/fnsys.2021.625919] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 08/17/2021] [Indexed: 11/26/2022] Open
Abstract
The neurophysiology of the subjective sensation of being conscious is elusive; therefore, it remains controversial how consciousness can be recognized in patients who are not responsive but seemingly awake. During general anesthesia, a model for the transition between consciousness and unconsciousness, specific covariance matrices between the activity of brain regions that we call patterns of global brain communication reliably disappear when people lose consciousness. This functional magnetic imaging study investigates how patterns of global brain communication relate to consciousness and unconsciousness in a heterogeneous sample during general anesthesia and after brain injury. First, we describe specific patterns of global brain communication during wakefulness that disappear during propofol (n = 11) and sevoflurane (n = 14) general anesthesia. Second, we search for these patterns in a cohort of unresponsive wakeful patients (n = 18) and unmatched healthy controls (n = 20) in order to evaluate their potential use in clinical practice. We found that patterns of global brain communication characterized by high covariance in sensory and motor areas or low overall covariance and their dynamic change were strictly associated with intact consciousness in this cohort. In addition, we show that the occurrence of these two patterns is significantly related to activity within the frontoparietal network of the brain, a network known to play a crucial role in conscious perception. We propose that this approach potentially recognizes consciousness in the clinical routine setting.
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Affiliation(s)
- Daniel Golkowski
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany.,Neurologische Klinik und Poliklinik, University of Heidelberg, Heidelberg, Germany
| | - Rebecca Willnecker
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jennifer Rösler
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany
| | - Gerhard Schneider
- Department of Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany
| | - Denis Jordan
- Department of Anesthesiology and Intensive Care, School of Medicine, Technical University of Munich, Munich, Germany
| | - Rüdiger Ilg
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany.,Asklepios Clinic, Department of Neurology, Bad Tölz, Germany
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23
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Luppi AI, Golkowski D, Ranft A, Ilg R, Jordan D, Menon DK, Stamatakis EA. Brain network integration dynamics are associated with loss and recovery of consciousness induced by sevoflurane. Hum Brain Mapp 2021; 42:2802-2822. [PMID: 33738899 PMCID: PMC8127159 DOI: 10.1002/hbm.25405] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 02/10/2021] [Accepted: 02/27/2021] [Indexed: 12/22/2022] Open
Abstract
The dynamic interplay of integration and segregation in the brain is at the core of leading theoretical accounts of consciousness. The human brain dynamically alternates between a sub-state where integration predominates, and a predominantly segregated sub-state, with different roles in supporting cognition and behaviour. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from healthy volunteers before, during, and after loss of responsiveness induced with different concentrations of the inhalational anaesthetic, sevoflurane. We show that dynamic states characterised by high brain integration are especially vulnerable to general anaesthesia, exhibiting attenuated complexity and diminished small-world character. Crucially, these effects are reversed upon recovery, demonstrating their association with consciousness. Higher doses of sevoflurane (3% vol and burst-suppression) also compromise the temporal balance of integration and segregation in the human brain. Additionally, we demonstrate that reduced anticorrelations between the brain's default mode and executive control networks dynamically reconfigure depending on the brain's state of integration or segregation. Taken together, our results demonstrate that the integrated sub-state of brain connectivity is especially vulnerable to anaesthesia, in terms of both its complexity and information capacity, whose breakdown represents a generalisable biomarker of loss of consciousness and its recovery.
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Affiliation(s)
- Andrea I. Luppi
- Division of AnaesthesiaUniversity of CambridgeCambridgeUK
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Daniel Golkowski
- Department of Neurology, Klinikum rechts der IsarTechnische Universität MünchenMünchenGermany
| | - Andreas Ranft
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum rechts der IsarTechnische Universität MünchenMünchenGermany
| | - Rüdiger Ilg
- Department of Neurology, Klinikum rechts der IsarTechnische Universität MünchenMünchenGermany
- Department of NeurologyAsklepios ClinicBad TölzGermany
| | - Denis Jordan
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum rechts der IsarTechnische Universität MünchenMünchenGermany
| | - David K. Menon
- Division of AnaesthesiaUniversity of CambridgeCambridgeUK
- Wolfon Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - Emmanuel A. Stamatakis
- Division of AnaesthesiaUniversity of CambridgeCambridgeUK
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
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24
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Vijayakrishnan Nair V, Kish BR, Yang HCS, Yu Z, Guo H, Tong Y, Liang Z. Monitoring anesthesia using simultaneous functional Near Infrared Spectroscopy and Electroencephalography. Clin Neurophysiol 2021; 132:1636-1646. [PMID: 34034088 DOI: 10.1016/j.clinph.2021.03.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 03/02/2021] [Accepted: 03/28/2021] [Indexed: 12/28/2022]
Abstract
OBJECTIVE This study aims to understand the neural and hemodynamic responses during general anesthesia in order to develop a comprehensive multimodal anesthesia depth monitor using simultaneous functional Near Infrared Spectroscopy (fNIRS) and Electroencephalogram (EEG). METHODS 37 adults and 17 children were monitored with simultaneous fNIRS and EEG, during the complete general anesthesia process. The coupling of fNIRS signals with neuronal signals (EEG) was calculated. Measures of complexity (sample entropy) and phase difference were also quantified from fNIRS signals to identify unique fNIRS based biomarkers of general anesthesia. RESULTS A significant decrease in the complexity and power of fNIRS signals characterize the anesthesia maintenance phase. Furthermore, responses to anesthesia vary between adults and children in terms of neurovascular coupling and frontal EEG alpha power. CONCLUSIONS This study shows that fNIRS signals could reliably quantify the underlying neuronal activity under general anesthesia and clearly distinguish the different phases throughout the procedure in adults and children (with less accuracy). SIGNIFICANCE A multimodal approach incorporating the specific differences between age groups, provides a reliable measure of anesthesia depth.
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Affiliation(s)
| | - Brianna R Kish
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
| | - Ho-Ching Shawn Yang
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
| | - Zhenyang Yu
- School of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Hang Guo
- Department of Anesthesiology, the Seventh Medical Center to Chinese PLA General Hospital, Beijing 100700, China
| | - Yunjie Tong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States.
| | - Zhenhu Liang
- School of Electrical Engineering, Yanshan University, Qinhuangdao, China
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25
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Pujol J, Blanco-Hinojo L, Gallart L, Moltó L, Martínez-Vilavella G, Vilà E, Pacreu S, Adalid I, Deus J, Pérez-Sola V, Fernández-Candil J. Largest scale dissociation of brain activity at propofol-induced loss of consciousness. Sleep 2021; 44:5894260. [PMID: 32813022 DOI: 10.1093/sleep/zsaa152] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 08/06/2020] [Indexed: 11/14/2022] Open
Abstract
The brain is a functional unit made up of multilevel connected elements showing a pattern of synchronized activity that varies in different states. The wake-sleep cycle is a major variation of brain functional condition that is ultimately regulated by subcortical arousal- and sleep-promoting cell groups. We analyzed the evolution of functional MRI (fMRI) signal in the whole cortex and in a deep region including most sleep- and wake-regulating subcortical nuclei at loss of consciousness induced by the hypnotic agent propofol. Optimal data were obtained in 21 of the 30 healthy participants examined. A dynamic analysis of fMRI time courses on a time-scale of seconds was conducted to characterize consciousness transition, and functional connectivity maps were generated to detail the anatomy of structures showing different dynamics. Inside the magnet, loss of consciousness was marked by the participants ceasing to move their hands. We observed activity synchronization after loss of consciousness within both the cerebral cortex and subcortical structures. However, the evolution of fMRI signal was dissociated, showing a transient reduction of global cortico-subcortical coupling that was restored during the unconscious state. An exception to cortico-subcortical decoupling was a brain network related to self-awareness (i.e. the default mode network) that remained connected to subcortical brain structures. Propofol-induced unconsciousness is thus characterized by an initial, transitory dissociated synchronization at the largest scale of brain activity. Such cortico-subcortical decoupling and subsequent recoupling may allow the brain to detach from waking activity and reorganize into a functionally distinct state.
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Affiliation(s)
- Jesus Pujol
- MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Spain.,Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain
| | - Laura Blanco-Hinojo
- MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Spain.,Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain
| | - Lluís Gallart
- Department of Anesthesiology, Hospital del Mar-IMIM, Barcelona, Spain.,Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Luís Moltó
- Department of Anesthesiology, Hospital del Mar-IMIM, Barcelona, Spain
| | | | - Esther Vilà
- Department of Anesthesiology, Hospital del Mar-IMIM, Barcelona, Spain
| | - Susana Pacreu
- Department of Anesthesiology, Hospital del Mar-IMIM, Barcelona, Spain
| | - Irina Adalid
- Department of Anesthesiology, Hospital del Mar-IMIM, Barcelona, Spain
| | - Joan Deus
- MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Spain.,Department of Psychobiology and Methodology in Health Sciences, Autonomous University of Barcelona, Barcelona, Spain
| | - Víctor Pérez-Sola
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain.,Institute of Neuropsychiatry and Addictions, Hospital del Mar-IMIM and Department of Psychiatry, Autonomous University of Barcelona, Barcelona, Spain
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26
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Kent L, Wittmann M. Special Issue: Consciousness science and its theories Time consciousness: the missing link in theories of consciousness. Neurosci Conscious 2021; 2021:niab011. [PMID: 33868714 PMCID: PMC8042366 DOI: 10.1093/nc/niab011] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 03/08/2021] [Accepted: 03/16/2021] [Indexed: 11/26/2022] Open
Abstract
There are plenty of issues to be solved in order for researchers to agree on a neural model of consciousness. Here we emphasize an often under-represented aspect in the debate: time consciousness. Consciousness and the present moment both extend in time. Experience flows through a succession of moments and progresses from future predictions, to present experiences, to past memories. However, a brief review finds that many dominant theories of consciousness only refer to brief, static, and discrete "functional moments" of time. Very few refer to more extended, dynamic, and continuous time, which is associated with conscious experience (cf. the "experienced moment"). This confusion between short and discrete versus long and continuous is, we argue, one of the core issues in theories of consciousness. Given the lack of work dedicated to time consciousness, its study could test novel predictions of rival theories of consciousness. It may be that different theories of consciousness are compatible/complementary if the different aspects of time are taken into account. Or, if it turns out that no existing theory can fully accommodate time consciousness, then perhaps it has something new to add. Regardless of outcome, the crucial step is to make subjective time a central object of study.
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Affiliation(s)
- Lachlan Kent
- Centre for Youth Mental Health, The University of Melbourne, 35 Poplar Rd, Parkville, Victoria 3052, Australia
- Orygen, 35 Poplar Rd, Parkville, Victoria 3052, Australia
| | - Marc Wittmann
- Institute for Frontier Areas of Psychology and Mental Health, Wilhelmstraße 3a, 79098 Freiburg i.Br., Germany
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27
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Golesorkhi M, Gomez-Pilar J, Tumati S, Fraser M, Northoff G. Temporal hierarchy of intrinsic neural timescales converges with spatial core-periphery organization. Commun Biol 2021; 4:277. [PMID: 33664456 PMCID: PMC7933253 DOI: 10.1038/s42003-021-01785-z] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 02/03/2021] [Indexed: 01/04/2023] Open
Abstract
The human cortex exhibits intrinsic neural timescales that shape a temporal hierarchy. Whether this temporal hierarchy follows the spatial hierarchy of its topography, namely the core-periphery organization, remains an open issue. Using magnetoencephalography data, we investigate intrinsic neural timescales during rest and task states; we measure the autocorrelation window in short (ACW-50) and, introducing a novel variant, long (ACW-0) windows. We demonstrate longer ACW-50 and ACW-0 in networks located at the core compared to those at the periphery with rest and task states showing a high ACW correlation. Calculating rest-task differences, i.e., subtracting the shared core-periphery organization, reveals task-specific ACW changes in distinct networks. Finally, employing kernel density estimation, machine learning, and simulation, we demonstrate that ACW-0 exhibits better prediction in classifying a region's time window as core or periphery. Overall, our findings provide fundamental insight into how the human cortex's temporal hierarchy converges with its spatial core-periphery hierarchy.
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Affiliation(s)
- Mehrshad Golesorkhi
- School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Shankar Tumati
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
- Neuropsychopharmacology research group, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Maia Fraser
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada.
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China.
- Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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28
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Higher-order sensorimotor circuit of the brain's global network supports human consciousness. Neuroimage 2021; 231:117850. [PMID: 33582277 DOI: 10.1016/j.neuroimage.2021.117850] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 12/29/2020] [Accepted: 02/08/2021] [Indexed: 12/17/2022] Open
Abstract
Consciousness is a mental characteristic of the human mind, whose exact neural features remain unclear. We aimed to identify the critical nodes within the brain's global functional network that support consciousness. To that end, we collected a large fMRI resting state dataset with subjects in at least one of the following three consciousness states: preserved (including the healthy awake state, and patients with a brain injury history (BI) that is fully conscious), reduced (including the N1-sleep state, and minimally conscious state), and lost (including the N3-sleep state, anesthesia, and unresponsive wakefulness state). We also included a unique dataset of subjects in rapid eye movement sleep state (REM-sleep) to test for the presence of consciousness with minimum movements and sensory input. To identify critical nodes, i.e., hubs, within the brain's global functional network, we used a graph-theoretical measure of degree centrality conjoined with ROI-based functional connectivity. Using these methods, we identified various higher-order sensory and motor regions including the supplementary motor area, bilateral supramarginal gyrus (part of inferior parietal lobule), supragenual/dorsal anterior cingulate cortex, and left middle temporal gyrus, that could be important hubs whose degree centrality was significantly reduced when consciousness was reduced or absent. Additionally, we identified a sensorimotor circuit, in which the functional connectivity among these regions was significantly correlated with levels of consciousness across the different groups, and remained present in the REM-sleep group. Taken together, we demonstrated that regions forming a higher-order sensorimotor integration circuit are involved in supporting consciousness within the brain's global functional network. That offers novel and more mechanism-guided treatment targets for disorders of consciousness.
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29
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Sugimura K, Iwasa Y, Kobayashi R, Honda T, Hashimoto J, Kashihara S, Zhu J, Yamamoto K, Kawahara T, Anno M, Nakagawa R, Hatano K, Nakao T. Association between long-range temporal correlations in intrinsic EEG activity and subjective sense of identity. Sci Rep 2021; 11:422. [PMID: 33431948 PMCID: PMC7801398 DOI: 10.1038/s41598-020-79444-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 12/09/2020] [Indexed: 01/29/2023] Open
Abstract
The long-range temporal correlation (LRTC) in resting-state intrinsic brain activity is known to be associated with temporal behavioral patterns, including decision making based on internal criteria such as self-knowledge. However, the association between the neuronal LRTC and the subjective sense of identity remains to be explored; in other words, whether our subjective sense of consistent self across time relates to the temporal consistency of neural activity. The present study examined the relationship between the LRTC of resting-state scalp electroencephalography (EEG) and a subjective sense of identity measured by the Erikson Psychosocial Stage Inventory (EPSI). Consistent with our prediction based on previous studies of neuronal-behavioral relationships, the frontocentral alpha LRTC correlated negatively with identity confusion. Moreover, from the descriptive analyses, centroparietal beta LRTC showed negative correlations with identity confusion, and frontal theta LRTC showed positive relationships with identity synthesis. These results suggest that more temporal consistency (reversely, less random noise) in intrinsic brain activity is associated with less confused and better-synthesized identity. Our data provide further evidence that the LRTC of intrinsic brain activity might serve as a noise suppression mechanism at the psychological level.
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Affiliation(s)
- Kazumi Sugimura
- grid.257022.00000 0000 8711 3200Graduate School of Humanities and Social Sciences, Hiroshima University, 1-1-1, Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8524 Japan
| | - Yasuhiro Iwasa
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Ryota Kobayashi
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Tatsuru Honda
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Junya Hashimoto
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Shiho Kashihara
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Jianhong Zhu
- grid.257022.00000 0000 8711 3200Graduate School of Humanities and Social Sciences, Hiroshima University, 1-1-1, Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8524 Japan
| | - Kazuki Yamamoto
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Tsuyoshi Kawahara
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Mayo Anno
- grid.257022.00000 0000 8711 3200Faculty of Education, Hiroshima University, Hiroshima, Japan
| | - Risa Nakagawa
- grid.257022.00000 0000 8711 3200Graduate School of Education, Hiroshima University, Hiroshima, Japan
| | - Kai Hatano
- grid.261455.10000 0001 0676 0594Faculty of Liberal Arts and Science, Osaka Prefecture University, Osaka, Japan
| | - Takashi Nakao
- grid.257022.00000 0000 8711 3200Graduate School of Humanities and Social Sciences, Hiroshima University, 1-1-1, Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8524 Japan
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30
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Zilio F, Gomez-Pilar J, Cao S, Zhang J, Zang D, Qi Z, Tan J, Hiromi T, Wu X, Fogel S, Huang Z, Hohmann MR, Fomina T, Synofzik M, Grosse-Wentrup M, Owen AM, Northoff G. Are intrinsic neural timescales related to sensory processing? Evidence from abnormal behavioral states. Neuroimage 2020; 226:117579. [PMID: 33221441 DOI: 10.1016/j.neuroimage.2020.117579] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 10/15/2020] [Accepted: 11/12/2020] [Indexed: 12/11/2022] Open
Abstract
The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioral states. We address these questions by investigating the brain's intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activity's intrinsic neural timescale is related to the neural capacity that specifically supports sensory rather than motor information processing in the healthy brain.
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Affiliation(s)
- Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy.
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Shumei Cao
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jun Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Di Zang
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Jiaxing Tan
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Tanigawa Hiromi
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Xuehai Wu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Stuart Fogel
- The Brain and Mind Institute, Department of Physiology and Pharmacology and the Department of Psychology, University of Western Ontario, Canada
| | - Zirui Huang
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Matthias R Hohmann
- Department for Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany
| | - Tatiana Fomina
- Department for Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany
| | - Matthis Synofzik
- Department of Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Moritz Grosse-Wentrup
- Research Group Neuroinformatics, Faculty of Computer Science, University of Vienna, Austria
| | - Adrian M Owen
- The Brain and Mind Institute, Department of Physiology and Pharmacology and the Department of Psychology, University of Western Ontario, Canada
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
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31
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Ghinda DC, Yang Y, Wu S, Lu J, Su L, Damiani S, Tumati S, Jansen G, Duffau H, Wu JS, Northoff G. Personalized Multimodal Demarcation of Peritumoral Tissue in Glioma. JCO Precis Oncol 2020; 4:1128-1140. [PMID: 35050774 DOI: 10.1200/po.20.00115] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
PURPOSE Gliomas are life-threatening brain tumors, and the extent of surgical resection is one of the strongest influences on survival rate. However, the proper distinction of infiltrated tissue remains elusive. The aim of this study was to use multimodal analyses to demarcate peritumoral tissue (PT) from tumoral (TT) and healthy tissue (HT). METHODS A total of 40 patients with histologically confirmed glioma were recruited. We analyzed resting-state functional magnetic resonance imaging (rs-fMRI) using the voxel-based mean blood-oxygen-level-dependent (BOLD) signal and the corresponding structural MRI (s-MRI) alongside RNA sequencing, whole-exome sequencing, and histology results of biopsy samples obtained from PT, HT, and TT. RESULTS We demarcated a functionally defined PT area where the mean BOLD signal gradually decreased near the edge of the tumor and extended beyond the TT borders (as defined by s-MRI), which was confirmed on a case-by-case basis. Correspondingly, genetic analyses showed a gene expression pattern and mutational landscape of the PT that were distinct from that seen in HT and TT. The genetic characterization of PT relative to HT and TT converged with the MRI-defined PT zones. This was confirmed in three individual cases after additional histologic analysis. A wider PT was associated with a longer progression-free survival, which suggests PT might act as an intermediate area between TT and HT. CONCLUSION Combined multimodal imaging and genetic analyses can allow for an objective demarcation of the PT in glioma and a robust classification of the degree of infiltration of the PT. These findings could help improve both neurosurgical resection and radio-oncologic therapy.
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Affiliation(s)
- Diana C Ghinda
- Department of Neurosurgery, The Ottawa Hospital, University of Ottawa, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.,Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.,Mind, Brain Imaging, and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada
| | - Yufei Yang
- Genetron Health (Beijing) Co Ltd, Beijing, China
| | - Shuai Wu
- Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Junfeng Lu
- Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lan Su
- Genetron Health (Beijing) Co Ltd, Beijing, China
| | - Stefano Damiani
- Department of Brain and Behavioral Science, University of Pavia, Pavia, Italy
| | - Shankar Tumati
- Mind, Brain Imaging, and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada
| | - Gerard Jansen
- Department of Neuropathology, The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Hugues Duffau
- Department of Neurosurgery, Hôpital Gui de Chauliac, Montpellier University Medical Center, Montpellier, France.,Brain Plasticity, Stem Cells, and Glial Tumors Team, National Institute for Health and Medical Research, Montpellier, France
| | - Jin-Song Wu
- Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Georg Northoff
- Mind, Brain Imaging, and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada
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Northoff G, Lamme V. Neural signs and mechanisms of consciousness: Is there a potential convergence of theories of consciousness in sight? Neurosci Biobehav Rev 2020; 118:568-587. [PMID: 32783969 DOI: 10.1016/j.neubiorev.2020.07.019] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 07/03/2020] [Accepted: 07/16/2020] [Indexed: 11/18/2022]
Abstract
Various theories for the neural basis of consciousness have been proposed, suggesting a diversity of neural signs and mechanisms. We ask to what extent this diversity is real, or whether many theories share the same basic ideas with a potential for convergence towards a more unified theory of the neural basis of consciousness. For that purpose, we review and compare the various neural signs, measures, and mechanisms proposed in the different theories. We demonstrate that different theories focus on neural signs and measures of distinct aspects of neural activity including stimulus-related, prestimulus, and resting state activity as well as on distinct features of consciousness. Therefore, the various mechanisms proposed in the different theories may, in part, complement each other. Together, we provide insight into the shared basis and convergences (and, in part, discrepancies) of the different theories of consciousness. We conclude that the different theories concern distinct aspects of both neural activity and consciousness which, as we suppose, may be integrated and nested within the brain's overall temporo-spatial dynamics.
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Affiliation(s)
- Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada; Centre for Research Ethics & Bioethics, University of Uppsala, Uppsala, Sweden.
| | - Victor Lamme
- Amsterdam Brain and Cognition (ABC), Department of Psychology, University of Amsterdam, the Netherlands
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Northoff G, Wainio-Theberge S, Evers K. Spatiotemporal neuroscience - what is it and why we need it. Phys Life Rev 2020; 33:78-87. [PMID: 32684435 DOI: 10.1016/j.plrev.2020.06.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 06/12/2020] [Indexed: 11/19/2022]
Abstract
The excellent commentaries to our target paper hint upon three main issues, (i) spatiotemporal neuroscience; (ii) neuro-mental relationship; and (iii) mind, brain, and world relationship. (i) We therefore discuss briefly the history of Spatiotemporal Neuroscience. Distinguishing it from Cognitive Neuroscience and related branches (like Affective, Social, etc. Neuroscience), Spatiotemporal Neuroscience can be characterized by focus on brain activity (rather than brain function), spatiotemporal relationship (rather than input-cognition-output relationship), and structure (rather than stimuli/contents). (ii) Taken in this sense, Spatiotemporal Neuroscience allows one to conceive the neuro-mental relationship in dynamic spatiotemporal terms that complement and extend (rather than contradict) their cognitive characterization. (iii) Finally, more philosophical issues like the need to dissolve the mind-body problem (and replace it by the world-brain relation) and the question for different levels of time including their nestedness are discussed.
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Affiliation(s)
- Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada; Centre for Research Ethics & Bioethics, University of Uppsala, Uppsala, Sweden. http://www.georgnorthoff.com
| | - Soren Wainio-Theberge
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
| | - Kathinka Evers
- Centre for Research Ethics & Bioethics, University of Uppsala, Uppsala, Sweden
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Zhang J, Huang Z, Tumati S, Northoff G. Rest-task modulation of fMRI-derived global signal topography is mediated by transient coactivation patterns. PLoS Biol 2020; 18:e3000733. [PMID: 32649707 PMCID: PMC7375654 DOI: 10.1371/journal.pbio.3000733] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 07/22/2020] [Accepted: 06/23/2020] [Indexed: 12/26/2022] Open
Abstract
Recent resting-state functional MRI (fMRI) studies have revealed that the global signal (GS) exhibits a nonuniform spatial distribution across the gray matter. Whether this topography is informative remains largely unknown. We therefore tested rest-task modulation of GS topography by analyzing static GS correlation and dynamic coactivation patterns in a large sample of an fMRI dataset (n = 837) from the Human Connectome Project. The GS topography in the resting state and in seven different tasks was first measured by correlating the GS with the local time series (GSCORR). In the resting state, high GSCORR was observed mainly in the primary sensory and motor regions, whereas low GSCORR was seen in the association brain areas. This pattern changed during the seven tasks, with mainly decreased GSCORR in sensorimotor cortex. Importantly, this rest-task modulation of GSCORR could be traced to transient coactivation patterns at the peak period of GS (GS-peak). By comparing the topography of GSCORR and respiration effects, we observed that the topography of respiration mimicked the topography of GS in the resting state, whereas both differed during the task states; because of such partial dissociation, we assume that GSCORR could not be equated with a respiration effect. Finally, rest-task modulation of GS topography could not be exclusively explained by other sources of physiological noise. Together, we here demonstrate the informative nature of GS topography by showing its rest-task modulation, the underlying dynamic coactivation patterns, and its partial dissociation from respiration effects during task states. Recent resting-state fMRI studies have shown that the global signal exhibits a nonuniform spatial distribution across gray matter, but is this informative? This neuroimaging study reveals novel insights into the informative nature of global signal by rest-task modulation of the global signal topography.
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Affiliation(s)
- Jianfeng Zhang
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, China
- College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China
| | - Zirui Huang
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Shankar Tumati
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
| | - Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, China
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
- Graduate Institute of Humanities in Medicine, Taipei Medical University, Taipei, Taiwan
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Propofol Anesthesia Alters Spatial and Topologic Organization of Rat Brain Metabolism. Anesthesiology 2020; 131:850-865. [PMID: 31343459 DOI: 10.1097/aln.0000000000002876] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Loss of consciousness during anesthesia reduces local and global rate of cerebral glucose metabolism. Despite this, the influence of gradual anesthetic-induced changes on consciousness across the entire brain metabolic network has barely been studied. The purpose of the present study was to identify specific cerebral metabolic patterns characteristic of different consciousness/anesthesia states induced by intravenous anesthetic propofol. METHODS At various times, 20 Sprague-Dawley adult rats were intravenously administered three different dosages of propofol to induce different anesthetic states: mild sedation (20 mg · kg · h), deep sedation (40 mg · kg · h), and deep anesthesia (80 mg · kg · h). Using [F]fluorodeoxyglucose positron emission tomography brain imaging, alterations in the spatial pattern of metabolic distribution and metabolic topography were investigated by applying voxel-based spatial covariance analysis and graph-theory analysis. RESULTS Evident reductions were found in baseline metabolism along with altered metabolic spatial distribution during propofol-induced anesthesia. Moreover, graph-theory analysis revealed a disruption in global and local efficiency of the metabolic brain network characterized by decreases in metabolic connectivity and energy efficiency during propofol-induced deep anesthesia (mild sedation global efficiency/local efficiency = 0.6985/0.7190, deep sedation global efficiency/local efficiency = 0.7444/0.7875, deep anesthesia global efficiency/local efficiency = 0.4498/0.6481; mild sedation vs. deep sedation, global efficiency: P = 0.356, local efficiency: P = 0.079; mild sedation vs. deep anesthesia, global efficiency: P < 0.0001, local efficiency: P < 0.0001; deep sedation vs. deep anesthesia, global efficiency: P < 0.0001, local efficiency: P < 0.0001). A strong spatial correlation was also found between cerebral metabolism and metabolic connectivity strength, which decreased significantly with deepening anesthesia level (correlation coefficients: mild sedation, r = 0.55, deep sedation, r = 0.47; deep anesthesia, r = 0.23; P < 0.0001 between the sedation and deep anesthesia groups). CONCLUSIONS The data revealed anesthesia-related alterations in spatial and topologic organization of metabolic brain network, as well as a close relationship between metabolic connectivity and cerebral metabolism during propofol anesthesia. These findings may provide novel insights into the metabolic mechanism of anesthetic-induced loss of consciousness.
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Nakao T, Miyagi M, Hiramoto R, Wolff A, Gomez-Pilar J, Miyatani M, Northoff G. From neuronal to psychological noise – Long-range temporal correlations in EEG intrinsic activity reduce noise in internally-guided decision making. Neuroimage 2019; 201:116015. [DOI: 10.1016/j.neuroimage.2019.116015] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 06/24/2019] [Accepted: 07/11/2019] [Indexed: 12/18/2022] Open
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37
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Prefrontal neural dynamics in consciousness. Neuropsychologia 2019; 131:25-41. [DOI: 10.1016/j.neuropsychologia.2019.05.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 05/17/2019] [Accepted: 05/20/2019] [Indexed: 12/11/2022]
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38
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"Average is good, extremes are bad" - Non-linear inverted U-shaped relationship between neural mechanisms and functionality of mental features. Neurosci Biobehav Rev 2019; 104:11-25. [PMID: 31251964 DOI: 10.1016/j.neubiorev.2019.06.030] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/18/2019] [Accepted: 06/20/2019] [Indexed: 01/22/2023]
Abstract
Traditionally, studies emphasize differences in neural measures between pathological and healthy groups, assuming a binary distinction between the groups, and a linear relationship between neural measures and symptoms. Here, we present four examples that show a continuous relation across the divide of normal and pathological states between neural measures and mental functions. This relation can be characterized by a non-linear inverted-U shaped curve. Along this curve, mid-range or average expression of a neural measure is associated with optimal function of a mental feature (in healthy states), whereas extreme expression, either high or low, is associated with sub-optimal function, and occurs in different neural disorders. Neural expression between the optimal or intermediate and pathological or extreme values is associated with sub-optimal function and at-risk mental states. Thus, this model of neuro-mental relationship can be summarized as "average is good, extremes are bad". By focussing on neuro-mental relationships, this model can facilitate the transition of psychiatry from a categorical to a dimensional and individualized approach needed in the era of precision medicine.
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Yin D, Zhang Z, Wang Z, Zeljic K, Lv Q, Cai D, Wang Y, Wang Z. Brain Map of Intrinsic Functional Flexibility in Anesthetized Monkeys and Awake Humans. Front Neurosci 2019; 13:174. [PMID: 30873000 PMCID: PMC6403192 DOI: 10.3389/fnins.2019.00174] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Accepted: 02/14/2019] [Indexed: 01/15/2023] Open
Abstract
Emerging neuroimaging studies emphasize the dynamic organization of spontaneous brain activity in both human and non-human primates, even under anesthesia. In a recent study, we were able to characterize the heterogeneous architecture of intrinsic functional flexibility in the awake, resting human brain using time-resolved analysis and a probabilistic model. However, it is unknown whether this organizational principle is preserved in the anesthetized monkey brain, and how anesthesia affects dynamic and static measurements of spontaneous brain activity. To investigate these issues, we collected resting-state functional magnetic resonance imaging (fMRI) datasets from 178 awake humans and 11 anesthetized monkeys (all healthy). Our recently established method, a complexity measurement (i.e., Shannon entropy) of dynamic functional connectivity patterns of each brain region, was used to map the intrinsic functional flexibility across the cerebral cortex. To further explore the potential effects of anesthesia, we performed time series analysis and correlation analysis between dynamic and static measurements within awake human and anesthetized monkey brains, respectively. We observed a heterogeneous profile of intrinsic functional flexibility in the anesthetized monkey brain, which showed some similarities to that of awake humans (r = 0.30, p = 0.007). However, we found that brain activity in anesthetized monkeys generally shifted toward random fluctuations. Moreover, there is a negative correlation between nodal entropy for the distribution of dynamic functional connectivity patterns and static functional connectivity strength in anesthetized monkeys, but not in awake humans. Our findings indicate that the heterogeneous architecture of intrinsic functional flexibility across cortex probably reflects an evolutionarily conserved aspect of functional brain organization, which persists across levels of cognitive processing (states of consciousness). The coupling between nodal entropy for the distribution of dynamic functional connectivity patterns and static functional connectivity strength may serve as a potential signature of anesthesia. This study not only offers fresh insight into the evolution of brain functional architecture, but also advances our understanding of the dynamics of spontaneous brain activity.
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Affiliation(s)
- Dazhi Yin
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zhao Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhiwei Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kristina Zeljic
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Qian Lv
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Danchao Cai
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yingwei Wang
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zheng Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
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40
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Deco G, Cruzat J, Kringelbach ML. Brain songs framework used for discovering the relevant timescale of the human brain. Nat Commun 2019; 10:583. [PMID: 30718478 PMCID: PMC6361902 DOI: 10.1038/s41467-018-08186-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 12/12/2018] [Indexed: 01/18/2023] Open
Abstract
A key unresolved problem in neuroscience is to determine the relevant timescale for understanding spatiotemporal dynamics across the whole brain. While resting state fMRI reveals networks at an ultraslow timescale (below 0.1 Hz), other neuroimaging modalities such as MEG and EEG suggest that much faster timescales may be equally or more relevant for discovering spatiotemporal structure. Here, we introduce a novel way to generate whole-brain neural dynamical activity at the millisecond scale from fMRI signals. This method allows us to study the different timescales through binning the output of the model. These timescales can then be investigated using a method (poetically named brain songs) to extract the spacetime motifs at a given timescale. Using independent measures of entropy and hierarchy to characterize the richness of the dynamical repertoire, we show that both methods find a similar optimum at a timescale of around 200 ms in resting state and in task data.
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Affiliation(s)
- Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018, Spain.
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, 08010, Spain.
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany.
- School of Psychological Sciences, Monash University, Melbourne, Clayton, VIC, 3800, Australia.
| | - Josephine Cruzat
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018, Spain
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK.
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, DK-8000, Denmark.
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41
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Damiani S, Scalabrini A, Gomez-Pilar J, Brondino N, Northoff G. Increased scale-free dynamics in salience network in adult high-functioning autism. Neuroimage Clin 2018; 21:101634. [PMID: 30558869 PMCID: PMC6411906 DOI: 10.1016/j.nicl.2018.101634] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 11/13/2018] [Accepted: 12/08/2018] [Indexed: 02/04/2023]
Abstract
Autism spectrum disorder (ASD) is clinically characterized by extremely slow and inflexible behavior. The neuronal mechanisms of these symptoms remain unclear though. Using fMRI, we investigate the resting state's temporal structure in the frequency domain (scale-free activity as measured with Power-Law Exponent, PLE, and Spectral Entropy, SE) and temporal variance (neural variability) in high-functioning, adult ASD comparing them with schizophrenic and neurotypical subjects. We show that ASD is characterized by high PLE in salience network, especially in dorsal anterior cingulate. This increase in PLE was 1) specific for salience network; 2) independent of other measures such as neuronal variability/SD and functional connectivity, which did not show any significant difference; 3) detected in two independent samples of ASD but not in the schizophrenia sample. Among salience network subregions, dorsal anterior cingulate cortex exhibited PLE differences between ASD and neurotypicals in both samples, showing high robustness in ROC curves values. Salience network abnormal temporal structure was confirmed by SE, which was strongly anticorrelated with PLE and thus decreased in ASD. Taken together, our findings show abnormal temporal structure (but normal temporal variance) in resting state salience network in adult high-functioning ASD. The abnormally high PLE indicates a relative predominance of slower over faster frequencies, which may underlie the slow adaptation to unexpected changes and the inflexible behavior observed in autistic individuals. The specificity of abnormal PLE in salience network suggests its potential utility as biomarker in ASD.
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Affiliation(s)
- Stefano Damiani
- Department of Brain and Behavioral Science, University of Pavia, 27100 Pavia, Italy.
| | - Andrea Scalabrini
- Department of Psychological, Health and Territorial Sciences (DiSPuTer), G. d'Annunzio University of Chieti-Pescara, 66013 Chieti, Italy
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, 47011 Valladolid, Spain
| | - Natascia Brondino
- Department of Brain and Behavioral Science, University of Pavia, 27100 Pavia, Italy
| | - Georg Northoff
- Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, China; Institute of Mental Health Research, University of Ottawa, K1Z 7K4 Ottawa, ON, Canada; Brain and Mind Research Institute, University of Ottawa, K1H 8M5 Ottawa, ON, Canada; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
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42
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Huang Z, Zhang J, Wu J, Liu X, Xu J, Zhang J, Qin P, Dai R, Yang Z, Mao Y, Hudetz AG, Northoff G. Disrupted neural variability during propofol-induced sedation and unconsciousness. Hum Brain Mapp 2018; 39:4533-4544. [PMID: 29974570 PMCID: PMC6223306 DOI: 10.1002/hbm.24304] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 06/04/2018] [Accepted: 06/24/2018] [Indexed: 12/16/2022] Open
Abstract
Variability quenching is a widespread neural phenomenon in which trial-to-trial variability (TTV) of neural activity is reduced by repeated presentations of a sensory stimulus. However, its neural mechanism and functional significance remain poorly understood. Recurrent network dynamics are suggested as a candidate mechanism of TTV, and they play a key role in consciousness. We thus asked whether the variability-quenching phenomenon is related to the level of consciousness. We hypothesized that TTV reduction would be compromised during reduced level of consciousness by propofol anesthetics. We recorded functional magnetic resonance imaging signals of resting-state and stimulus-induced activities in three conditions: wakefulness, sedation, and unconsciousness (i.e., deep anesthesia). We measured the average (trial-to-trial mean, TTM) and variability (TTV) of auditory stimulus-induced activity under the three conditions. We also examined another form of neural variability (temporal variability, TV), which quantifies the overall dynamic range of ongoing neural activity across time, during both the resting-state and the task. We found that (a) TTM deceased gradually from wakefulness through sedation to anesthesia, (b) stimulus-induced TTV reduction normally seen during wakefulness was abolished during both sedation and anesthesia, and (c) TV increased in the task state as compared to resting-state during both wakefulness and sedation, but not anesthesia. Together, our results reveal distinct effects of propofol on the two forms of neural variability (TTV and TV). They imply that the anesthetic disrupts recurrent network dynamics, thus prevents the stabilization of cortical activity states. These findings shed new light on the temporal dynamics of neuronal variability and its alteration during anesthetic-induced unconsciousness.
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Affiliation(s)
- Zirui Huang
- Department of Anesthesiology and Center for Consciousness ScienceUniversity of MichiganAnn ArborMichigan
| | - Jun Zhang
- Department of AnesthesiologyHuashan Hospital, Fudan UniversityShanghaiPeople's Republic of China
| | - Jinsong Wu
- Neurological Surgery DepartmentHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiPeople's Republic of China
| | - Xiaoge Liu
- Department of AnesthesiologyHuashan Hospital, Fudan UniversityShanghaiPeople's Republic of China
| | - Jianghui Xu
- Department of AnesthesiologyHuashan Hospital, Fudan UniversityShanghaiPeople's Republic of China
| | - Jianfeng Zhang
- College of Biomedical Engineering and Instrument ScienceZhejiang UniversityHangzhouPeople's Republic of China
| | - Pengmin Qin
- School of PsychologySouth China Normal UniversityGuangzhouPeople's Republic of China
| | - Rui Dai
- State Key Laboratory of Brain and Cognitive ScienceInstitute of Biophysics, Chinese Academy of SciencesBeijingPeople's Republic of China
| | - Zhong Yang
- Department of RadiologyHuashan Hospital, Fudan UniversityShanghaiPeople's Republic of China
| | - Ying Mao
- Neurological Surgery DepartmentHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiPeople's Republic of China
| | - Anthony G. Hudetz
- Department of Anesthesiology and Center for Consciousness ScienceUniversity of MichiganAnn ArborMichigan
| | - Georg Northoff
- Institute of Mental Health ResearchUniversity of OttawaOttawaOntarioCanada
- Center for Cognition and Brain DisordersHangzhou Normal UniversityHangzhouPeople's Republic of China
- Mental Health CentreZhejiang University School of MedicineHangzhouPeople's Republic of China
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Liang Z, Li J, Xia X, Wang Y, Li X, He J, Bai Y. Long-Range Temporal Correlations of Patients in Minimally Conscious State Modulated by Spinal Cord Stimulation. Front Physiol 2018; 9:1511. [PMID: 30420813 PMCID: PMC6215825 DOI: 10.3389/fphys.2018.01511] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 10/08/2018] [Indexed: 01/08/2023] Open
Abstract
Spinal cord stimulation (SCS) has been shown to improve the consciousness levels of patients with disorder of consciousness (DOC). However, the underlying mechanisms of SCS remain poorly understood. This study recorded resting-state electroencephalograms (EEG) from 16 patients with minimally conscious state (MCS), before and after SCS, and investigated the mechanisms of SCS on the neuronal dynamics in MCS patients. Detrended fluctuation analysis (DFA), combined with surrogate data method, was employed to measure the long-range temporal correlations (LRTCs) of the EEG signals. A surrogate data method was utilized to acquire the genuine DFA exponents (GDFAE) reflecting the genuine LRTCs of brain activity. We analyzed the GDFAE in four brain regions (frontal, central, posterior, and occipital) at five EEG frequency bands [delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-45 Hz)]. The GDFAE values ranged from 0.5 to 1, and showed temporal and spatial variation between the pre-SCS and the post-SCS states. We found that the channels with GDFAE spread wider after SCS. This phenomenon may indicate that more cortical areas were engaged in the information integration after SCS. In addition, the GDFAE values increased significantly in the frontal area at delta, theta, and alpha bands after SCS. At the theta band, a significant increase in GDFAE was observed in the occipital area. No significant change was found at beta or gamma bands in any brain region. These findings show that the enhanced LRTCs after SCS occurred primarily at low-frequency bands in the frontal and occipital regions. As the LRTCs reflect the long-range temporal integration of EEG signals, our results indicate that information integration became more "complex" after SCS. We concluded that the brain activities at low-frequency oscillations, particularly in the frontal and occipital regions, were improved by SCS.
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Affiliation(s)
- Zhenhu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Jiani Li
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Xiaoyu Xia
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Yong Wang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jianghong He
- Department of Neurosurgery, PLA Army General Hospital, Beijing, China
| | - Yang Bai
- Department of Basic Medical Science, School of Medicine, Hangzhou Normal University, Hangzhou, China
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Lee H, Huang Z, Liu X, Lee U, Hudetz AG. Topographic Reconfiguration of Local and Shared Information in Anesthetic-Induced Unconsciousness. ENTROPY 2018; 20. [PMID: 30792571 PMCID: PMC6380508 DOI: 10.3390/e20070518] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Theoretical consideration predicts that the alteration of local and shared information in the brain is a key element in the mechanism of anesthetic-induced unconsciousness. Ordinal pattern analysis, such as permutation entropy (PE) and symbolic mutual information (SMI), have been successful in quantifying local and shared information in neurophysiological data; however, they have been rarely applied to altered states of consciousness, especially to data obtained with functional magnetic resonance imaging (fMRI). PE and SMI analysis, together with the superb spatial resolution of fMRI recording, enables us to explore the local information of specific brain areas, the shared information between the areas, and the relationship between the two. Given the spatially divergent action of anesthetics on regional brain activity, we hypothesized that anesthesia would differentially influence entropy (PE) and shared information (SMI) across various brain areas, which may represent fundamental, mechanistic indicators of loss of consciousness. FMRI data were collected from 15 healthy participants during four states: wakefulness (W), light (conscious) sedation (L), deep (unconscious) sedation (D), and recovery (R). Sedation was produced by the common, clinically used anesthetic, propofol. Firstly, we found that that global PE decreased from W to D, and increased from D to R. The PE was differentially affected across the brain areas; specifically, the PE in the subcortical network was reduced more than in the cortical networks. Secondly, SMI was also differentially affected in different areas, as revealed by the reconfiguration of its spatial pattern (topographic structure). The topographic structures of SMI in the conscious states W, L, and R were distinctively different from that of the unconscious state D. Thirdly, PE and SMI were positively correlated in W, L, and R, whereas this correlation was disrupted in D. And lastly, PE changes occurred preferentially in highly connected hub regions. These findings advance our understanding of brain dynamics and information exchange, emphasizing the importance of topographic structure and the relationship of local and shared information in anesthetic-induced unconsciousness.
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Affiliation(s)
- Heonsoo Lee
- Department of Anesthesiology, Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA; (Z.H.); (U.L.)
| | - Zirui Huang
- Department of Anesthesiology, Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA; (Z.H.); (U.L.)
| | - Xiaolin Liu
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA;
| | - UnCheol Lee
- Department of Anesthesiology, Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA; (Z.H.); (U.L.)
| | - Anthony G Hudetz
- Department of Anesthesiology, Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA; (Z.H.); (U.L.)
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Zhang J, Huang Z, Chen Y, Zhang J, Ghinda D, Nikolova Y, Wu J, Xu J, Bai W, Mao Y, Yang Z, Duncan N, Qin P, Wang H, Chen B, Weng X, Northoff G. Breakdown in the temporal and spatial organization of spontaneous brain activity during general anesthesia. Hum Brain Mapp 2018; 39:2035-2046. [PMID: 29377435 DOI: 10.1002/hbm.23984] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 12/23/2017] [Accepted: 01/16/2018] [Indexed: 01/02/2023] Open
Abstract
Which temporal features that can characterize different brain states (i.e., consciousness or unconsciousness) is a fundamental question in the neuroscience of consciousness. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated the spatial patterns of two temporal features: the long-range temporal correlations (LRTCs), measured by power-law exponent (PLE), and temporal variability, measured by standard deviation (SD) during wakefulness and anesthetic-induced unconsciousness. We found that both PLE and SD showed global reductions across the whole brain during anesthetic state comparing to wakefulness. Importantly, the relationship between PLE and SD was altered in anesthetic state, in terms of a spatial "decoupling." This decoupling was mainly driven by a spatial pattern alteration of the PLE, rather than the SD, in the anesthetic state. Our results suggest differential physiological grounds of PLE and SD and highlight the functional importance of the topographical organization of LRTCs in maintaining an optimal spatiotemporal configuration of the neural dynamics during normal level of consciousness. The central role of the spatial distribution of LRTCs, reflecting temporo-spatial nestedness, may support the recently introduced temporo-spatial theory of consciousness (TTC).
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Affiliation(s)
- Jianfeng Zhang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.,Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.,Zhejiang University School of Medicine, Mental Health Center, Hangzhou, Zhejiang Province, China.,College of Biomedical Engineering and Instrument Sciences, Zhejiang University, China
| | - Zirui Huang
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48105
| | - Yali Chen
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Jun Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Diana Ghinda
- Department of Neurosurgery, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Yuliya Nikolova
- Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, M5T 1R8, Canada
| | - Jinsong Wu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Jianghui Xu
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Wenjie Bai
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Zhong Yang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Niall Duncan
- Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, K1Z 7K4, Canada
| | - Pengmin Qin
- School of Psychology, South China Normal University, Guangzhou, China
| | - Hao Wang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.,Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China
| | - Bing Chen
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.,Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China
| | - Xuchu Weng
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.,Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China
| | - Georg Northoff
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.,Zhejiang University School of Medicine, Mental Health Center, Hangzhou, Zhejiang Province, China.,Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, K1Z 7K4, Canada.,Taipei Medical University, Graduate Institute of Humanities in Medicine, Taipei, Taiwan
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