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Zhao Z, Feng Y, Wang M, Wei J, Tan T, Li R, Hu H, Wang M, Chen P, Gao X, Wei Y, Wang C, Gao Z, Jiang W, Zhou X, Li M, Wang C, Pang T, Yu Y. Investigating cortical complexity and connectivity in rats with schizophrenia. Front Neuroinform 2024; 18:1392271. [PMID: 39211912 PMCID: PMC11358091 DOI: 10.3389/fninf.2024.1392271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 07/29/2024] [Indexed: 09/04/2024] Open
Abstract
Background The above studies indicate that the SCZ animal model has abnormal gamma oscillations and abnormal functional coupling ability of brain regions at the cortical level. However, few researchers have focused on the correlation between brain complexity and connectivity at the cortical level. In order to provide a more accurate representation of brain activity, we studied the complexity of electrocorticogram (ECoG) signals and the information interaction between brain regions in schizophrenic rats, and explored the correlation between brain complexity and connectivity. Methods We collected ECoG signal from SCZ rats. The frequency domain and time domain functional connectivity of SCZ rats were evaluated by magnitude square coherence and mutual information (MI). Permutation entropy (PE) and permutation Lempel-Ziv complexity (PLZC) were used to analyze the complexity of ECoG, and the relationship between them was evaluated. In addition, in order to further understand the causal structure of directional information flow among brain regions, we used phase transfer entropy (PTE) to analyze the effective connectivity of the brain. Results Firstly, in the high gamma band, the complexity of brain regions in SCZ rats is higher than that in normal rats, and the neuronal activity is irregularity. Secondly, the information integration ability of SCZ rats decreased and the communication of brain network information was hindered at the cortical level. Finally, compared with normal rats, the causal relationship between brain regions of SCZ rats was closer, but the information interaction center was not clear. Conclusion The above findings suggest that at the cortical level, complexity and connectivity are valid biomarkers for identifying SCZ. This bridges the gap between peak potentials and EEG. This may help to understand the pathophysiological mechanisms at the cortical level in schizophrenics.
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Affiliation(s)
- Zongya Zhao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Yifan Feng
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Menghan Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Jiarong Wei
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Tao Tan
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Ruijiao Li
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Heshun Hu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Mengke Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Peiqi Chen
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Xudong Gao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Yinping Wei
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Chang Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Zhixian Gao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Wenshuai Jiang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Xuezhi Zhou
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Mingcai Li
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Chong Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Ting Pang
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Center of Image and Signal Processing, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Yi Yu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
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Herzog R, Barbey FM, Islam MN, Rueda-Delgado L, Nolan H, Prado P, Krylova M, Izyurov I, Javaheripour N, Danyeli LV, Sen ZD, Walter M, O'Donnell P, Buhl DL, Murphy B, Ibanez A. High-order brain interactions in ketamine during rest and task: a double-blinded cross-over design using portable EEG on male participants. Transl Psychiatry 2024; 14:310. [PMID: 39068157 PMCID: PMC11283531 DOI: 10.1038/s41398-024-03029-0] [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: 02/13/2024] [Revised: 07/12/2024] [Accepted: 07/17/2024] [Indexed: 07/30/2024] Open
Abstract
Ketamine is a dissociative anesthetic that induces a shift in global consciousness states and related brain dynamics. Portable low-density EEG systems could be used to monitor these effects. However, previous evidence is almost null and lacks adequate methods to address global dynamics with a small number of electrodes. This study delves into brain high-order interactions (HOI) to explore the effects of ketamine using portable EEG. In a double-blinded cross-over design, 30 male adults (mean age = 25.57, SD = 3.74) were administered racemic ketamine and compared against saline infusion as a control. Both task-driven (auditory oddball paradigm) and resting-state EEG were recorded. HOI were computed using advanced multivariate information theory tools, allowing us to quantify nonlinear statistical dependencies between all possible electrode combinations. Ketamine induced an increase in redundancy in brain dynamics (copies of the same information that can be retrieved from 3 or more electrodes), most significantly in the alpha frequency band. Redundancy was more evident during resting state, associated with a shift in conscious states towards more dissociative tendencies. Furthermore, in the task-driven context (auditory oddball), the impact of ketamine on redundancy was more significant for predictable (standard stimuli) compared to deviant ones. Finally, associations were observed between ketamine's HOI and experiences of derealization. Ketamine appears to increase redundancy and HOI across psychometric measures, suggesting these effects are correlated with alterations in consciousness towards dissociation. In comparisons with event-related potential (ERP) or standard functional connectivity metrics, HOI represent an innovative method to combine all signal spatial interactions obtained from low-density dry EEG in drug interventions, as it is the only approach that exploits all possible combinations between electrodes. This research emphasizes the potential of complexity measures coupled with portable EEG devices in monitoring shifts in consciousness, especially when paired with low-density configurations, paving the way for better understanding and monitoring of pharmacological-induced changes.
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Affiliation(s)
- Rubén Herzog
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile.
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, Paris, France.
| | | | | | | | - Hugh Nolan
- Cumulus Neuroscience Ltd, Dublin, Ireland
| | - Pavel Prado
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Marina Krylova
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Igor Izyurov
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Nooshin Javaheripour
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Lena Vera Danyeli
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Zümrüt Duygu Sen
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Jena, Germany
| | - Patricio O'Donnell
- Neuroscience Drug Discovery Unit, Takeda Pharmaceuticals, Cambridge, MA, 02390, USA
| | - Derek L Buhl
- Neuroscience Drug Discovery Unit, Takeda Pharmaceuticals, Cambridge, MA, 02390, USA
| | | | - Agustin Ibanez
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile.
- Global Brain Health Institute, UCSF and Trinity College Dublin, Dublin, Ireland.
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Ibanez A, Herzog R, Barbey F, Islam MN, Rueda-Delgado L, Nolan H, Prado P, Krylova M, Javaheripour N, Danyeli L, Sen Z, Walter M, Odonnell P, Buhl D, Murphy B, Izyurov I. High-order brain interactions in ketamine during rest and task: A double-blinded cross-over design using portable EEG. RESEARCH SQUARE 2024:rs.3.rs-3954073. [PMID: 38562802 PMCID: PMC10984031 DOI: 10.21203/rs.3.rs-3954073/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
In a double-blinded cross-over design, 30 adults (mean age = 25.57, SD = 3.74; all male) were administered racemic ketamine and compared against saline infusion as a control. Both task-driven (auditory oddball paradigm) and resting-state EEG were recorded. HOI were computed using advanced multivariate information theory tools, allowing us to quantify nonlinear statistical dependencies between all possible electrode combinations. Results: Ketamine increased redundancy in brain dynamics, most significantly in the alpha frequency band. Redundancy was more evident during the resting state, associated with a shift in conscious states towards more dissociative tendencies. Furthermore, in the task-driven context (auditory oddball), the impact of ketamine on redundancy was more significant for predictable (standard stimuli) compared to deviant ones. Finally, associations were observed between ketamine's HOI and experiences of derealization. Conclusions: Ketamine appears to increase redundancy and genuine HOI across metrics, suggesting these effects correlate with consciousness alterations towards dissociation. HOI represents an innovative method to combine all signal spatial interactions obtained from low-density dry EEG in drug interventions, as it is the only approach that exploits all possible combinations from different electrodes. This research emphasizes the potential of complexity measures coupled with portable EEG devices in monitoring shifts in consciousness, especially when paired with low-density configurations, paving the way for better understanding and monitoring of pharmacological-induced changes.
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Hipólito I, Mago J, Rosas FE, Carhart-Harris R. Pattern breaking: a complex systems approach to psychedelic medicine. Neurosci Conscious 2023; 2023:niad017. [PMID: 37424966 PMCID: PMC10325487 DOI: 10.1093/nc/niad017] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 05/19/2023] [Accepted: 06/08/2023] [Indexed: 07/11/2023] Open
Abstract
Recent research has demonstrated the potential of psychedelic therapy for mental health care. However, the psychological experience underlying its therapeutic effects remains poorly understood. This paper proposes a framework that suggests psychedelics act as destabilizers, both psychologically and neurophysiologically. Drawing on the 'entropic brain' hypothesis and the 'RElaxed Beliefs Under pSychedelics' model, this paper focuses on the richness of psychological experience. Through a complex systems theory perspective, we suggest that psychedelics destabilize fixed points or attractors, breaking reinforced patterns of thinking and behaving. Our approach explains how psychedelic-induced increases in brain entropy destabilize neurophysiological set points and lead to new conceptualizations of psychedelic psychotherapy. These insights have important implications for risk mitigation and treatment optimization in psychedelic medicine, both during the peak psychedelic experience and during the subacute period of potential recovery.
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Affiliation(s)
- Inês Hipólito
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany
- Department of Philosophy, Macquarie University, New South Wales 2109, Australia
| | - Jonas Mago
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, United Kingdom
- Integrative Program in Neuroscience, McGill University, Montreal, Quebec QC H3A, Canada
| | - Fernando E Rosas
- Department of Brain Sciences, Centre for Psychedelic Research, Imperial College London, London SW7 2BX, United Kingdom
- Centre for Complexity Science, Imperial College London, London SW7 2BX, United Kingdom
- Data Science Institute, Imperial College London, London SW7 2BX, United Kingdom
- Department of Informatics, University of Sussex, Brighton BN1 9RH, United Kingdom
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford OX3 9BX, United Kingdom
| | - Robin Carhart-Harris
- Department of Brain Sciences, Centre for Psychedelic Research, Imperial College London, London SW7 2BX, United Kingdom
- Psychedelics Division, University of California San Francisco, San Francisco, CA 92521, United States
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