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Lau ZJ, Pham T, Chen SHA, Makowski D. Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations. Eur J Neurosci 2022; 56:5047-5069. [PMID: 35985344 PMCID: PMC9826422 DOI: 10.1111/ejn.15800] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 07/20/2022] [Accepted: 08/10/2022] [Indexed: 01/11/2023]
Abstract
There has been an increasing trend towards the use of complexity analysis in quantifying neural activity measured by electroencephalography (EEG) signals. On top of revealing complex neuronal processes of the brain that may not be possible with linear approaches, EEG complexity measures have also demonstrated their potential as biomarkers of psychopathology such as depression and schizophrenia. Unfortunately, the opacity of algorithms and descriptions originating from mathematical concepts have made it difficult to understand what complexity is and how to draw consistent conclusions when applied within psychology and neuropsychiatry research. In this review, we provide an overview and entry-level explanation of existing EEG complexity measures, which can be broadly categorized as measures of predictability and regularity. We then synthesize complexity findings across different areas of psychological science, namely, in consciousness research, mood and anxiety disorders, schizophrenia, neurodevelopmental and neurodegenerative disorders, as well as changes across the lifespan, while addressing some theoretical and methodological issues underlying the discrepancies in the data. Finally, we present important considerations when choosing and interpreting these metrics.
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Affiliation(s)
- Zen J. Lau
- School of Social SciencesNanyang Technological UniversitySingapore
| | - Tam Pham
- School of Social SciencesNanyang Technological UniversitySingapore
| | - S. H. Annabel Chen
- School of Social SciencesNanyang Technological UniversitySingapore,Centre for Research and Development in LearningNanyang Technological UniversitySingapore,Lee Kong Chian School of MedicineNanyang Technological UniversitySingapore,National Institute of EducationNanyang Technological UniversitySingapore
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Martial C, Mensen A, Charland-Verville V, Vanhaudenhuyse A, Rentmeister D, Bahri MA, Cassol H, Englebert J, Gosseries O, Laureys S, Faymonville ME. Neurophenomenology of near-death experience memory in hypnotic recall: a within-subject EEG study. Sci Rep 2019; 9:14047. [PMID: 31575924 PMCID: PMC6773844 DOI: 10.1038/s41598-019-50601-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 09/12/2019] [Indexed: 12/30/2022] Open
Abstract
The neurobiological basis of near-death experiences (NDEs) is unknown, but a few studies attempted to investigate it by reproducing in laboratory settings phenomenological experiences that seem to closely resemble NDEs. So far, no study has induced NDE-like features via hypnotic modulation while simultaneously measuring changes in brain activity using high-density EEG. Five volunteers who previously had experienced a pleasant NDE were invited to re-experience the NDE memory and another pleasant autobiographical memory (dating to the same time period), in normal consciousness and with hypnosis. We compared the hypnosis-induced subjective experience with the one of the genuine experience memory. Continuous high-density EEG was recorded throughout. At a phenomenological level, we succeeded in recreating NDE-like features without any adverse effects. Absorption and dissociation levels were reported as higher during all hypnosis conditions as compared to normal consciousness conditions, suggesting that our hypnosis-based protocol increased the felt subjective experience in the recall of both memories. The recall of a NDE phenomenology was related to an increase of alpha activity in frontal and posterior regions. This study provides a proof-of-concept methodology for studying the phenomenon, enabling to prospectively explore the NDE-like features and associated EEG changes in controlled settings.
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Affiliation(s)
- Charlotte Martial
- GIGA-Consciousness, University of Liège, Liège, Belgium. .,Centre du Cerveau², University Hospital of Liège, Liège, Belgium.
| | - Armand Mensen
- GIGA-Consciousness, University of Liège, Liège, Belgium
| | - Vanessa Charland-Verville
- GIGA-Consciousness, University of Liège, Liège, Belgium.,Centre du Cerveau², University Hospital of Liège, Liège, Belgium
| | - Audrey Vanhaudenhuyse
- GIGA-Sensation & Perception Research Group, University of Liège, Liège, Belgium.,Department of Algology, University Hospital of Liège, Liège, Belgium
| | | | - Mohamed Ali Bahri
- GIGA-Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Héléna Cassol
- GIGA-Consciousness, University of Liège, Liège, Belgium.,Centre du Cerveau², University Hospital of Liège, Liège, Belgium
| | | | - Olivia Gosseries
- GIGA-Consciousness, University of Liège, Liège, Belgium.,Centre du Cerveau², University Hospital of Liège, Liège, Belgium
| | - Steven Laureys
- GIGA-Consciousness, University of Liège, Liège, Belgium.,Centre du Cerveau², University Hospital of Liège, Liège, Belgium
| | - Marie-Elisabeth Faymonville
- GIGA-Sensation & Perception Research Group, University of Liège, Liège, Belgium.,Department of Algology, University Hospital of Liège, Liège, Belgium
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Soffer‐Dudek N, Todder D, Shelef L, Deutsch I, Gordon S. A neural correlate for common trait dissociation: Decreased EEG connectivity is related to dissociative absorption. J Pers 2018; 87:295-309. [DOI: 10.1111/jopy.12391] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 02/05/2018] [Accepted: 03/26/2018] [Indexed: 12/21/2022]
Affiliation(s)
| | - Doron Todder
- Mental Health Center, Ministry of HealthBeer‐Sheva Israel
- Zlotowski Center for NeuroscienceBen‐Gurion University of the Negev
| | - Leah Shelef
- Israel Defense Force Medical CorpsTel Hashomer Ramat‐Gan Israel
| | - Inbal Deutsch
- Israel Defense Force Medical CorpsTel Hashomer Ramat‐Gan Israel
| | - Shirley Gordon
- Department of PsychologyBen‐Gurion University of the Negev
- Israel Defense Force Medical CorpsTel Hashomer Ramat‐Gan Israel
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Soffer-Dudek N. Dissociative absorption, mind-wandering, and attention-deficit symptoms: Associations with obsessive-compulsive symptoms. BRITISH JOURNAL OF CLINICAL PSYCHOLOGY 2018; 58:51-69. [DOI: 10.1111/bjc.12186] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Indexed: 11/26/2022]
Affiliation(s)
- Nirit Soffer-Dudek
- Consciousness and Psychopathology Laboratory; Department of Psychology; Ben-Gurion University of the Negev; Beer-Sheva Israel
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Aydin S, Arica N, Ergul E, Tan O. Classification of Obsessive Compulsive Disorder by EEG Complexity and Hemispheric Dependency Measurements. Int J Neural Syst 2015; 25:1550010. [DOI: 10.1142/s0129065715500100] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
In the present study, both single channel electroencephalography (EEG) complexity and two channel interhemispheric dependency measurements have newly been examined for classification of patients with obsessive–compulsive disorder (OCD) and controls by using support vector machine classifiers. Three embedding entropy measurements (approximate entropy, sample entropy, permutation entropy (PermEn)) are used to estimate single channel EEG complexity for 19-channel eyes closed cortical measurements. Mean coherence and mutual information are examined to measure the level of interhemispheric dependency in frequency and statistical domain, respectively for eight distinct electrode pairs placed on the scalp with respect to the international 10–20 electrode placement system. All methods are applied to short EEG segments of 2 s. The classification performance is measured 20 times with different 2-fold cross-validation data for both single channel complexity features (19 features) and interhemispheric dependency features (eight features). The highest classification accuracy of 85 ±5.2% is provided by PermEn at prefrontal regions of the brain. Even if the classification success do not provided by other methods as high as PermEn, the clear differences between patients and controls at prefrontal regions can also be obtained by using other methods except coherence. In conclusion, OCD, defined as illness of orbitofronto-striatal structures [Beucke et al., JAMA Psychiatry 70 (2013) 619–629; Cavedini et al., Psychiatry Res. 78 (1998) 21–28; Menzies et al., Neurosci. Biobehav. Rev. 32(3) (2008) 525–549], is caused by functional abnormalities in the pre-frontal regions. Particularly, patients are characterized by lower EEG complexity at both pre-frontal regions and right fronto-temporal locations. Our results are compatible with imaging studies that define OCD as a sub group of anxiety disorders exhibited a decreased complexity (such as anorexia nervosa [Toth et al., Int. J. Psychophysiol. 51(3) (2004) 253–260] and panic disorder [Bob et al., Physiol. Res. 55 (2006) S113–S119]).
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Affiliation(s)
- Serap Aydin
- Biomedical Engineering Department, Bahçeşehir University, Beşiktaş Istanbul 34353, Turkey
| | - Nafiz Arica
- Software Engineering Department, Bahçeşehir University, Beşiktaş Istanbul 34353, Turkey
| | - Emrah Ergul
- Electronics and Communications Engineering Department, Kocaeli University, Kocaeli, Turkey
| | - Oğuz Tan
- Uskudar University, Neuropsychiatry Health, Practice and Research Center Istanbul, Turkey
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Reinsberger C, Sarkis R, Papadelis C, Doshi C, Perez DL, Baslet G, Loddenkemper T, Dworetzky BA. Autonomic changes in psychogenic nonepileptic seizures: toward a potential diagnostic biomarker? Clin EEG Neurosci 2015; 46:16-25. [PMID: 25780264 DOI: 10.1177/1550059414567739] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Disturbances of the autonomic nervous system (ANS) are common in neuropsychiatric disorders. Disease specific alterations of both sympathetic and parasympathetic activity can be assessed by heart rate variability (HRV), whereas electrodermal activity (EDA) can assess sympathetic activity. In posttraumatic stress disorder (PTSD), parasympathetic HRV parameters are typically decreased and EDA is increased, whereas in major depressive disorder (MDD) and dissociation, both parasympathetic and sympathetic markers are decreased. ANS abnormalities have also been identified in psychogenic nonepileptic seizures (PNES) by using HRV, indicating lower parasympathetic activity at baseline. In addition to reviewing the current literature on ANS abnormalities in PTSD, MDD, and disorders with prominent dissociation, including borderline personality disorder (BPD), this article also presents data from a pilot study on EDA in patients with PNES. Eleven patients with PNES, during an admission to our epilepsy monitoring unit (EMU), were compared with 9 with generalized tonic-clonic seizures (GTCS). The area under the EDA curve, the number of EDA responses lasting longer than 2 seconds, and the number of EDA surges during sleep (sympathetic sleep storms) were calculated on ictal and interictal days by an automated algorithm. EDA changes in PNES patients did not follow a systematic pattern of sympathetic hyperarousal (like EDA after GTCS) but were more variable. How specific PNES semiologies, and/or underlying neuropsychiatric disorders, may influence ictal and interictal EDA patterns, and lead to a novel diagnostic biomarker remains to be evaluated in future larger studies.
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Affiliation(s)
- Claus Reinsberger
- Edward B. Bromfield Epilepsy Center, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Institute of Sports Medicine, University of Paderborn, Paderborn, Germany
| | - Rani Sarkis
- Edward B. Bromfield Epilepsy Center, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Chiran Doshi
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - David L Perez
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Gaston Baslet
- Edward B. Bromfield Epilepsy Center, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Barbara A Dworetzky
- Edward B. Bromfield Epilepsy Center, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Farina B, Speranza AM, Dittoni S, Gnoni V, Trentini C, Vergano CM, Liotti G, Brunetti R, Testani E, Della Marca G. Memories of attachment hamper EEG cortical connectivity in dissociative patients. Eur Arch Psychiatry Clin Neurosci 2014; 264:449-58. [PMID: 24121863 DOI: 10.1007/s00406-013-0461-9] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2013] [Accepted: 09/30/2013] [Indexed: 11/24/2022]
Abstract
In this study, we evaluated cortical connectivity modifications by electroencephalography (EEG) lagged coherence analysis, in subjects with dissociative disorders and in controls, after retrieval of attachment memories. We asked thirteen patients with dissociative disorders and thirteen age- and sex-matched healthy controls to retrieve personal attachment-related autobiographical memories through adult attachment interviews (AAI). EEG was recorded in the closed eyes resting state before and after the AAI. EEG lagged coherence before and after AAI was compared in all subjects. In the control group, memories of attachment promoted a widespread increase in EEG connectivity, in particular in the high-frequency EEG bands. Compared to controls, dissociative patients did not show an increase in EEG connectivity after the AAI. Conclusions: These results shed light on the neurophysiology of the disintegrative effect of retrieval of traumatic attachment memories in dissociative patients.
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Takahashi T. Complexity of spontaneous brain activity in mental disorders. Prog Neuropsychopharmacol Biol Psychiatry 2013; 45:258-66. [PMID: 22579532 DOI: 10.1016/j.pnpbp.2012.05.001] [Citation(s) in RCA: 97] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2012] [Revised: 04/05/2012] [Accepted: 05/01/2012] [Indexed: 11/17/2022]
Abstract
Recent reports of functional and anatomical studies have provided evidence that aberrant neural connectivity lies at the heart of many mental disorders. Information related to neural networks has elucidated the nonlinear dynamical complexity in brain signals over a range of temporal scales. The recent advent of nonlinear analytic methods, which have served for the quantitative description of the brain signal complexity, has provided new insights into aberrant neural connectivity in many mental disorders. Although many studies have underpinned aberrant neural connectivity, findings related to complexity behavior are still inconsistent. This inconsistency might result from (i) heterogeneity in mental disorders, (ii) analytical issues, (iii) interference of typical development and aging. First, most mental disorders are heterogeneous in their clinical feature or intrinsic pathological mechanisms. Second, neurophysiologic output signals from complex brain connectivity might be characterized with multiple time scales or frequencies. Finally, age-related brain complexity changes must be considered when investigating pathological brain because typical brain complexity is not constant across generations. Future systematic studies addressing these issues will greatly expand our knowledge of neural connections and dynamics related to mental disorders.
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Affiliation(s)
- Tetsuya Takahashi
- Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji-cho, Yoshida-gun, Fukui 910-1193, Japan.
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