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Wolfson EJ, Fekete T, Loewenstein Y, Shriki O. Multi-scale entropy assessment of magnetoencephalography signals in schizophrenia. Sci Rep 2024; 14:14680. [PMID: 38918430 PMCID: PMC11199523 DOI: 10.1038/s41598-024-64704-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 06/12/2024] [Indexed: 06/27/2024] Open
Abstract
Schizophrenia is a severe disruption in cognition and emotion, affecting fundamental human functions. In this study, we applied Multi-Scale Entropy analysis to resting-state Magnetoencephalography data from 54 schizophrenia patients and 98 healthy controls. This method quantifies the temporal complexity of the signal across different time scales using the concept of sample entropy. Results show significantly higher sample entropy in schizophrenia patients, primarily in central, parietal, and occipital lobes, peaking at time scales equivalent to frequencies between 15 and 24 Hz. To disentangle the contributions of the amplitude and phase components, we applied the same analysis to a phase-shuffled surrogate signal. The analysis revealed that most differences originate from the amplitude component in the δ, α, and β power bands. While the phase component had a smaller magnitude, closer examination reveals clear spatial patterns and significant differences across specific brain regions. We assessed the potential of multi-scale entropy as a schizophrenia biomarker by comparing its classification performance to conventional spectral analysis and a cognitive task (the n-back paradigm). The discriminative power of multi-scale entropy and spectral features was similar, with a slight advantage for multi-scale entropy features. The results of the n-back test were slightly below those obtained from multi-scale entropy and spectral features.
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Affiliation(s)
- E J Wolfson
- Department of Cognitive and Brain Sciences, Ben Gurion University of the Negev, 1 Ben-Gurion Blvd., Beer-Sheva, Israel
| | - T Fekete
- Department of Cognitive and Brain Sciences, Ben Gurion University of the Negev, 1 Ben-Gurion Blvd., Beer-Sheva, Israel
| | - Y Loewenstein
- The Edmond & Lily Safra Center for Brain Sciences, Department of Cognitive and Brain Sciences,The Alexander Silberman Institute of Life Sciences and The Federmann Center for the Study of Rationality, The Hebrew University, Jerusalem, Israel
| | - O Shriki
- Department of Cognitive and Brain Sciences, Ben Gurion University of the Negev, 1 Ben-Gurion Blvd., Beer-Sheva, Israel.
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Proshina E, Martynova O, Portnova G, Khayrullina G, Sysoeva O. Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder. Front Neuroinform 2024; 18:1339590. [PMID: 38450096 PMCID: PMC10914983 DOI: 10.3389/fninf.2024.1339590] [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: 11/16/2023] [Accepted: 01/29/2024] [Indexed: 03/08/2024] Open
Abstract
Introduction Mental disorders are a significant concern in contemporary society, with a pressing need to identify biological markers. Long-range temporal correlations (LRTC) of brain rhythms have been widespread in clinical cohort studies, especially in major depressive disorder (MDD). However, research on LRTC in obsessive-compulsive disorder (OCD) is severely limited. Given the high co-occurrence of OCD and MDD, we conducted a comparative LRTC investigation. We assumed that the LRTC patterns will allow us to compare measures of brain cortical balance of excitation and inhibition in OCD and MDD, which will be useful in the area of differential diagnosis. Methods In this study, we used the 64-channel resting state EEG of 29 MDD participants, 26 OCD participants, and a control group of 37 volunteers. Detrended fluctuation analyzes was used to assess LRTC. Results Our results indicate that all scaling exponents of the three subject groups exhibited persistent LRTC of EEG oscillations. There was a tendency for LRTC to be higher in disorders than in controls, but statistically significant differences were found between the OCD and control groups in the entire frontal and left parietal occipital areas, and between the MDD and OCD groups in the middle and right frontal areas. Discussion We believe that these results indicate abnormalities in the inhibitory and excitatory neurotransmitter systems, predominantly affecting areas related to executive functions.
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Affiliation(s)
- Ekaterina Proshina
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Olga Martynova
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russia
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow, Russia
| | - Galina Portnova
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russia
| | - Guzal Khayrullina
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russia
| | - Olga Sysoeva
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russia
- Sirius Center for Cognitive Sciences, Sirius University of Science and Technology, Sochi, Russia
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Wei X, Yan Z, Cai L, Lu M, Yi G, Wang J, Dong Y. Aberrant temporal correlations of ongoing oscillations in disorders of consciousness on multiple time scales. Cogn Neurodyn 2023; 17:633-645. [PMID: 37265651 PMCID: PMC10229524 DOI: 10.1007/s11571-022-09852-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 05/19/2022] [Accepted: 07/06/2022] [Indexed: 11/27/2022] Open
Abstract
Changes in neural oscillation amplitude across states of consciousness has been widely reported, but little is known about the link between temporal dynamics of these oscillations on different time scales and consciousness levels. To address this question, we analyzed amplitude fluctuation of the oscillations extracted from spontaneous resting-state EEG recorded from the patients with disorders of consciousness (DOC) and healthy controls. Detrended fluctuation analysis (DFA) and measures of life-time and waiting-time were employed to characterize the temporal structure of EEG oscillations on long time scales (1-20 s) and short time scales (< 1 s), in groups with different consciousness states: patients in minimally conscious state (MCS), patients with unresponsive wakefulness syndrome (UWS) and healthy subjects. Results revealed increased DFA exponents that implies higher long-range temporal correlations (LRTC), especially in the central brain area in alpha and beta bands. On short time scales, declined bursts of oscillations were also observed. All the metrics exhibited lower individual variability in the UWS or MCS group, which may be attributed to the reduced spatial variability of oscillation dynamics. In addition, the temporal dynamics of EEG oscillations showed significant correlations with the behavioral responsiveness of patients. In summary, our findings shows that loss of consciousness is accompanied by alternation of temporal structure in neural oscillations on multiple time scales, and thus may help uncover the mechanism of underlying neuronal correlates of consciousness. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09852-9.
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Affiliation(s)
- Xile Wei
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Zhuang Yan
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Lihui Cai
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Meili Lu
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin, 300222 China
| | - Guosheng Yi
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Yueqing Dong
- Xincheng Hospital of Tianjin University, Tianjin, China
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4
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Sihn D, Kim JS, Kwon OS, Kim SP. Breakdown of long-range spatial correlations of infraslow amplitude fluctuations of EEG oscillations in patients with current and past major depressive disorder. Front Psychiatry 2023; 14:1132996. [PMID: 37181866 PMCID: PMC10169687 DOI: 10.3389/fpsyt.2023.1132996] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 04/05/2023] [Indexed: 05/16/2023] Open
Abstract
Introduction Identifying biomarkers for depression from brain activity is important for the diagnosis and treatment of depression disorders. We investigated spatial correlations of the amplitude fluctuations of electroencephalography (EEG) oscillations as a potential biomarker of depression. The amplitude fluctuations of EEG oscillations intrinsically reveal both temporal and spatial correlations, indicating rapid and functional organization of the brain networks. Amid these correlations, long-range temporal correlations are reportedly impaired in patients with depression, exhibiting amplitude fluctuations closer to a random process. Based on this occurrence, we hypothesized that the spatial correlations of amplitude fluctuations would also be altered by depression. Methods In the present study, we extracted the amplitude fluctuations of EEG oscillations by filtering them through infraslow frequency band (0.05-0.1 Hz). Results We found that the amplitude fluctuations of theta oscillations during eye-closed rest depicted lower levels of spatial correlation in patients with major depressive disorder (MDD) compared to control individuals. This breakdown of spatial correlations was most prominent in the left fronto - temporal network, specifically in patients with current MDD rather than in those with past MDD. We also found that the amplitude fluctuations of alpha oscillations during eye-open rest exhibited lower levels of spatial correlation in patients with past MDD compared to control individuals or patients with current MDD. Discussion Our results suggest that breakdown of long-range spatial correlations may offer a biomarker for the diagnosis of depression (current MDD), as well as the tracking of the recovery from depression (past MDD).
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Affiliation(s)
- Duho Sihn
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Ji Sun Kim
- Department of Psychiatry, College of Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea
| | - Oh-Sang Kwon
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
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Gordillo D, Ramos da Cruz J, Moreno D, Garobbio S, Herzog MH. Do we really measure what we think we are measuring? iScience 2023; 26:106017. [PMID: 36844457 PMCID: PMC9947309 DOI: 10.1016/j.isci.2023.106017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/18/2022] [Accepted: 01/16/2023] [Indexed: 01/21/2023] Open
Abstract
Tests used in the empirical sciences are often (implicitly) assumed to be representative of a given research question in the sense that similar tests should lead to similar results. Here, we show that this assumption is not always valid. We illustrate our argument with the example of resting-state electroencephalogram (EEG). We used multiple analysis methods, contrary to typical EEG studies where one analysis method is used. We found, first, that many EEG features correlated significantly with cognitive tasks. However, these EEG features correlated weakly with each other. Similarly, in a second analysis, we found that many EEG features were significantly different in older compared to younger participants. When we compared these EEG features pairwise, we did not find strong correlations. In addition, EEG features predicted cognitive tasks poorly as shown by cross-validated regression analysis. We discuss several explanations of these results.
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Affiliation(s)
- Dario Gordillo
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- Corresponding author
| | - Janir Ramos da Cruz
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- Institute for Systems and Robotics – Lisboa (LARSyS), Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal
- Wyss Center for Bio and Neuroengineering, CH-1202 Geneva, Switzerland
| | - Dana Moreno
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Simona Garobbio
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Michael H. Herzog
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
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6
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Perquin MN, van Vugt MK, Hedge C, Bompas A. Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? COMPUTATIONAL BRAIN & BEHAVIOR 2023; 6:1-38. [PMID: 36618326 PMCID: PMC9810256 DOI: 10.1007/s42113-022-00162-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 11/22/2022] [Indexed: 01/05/2023]
Abstract
Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures - to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers. Supplementary Information The online version contains supplementary material available at 10.1007/s42113-022-00162-1.
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Affiliation(s)
- Marlou Nadine Perquin
- Biopsychology & Cognitive Neuroscience, Faculty of Psychology and Sports Science, Bielefeld University, Bielefeld, Germany
- Cognitive Neuroscience, Faculty of Biology, Bielefeld University, Bielefeld, Germany
- CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
| | - Marieke K. van Vugt
- Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, Netherlands
| | - Craig Hedge
- School of Psychology, College of Health & Life Sciences, Aston University, Aston, UK
| | - Aline Bompas
- CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
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Zhang M, Force RB, Walker C, Ahn S, Jarskog LF, Frohlich F. Alpha transcranial alternating current stimulation reduces depressive symptoms in people with schizophrenia and auditory hallucinations: a double-blind, randomized pilot clinical trial. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:114. [PMID: 36566277 PMCID: PMC9789318 DOI: 10.1038/s41537-022-00321-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 11/29/2022] [Indexed: 12/25/2022]
Abstract
People with schizophrenia exhibit reduced alpha oscillations and frontotemporal coordination of brain activity. Alpha oscillations are associated with top-down inhibition. Reduced alpha oscillations may fail to censor spurious endogenous activity, leading to auditory hallucinations. Transcranial alternating current stimulation (tACS) at the alpha frequency was shown to enhance alpha oscillations in people with schizophrenia and may thus be a network-based treatment for auditory hallucinations. We conducted a double-blind, randomized, placebo-controlled pilot clinical trial to examine the efficacy of 10-Hz tACS in treating auditory hallucinations in people with schizophrenia. 10-Hz tACS was administered in phase at the dorsolateral prefrontal cortex and the temporoparietal junction with a return current at Cz. Patients were randomized to receive tACS or sham for five consecutive days during the treatment week (40 min/day), followed by a maintenance period, during which participants received weekly tACS (40 min/visit) or sham. tACS treatment reduced general psychopathology (p < 0.05, Cohen's d = -0.690), especially depression (p < 0.005, Cohen's d = -0.806), but not auditory hallucinations. tACS treatment increased alpha power in the target region (p < 0.05), increased the frequency of peak global functional connectivity towards 10 Hz (p < 0.05), and reduced left-right frontal functional connectivity (p < 0.005). Importantly, changes in brain functional connectivity significantly correlated with symptom improvement (p < 0.05). Daily 10 Hz-tACS increased alpha power and altered alpha-band functional connectivity. Successful target engagement reduced depression and other general psychopathology symptoms, but not auditory hallucinations. Considering existing research of 10Hz tACS as a treatment for major depressive disorder, our study demonstrates its transdiagnostic potential for treating depression.
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Affiliation(s)
- Mengsen Zhang
- grid.410711.20000 0001 1034 1720Department of Psychiatry, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC USA
| | - Rachel B. Force
- grid.410711.20000 0001 1034 1720Department of Psychiatry, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC USA
| | - Christopher Walker
- grid.410711.20000 0001 1034 1720Department of Psychiatry, University of North Carolina, Chapel Hill, NC USA
| | - Sangtae Ahn
- grid.410711.20000 0001 1034 1720Department of Psychiatry, University of North Carolina, Chapel Hill, NC USA ,grid.258803.40000 0001 0661 1556School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea
| | - L. Fredrik Jarskog
- grid.410711.20000 0001 1034 1720Department of Psychiatry, University of North Carolina, Chapel Hill, NC USA
| | - Flavio Frohlich
- grid.410711.20000 0001 1034 1720Department of Psychiatry, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Neuroscience Center, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Department of Neurology, University of North Carolina, Chapel Hill, NC USA
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Stephani T, Nierula B, Villringer A, Eippert F, Nikulin VV. Cortical response variability is driven by local excitability changes with somatotopic organization. Neuroimage 2022; 264:119687. [PMID: 36257491 DOI: 10.1016/j.neuroimage.2022.119687] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 09/23/2022] [Accepted: 10/14/2022] [Indexed: 11/09/2022] Open
Abstract
Identical sensory stimuli can lead to different neural responses depending on the instantaneous brain state. Specifically, neural excitability in sensory areas may shape the brain´s response already from earliest cortical processing onwards. However, whether these dynamics affect a given sensory domain as a whole or occur on a spatially local level is largely unknown. We studied this in the somatosensory domain of 38 human participants with EEG, presenting stimuli to the median and tibial nerves alternatingly, and testing the co-variation of initial cortical responses in hand and foot areas, as well as their relation to pre-stimulus oscillatory states. We found that amplitude fluctuations of initial cortical responses to hand and foot stimulation - the N20 and P40 components of the somatosensory evoked potential (SEP), respectively - were not related, indicating local excitability changes in primary sensory regions. In addition, effects of pre-stimulus alpha (8-13 Hz) and beta (18-23 Hz) band amplitude on hand-related responses showed a robust somatotopic organization, thus further strengthening the notion of local excitability fluctuations. However, for foot-related responses, the spatial specificity of pre-stimulus effects was less consistent across frequency bands, with beta appearing to be more foot-specific than alpha. Connectivity analyses in source space suggested this to be due to a somatosensory alpha rhythm that is primarily driven by activity in hand regions while beta frequencies may operate in a more hand-region-independent manner. Altogether, our findings suggest spatially distinct excitability dynamics within the primary somatosensory cortex, yet with the caveat that frequency-specific processes in one sub-region may not readily generalize to other sub-regions.
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Affiliation(s)
- T Stephani
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany.
| | - B Nierula
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - F Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - V V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Neurophysics Group, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Berlin, Germany.
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9
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From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans. Transl Psychiatry 2022; 12:467. [PMID: 36344497 PMCID: PMC9640647 DOI: 10.1038/s41398-022-02218-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 08/22/2022] [Accepted: 10/06/2022] [Indexed: 11/09/2022] Open
Abstract
Brain function is a product of the balance between excitatory and inhibitory (E/I) brain activity. Variation in the regulation of this activity is thought to give rise to normal variation in human traits, and disruptions are thought to potentially underlie a spectrum of neuropsychiatric conditions (e.g., Autism, Schizophrenia, Downs' Syndrome, intellectual disability). Hypotheses related to E/I dysfunction have the potential to provide cross-diagnostic explanations and to combine genetic and neurological evidence that exists within and between psychiatric conditions. However, the hypothesis has been difficult to test because: (1) it lacks specificity-an E/I dysfunction could pertain to any level in the neural system- neurotransmitters, single neurons/receptors, local networks of neurons, or global brain balance - most researchers do not define the level at which they are examining E/I function; (2) We lack validated methods for assessing E/I function at any of these neural levels in humans. As a result, it has not been possible to reliably or robustly test the E/I hypothesis of psychiatric disorders in a large cohort or longitudinal patient studies. Currently available, in vivo markers of E/I in humans either carry significant risks (e.g., deep brain electrode recordings or using Positron Emission Tomography (PET) with radioactive tracers) and/or are highly restrictive (e.g., limited spatial extent for Transcranial Magnetic Stimulation (TMS) and Magnetic Resonance Spectroscopy (MRS). More recently, a range of novel Electroencephalography (EEG) features has been described, which could serve as proxy markers for E/I at a given level of inference. Thus, in this perspective review, we survey the theories and experimental evidence underlying 6 novel EEG markers and their biological underpinnings at a specific neural level. These cheap-to-record and scalable proxy markers may offer clinical utility for identifying subgroups within and between diagnostic categories, thus directing more tailored sub-grouping and, therefore, treatment strategies. However, we argue that studies in clinical populations are premature. To maximize the potential of prospective EEG markers, we first need to understand the link between underlying E/I mechanisms and measurement techniques.
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10
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O'Byrne J, Jerbi K. How critical is brain criticality? Trends Neurosci 2022; 45:820-837. [PMID: 36096888 DOI: 10.1016/j.tins.2022.08.007] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/27/2022] [Accepted: 08/10/2022] [Indexed: 10/31/2022]
Abstract
Criticality is the singular state of complex systems poised at the brink of a phase transition between order and randomness. Such systems display remarkable information-processing capabilities, evoking the compelling hypothesis that the brain may itself be critical. This foundational idea is now drawing renewed interest thanks to high-density data and converging cross-disciplinary knowledge. Together, these lines of inquiry have shed light on the intimate link between criticality, computation, and cognition. Here, we review these emerging trends in criticality neuroscience, highlighting new data pertaining to the edge of chaos and near-criticality, and making a case for the distance to criticality as a useful metric for probing cognitive states and mental illness. This unfolding progress in the field contributes to establishing criticality theory as a powerful mechanistic framework for studying emergent function and its efficiency in both biological and artificial neural networks.
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Affiliation(s)
- Jordan O'Byrne
- Cognitive and Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, Quebec, Canada
| | - Karim Jerbi
- Cognitive and Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, Quebec, Canada; MILA (Quebec Artificial Intelligence Institute), Montreal, Quebec, Canada; UNIQUE Center (Quebec Neuro-AI Research Center), Montreal, Quebec, Canada.
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11
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Gordillo D, da Cruz JR, Chkonia E, Lin WH, Favrod O, Brand A, Figueiredo P, Roinishvili M, Herzog MH. The EEG multiverse of schizophrenia. Cereb Cortex 2022; 33:3816-3826. [PMID: 36030389 PMCID: PMC10068296 DOI: 10.1093/cercor/bhac309] [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: 03/14/2022] [Revised: 07/15/2022] [Accepted: 07/15/2022] [Indexed: 11/14/2022] Open
Abstract
Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. One tacit assumption of these "deep rooting" approaches is that paradigms tap into common and representative aspects of the disorder. Here, we analyzed the resting-state electroencephalogram (EEG) of 121 schizophrenia patients and 75 controls. Using multiple signal processing methods, we extracted 194 EEG features. Sixty-nine out of the 194 EEG features showed a significant difference between patients and controls, indicating that these features detect an important aspect of schizophrenia. Surprisingly, the correlations between these features were very low. We discuss several explanations to our results and propose that complementing "deep" with "shallow" rooting approaches might help in understanding the underlying mechanisms of the disorder.
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Affiliation(s)
- Dario Gordillo
- Corresponding author: Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.
| | | | - Eka Chkonia
- Department of Psychiatry, Tbilisi State Medical University (TSMU), 0186 Tbilisi, Georgia
- Institute of Cognitive Neurosciences, Free University of Tbilisi, 0159 Tbilisi, Georgia
| | - Wei-Hsiang Lin
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Ophélie Favrod
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Andreas Brand
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Patrícia Figueiredo
- Institute for Systems and Robotics – Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal
| | - Maya Roinishvili
- Institute of Cognitive Neurosciences, Free University of Tbilisi, 0159 Tbilisi, Georgia
- Laboratory of Vision Physiology, Ivane Beritashvili Centre of Experimental Biomedicine, 0160 Tbilisi, Georgia
| | - Michael H Herzog
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
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12
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E DO, V MS, S LV, E SY. Fractal Structure of Brain Electrical Activity of Patients With Mental Disorders. Front Physiol 2022; 13:905318. [PMID: 35923231 PMCID: PMC9340582 DOI: 10.3389/fphys.2022.905318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 06/23/2022] [Indexed: 11/19/2022] Open
Abstract
This work was aimed at a comparative analysis of the degree of multifractality of electroencephalographic time series obtained from a group of healthy subjects and from patients with mental disorders. We analyzed long-term records of patients with paranoid schizophrenia and patients with depression. To evaluate the properties of multifractal scaling of various electroencephalographic time series, the method of maximum modulus of the wavelet transform and multifractal analysis of fluctuations without a trend were used. The stability of the width and position of the singularity spectrum for each of the test groups was revealed, and a relationship was established between the correlation and anticorrelation dynamics of successive values of the electroencephalographic time series and the type of mental disorders. It was shown that the main differences between the multifractal properties of brain activity in normal and pathological conditions lie in the different width of the multifractality spectrum and its location associated with the correlated or anticorrelated dynamics of the values of successive time series. It was found that the schizophrenia group is characterized by a greater degree of multifractality compared to the depression group. Thus, the degree of multifractality can be included in a set of tests for differential diagnosis and research of mental disorders.
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Affiliation(s)
- Dick O. E
- Laboratory of Physiology of Reception, Pavlov Institute of Physiology of Russian Academy of Science, St. Petersburg, Russia
- *Correspondence: Dick O. E,
| | - Murav’eva S. V
- Laboratory of Vision Physiology, Pavlov Institute of Physiology of Russian Academy of Science, St. Petersburg, Russia
| | - Lebedev V. S
- Laboratory of Vision Physiology, Pavlov Institute of Physiology of Russian Academy of Science, St. Petersburg, Russia
| | - Shelepin Yu. E
- Laboratory of Vision Physiology, Pavlov Institute of Physiology of Russian Academy of Science, St. Petersburg, Russia
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13
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Tian Q, Yang NB, Fan Y, Dong F, Bo QJ, Zhou FC, Zhang JC, Li L, Yin GZ, Wang CY, Fan M. Detection of Schizophrenia Cases From Healthy Controls With Combination of Neurocognitive and Electrophysiological Features. Front Psychiatry 2022; 13:810362. [PMID: 35449564 PMCID: PMC9016153 DOI: 10.3389/fpsyt.2022.810362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 02/21/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The search for a method that utilizes biomarkers to identify patients with schizophrenia from healthy individuals has occupied researchers for decades. However, no single indicator can be employed to achieve the good in clinical practice. We aim to develop a comprehensive machine learning pipeline based on neurocognitive and electrophysiological combined features for distinguishing schizophrenia patients from healthy people. METHODS In the present study, 69 patients with schizophrenia and 50 healthy controls participated. Neurocognitive (contains seven specific domains of cognition) and electrophysiological [prepulse inhibition, electroencephalography (EEG) power spectrum, detrended fluctuation analysis, and fractal dimension (FD)] features were collected, all these features were taken together to generate the identification models of schizophrenia by applying logistics, random forest, and extreme gradient boosting algorithm. The classification capabilities of these models were also evaluated. RESULTS Both the neurocognitive and electrophysiological feature sets showed a good classification effect with the highest accuracy greater than 85% and AUC greater than 90%. Specifically, the performances of the combined neurocognitive and electrophysiological feature sets achieved the highest accuracy of 93.28% and AUC of 97.91%. The extreme gradient boosting algorithm as a whole presented more stably and precisely in classification efficiency. CONCLUSION The highest classification accuracy of 93.28% by combination of neurocognitive and electrophysiological features shows that both measurements are appropriate indicators to be used in discriminating schizophrenia patients and healthy individuals. Also, among three algorithms, extreme gradient boosting had better classified performances than logistics and random forest algorithms.
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Affiliation(s)
- Qing Tian
- Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China.,Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, The Institute of Mental Health, Suzhou, China.,Beijing Key Laboratory of Mental Disorders, The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Beijing Institute for Brain Disorders Center of Schizophrenia, Capital Medical University, Beijing, China
| | - Ning-Bo Yang
- Department of Psychiatry, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, China
| | - Yu Fan
- Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, The Institute of Mental Health, Suzhou, China.,Beijing Key Laboratory of Mental Disorders, The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Beijing Institute for Brain Disorders Center of Schizophrenia, Capital Medical University, Beijing, China
| | - Fang Dong
- Beijing Key Laboratory of Mental Disorders, The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Beijing Institute for Brain Disorders Center of Schizophrenia, Capital Medical University, Beijing, China
| | - Qi-Jing Bo
- Beijing Key Laboratory of Mental Disorders, The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Beijing Institute for Brain Disorders Center of Schizophrenia, Capital Medical University, Beijing, China
| | - Fu-Chun Zhou
- Beijing Key Laboratory of Mental Disorders, The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Beijing Institute for Brain Disorders Center of Schizophrenia, Capital Medical University, Beijing, China
| | - Ji-Cong Zhang
- Beijing Advanced Innovation Centre for Biomedical Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, The School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Liang Li
- Department of Psychology, Peking University, Beijing, China
| | - Guang-Zhong Yin
- Suzhou Guangji Hospital, The Affiliated Guangji Hospital of Soochow University, The Institute of Mental Health, Suzhou, China
| | - Chuan-Yue Wang
- Beijing Key Laboratory of Mental Disorders, The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Beijing Institute for Brain Disorders Center of Schizophrenia, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Ming Fan
- Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China.,Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, China
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14
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Huang J, Ahlers E, Bogatsch H, Böhme P, Ethofer T, Fallgatter AJ, Gallinat J, Hegerl U, Heuser I, Hoffmann K, Kittel-Schneider S, Reif A, Schöttle D, Unterecker S, Gärtner M, Strauß M. The role of comorbid depressive symptoms on long-range temporal correlations in resting EEG in adults with ADHD. Eur Arch Psychiatry Clin Neurosci 2022; 272:1421-1435. [PMID: 35781841 PMCID: PMC9653316 DOI: 10.1007/s00406-022-01452-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 06/12/2022] [Indexed: 11/23/2022]
Abstract
Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder, characterized by core symptoms of inattention, hyperactivity and impulsivity. Comorbid depression is commonly observed in ADHD-patients. Psychostimulants are recommended as first-line treatment for ADHD. Aberrant long-range temporal correlations (LRTCs) of neuronal activities in resting-state are known to be associated with disorganized thinking and concentrating difficulties (typical in ADHD) and with maladaptive thinking (typical in depression). It has yet to be examined whether (1) LRTC occur in ADHD-patients, and if so, (2) whether LRTC might be a competent biomarker in ADHD comorbid with current depression and (3) how depression affects psychostimulant therapy of ADHD symptoms. The present study registered and compared LRTCs in different EEG frequency bands in 85 adults with ADHD between groups with (n = 28) and without (n = 57) additional depressive symptoms at baseline. Treatment-related changes in ADHD, depressive symptoms and LRTC were investigated in the whole population and within each group. Our results revealed significant LRTCs existed in all investigated frequency bands. There were, however, no significant LRTC-differences between ADHD-patients with and without depressive symptoms at baseline and no LRTC-changes following treatment. However, depressed ADHD patients did seem to benefit more from the therapy with psychostimulant based on self-report.
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Affiliation(s)
- Jue Huang
- Department of Psychiatry and Psychotherapy, University of Leipzig, 04103, Leipzig, Germany.
| | - Eike Ahlers
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin, 10117 Berlin, Germany
| | - Holger Bogatsch
- grid.9647.c0000 0004 7669 9786Clinical Trial Centre Leipzig, Faculty of Medicine, University of Leipzig, 04107 Leipzig, Germany
| | - Pierre Böhme
- grid.411091.cDepartment of Psychiatry Psychotherapy and Preventive Medicine, University Hospital of Bochum, 44791 Bochum, Germany
| | - Thomas Ethofer
- grid.411544.10000 0001 0196 8249Department of Biomedical Magnetic Resonance, University Hospital of Tübingen, 72076 Tübingen, Germany ,grid.10392.390000 0001 2190 1447Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, 72076 Tübingen, Germany
| | - Andreas J. Fallgatter
- grid.10392.390000 0001 2190 1447Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, 72076 Tübingen, Germany
| | - Jürgen Gallinat
- grid.13648.380000 0001 2180 3484Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Ulrich Hegerl
- grid.411088.40000 0004 0578 8220Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, University Hospital of Frankfurt – Goethe University, 60528 Frankfurt am Main, Germany
| | - Isabella Heuser
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin, 10117 Berlin, Germany
| | - Knut Hoffmann
- grid.411091.cDepartment of Psychiatry Psychotherapy and Preventive Medicine, University Hospital of Bochum, 44791 Bochum, Germany
| | - Sarah Kittel-Schneider
- grid.411088.40000 0004 0578 8220Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, University Hospital of Frankfurt – Goethe University, 60528 Frankfurt am Main, Germany ,grid.411760.50000 0001 1378 7891Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, 97080 Würzburg, Germany
| | - Andreas Reif
- grid.411088.40000 0004 0578 8220Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, University Hospital of Frankfurt – Goethe University, 60528 Frankfurt am Main, Germany
| | - Daniel Schöttle
- grid.13648.380000 0001 2180 3484Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Stefan Unterecker
- grid.411760.50000 0001 1378 7891Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, 97080 Würzburg, Germany
| | - Matti Gärtner
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin, 10117 Berlin, Germany ,grid.466457.20000 0004 1794 7698MSB Medical School Berlin, 14179 Berlin, Germany
| | - Maria Strauß
- grid.9647.c0000 0004 7669 9786Department of Psychiatry and Psychotherapy, University of Leipzig, 04103 Leipzig, Germany
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15
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Alamian G, Lajnef T, Pascarella A, Lina JM, Knight L, Walters J, Singh KD, Jerbi K. Altered Brain Criticality in Schizophrenia: New Insights From Magnetoencephalography. Front Neural Circuits 2022; 16:630621. [PMID: 35418839 PMCID: PMC8995790 DOI: 10.3389/fncir.2022.630621] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 03/03/2022] [Indexed: 12/13/2022] Open
Abstract
Schizophrenia has a complex etiology and symptomatology that is difficult to untangle. After decades of research, important advancements toward a central biomarker are still lacking. One of the missing pieces is a better understanding of how non-linear neural dynamics are altered in this patient population. In this study, the resting-state neuromagnetic signals of schizophrenia patients and healthy controls were analyzed in the framework of criticality. When biological systems like the brain are in a state of criticality, they are thought to be functioning at maximum efficiency (e.g., optimal communication and storage of information) and with maximum adaptability to incoming information. Here, we assessed the self-similarity and multifractality of resting-state brain signals recorded with magnetoencephalography in patients with schizophrenia patients and in matched controls. Schizophrenia patients had similar, although attenuated, patterns of self-similarity and multifractality values. Statistical tests showed that patients had higher values of self-similarity than controls in fronto-temporal regions, indicative of more regularity and memory in the signal. In contrast, patients had less multifractality than controls in the parietal and occipital regions, indicative of less diverse singularities and reduced variability in the signal. In addition, supervised machine-learning, based on logistic regression, successfully discriminated the two groups using measures of self-similarity and multifractality as features. Our results provide new insights into the baseline cognitive functioning of schizophrenia patients by identifying key alterations of criticality properties in their resting-state brain data.
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Affiliation(s)
- Golnoush Alamian
- CoCo Lab, Department of Psychology, Université de Montréal, Montréal, QC, Canada
| | - Tarek Lajnef
- CoCo Lab, Department of Psychology, Université de Montréal, Montréal, QC, Canada
| | - Annalisa Pascarella
- Institute for Applied Mathematics Mauro Picone, National Research Council, Roma, Italy
| | - Jean-Marc Lina
- Department of Electrical Engineering, École de Technologie Supérieure, Montréal, QC, Canada.,Mathematical Research Center, Université de Montréal, Montréal, QC, Canada.,Centre UNIQUE, Union Neurosciences et Intelligence Artificielle - Québec, Montréal, QC, Canada
| | - Laura Knight
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom
| | - James Walters
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom
| | - Krish D Singh
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom
| | - Karim Jerbi
- CoCo Lab, Department of Psychology, Université de Montréal, Montréal, QC, Canada.,Centre UNIQUE, Union Neurosciences et Intelligence Artificielle - Québec, Montréal, QC, Canada.,MEG Center, Université de Montréal, Montréal, QC, Canada
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16
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Hirano Y, Uhlhaas PJ. Current findings and perspectives on aberrant neural oscillations in schizophrenia. Psychiatry Clin Neurosci 2021; 75:358-368. [PMID: 34558155 DOI: 10.1111/pcn.13300] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/20/2021] [Accepted: 09/09/2021] [Indexed: 12/11/2022]
Abstract
There is now consistent evidence that neural oscillation at low- and high-frequencies constitute an important aspect of the pathophysiology of schizophrenia. Specifically, impaired rhythmic activity may underlie the deficit to generate coherent cognition and behavior, leading to the characteristic symptoms of psychosis and cognitive deficits. Importantly, the generating mechanisms of neural oscillations are relatively well-understood and thus enable the targeted search for the underlying circuit impairments and novel treatment targets. In the following review, we will summarize and assess the evidence for aberrant rhythmic activity in schizophrenia through evaluating studies that have utilized Electro/Magnetoencephalography to examine neural oscillations during sensory and cognitive tasks as well as during resting-state measurements. These data will be linked to current evidence from post-mortem, neuroimaging, genetics, and animal models that have implicated deficits in GABAergic interneurons and glutamatergic neurotransmission in oscillatory deficits in schizophrenia. Finally, we will highlight methodological and analytical challenges as well as provide recommendations for future research.
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Affiliation(s)
- Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
| | - Peter J Uhlhaas
- Department of Child and Adolescent Psychiatry, Charité - Universitätsmedizin, Berlin, Germany
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
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17
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Golemme M, Tatti E, Di Bernardi Luft C, Bhattacharya J, Herrojo Ruiz M, Cappelletti M. Multivariate patterns and long-range temporal correlations of alpha oscillations are associated with flexible manipulation of visual working memory representations. Eur J Neurosci 2021; 54:7260-7273. [PMID: 34618375 DOI: 10.1111/ejn.15486] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 11/29/2022]
Abstract
The ability to flexibly manipulate memory representations is embedded in visual working memory (VWM) and can be tested using paradigms with retrospective cues. Although valid retrospective cues often facilitate memory recall, invalid ones may or may not result in performance costs. We investigated individual differences in utilising retrospective cues and evaluated how these individual differences are associated with brain oscillatory activity at rest. At the behavioural level, we operationalised flexibility as the ability to make effective use of retrospective cues or disregard them if required. At the neural level, we tested whether individual differences in such flexibility were associated with properties of resting-state alpha oscillatory activity (8-12 Hz). To capture distinct aspects of these brain oscillations, we evaluated their power spectral density and temporal dynamics using long-range temporal correlations (LRTCs). In addition, we performed multivariate patterns analysis (MVPA) to classify individuals' level of behavioural flexibility based on these neural measures. We observed that alpha power alone (magnitude) at rest was not associated with flexibility. However, we found that the participants' ability to manipulate VWM representations was correlated with alpha LRTC and could be decoded using MVPA on patterns of alpha power. Our findings suggest that alpha LRTC and multivariate patterns of alpha power at rest may underlie some of the individual differences in using retrospective cues in working memory tasks.
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Affiliation(s)
- Mara Golemme
- Department of Psychology, Goldsmiths, University of London, London, UK.,UK Dementia Research Institute, Imperial College London, London, UK
| | - Elisa Tatti
- Department of Psychology, Goldsmiths, University of London, London, UK.,CUNY, School of Medicine, City College Of New York, New York, New York, USA
| | | | | | - Maria Herrojo Ruiz
- Department of Psychology, Goldsmiths, University of London, London, UK.,Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Marinella Cappelletti
- Department of Psychology, Goldsmiths, University of London, London, UK.,Institute of Cognitive Neuroscience, University College London, London, UK
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18
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Smit DJA, Andreassen OA, Boomsma DI, Burwell SJ, Chorlian DB, de Geus EJC, Elvsåshagen T, Gordon RL, Harper J, Hegerl U, Hensch T, Iacono WG, Jawinski P, Jönsson EG, Luykx JJ, Magne CL, Malone SM, Medland SE, Meyers JL, Moberget T, Porjesz B, Sander C, Sisodiya SM, Thompson PM, van Beijsterveldt CEM, van Dellen E, Via M, Wright MJ. Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity. Brain Behav 2021; 11:e02188. [PMID: 34291596 PMCID: PMC8413828 DOI: 10.1002/brb3.2188] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 03/12/2021] [Accepted: 04/30/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND AND PURPOSE The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.
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Affiliation(s)
- Dirk J A Smit
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Scott J Burwell
- Department of Psychology, Minnesota Center for Twin and Family Research, University of Minnesota, Minneapolis, MN, USA.,Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Reyna L Gordon
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jeremy Harper
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Goethe Universität Frankfurt am Main, Frankfurt, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany.,LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,IU International University, Erfurt, Germany
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Philippe Jawinski
- LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Erik G Jönsson
- TOP-Norment, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Outpatient Second Opinion Clinic, GGNet Mental Health, Apeldoorn, The Netherlands
| | - Cyrille L Magne
- Psychology Department, Middle Tennessee State University, Murfreesboro, TN, USA.,Literacy Studies Ph.D. Program, Middle Tennessee State University, Mufreesboro, TN, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA.,Department of Psychiatry, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Torgeir Moberget
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont-St-Peter, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Edwin van Dellen
- Department of Psychiatry, Department of Intensive Care Medicine, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marc Via
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, and Institute of Neurosciences (UBNeuro), Universitat de Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Spain
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
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19
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Cruz G, Grent-'t-Jong T, Krishnadas R, Palva JM, Palva S, Uhlhaas PJ. Long range temporal correlations (LRTCs) in MEG-data during emerging psychosis: Relationship to symptoms, medication-status and clinical trajectory. Neuroimage Clin 2021; 31:102722. [PMID: 34130193 PMCID: PMC8209846 DOI: 10.1016/j.nicl.2021.102722] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 04/30/2021] [Accepted: 06/04/2021] [Indexed: 12/24/2022]
Abstract
Long-Range Temporal Correlations (LRTCs) index the capacity of the brain to optimally process information. Previous research has shown that patients with chronic schizophrenia present altered LRTCs at alpha and beta oscillations. However, it is currently unclear at which stage of schizophrenia aberrant LRTCs emerge. To address this question, we investigated LRTCs in resting-state magnetoencephalographic (MEG) recordings obtained from patients with affective disorders and substance abuse (clinically at low-risk of psychosis, CHR-N), patients at clinical high-risk of psychosis (CHR-P) (n = 115), as well as patients with a first episode (FEP) (n = 25). Matched healthy controls (n = 47) served as comparison group. LRTCs were obtained for frequencies from 4 to 40 Hz and correlated with clinical and neuropsychological data. In addition, we examined the relationship between LRTCs and transition to psychosis in CHR-P participants, and the relationship between LRTC and antipsychotic medication in FEP participants. Our results show that participants from the clinical groups have similar LRTCs to controls. In addition, LRTCs did not correlate with clinical and neurocognitive variables across participants nor did LRTCs predict transition to psychosis. Therefore, impaired LRTCs do not reflect a feature in the clinical trajectory of psychosis. Nevertheless, reduced LRTCs in the beta-band over posterior sensors of medicated FEP participants indicate that altered LRTCs may appear at the onset of the illness. Future studies are needed to elucidate the role of anti-psychotic medication in altered LRTCs.
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Affiliation(s)
- Gabriela Cruz
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom.
| | - Tineke Grent-'t-Jong
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom; Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Rajeev Krishnadas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
| | - J Matias Palva
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom; Neuroscience Centre, Helsinki Institute of Life Science, University of Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University, Finland
| | - Satu Palva
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom; Neuroscience Centre, Helsinki Institute of Life Science, University of Helsinki, Finland
| | - Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom; Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
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20
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Temporal structure of brain oscillations predicts learned nocebo responses to pain. Sci Rep 2021; 11:9807. [PMID: 33963251 PMCID: PMC8105329 DOI: 10.1038/s41598-021-89368-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 04/19/2021] [Indexed: 02/03/2023] Open
Abstract
This study aimed to identify electrophysiological correlates of nocebo-augmented pain. Nocebo hyperalgesia (i.e., increases in perceived pain resulting from negative expectations) has been found to impact how healthy and patient populations experience pain and is a phenomenon that could be better understood in terms of its neurophysiological underpinnings. In this study, nocebo hyperalgesia was induced in 36 healthy participants through classical conditioning and negative suggestions. Electroencephalography was recorded during rest (pre- and post-acquisition) and during pain stimulation (baseline, acquisition, evocation) First, participants received baseline high thermal pain stimulations. During nocebo acquisition, participants learned to associate an inert gel applied to their forearm with administered high pain stimuli, relative to moderate intensity control stimuli administered without gel. During evocation, all stimuli were accompanied by moderate pain, to measure nocebo responses to the inert gel. Pre- to post-acquisition beta-band alterations in long-range temporal correlations (LRTC) were negatively associated with nocebo magnitudes. Individuals with strong resting LRTC showed larger nocebo responses than those with weaker LRTC. Nocebo acquisition trials showed reduced alpha power. Alpha power was higher while LRTC were lower during nocebo-augmented pain, compared to baseline. These findings support nocebo learning theories and highlight a role of nocebo-induced cognitive processing.
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21
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Racz FS, Farkas K, Stylianou O, Kaposzta Z, Czoch A, Mukli P, Csukly G, Eke A. Separating scale-free and oscillatory components of neural activity in schizophrenia. Brain Behav 2021; 11:e02047. [PMID: 33538105 PMCID: PMC8119820 DOI: 10.1002/brb3.2047] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 12/07/2020] [Accepted: 01/08/2021] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION Alterations in narrow-band spectral power of electroencephalography (EEG) recordings are commonly reported in patients with schizophrenia (SZ). It is well established however that electrophysiological signals comprise a broadband scale-free (or fractal) component generated by mechanisms different from those producing oscillatory neural activity. Despite this known feature, it has not yet been investigated if spectral abnormalities found in SZ could be attributed to scale-free or oscillatory brain function. METHODS In this study, we analyzed resting-state EEG recordings of 14 SZ patients and 14 healthy controls. Scale-free and oscillatory components of the power spectral density (PSD) were separated, and band-limited power (BLP) of the original (mixed) PSD, as well as its fractal and oscillatory components, was estimated in five frequency bands. The scaling property of the fractal component was characterized by its spectral exponent in two distinct frequency ranges (1-13 and 13-30 Hz). RESULTS Analysis of the mixed PSD revealed a decrease of BLP in the delta band in SZ over the central regions; however, this difference could be attributed almost exclusively to a shift of power toward higher frequencies in the fractal component. Broadband neural activity expressed a true bimodal nature in all except frontal regions. Furthermore, both low- and high-range spectral exponents exhibited a characteristic topology over the cortex in both groups. CONCLUSION Our results imply strong functional significance of scale-free neural activity in SZ and suggest that abnormalities in PSD may emerge from alterations of the fractal and not only the oscillatory components of neural activity.
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Affiliation(s)
| | - Kinga Farkas
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | | | - Zalan Kaposzta
- Department of Physiology, Semmelweis University, Budapest, Hungary
| | - Akos Czoch
- Department of Physiology, Semmelweis University, Budapest, Hungary
| | - Peter Mukli
- Department of Physiology, Semmelweis University, Budapest, Hungary
| | - Gabor Csukly
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Andras Eke
- Department of Physiology, Semmelweis University, Budapest, Hungary
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22
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Auno S, Lauronen L, Wilenius J, Peltola M, Vanhatalo S, Palva JM. Detrended fluctuation analysis in the presurgical evaluation of parietal lobe epilepsy patients. Clin Neurophysiol 2021; 132:1515-1525. [PMID: 34030053 DOI: 10.1016/j.clinph.2021.03.041] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 02/22/2021] [Accepted: 03/02/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To examine the usability of long-range temporal correlations (LRTCs) in non-invasive localization of the epileptogenic zone (EZ) in refractory parietal lobe epilepsy (RPLE) patients. METHODS We analyzed 10 RPLE patients who had presurgical MEG and underwent epilepsy surgery. We quantified LRTCs with detrended fluctuation analysis (DFA) at four frequency bands for 200 cortical regions estimated using individual source models. We correlated individually the DFA maps to the distance from the resection area and from cortical locations of interictal epileptiform discharges (IEDs). Additionally, three clinical experts inspected the DFA maps to visually assess the most likely EZ locations. RESULTS The DFA maps correlated with the distance to resection area in patients with type II focal cortical dysplasia (FCD) (p<0.05), but not in other etiologies. Similarly, the DFA maps correlated with the IED locations only in the FCD II patients. Visual analysis of the DFA maps showed high interobserver agreement and accuracy in FCD patients in assigning the affected hemisphere and lobe. CONCLUSIONS Aberrant LRTCs correlate with the resection areas and IED locations. SIGNIFICANCE This methodological pilot study demonstrates the feasibility of approximating cortical LRTCs from MEG that may aid in the EZ localization and provide new non-invasive insight into the presurgical evaluation of epilepsy.
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Affiliation(s)
- Sami Auno
- Epilepsia Helsinki, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Clinical Neurophysiology and BABA center, Children's Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital (HUH), Helsinki, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland.
| | - Leena Lauronen
- Epilepsia Helsinki, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Clinical Neurophysiology and BABA center, Children's Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital (HUH), Helsinki, Finland
| | - Juha Wilenius
- Epilepsia Helsinki, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Clinical Neurophysiology and BABA center, Children's Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital (HUH), Helsinki, Finland; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital(HUH), Helsinki, Finland
| | - Maria Peltola
- Epilepsia Helsinki, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Clinical Neurophysiology and BABA center, Children's Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital (HUH), Helsinki, Finland
| | - Sampsa Vanhatalo
- Department of Clinical Neurophysiology and BABA center, Children's Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital (HUH), Helsinki, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - J Matias Palva
- Department of Neuroscience and Biomedical Engineering, Aalto University, Finland; Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, United Kingdom; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
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23
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Fotia F, Cooke J, Van Dam L, Ferri F, Romei V. The temporal sensitivity to the tactile-induced double flash illusion mediates the impact of beta oscillations on schizotypal personality traits. Conscious Cogn 2021; 91:103121. [PMID: 33853020 DOI: 10.1016/j.concog.2021.103121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 10/30/2020] [Accepted: 03/17/2021] [Indexed: 11/28/2022]
Abstract
The coherent experience of the self and the world depends on the ability to integrate vs. segregate sensory information. Optimal temporal integration between the senses is mediated by oscillatory properties of neural activity. Previous research showed reduced temporal sensitivity to multisensory events in schizotypy, a personality trait linked to schizophrenia. Here we used the tactile-induced Double-Flash-Illusion (tDFI) to investigate the tactile-to-visual temporal sensitivity in schizotypy, as indexed by the temporal window of illusion (TWI) and its neural underpinnings. We measured EEG oscillations within the beta band, recently shown to correlate with the tDFI. We found individuals with higher schizotypal traits to have wider TWI and slower beta waves accounting for the temporal window within which they perceive the illusion. Our results indicate reduced tactile-to-visual temporal sensitivity to mediate the effect of slowed oscillatory beta activity on schizotypal personality traits. We conclude that slowed oscillatory patterns might constitute an early marker for psychosis proneness.
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Affiliation(s)
| | | | | | - Francesca Ferri
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Italy
| | - Vincenzo Romei
- Centre for Studies and Research in Cognitive Neuroscience, Universita' di Bologna, Cesena, Italy
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24
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Thomaidou MA, Peerdeman KJ, Koppeschaar MI, Evers AWM, Veldhuijzen DS. How Negative Experience Influences the Brain: A Comprehensive Review of the Neurobiological Underpinnings of Nocebo Hyperalgesia. Front Neurosci 2021; 15:652552. [PMID: 33841092 PMCID: PMC8024470 DOI: 10.3389/fnins.2021.652552] [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: 01/12/2021] [Accepted: 03/05/2021] [Indexed: 01/06/2023] Open
Abstract
This comprehensive review summarizes and interprets the neurobiological correlates of nocebo hyperalgesia in healthy humans. Nocebo hyperalgesia refers to increased pain sensitivity resulting from negative experiences and is thought to be an important variable influencing the experience of pain in healthy and patient populations. The young nocebo field has employed various methods to unravel the complex neurobiology of this phenomenon and has yielded diverse results. To comprehend and utilize current knowledge, an up-to-date, complete review of this literature is necessary. PubMed and PsychInfo databases were searched to identify studies examining nocebo hyperalgesia while utilizing neurobiological measures. The final selection included 22 articles. Electrophysiological findings pointed toward the involvement of cognitive-affective processes, e.g., modulation of alpha and gamma oscillatory activity and P2 component. Findings were not consistent on whether anxiety-related biochemicals such as cortisol plays a role in nocebo hyperalgesia but showed an involvement of the cyclooxygenase-prostaglandin pathway, endogenous opioids, and dopamine. Structural and functional neuroimaging findings demonstrated that nocebo hyperalgesia amplified pain signals in the spinal cord and brain regions involved in sensory and cognitive-affective processing including the prefrontal cortex, insula, amygdala, and hippocampus. These findings are an important step toward identifying the neurobiological mechanisms through which nocebo effects may exacerbate pain. Results from the studies reviewed are discussed in relation to cognitive-affective and physiological processes involved in nocebo and pain. One major limitation arising from this review is the inconsistency in methods and results in the nocebo field. Yet, while current findings are diverse and lack replication, methodological differences are able to inform our understanding of the results. We provide insights into the complexities and involvement of neurobiological processes in nocebo hyperalgesia and call for more consistency and replication studies. By summarizing and interpreting the challenging and complex neurobiological nocebo studies this review contributes, not only to our understanding of the mechanisms through which nocebo effects exacerbate pain, but also to our understanding of current shortcomings in this field of neurobiological research.
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Affiliation(s)
- Mia A. Thomaidou
- Health, Medical & Neuropsychology Unit, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
| | - Kaya J. Peerdeman
- Health, Medical & Neuropsychology Unit, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
| | | | - Andrea W. M. Evers
- Health, Medical & Neuropsychology Unit, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
- Medical Delta Healthy Society, Leiden University, Technical University Delft, & Erasmus UniversityRotterdam, Netherlands
- Department of Psychiatry, Leiden University Medical Centre, Leiden, Netherlands
| | - Dieuwke S. Veldhuijzen
- Health, Medical & Neuropsychology Unit, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
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25
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Herzog ND, Steinfath TP, Tarrasch R. Critical Dynamics in Spontaneous Resting-State Oscillations Are Associated With the Attention-Related P300 ERP in a Go/Nogo Task. Front Neurosci 2021; 15:632922. [PMID: 33828446 PMCID: PMC8019703 DOI: 10.3389/fnins.2021.632922] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 02/26/2021] [Indexed: 11/13/2022] Open
Abstract
Sustained attention is the ability to continually concentrate on task-relevant information, even in the presence of distraction. Understanding the neural mechanisms underlying this ability is critical for comprehending attentional processes as well as neuropsychiatric disorders characterized by attentional deficits, such as attention deficit hyperactivity disorder (ADHD). In this study, we aimed to investigate how trait-like critical oscillations during rest relate to the P300 evoked potential-a biomarker commonly used to assess attentional deficits. We measured long-range temporal correlations (LRTC) in resting-state EEG oscillations as index for criticality of the signal. In addition, the attentional performance of the subjects was assessed as reaction time variability (RTV) in a continuous performance task following an oddball paradigm. P300 amplitude and latencies were obtained from EEG recordings during this task. We found that, after controlling for individual variability in task performance, LRTC were positively associated with P300 amplitudes but not latencies. In line with previous findings, good performance in the sustained attention task was related to higher P300 amplitudes and earlier peak latencies. Unexpectedly, we observed a positive relationship between LRTC in ongoing oscillations during rest and RTV, indicating that greater criticality in brain oscillations during rest relates to worse task performance. In summary, our results show that resting-state neuronal activity, which operates near a critical state, relates to the generation of higher P300 amplitudes. Brain dynamics close to criticality potentially foster a computationally advantageous state which promotes the ability to generate higher event-related potential (ERP) amplitudes.
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Affiliation(s)
- Nadine D Herzog
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,School of Education and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Tim P Steinfath
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ricardo Tarrasch
- School of Education and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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26
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Di Cosmo G, Costantini M, Ambrosini E, Salone A, Martinotti G, Corbo M, Di Giannantonio M, Ferri F. Body-environment integration: Temporal processing of tactile and auditory inputs along the schizophrenia continuum. J Psychiatr Res 2021; 134:208-214. [PMID: 33418447 DOI: 10.1016/j.jpsychires.2020.12.034] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 11/06/2020] [Accepted: 12/09/2020] [Indexed: 12/20/2022]
Abstract
According to the dimensional approach to psychosis, there is a continuum from low schizotypy to schizophrenia patients. The temporal aspect of sensory processing seems to be compromised across such continuum, as suggested by different studies separately investigating unisensory or multisensory domains. Most of these studies have so far focused primarily on the temporal processing of visual and auditory stimuli, either in schizotypy or schizophrenia, while leaving the tactile domain and the integration of touch with other senses mostly unexplored. Given the relevance of body-related perceptual abnormalities for psychosis proneness, we aimed at filling this gap in the literature across two studies. We asked participants with increasing levels of schizotypy (study 1) and schizophrenia patients (study 2) to perform three simultaneity judgement tasks: a unimodal tactile task, a unimodal auditory task and a bimodal audio-tactile task. Each task allowed estimating a simultaneity range (SR), as a proxy of the individual tolerance to asynchronies in the tactile, auditory and audio-tactile domains, respectively. Results showed larger SRs as the level of schizotypy increases. Specifically, the linear effect of schizotypy levels on the audio-tactile task was stronger than on the auditory task, which in turn was greater than the effect on the tactile task (study 1). Differently, schizophrenia patients showed larger SRs than controls in all the three tasks (study 2). The current study is the first empirical investigation across the continuum from low schizotypy to schizophrenia of the tolerance to asynchronies in the processing of external (auditory) and body-related (tactile) inputs.
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Affiliation(s)
- Giulio Di Cosmo
- Institute for Advanced Biomedical Technologies, ITAB, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
| | - Marcello Costantini
- Institute for Advanced Biomedical Technologies, ITAB, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Department of Psychological, Health and Territorial Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | | | - Anatolia Salone
- Institute for Advanced Biomedical Technologies, ITAB, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Department of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Giovanni Martinotti
- Institute for Advanced Biomedical Technologies, ITAB, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Department of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Mariangela Corbo
- Institute for Advanced Biomedical Technologies, ITAB, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Department of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Massimo Di Giannantonio
- Institute for Advanced Biomedical Technologies, ITAB, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Department of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Francesca Ferri
- Institute for Advanced Biomedical Technologies, ITAB, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Department of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
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27
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Välimäki M, Yang M, Lam YTJ, Lantta T, Palva M, Palva S, Yee B, Yip SH, Yu KSD, Chang HCC, Cheng PYI, Bressington D. The impact of video gaming on cognitive functioning of people with schizophrenia (GAME-S): study protocol of a randomised controlled trial. BMC Psychiatry 2021; 21:46. [PMID: 33461506 PMCID: PMC7814579 DOI: 10.1186/s12888-020-03031-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 12/22/2020] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Video gaming is a promising intervention for cognitive and social impairment in patients with schizophrenia. A number of gaming interventions have been evaluated in small-scale studies with various patient groups, but studies on patients with schizophrenia remain scarce and rarely include the evaluation of both clinical and neurocognitive outcomes. In this study, we will test the effectiveness of two interventions with gaming elements to improve cognitive and clinical outcomes among persons with schizophrenia. METHODS The participants will be recruited from different outpatient units (e.g., outpatient psychiatric units, day hospitals, residential care homes). The controlled clinical trial will follow a three-arm parallel-group design: 1) cognitive training (experimental group, CogniFit), 2) entertainment gaming (active control group, SIMS 4), and 3) treatment as usual. The primary outcomes are working memory function at 3-month and 6-month follow-ups. The secondary outcomes are patients' other cognitive and social functioning, the ability to experience pleasure, self-efficacy, and negative symptoms at 3-month and 6-month follow-ups. We will also test the effectiveness of gaming interventions on neurocognitive outcomes (EEG and 3 T MRI plus rs-fMRI) at a 3-month follow-up as an additional secondary outcome. Data will be collected in outpatient psychiatric services in Hong Kong. Participants will have a formal diagnosis of schizophrenia and be between 18 and 60 years old. We aim to have a total of 234 participants, randomly allocated to the three arms. A sub-sample of patients (N = 150) will be recruited to undergo an EEG. For neuroimaging assessment, patients will be randomly allocated to a subset of patients (N=126). We will estimate the efficacy of the interventions on the primary and secondary outcomes based on the intention-to-treat principle. Behavioural and EEG data will be analysed separately. DISCUSSION The study will characterise benefits of gaming on patients' health and well-being, and contribute towards the development of new treatment approaches for patients with schizophrenia. TRIAL REGISTRATION ClinicalTrials.gov NCT03133143 . Registered on April 28, 2017.
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Affiliation(s)
- Maritta Välimäki
- Xiangya Nursing School, Central South University, 172 Tongzipo Road, Changsha, 410013, Hunan, China. .,School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Hong Kong SAR. .,Department of Nursing Science, Faculty of Medicine, University of Turku, 20014, Turku, Finland.
| | - Min Yang
- grid.13291.380000 0001 0807 1581West China School of Public Health, Sichuan University, Chengdu, China ,grid.1027.40000 0004 0409 2862Faculty of Health, Art and Design, Swinburne University of Technology, Melbourne, Victoria 3122 Australia
| | - Yuen Ting Joyce Lam
- grid.16890.360000 0004 1764 6123School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Hong Kong SAR
| | - Tella Lantta
- grid.1374.10000 0001 2097 1371Department of Nursing Science, Faculty of Medicine, University of Turku, 20014 Turku, Finland
| | - Matias Palva
- grid.7737.40000 0004 0410 2071Neuroscience Center, University of Helsinki, Helsinki, Finland
| | - Satu Palva
- grid.7737.40000 0004 0410 2071Neuroscience Center, University of Helsinki, Helsinki, Finland
| | - Benjamin Yee
- grid.16890.360000 0004 1764 6123Department of Rehabilitation Sciences, Hung Hom, Kowloon, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR
| | - Siu Hung Yip
- grid.415504.10000 0004 1794 2766Department of Psychiatry, Kowloon Hospital, Hong Kong, Hong Kong SAR
| | - Kin-sun Dan Yu
- The Mental Health Association of Hong Kong, 2 Kung Lok Road, Hong Kong, Hong Kong SAR
| | - Hing Chiu Charles Chang
- grid.194645.b0000000121742757Department of Diagnostic Radiology, The Hong Kong Jockey Club for Interdisciplinary Research, The University of Hong Kong, 5 Sassoon Road, Hong Kong, Hong Kong SAR
| | - Po Yee Ivy Cheng
- grid.417134.40000 0004 1771 4093Department of Psychiatry, Community Psychiatry, Pamela Youde Nethersole Eastern Hospital, Hong Kong, Hong Kong SAR
| | - Daniel Bressington
- grid.1043.60000 0001 2157 559XCollege of Nursing and Midwifery, Charles Darwin University, Darwin, Australia
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28
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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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29
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Alamian G, Pascarella A, Lajnef T, Knight L, Walters J, Singh KD, Jerbi K. Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia. Neuroimage Clin 2020; 28:102485. [PMID: 33395976 PMCID: PMC7691748 DOI: 10.1016/j.nicl.2020.102485] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 12/19/2022]
Abstract
Current theories of schizophrenia emphasize the role of altered information integration as the core dysfunction of this illness. While ample neuroimaging evidence for such accounts comes from investigations of spatial connectivity, understanding temporal disruptions is important to fully capture the essence of dysconnectivity in schizophrenia. Recent electrophysiology studies suggest that long-range temporal correlation (LRTC) in the amplitude dynamics of neural oscillations captures the integrity of transferred information in the healthy brain. Thus, in this study, 25 schizophrenia patients and 25 controls (8 females/group) were recorded during two five-minutes of resting-state magnetoencephalography (once with eyes-open and once with eyes-closed). We used source-level analyses to investigate temporal dysconnectivity in patients by characterizing LRTCs across cortical and sub-cortical brain regions. In addition to standard statistical assessments, we applied a machine learning framework using support vector machine to evaluate the discriminative power of LRTCs in identifying patients from healthy controls. We found that neural oscillations in schizophrenia patients were characterized by reduced signal memory and higher variability across time, as evidenced by cortical and subcortical attenuations of LRTCs in the alpha and beta frequency bands. Support vector machine significantly classified participants using LRTCs in key limbic and paralimbic brain areas, with decoding accuracy reaching 82%. Importantly, these brain regions belong to networks that are highly relevant to the symptomology of schizophrenia. These findings thus posit temporal dysconnectivity as a hallmark of altered information processing in schizophrenia, and help advance our understanding of this pathology.
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Affiliation(s)
- Golnoush Alamian
- CoCo Lab, Department of Psychology, Université de Montréal, Canada.
| | | | - Tarek Lajnef
- CoCo Lab, Department of Psychology, Université de Montréal, Canada
| | - Laura Knight
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, UK
| | - James Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, UK
| | - Krish D Singh
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, UK
| | - Karim Jerbi
- CoCo Lab, Department of Psychology, Université de Montréal, Canada; MEG Center, University of Montreal, Canada; UNIQUE Centre (Unifying AI and Neuroscience - Québec), Quebec, Canada; Mila (Quebec AI Institute), Montreal, QC, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Montreal, QC, Canada
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30
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Zimmern V. Why Brain Criticality Is Clinically Relevant: A Scoping Review. Front Neural Circuits 2020; 14:54. [PMID: 32982698 PMCID: PMC7479292 DOI: 10.3389/fncir.2020.00054] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 07/23/2020] [Indexed: 12/13/2022] Open
Abstract
The past 25 years have seen a strong increase in the number of publications related to criticality in different areas of neuroscience. The potential of criticality to explain various brain properties, including optimal information processing, has made it an increasingly exciting area of investigation for neuroscientists. Recent reviews on this topic, sometimes termed brain criticality, make brief mention of clinical applications of these findings to several neurological disorders such as epilepsy, neurodegenerative disease, and neonatal hypoxia. Other clinicallyrelevant domains - including anesthesia, sleep medicine, developmental-behavioral pediatrics, and psychiatry - are seldom discussed in review papers of brain criticality. Thorough assessments of these application areas and their relevance for clinicians have also yet to be published. In this scoping review, studies of brain criticality involving human data of all ages are evaluated for their current and future clinical relevance. To make the results of these studies understandable to a more clinical audience, a review of the key concepts behind criticality (e.g., phase transitions, long-range temporal correlation, self-organized criticality, power laws, branching processes) precedes the discussion of human clinical studies. Open questions and forthcoming areas of investigation are also considered.
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Affiliation(s)
- Vincent Zimmern
- Division of Child Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
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31
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Low-frequency oscillations reflect aberrant tone restoration during the auditory continuity illusion in schizophrenia. Sci Rep 2020; 10:11872. [PMID: 32681138 PMCID: PMC7367839 DOI: 10.1038/s41598-020-68414-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 06/23/2020] [Indexed: 11/09/2022] Open
Abstract
Patients with schizophrenia (ScZ) often show impairments in auditory information processing. These impairments have been related to clinical symptoms, such as auditory hallucinations. Some researchers have hypothesized that aberrant low-frequency oscillations contribute to auditory information processing deficits in ScZ. A paradigm for which modulations in low-frequency oscillations are consistently found in healthy individuals is the auditory continuity illusion (ACI), in which restoration processes lead to a perceptual grouping of tone fragments and a mask, so that a physically interrupted sound is perceived as continuous. We used the ACI paradigm to test the hypothesis that low-frequency oscillations play a role in aberrant auditory information processing in patients with ScZ (N = 23). Compared with healthy control participants we found that patients with ScZ show elevated continuity illusions of interrupted, partially-masked tones. Electroencephalography data demonstrate that this elevated continuity perception is reflected by diminished 3 Hz power. This suggests that reduced low-frequency oscillations relate to elevated restoration processes in ScZ. Our findings support the hypothesis that aberrant low-frequency oscillations contribute to altered perception-related auditory information processing in ScZ.
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32
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Duncan NW, Hsu TY, Cheng PZ, Wang HY, Lee HC, Lane TJ. Intrinsic activity temporal structure reactivity to behavioural state change is correlated with depressive symptoms. Eur J Neurosci 2020; 52:4840-4850. [PMID: 32524682 DOI: 10.1111/ejn.14858] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 06/01/2020] [Accepted: 06/02/2020] [Indexed: 01/24/2023]
Abstract
The brain's intrinsic activity plays a fundamental role in its function. In normal conditions this activity is responsive to behavioural context, changing as an individual switches between directed tasks and task-free conditions. A key feature of such changes is the movement of the brain between corresponding critical and sub-critical states, with these dynamics supporting efficient cognitive processing. Breakdowns in processing efficiency can occur, however, in brain disorders such as depression. It was therefore hypothesised that depressive symptoms would be related to reduced intrinsic activity responsiveness to changes in behavioural state. This was tested in a mixed group of major depressive disorder patients (n = 26) and healthy participants (n = 37) by measuring intrinsic EEG activity temporal structure, quantified with detrended fluctuation analysis (DFA), in eyes-closed (EC) and eyes-open task-free states and contrasting between the conditions. The degree to which DFA values changed between the states was found to correlate negatively with depressive symptoms. DFA values did not differ between states in those with higher symptom levels, meaning that the brain remained in a less flexible sub-critical condition. This sub-critical condition in the EC state was further found to correlate with levels of maladaptive rumination. This may reflect a general cognitive inflexibility resulting from a lack in neural activity reactivity that may predispose people to overly engage in self-directed attention. These results provide an initial link between intrinsic activity reactivity and psychological features found in psychiatric disorders.
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Affiliation(s)
- Niall W Duncan
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City, Taiwan
| | - Tzu-Yu Hsu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City, Taiwan
| | - Paul Z Cheng
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City, Taiwan
| | - Hsin-Yi Wang
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City, Taiwan
| | - Hsin-Chien Lee
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Psychiatry, TMU Shuang-Ho Hospital, New Taipei City, Taiwan
| | - Timothy J Lane
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, TMU Shuang-Ho Hospital, New Taipei City, Taiwan.,College of Humanities and Social Science, Taipei Medical University, Taipei, Taiwan
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33
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Freche D, Naim-Feil J, Hess S, Peled A, Grinshpoon A, Moses E, Levit-Binnun N. Phase-Amplitude Markers of Synchrony and Noise: A Resting-State and TMS-EEG Study of Schizophrenia. Cereb Cortex Commun 2020; 1:tgaa013. [PMID: 34296092 PMCID: PMC8152916 DOI: 10.1093/texcom/tgaa013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 04/30/2020] [Indexed: 01/01/2023] Open
Abstract
The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here, we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity, we used 3 weekly sessions and analyzed both resting-state and TMS-EEG data. For the TMS responses, our analysis verifies known results. For the resting state, we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha, and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha- and beta-resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally, and temporally correlated activity is reduced in schizophrenia, a conclusion, that is, in accord with previous experiments on TMS-EEG and on resting-state EEG.
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Affiliation(s)
- Dominik Freche
- Sagol Center of Brain and Mind, Ivcher School of Psychology, Interdisciplinary Center (IDC), Herzliya 4610101, Israel
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Jodie Naim-Feil
- Sagol Center of Brain and Mind, Ivcher School of Psychology, Interdisciplinary Center (IDC), Herzliya 4610101, Israel
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton 3800, Australia
| | - Shmuel Hess
- Geha Mental Health Center, Petah Tikvah 49100, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Avraham Peled
- Rappaport Faculty of Medicine, Technion, Haifa 3200003, Israel
- Institute for Psychiatric Studies, Shaar Menashe Mental Health Center, Menashe 38814, Pardes Hanna-Karkur, Israel
| | - Alexander Grinshpoon
- Rappaport Faculty of Medicine, Technion, Haifa 3200003, Israel
- Institute for Psychiatric Studies, Shaar Menashe Mental Health Center, Menashe 38814, Pardes Hanna-Karkur, Israel
| | - Elisha Moses
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Nava Levit-Binnun
- Sagol Center of Brain and Mind, Ivcher School of Psychology, Interdisciplinary Center (IDC), Herzliya 4610101, Israel
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34
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Shirai S, Acharya SK, Bose SK, Mallinson JB, Galli E, Pike MD, Arnold MD, Brown SA. Long-range temporal correlations in scale-free neuromorphic networks. Netw Neurosci 2020; 4:432-447. [PMID: 32537535 PMCID: PMC7286302 DOI: 10.1162/netn_a_00128] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 01/17/2020] [Indexed: 12/05/2022] Open
Abstract
Biological neuronal networks are the computing engines of the mammalian brain. These networks exhibit structural characteristics such as hierarchical architectures, small-world attributes, and scale-free topologies, providing the basis for the emergence of rich temporal characteristics such as scale-free dynamics and long-range temporal correlations. Devices that have both the topological and the temporal features of a neuronal network would be a significant step toward constructing a neuromorphic system that can emulate the computational ability and energy efficiency of the human brain. Here we use numerical simulations to show that percolating networks of nanoparticles exhibit structural properties that are reminiscent of biological neuronal networks, and then show experimentally that stimulation of percolating networks by an external voltage stimulus produces temporal dynamics that are self-similar, follow power-law scaling, and exhibit long-range temporal correlations. These results are expected to have important implications for the development of neuromorphic devices, especially for those based on the concept of reservoir computing. Biological neuronal networks exhibit well-defined properties such as hierarchical structures and scale-free topologies, as well as a high degree of local clustering and short path lengths between nodes. These structural properties are intimately connected to the observed long-range temporal correlations in the network dynamics. Fabrication of artificial networks with similar structural properties would facilitate brain-like (“neuromorphic”) computing. Here we show experimentally that percolating networks of nanoparticles exhibit similar long-range temporal correlations to those of biological neuronal networks and use simulations to demonstrate that the dynamics arise from an underlying scale-free network architecture. We discuss similarities between the biological and percolating systems and highlight the potential for the percolating networks to be used in neuromorphic computing applications.
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Affiliation(s)
- Shota Shirai
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matū, University of Canterbury, Christchurch, New Zealand
| | - Susant Kumar Acharya
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matū, University of Canterbury, Christchurch, New Zealand
| | - Saurabh Kumar Bose
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matū, University of Canterbury, Christchurch, New Zealand
| | - Joshua Brian Mallinson
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matū, University of Canterbury, Christchurch, New Zealand
| | - Edoardo Galli
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matū, University of Canterbury, Christchurch, New Zealand
| | - Matthew D Pike
- Electrical and Electronics Engineering, University of Canterbury, Christchurch, New Zealand
| | - Matthew D Arnold
- School of Mathematical and Physical Sciences, University of Technology Sydney, Australia
| | - Simon Anthony Brown
- The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matū, University of Canterbury, Christchurch, New Zealand
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35
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Miasnikova A, Troshkov D, Baklushev M, Perevoznyuk G. Predicting States of Abstract Reasoning Using EEG Functional Connectivity Markers. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:2451-2454. [PMID: 31946394 DOI: 10.1109/embc.2019.8857031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
High order abstract reasoning is impaired in patients suffering from mental disorders especially from schizophrenia. Thought and language disorders typical of schizophrenia are presumably connected with the aberrant ability to filter out irrelevant associations. We hypothesized that EEG biomarkers in healthy population could be detected, extracted and validated with regard to the ability to abstract a general principle underlying presented words while ignoring irrelevant associations and retaining only relevant ones. We developed three models of abstract reasoning: a direct generalization presented by nouns from the same semantic category, a latent association based on a loose relation between the presented words, and no associations introduced by non-related words. In the present EEG study 17 healthy participants solved tasks trying to figure out a general principle in a group of words. Subsequently, we carried out a functional connectivity analysis in order to restore synchronous neuronal interactions in the theta-alpha frequency range. We used the obtained spatial patters restored individually and relevant phase locking values (PLVs) as features for the Support Vector Machine classifier with Gaussian kernel. The accuracy rating validated on an independent sample made up 62.5% which is a promising result if inter-subject variability in cognitive processing is taken into account. Being validated on the same sample, the accuracy reached 82%. The results indicate that spatial patterns of functional connectivity and PLVs can be used as predictors of types of abstract reasoning.
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36
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Moran JK, Michail G, Heinz A, Keil J, Senkowski D. Long-Range Temporal Correlations in Resting State Beta Oscillations are Reduced in Schizophrenia. Front Psychiatry 2019; 10:517. [PMID: 31379629 PMCID: PMC6659128 DOI: 10.3389/fpsyt.2019.00517] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 07/01/2019] [Indexed: 01/26/2023] Open
Abstract
Symptoms of schizophrenia (SCZ) are likely to be generated by genetically mediated synaptic dysfunction, which contribute to large-scale functional neural dysconnectivity. Recent electrophysiological studies suggest that this dysconnectivity is present not only at a spatial level but also at a temporal level, operationalized as long-range temporal correlations (LRTCs). Previous research suggests that alpha and beta frequency bands have weaker temporal stability in people with SCZ. This study sought to replicate these findings with high-density electroencephalography (EEG), enabling a spatially more accurate analysis of LRTC differences, and to test associations with characteristic SCZ symptoms and cognitive deficits. A 128-channel EEG was used to record eyes-open resting state brain activity of 23 people with SCZ and 24 matched healthy controls (HCs). LRTCs were derived for alpha (8-12 Hz) and beta (13-25 Hz) frequency bands. As an exploratory analysis, LRTC was source projected using sLoreta. People with SCZ showed an area of significantly reduced beta-band LRTC compared with HCs over bilateral posterior regions. There were no between-group differences in alpha-band activity. Individual symptoms of SCZ were not related to LRTC values nor were cognitive deficits. The study confirms that people with SCZ have reduced temporal stability in the beta frequency band. The absence of group differences in the alpha band may be attributed to the fact that people had, in contrast to previous studies, their eyes open in the current study. Taken together, our study confirms the utility of LRTC as a marker of network instability in people with SCZ and provides a novel empirical perspective for future examinations of network dysfunction salience in SCZ research.
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Affiliation(s)
- James K. Moran
- Department of Psychiatry and Psychotherapy, St. Hedwig Hospital, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Georgios Michail
- Department of Psychiatry and Psychotherapy, St. Hedwig Hospital, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, St. Hedwig Hospital, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Julian Keil
- Biological Psychology, Christian-Albrechts University Kiel, Kiel, Germany
| | - Daniel Senkowski
- Department of Psychiatry and Psychotherapy, St. Hedwig Hospital, Charité-Universitätsmedizin Berlin, Berlin, Germany
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37
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Ovadia-Caro S, Khalil AA, Sehm B, Villringer A, Nikulin VV, Nazarova M. Predicting the Response to Non-invasive Brain Stimulation in Stroke. Front Neurol 2019; 10:302. [PMID: 31001190 PMCID: PMC6454031 DOI: 10.3389/fneur.2019.00302] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Accepted: 03/11/2019] [Indexed: 01/10/2023] Open
Affiliation(s)
- Smadar Ovadia-Caro
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Neurophysics Group, Department of Neurology, Campus Benjamin Franklin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ahmed A. Khalil
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Bernhard Sehm
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Cognitive Neurology, University Hospital Leipzig and Faculty of Medicine, University of Leipzig, Leipzig, Germany
| | - Vadim V. Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Neurophysics Group, Department of Neurology, Campus Benjamin Franklin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Maria Nazarova
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
- Federal Center for Cerebrovascular Pathology and Stroke, The Ministry of Healthcare of the Russian Federation, Federal State Budget Institution, Moscow, Russia
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38
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Aguilar-Velázquez D, Guzmán-Vargas L. Critical synchronization and 1/f noise in inhibitory/excitatory rich-club neural networks. Sci Rep 2019; 9:1258. [PMID: 30718817 PMCID: PMC6361933 DOI: 10.1038/s41598-018-37920-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 12/17/2018] [Indexed: 12/16/2022] Open
Abstract
In recent years, diverse studies have reported that different brain regions, which are internally densely connected, are also highly connected to each other. This configuration seems to play a key role in integrating and interchanging information between brain areas. Also, changes in the rich-club connectivity and the shift from inhibitory to excitatory behavior of hub neurons have been associated with several diseases. However, there is not a clear understanding about the role of the proportion of inhibitory/excitatory hub neurons, the dynamic consequences of rich-club disconnection, and hub inhibitory/excitatory shifts. Here, we study the synchronization and temporal correlations in the neural Izhikevich model, which comprises excitatory and inhibitory neurons located in a scale-free hierarchical network with rich-club connectivity. We evaluated the temporal autocorrelations and global synchronization dynamics displayed by the system in terms of rich-club connectivity and hub inhibitory/excitatory population. We evaluated the synchrony between pairs of sets of neurons by means of the global lability synchronization, based on the rate of change in the total number of synchronized signals. The results show that for a wide range of excitatory/inhibitory hub ratios the network displays 1/f dynamics with critical synchronization that is concordant with numerous health brain registers, while a network configuration with a vast majority of excitatory hubs mostly exhibits short-term autocorrelations with numerous large avalanches. Furthermore, rich-club connectivity promotes the increase of the global lability of synchrony and the temporal persistence of the system.
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Affiliation(s)
- Daniel Aguilar-Velázquez
- Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, Instituto Politécnico Nacional, Av. IPN No. 2580, L. Ticomán, Ciudad de México, 07340, Mexico
| | - Lev Guzmán-Vargas
- Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, Instituto Politécnico Nacional, Av. IPN No. 2580, L. Ticomán, Ciudad de México, 07340, Mexico.
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39
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Kwok EYL, Cardy JO, Allman BL, Allen P, Herrmann B. Dynamics of spontaneous alpha activity correlate with language ability in young children. Behav Brain Res 2018; 359:56-65. [PMID: 30352251 DOI: 10.1016/j.bbr.2018.10.024] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 09/21/2018] [Accepted: 10/16/2018] [Indexed: 11/18/2022]
Abstract
Early childhood is a period of tremendous growth in both language ability and brain maturation. To understand the dynamic interplay between neural activity and spoken language development, we used resting-state EEG recordings to explore the relation between alpha oscillations (7-10 Hz) and oral language ability in 4- to 6-year-old children with typical development (N = 41). Three properties of alpha oscillations were investigated: a) alpha power using spectral analysis, b) flexibility of the alpha frequency quantified via the oscillation's moment-to-moment fluctuations, and c) scaling behavior of the alpha oscillator investigated via the long-range temporal correlation in the alpha-amplitude time course. All three properties of the alpha oscillator correlated with children's oral language abilities. Higher language scores were correlated with lower alpha power, greater flexibility of the alpha frequency, and longer temporal correlations in the alpha-amplitude time course. Our findings demonstrate a cognitive role of several properties of the alpha oscillator that has largely been overlooked in the literature.
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Affiliation(s)
- Elaine Y L Kwok
- Communication Sciences and Disorders, The University of Western Ontario, London, ON, N6G 1H1, Canada.
| | - Janis Oram Cardy
- Communication Sciences and Disorders, The University of Western Ontario, London, ON, N6G 1H1, Canada; Brain and Mind Institute, The University of Western Ontario, London, ON, N6A 5B7, Canada; National Centre for Audiology, The University of Western Ontario, London, ON, N6G 1H1, Canada
| | - Brian L Allman
- National Centre for Audiology, The University of Western Ontario, London, ON, N6G 1H1, Canada; Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, ON, N6A 5C1, Canada
| | - Prudence Allen
- Communication Sciences and Disorders, The University of Western Ontario, London, ON, N6G 1H1, Canada; National Centre for Audiology, The University of Western Ontario, London, ON, N6G 1H1, Canada
| | - Björn Herrmann
- Brain and Mind Institute, The University of Western Ontario, London, ON, N6A 5B7, Canada; Department of Psychology, The University of Western Ontario, London, ON, N6A 5C2, Canada.
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40
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Irrmischer M, Poil S, Mansvelder HD, Intra FS, Linkenkaer‐Hansen K. Strong long-range temporal correlations of beta/gamma oscillations are associated with poor sustained visual attention performance. Eur J Neurosci 2018; 48:2674-2683. [PMID: 28858404 PMCID: PMC6221163 DOI: 10.1111/ejn.13672] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 07/27/2017] [Accepted: 08/25/2017] [Indexed: 12/11/2022]
Abstract
Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist over thousands of oscillatory cycles. Such long-range temporal correlations (LRTC) are thought to reflect neuronal systems poised near a critical state, which would render them capable of quick reorganization and responsive to changing processing demands. When we concentrate, however, the influence of internal and external sources of distraction is better reduced, suggesting that neuronal systems involved with sustained attention could benefit from a shift toward the less volatile sub-critical state. To test these ideas, we recorded electroencephalography (EEG) from healthy volunteers during eyes-closed rest and during a sustained attention task requiring a speeded response to images deviating in their presentation duration. We show that for oscillations recorded during rest, high levels of alpha-band LRTC in the sensorimotor region predicted good reaction-time performance in the attention task. During task execution, however, fast reaction times were associated with high-amplitude beta and gamma oscillations with low LRTC. Finally, we show that reduced LRTC during the attention task compared to the rest condition correlates with better performance, while increased LRTC of oscillations from rest to attention is associated with reduced performance. To our knowledge, this is the first empirical evidence that 'resting-state criticality' of neuronal networks predicts swift behavioral responses in a sensorimotor task, and that steady attentive processing of visual stimuli requires brain dynamics with suppressed temporal complexity.
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Affiliation(s)
- Mona Irrmischer
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR)Amsterdam NeuroscienceVU University Amsterdam1081 HVAmsterdamThe Netherlands
| | - Simon‐Shlomo Poil
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR)Amsterdam NeuroscienceVU University Amsterdam1081 HVAmsterdamThe Netherlands
- NBT Analytics BVAmsterdamThe Netherlands
| | - Huibert D. Mansvelder
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR)Amsterdam NeuroscienceVU University Amsterdam1081 HVAmsterdamThe Netherlands
| | - Francesca Sangiuliano Intra
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR)Amsterdam NeuroscienceVU University Amsterdam1081 HVAmsterdamThe Netherlands
- IRCCSDon Gnocchi FoundationMilanItaly
| | - Klaus Linkenkaer‐Hansen
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR)Amsterdam NeuroscienceVU University Amsterdam1081 HVAmsterdamThe Netherlands
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41
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Ros T, Frewen P, Théberge J, Michela A, Kluetsch R, Mueller A, Candrian G, Jetly R, Vuilleumier P, Lanius RA. Neurofeedback Tunes Scale-Free Dynamics in Spontaneous Brain Activity. Cereb Cortex 2018; 27:4911-4922. [PMID: 27620975 DOI: 10.1093/cercor/bhw285] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Accepted: 08/19/2016] [Indexed: 11/13/2022] Open
Abstract
Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the regularity of their fluctuations: low values representing more random (decorrelated) while high values more persistent (correlated) dynamics. LRTCs constitute supporting evidence that the brain operates near criticality, a state where neuronal activities are balanced between order and randomness. Here, healthy adults used closed-loop brain training (neurofeedback, NFB) to reduce the amplitude of alpha oscillations, producing a significant increase in spontaneous LRTCs post-training. This effect was reproduced in patients with post-traumatic stress disorder, where abnormally random dynamics were reversed by NFB, correlating with significant improvements in hyperarousal. Notably, regions manifesting abnormally low LRTCs (i.e., excessive randomness) normalized toward healthy population levels, consistent with theoretical predictions about self-organized criticality. Hence, when exposed to appropriate training, spontaneous cortical activity reveals a residual capacity for "self-tuning" its own temporal complexity, despite manifesting the abnormal dynamics seen in individuals with psychiatric disorder. Lastly, we observed an inverse-U relationship between strength of LRTC and oscillation amplitude, suggesting a breakdown of long-range dependence at high/low synchronization extremes, in line with recent computational models. Together, our findings offer a broader mechanistic framework for motivating research and clinical applications of NFB, encompassing disorders with perturbed LRTCs.
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Affiliation(s)
- T Ros
- Geneva Neuroscience Center, Department of Neuroscience, University of Geneva, CH-1202 Geneva, Switzerland
| | - P Frewen
- Department of Psychiatry, Western University, London N6A 5A5, Ontario, Canada
| | - J Théberge
- Department of Medical Imaging, Lawson Health Research Institute, London N6C 2R5, Ontario, Canada
| | - A Michela
- Geneva Neuroscience Center, Department of Neuroscience, University of Geneva, CH-1202 Geneva, Switzerland
| | - R Kluetsch
- Department of Psychosomatic Medicine and Psychotherapy, Mannheim-Heidelberg University, 68159 Mannheim, Germany
| | - A Mueller
- Brain and Trauma Foundation, CH-7000 Chur, Switzerland
| | - G Candrian
- Brain and Trauma Foundation, CH-7000 Chur, Switzerland
| | - R Jetly
- Directorate of Mental Health, Canadian Forces Health Services, Ottawa K1A 0K6, Canada
| | - P Vuilleumier
- Geneva Neuroscience Center, Department of Neuroscience, University of Geneva, CH-1202 Geneva, Switzerland
| | - R A Lanius
- Department of Psychiatry, Western University, London N6A 5A5, Ontario, Canada
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42
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Thiery T, Lajnef T, Combrisson E, Dehgan A, Rainville P, Mashour GA, Blain-Moraes S, Jerbi K. Long-range temporal correlations in the brain distinguish conscious wakefulness from induced unconsciousness. Neuroimage 2018; 179:30-39. [PMID: 29885482 DOI: 10.1016/j.neuroimage.2018.05.069] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Revised: 04/18/2018] [Accepted: 05/29/2018] [Indexed: 12/20/2022] Open
Abstract
Rhythmic neuronal synchronization across large-scale networks is thought to play a key role in the regulation of conscious states. Changes in neuronal oscillation amplitude across states of consciousness have been widely reported, but little is known about possible changes in the temporal dynamics of these oscillations. The temporal structure of brain oscillations may provide novel insights into the neural mechanisms underlying consciousness. To address this question, we examined long-range temporal correlations (LRTC) of EEG oscillation amplitudes recorded during both wakefulness and anesthetic-induced unconsciousness. Importantly, the time-varying EEG oscillation envelopes were assessed over the course of a sevoflurane sedation protocol during which the participants alternated between states of consciousness and unconsciousness. Both spectral power and LRTC in oscillation amplitude were computed across multiple frequency bands. State-dependent differences in these features were assessed using non-parametric tests and supervised machine learning. We found that periods of unconsciousness were associated with increases in LRTC in beta (15-30Hz) amplitude over frontocentral channels and with a suppression of alpha (8-13Hz) amplitude over occipitoparietal electrodes. Moreover, classifiers trained to predict states of consciousness on single epochs demonstrated that the combination of beta LRTC with alpha amplitude provided the highest classification accuracy (above 80%). These results suggest that loss of consciousness is accompanied by an augmentation of temporal persistence in neuronal oscillation amplitude, which may reflect an increase in regularity and a decrease in network repertoire compared to the brain's activity during resting-state consciousness.
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Affiliation(s)
- Thomas Thiery
- Psychology Department, University of Montreal, QC, Canada.
| | - Tarek Lajnef
- Psychology Department, University of Montreal, QC, Canada
| | - Etienne Combrisson
- Psychology Department, University of Montreal, QC, Canada; Center of Research and Innovation in Sport, Mental Processes and Motor Performance, University Claude Bernard Lyon I, University of Lyon, Villeurbanne, France; Brain Dynamics and Cognition, Lyon Neuroscience Research Center, INSERM U1028, UMR 5292, University of Lyon, Villeurbanne, France
| | - Arthur Dehgan
- Psychology Department, University of Montreal, QC, Canada
| | | | - George A Mashour
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan, USA
| | - Stefanie Blain-Moraes
- School of Physical and Occupational Therapy, McGill University, Montreal, QC, Canada
| | - Karim Jerbi
- Psychology Department, University of Montreal, QC, Canada
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43
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Sangiuliano Intra F, Avramiea AE, Irrmischer M, Poil SS, Mansvelder HD, Linkenkaer-Hansen K. Long-Range Temporal Correlations in Alpha Oscillations Stabilize Perception of Ambiguous Visual Stimuli. Front Hum Neurosci 2018; 12:159. [PMID: 29740303 PMCID: PMC5928216 DOI: 10.3389/fnhum.2018.00159] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 04/06/2018] [Indexed: 02/05/2023] Open
Abstract
Ongoing brain dynamics have been proposed as a type of “neuronal noise” that can trigger perceptual switches when viewing an ambiguous, bistable stimulus. However, no prior study has directly quantified how such neuronal noise relates to the rate of percept reversals. Specifically, it has remained unknown whether individual differences in complexity of resting-state oscillations—as reflected in long-range temporal correlations (LRTC)—are associated with perceptual stability. We hypothesized that participants with stronger resting-state LRTC in the alpha band experience more stable percepts, and thereby fewer perceptual switches. Furthermore, we expected that participants who report less discontinuous thoughts during rest, experience less switches. To test this, we recorded electroencephalography (EEG) in 65 healthy volunteers during 5 min Eyes-Closed Rest (ECR), after which they filled in the Amsterdam Resting-State Questionnaire (ARSQ). This was followed by three conditions where participants attended an ambiguous structure-from-motion stimulus—Neutral (passively observe the stimulus), Hold (the percept for as long as possible), and Switch (as often as possible). LRTC of resting-state alpha oscillations predicted the number of switches only in the Hold condition, with stronger LRTC associated with less switches. Contrary to our expectations, there was no association between resting-state Discontinuity of Mind and percept stability. Participants were capable of controlling switching according to task goals, and this was accompanied by increased alpha power during Hold and decreased power during Switch. Fewer switches were associated with stronger task-related alpha LRTC in all conditions. Together, our data suggest that bistable visual perception is to some extent under voluntary control and influenced by LRTC of alpha oscillations.
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Affiliation(s)
- Francesca Sangiuliano Intra
- IRCCS, Don Gnocchi Foundation, Milan, Italy.,Department of Integrative Neurophysiology, CNCR, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Arthur-Ervin Avramiea
- Department of Integrative Neurophysiology, CNCR, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Mona Irrmischer
- Department of Integrative Neurophysiology, CNCR, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | | | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, CNCR, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, CNCR, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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44
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Irrmischer M, Houtman SJ, Mansvelder HD, Tremmel M, Ott U, Linkenkaer‐Hansen K. Controlling the Temporal Structure of Brain Oscillations by Focused Attention Meditation. Hum Brain Mapp 2018; 39:1825-1838. [PMID: 29331064 PMCID: PMC6585826 DOI: 10.1002/hbm.23971] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 12/09/2017] [Accepted: 01/04/2018] [Indexed: 12/31/2022] Open
Abstract
Our focus of attention naturally fluctuates between different sources of information even when we desire to focus on a single object. Focused attention (FA) meditation is associated with greater control over this process, yet the neuronal mechanisms underlying this ability are not entirely understood. Here, we hypothesize that the capacity of attention to transiently focus and swiftly change relates to the critical dynamics emerging when neuronal systems balance at a point of instability between order and disorder. In FA meditation, however, the ability to stay focused is trained, which may be associated with a more homogeneous brain state. To test this hypothesis, we applied analytical tools from criticality theory to EEG in meditation practitioners and meditation-naïve participants from two independent labs. We show that in practitioners-but not in controls-FA meditation strongly suppressed long-range temporal correlations (LRTC) of neuronal oscillations relative to eyes-closed rest with remarkable consistency across frequency bands and scalp locations. The ability to reduce LRTC during meditation increased after one year of additional training and was associated with the subjective experience of fully engaging one's attentional resources, also known as absorption. Sustained practice also affected normal waking brain dynamics as reflected in increased LRTC during an eyes-closed rest state, indicating that brain dynamics are altered beyond the meditative state. Taken together, our findings suggest that the framework of critical brain dynamics is promising for understanding neuronal mechanisms of meditative states and, specifically, we have identified a clear electrophysiological correlate of the FA meditation state.
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Affiliation(s)
- Mona Irrmischer
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU AmsterdamAmsterdam1081 HVNetherlands
| | - Simon J. Houtman
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU AmsterdamAmsterdam1081 HVNetherlands
| | - Huibert D. Mansvelder
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU AmsterdamAmsterdam1081 HVNetherlands
| | - Michael Tremmel
- Bender Institute of Neuroimaging (BION), Justus Liebig University GiessenGiessen35394Germany
| | - Ulrich Ott
- Bender Institute of Neuroimaging (BION), Justus Liebig University GiessenGiessen35394Germany
| | - Klaus Linkenkaer‐Hansen
- Department of Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU AmsterdamAmsterdam1081 HVNetherlands
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45
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Munia TTK, Haider A, Schneider C, Romanick M, Fazel-Rezai R. A Novel EEG Based Spectral Analysis of Persistent Brain Function Alteration in Athletes with Concussion History. Sci Rep 2017; 7:17221. [PMID: 29222477 PMCID: PMC5722818 DOI: 10.1038/s41598-017-17414-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 11/21/2017] [Indexed: 11/09/2022] Open
Abstract
The neurocognitive sequelae of a sport-related concussion and its management are poorly defined. Detecting deficits are vital in making a decision about the treatment plan as it can persist one year or more following a brain injury. The reliability of traditional cognitive assessment tools is debatable, and thus attention has turned to assessments based on electroencephalogram (EEG) to evaluate subtle post-concussive alterations. In this study, we calculated neurocognitive deficits combining EEG analysis with three standard post-concussive assessment tools. Data were collected for all testing modalities from 21 adolescent athletes (seven concussive and fourteen healthy) in three different trials. For EEG assessment, along with linear frequency-based features, we introduced a set of time-frequency (Hjorth Parameters) and nonlinear features (approximate entropy and Hurst exponent) for the first time to explore post-concussive deficits. Besides traditional frequency-band analysis, we also presented a new individual frequency-based approach for EEG assessment. While EEG analysis exhibited significant discrepancies between the groups, none of the cognitive assessment resulted in significant deficits. Therefore, the evidence from the study highlights that our proposed EEG analysis and markers are more efficient at deciphering post-concussion residual neurocognitive deficits and thus has a potential clinical utility of proper concussion assessment and management.
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Affiliation(s)
- Tamanna T K Munia
- Department of Electrical Engineering, University of North Dakota, Grand Forks, 58202, USA
| | - Ali Haider
- Department of Electrical Engineering, University of North Dakota, Grand Forks, 58202, USA
| | - Charles Schneider
- Department of Electrical Engineering, University of North Dakota, Grand Forks, 58202, USA
| | - Mark Romanick
- Department of Physical Therapy, University of North Dakota, Grand Forks, 58202, USA
| | - Reza Fazel-Rezai
- Department of Electrical Engineering, University of North Dakota, Grand Forks, 58202, USA.
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46
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Attenuation of temporal correlations of neuronal oscillations in patients with mild spastic diplegia. Sci Rep 2017; 7:14966. [PMID: 29097718 PMCID: PMC5668314 DOI: 10.1038/s41598-017-14879-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Accepted: 10/19/2017] [Indexed: 11/08/2022] Open
Abstract
The aim of this study was to investigate the temporal correlations of neuronal oscillations in patients with mild spastic diplegia (MSD). Resting-state electroencephalography (EEG) was recorded from 15 male adolescent and young adult patients with MSD and 15 healthy controls. We characterized the temporal correlations of neuronal oscillations, both on long temporal scale (i.e., >1 second) and short-to-intermediate temporal scale (i.e., <≈1 second) using detrended fluctuation analysis (DFA) and an analysis of the life- and waiting-time statistics of oscillation bursts respectively. The DFA exponents at alpha and beta bands, the life-time biomarker of alpha oscillation, and the life- and waiting-time biomarkers of beta oscillation were significantly attenuated in the patients compared with controls. Moreover, altered scalp distributions of some temporal correlation measures were found at alpha and beta bands in these patients. All these findings suggest that MSD is associated with highly volatile neuronal states of alpha and beta oscillations on short-to-intermediate and much longer time scales, which may be related to cognitive dysfunction in patients with MSD.
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47
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Vlaskamp C, Poil SS, Jansen F, Linkenkaer-Hansen K, Durston S, Oranje B, Bruining H. Bumetanide As a Candidate Treatment for Behavioral Problems in Tuberous Sclerosis Complex. Front Neurol 2017; 8:469. [PMID: 28943860 PMCID: PMC5596068 DOI: 10.3389/fneur.2017.00469] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 08/25/2017] [Indexed: 11/22/2022] Open
Abstract
Background Recent studies indicate excitatory GABA action in and around tubers in patients with tuberous sclerosis complex (TSC). This may contribute to recurrent seizures and behavioral problems that may be treated by agents that enhance GABAergic transmission by influencing chloride regulation. Case presentation Here, we used the chloride transporter antagonist bumetanide to treat a female adolescent TSC patient with refractory seizures, sensory hyper-reactivity, and a variety of repetitive and compulsive behaviors. Methods To evaluate the effect of bumetanide on behavior, auditory sensory processing, and hyperexcitability, we obtained questionnaire data, event-related potentials (ERP), and resting state EEG at baseline, after 3 and 6 months of treatment and after 1 month washout period. Discussion Six months of treatment resulted in a marked improvement in all relevant behavioral domains, as was substantiated by the parent questionnaires. In addition, resting-state electroencephalography and ERP suggested a favorable effect of bumetanide on hyperexcitability and sensory processing. These findings encourage further studies of bumetanide on neuropsychiatric outcome in TSC.
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Affiliation(s)
- Chantal Vlaskamp
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands
| | | | - Floor Jansen
- Department of Child Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands
| | | | - Sarah Durston
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Bob Oranje
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Hilgo Bruining
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands
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48
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Hou D, Wang C, Chen Y, Wang W, Du J. Long-range temporal correlations of broadband EEG oscillations for depressed subjects following different hemispheric cerebral infarction. Cogn Neurodyn 2017; 11:529-538. [PMID: 29147145 DOI: 10.1007/s11571-017-9451-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Revised: 07/10/2017] [Accepted: 08/16/2017] [Indexed: 02/07/2023] Open
Abstract
Abnormal long-range temporal correlation (LRTC) in EEG oscillation has been observed in several brain pathologies and mental disorders. This study examined the relationship between the LRTC of broadband EEG oscillation and depression following cerebral infarction with different hemispheric lesions to provide a novel insight into such depressive disorders. Resting EEGs of 16 channels in 18 depressed (9 left and 9 right lesions) and 21 non-depressed (11 left and 10 right lesions) subjects following cerebral infarction and 19 healthy control subjects were analysed by means of detrended fluctuation analysis, a quantitative measurement of LRTC. The difference among groups and the correlation between the severity of depression and LRTC in EEG oscillation were investigated by statistical analysis. The results showed that LRTC of broadband EEG oscillations in depressive subjects was still preserved but attenuated in right hemispheric lesion subjects especially in left pre-frontal and right inferior frontal and posterior temporal regions. Moreover, an association between the severity of psychiatric symptoms and the attenuation of the LRTC was found in frontal, central and temporal regions for stroke subjects with right lesions. A high discriminating ability of the LRTC in the frontal and central regions to distinguish depressive from non-depressive subjects suggested potential feasibility for LRTC as an assessment indicator for depression following right hemispheric cerebral infarction. Different performance of temporal correlation in depressed subjects following the two hemispheric lesions implied complex association between depression and stroke lesion location.
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Affiliation(s)
- Dongzhe Hou
- Neurorehabilitation Department, Tianjin Huanhu Hospital, Tianjin, People's Republic of China
| | - Chunfang Wang
- Rehabilitation Medical Department, Tianjin Union Medical Center, Tianjin, 300121 People's Republic of China.,Rehabilitation Medical Research Center of Tianjin, Tianjin, 300121 People's Republic of China
| | - Yuanyuan Chen
- Lab of Neural Engineering and Rehabilitation, Department of Biomedical Engineering, Tianjin University, Tianjin, People's Republic of China
| | - Weijie Wang
- Tayside Orthopaedics and Rehabilitation Technology Centre, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Jingang Du
- Rehabilitation Medical Department, Tianjin Union Medical Center, Tianjin, 300121 People's Republic of China.,Rehabilitation Medical Research Center of Tianjin, Tianjin, 300121 People's Republic of China
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49
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Gärtner M, Irrmischer M, Winnebeck E, Fissler M, Huntenburg JM, Schroeter TA, Bajbouj M, Linkenkaer-Hansen K, Nikulin VV, Barnhofer T. Aberrant Long-Range Temporal Correlations in Depression Are Attenuated after Psychological Treatment. Front Hum Neurosci 2017; 11:340. [PMID: 28701943 PMCID: PMC5488389 DOI: 10.3389/fnhum.2017.00340] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 06/12/2017] [Indexed: 01/21/2023] Open
Abstract
The spontaneous oscillatory activity in the human brain shows long-range temporal correlations (LRTC) that extend over time scales of seconds to minutes. Previous research has demonstrated aberrant LRTC in depressed patients; however, it is unknown whether the neuronal dynamics normalize after psychological treatment. In this study, we recorded EEG during eyes-closed rest in depressed patients (N = 71) and healthy controls (N = 25), and investigated the temporal dynamics in depressed patients at baseline, and after attending either a brief mindfulness training or a stress reduction training. Compared to the healthy controls, depressed patients showed stronger LRTC in theta oscillations (4-7 Hz) at baseline. Following the psychological interventions both groups of patients demonstrated reduced LRTC in the theta band. The reduction of theta LRTC differed marginally between the groups, and explorative analyses of separate groups revealed noteworthy topographic differences. A positive relationship between the changes in LRTC, and changes in depressive symptoms was observed in the mindfulness group. In summary, our data show that aberrant temporal dynamics of ongoing oscillations in depressive patients are attenuated after treatment, and thus may help uncover the mechanisms with which psychotherapeutic interventions affect the brain.
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Affiliation(s)
- Matti Gärtner
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Benjamin FranklinBerlin, Germany
| | - Mona Irrmischer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit AmsterdamAmsterdam, Netherlands
| | - Emilia Winnebeck
- Dahlem Center for Neuroimaging of Emotions, Freie Universität BerlinBerlin, Germany
| | - Maria Fissler
- Dahlem Center for Neuroimaging of Emotions, Freie Universität BerlinBerlin, Germany
| | - Julia M Huntenburg
- Dahlem Center for Neuroimaging of Emotions, Freie Universität BerlinBerlin, Germany
| | - Titus A Schroeter
- Dahlem Center for Neuroimaging of Emotions, Freie Universität BerlinBerlin, Germany
| | - Malek Bajbouj
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Benjamin FranklinBerlin, Germany
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit AmsterdamAmsterdam, Netherlands
| | - Vadim V Nikulin
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Benjamin FranklinBerlin, Germany.,Center for Cognition and Decision Making, National Research University Higher School of EconomicsMoscow, Russia.,Department of Neurology and Clinical Neurophysiology, Charité-Universitätsmedizin Berlin, Campus Benjamin FranklinBerlin, Germany
| | - Thorsten Barnhofer
- Dahlem Center for Neuroimaging of Emotions, Freie Universität BerlinBerlin, Germany
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50
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Simola J, Zhigalov A, Morales-Muñoz I, Palva JM, Palva S. Critical dynamics of endogenous fluctuations predict cognitive flexibility in the Go/NoGo task. Sci Rep 2017; 7:2909. [PMID: 28588303 PMCID: PMC5460255 DOI: 10.1038/s41598-017-02750-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Accepted: 04/18/2017] [Indexed: 12/11/2022] Open
Abstract
Fluctuations with power-law scaling and long-range temporal correlations (LRTCs) are characteristic to human psychophysical performance. Systems operating in a critical state exhibit such LRTCs, but phenomenologically similar fluctuations and LRTCs may also be caused by slow decay of the system’s memory without the system being critical. Theoretically, criticality endows the system with the greatest representational capacity and flexibility in state transitions. Without criticality, however, slowly decaying system memory would predict inflexibility. We addressed these contrasting predictions of the ‘criticality’ and ‘long-memory’ candidate mechanisms of human behavioral LRTCs by using a Go/NoGo task wherein the commission errors constitute a measure of cognitive flexibility. Response time (RT) fluctuations in this task exhibited power-law frequency scaling, autocorrelations, and LRTCs. We show here that the LRTC scaling exponents, quantifying the strength of long-range correlations, were negatively correlated with the commission error rates. Strong LRTCs hence parallel optimal cognitive flexibility and, in line with the criticality hypothesis, indicate a functionally advantageous state. This conclusion was corroborated by a positive correlation between the LRTC scaling exponents and executive functions measured with the Rey-Osterrieth Complex Figure test. Our results hence support the notion that LRTCs arise from critical dynamics that is functionally significant for human cognitive performance.
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Affiliation(s)
- Jaana Simola
- Helsinki Institute for Lifesciences, Neuroscience Center, University of Helsinki, P.O. Box 56 (Viikinkaari 4), FI-00014, Helsinki, Finland.
| | - Alexander Zhigalov
- Helsinki Institute for Lifesciences, Neuroscience Center, University of Helsinki, P.O. Box 56 (Viikinkaari 4), FI-00014, Helsinki, Finland
| | - Isabel Morales-Muñoz
- Helsinki Institute for Lifesciences, Neuroscience Center, University of Helsinki, P.O. Box 56 (Viikinkaari 4), FI-00014, Helsinki, Finland
| | - J Matias Palva
- Helsinki Institute for Lifesciences, Neuroscience Center, University of Helsinki, P.O. Box 56 (Viikinkaari 4), FI-00014, Helsinki, Finland
| | - Satu Palva
- Helsinki Institute for Lifesciences, Neuroscience Center, University of Helsinki, P.O. Box 56 (Viikinkaari 4), FI-00014, Helsinki, Finland.
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