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Zhao CL, Hou W, Jia Y, Sahakian BJ, Luo Q. Sex differences of signal complexity at resting-state functional magnetic resonance imaging and their associations with the estrogen-signaling pathway in the brain. Cogn Neurodyn 2024; 18:973-986. [PMID: 38826661 PMCID: PMC11143120 DOI: 10.1007/s11571-023-09954-y] [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: 10/06/2022] [Revised: 01/27/2023] [Accepted: 03/08/2023] [Indexed: 06/04/2024] Open
Abstract
Sex differences in the brain have been widely reported and may hold the key to elucidating sex differences in many medical conditions and drug response. However, the molecular correlates of these sex differences in structural and functional brain measures in the human brain remain unclear. Herein, we used sample entropy (SampEn) to quantify the signal complexity of resting-state functional magnetic resonance imaging (rsfMRI) in a large neuroimaging cohort (N = 1,642). The frontoparietal control network and the cingulo-opercular network had high signal complexity while the cerebellar and sensory motor networks had low signal complexity in both men and women. Compared with those in male brains, we found greater signal complexity in all functional brain networks in female brains with the default mode network exhibiting the largest sex difference. Using the gene expression data in brain tissues, we identified genes that were significantly associated with sex differences in brain signal complexity. The significant genes were enriched in the gene sets that were differentially expressed between the brain cortex and other tissues, the estrogen-signaling pathway, and the biological function of neural plasticity. In particular, the G-protein-coupled estrogen receptor 1 gene in the estrogen-signaling pathway was expressed more in brain regions with greater sex differences in SampEn. In conclusion, greater complexity in female brains may reflect the interactions between sex hormone fluctuations and neuromodulation of estrogen in women. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-023-09954-y.
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Affiliation(s)
- Cheng-li Zhao
- College of Science, National University of Defense Technology, Changsha, 410073 China
| | - Wenjie Hou
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433 China
- Center for Computational Psychiatry, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Human Phenome Institute, Fudan University, Shanghai, 200438 China
| | - Yanbing Jia
- School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, 471000 China
| | - Barbara J. Sahakian
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ UK
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB UK
| | - the DIRECT Consortium
- College of Science, National University of Defense Technology, Changsha, 410073 China
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433 China
- Center for Computational Psychiatry, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Human Phenome Institute, Fudan University, Shanghai, 200438 China
- School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, 471000 China
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ UK
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB UK
| | - Qiang Luo
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433 China
- Center for Computational Psychiatry, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Human Phenome Institute, Fudan University, Shanghai, 200438 China
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2
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Xin X, Yu J, Gao X. The brain entropy dynamics in resting state. Front Neurosci 2024; 18:1352409. [PMID: 38595975 PMCID: PMC11002175 DOI: 10.3389/fnins.2024.1352409] [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: 12/08/2023] [Accepted: 03/08/2024] [Indexed: 04/11/2024] Open
Abstract
As a novel measure for irregularity and complexity of the spontaneous fluctuations of brain activities, brain entropy (BEN) has attracted much attention in resting-state functional magnetic resonance imaging (rs-fMRI) studies during the last decade. Previous studies have shown its associations with cognitive and mental functions. While most previous research assumes BEN is approximately stationary during scan sessions, the brain, even at its resting state, is a highly dynamic system. Such dynamics could be characterized by a series of reoccurring whole-brain patterns related to cognitive and mental processes. The present study aims to explore the time-varying feature of BEN and its potential links with general cognitive ability. We adopted a sliding window approach to derive the dynamical brain entropy (dBEN) of the whole-brain functional networks from the HCP (Human Connectome Project) rs-fMRI dataset that includes 812 young healthy adults. The dBEN was further clustered into 4 reoccurring BEN states by the k-means clustering method. The fraction window (FW) and mean dwell time (MDT) of one BEN state, characterized by the extremely low overall BEN, were found to be negatively correlated with general cognitive abilities (i.e., cognitive flexibility, inhibitory control, and processing speed). Another BEN state, characterized by intermediate overall BEN and low within-state BEN located in DMN, ECN, and part of SAN, its FW, and MDT were positively correlated with the above cognitive abilities. The results of our study advance our understanding of the underlying mechanism of BEN dynamics and provide a potential framework for future investigations in clinical populations.
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Affiliation(s)
- Xiaoyang Xin
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
- Preschool College, Luoyang Normal University, Luoyang, China
| | - Jiaqian Yu
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
| | - Xiaoqing Gao
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
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Liu H, Gao W, Cao W, Meng Q, Xu L, Kuang L, Guo Y, Cui D, Qiu J, Jiao Q, Su L, Lu G. Immediate visual reproduction negatively correlates with brain entropy of parahippocampal gyrus and inferior occipital gyrus in bipolar II disorder adolescents. BMC Psychiatry 2023; 23:515. [PMID: 37464363 DOI: 10.1186/s12888-023-05012-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 07/07/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND Brain entropy reveals complexity and irregularity of brain, and it has been proven to reflect brain complexity alteration in disease states. Previous studies found that bipolar disorder adolescents showed cognitive impairment. The relationship between complexity of brain neural activity and cognition of bipolar II disorder (BD-II) adolescents remains unclear. METHODS Nineteen BD-II patients (14.63 ±1.57 years old) and seventeen age-gender matched healthy controls (HCs) (14.18 ± 1.51 years old) were enlisted. Entropy values of all voxels of the brain in resting-state functional MRI data were calculated and differences of them between BD-II and HC groups were evaluated. After that, correlation analyses were performed between entropy values of brain regions showing significant entropy differences and clinical indices in BD-II adolescents. RESULTS Significant differences were found in scores of immediate visual reproduction subtest (VR-I, p = 0.003) and Stroop color-word test (SCWT-1, p = 0.015; SCWT-2, p = 0.004; SCWT-3, p = 0.003) between the two groups. Compared with HCs, BD-II adolescents showed significant increased brain entropy in right parahippocampal gyrus and right inferior occipital gyrus. Besides, significant negative correlations between brain entropy values of right parahippocampal gyrus, right inferior occipital gyrus and immediate visual reproduction subtest scores were observed in BD-II adolescents. CONCLUSIONS The findings of the present study suggested that the disrupted function of corticolimbic system is related with cognitive abnormality of BD-II adolescents. And from the perspective temporal dynamics of brain system, the current study, brain entropy may provide available evidences for understanding the underlying neural mechanism in BD-II adolescents.
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Affiliation(s)
- Haiqin Liu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Weijia Gao
- Department of Child Psychology, The Children' s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Weifang Cao
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Qingmin Meng
- Department of interventional radiology, Taian Central Hospital, Tai'an, China
| | - Longchun Xu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, China
| | - Liangfeng Kuang
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Yongxin Guo
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Dong Cui
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Jianfeng Qiu
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Qing Jiao
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, China.
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China.
| | - Linyan Su
- Key Laboratory of Psychiatry and Mental Health of Hunan Province, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, China
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Yurchenko SB. A systematic approach to brain dynamics: cognitive evolution theory of consciousness. Cogn Neurodyn 2023; 17:575-603. [PMID: 37265655 PMCID: PMC10229528 DOI: 10.1007/s11571-022-09863-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/29/2022] [Accepted: 07/21/2022] [Indexed: 12/18/2022] Open
Abstract
The brain integrates volition, cognition, and consciousness seamlessly over three hierarchical (scale-dependent) levels of neural activity for their emergence: a causal or 'hard' level, a computational (unconscious) or 'soft' level, and a phenomenal (conscious) or 'psyche' level respectively. The cognitive evolution theory (CET) is based on three general prerequisites: physicalism, dynamism, and emergentism, which entail five consequences about the nature of consciousness: discreteness, passivity, uniqueness, integrity, and graduation. CET starts from the assumption that brains should have primarily evolved as volitional subsystems of organisms, not as prediction machines. This emphasizes the dynamical nature of consciousness in terms of critical dynamics to account for metastability, avalanches, and self-organized criticality of brain processes, then coupling it with volition and cognition in a framework unified over the levels. Consciousness emerges near critical points, and unfolds as a discrete stream of momentary states, each volitionally driven from oldest subcortical arousal systems. The stream is the brain's way of making a difference via predictive (Bayesian) processing. Its objective observables could be complexity measures reflecting levels of consciousness and its dynamical coherency to reveal how much knowledge (information gain) the brain acquires over the stream. CET also proposes a quantitative classification of both disorders of consciousness and mental disorders within that unified framework.
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The Perturbational Map of Low Frequency Repetitive Transcranial Magnetic Stimulation of Primary Motor Cortex in Movement Disorders. BRAIN DISORDERS 2023. [DOI: 10.1016/j.dscb.2023.100071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
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6
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Qin Y, Mahdavi A, Bertschy M, Anderson PM, Kulikova S, Pinault D. The psychotomimetic ketamine disrupts the transfer of late sensory information in the corticothalamic network. Eur J Neurosci 2023; 57:440-455. [PMID: 36226598 PMCID: PMC10092610 DOI: 10.1111/ejn.15845] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/17/2022] [Accepted: 09/01/2022] [Indexed: 02/04/2023]
Abstract
In prodromal and early schizophrenia, disorders of attention and perception are associated with structural and chemical brain abnormalities and with dysfunctional corticothalamic networks exhibiting disturbed brain rhythms. The underlying mechanisms are elusive. The non-competitive NMDA receptor antagonist ketamine simulates the symptoms of prodromal and early schizophrenia, including disturbances in ongoing and task & sensory-related broadband beta-/gamma-frequency (17-29 Hz/30-80 Hz) oscillations in corticothalamic networks. In normal healthy subjects and rodents, complex integration processes, like sensory perception, induce transient, large-scale synchronised beta/gamma oscillations in a time window of a few hundred ms (200-700 ms) after the presentation of the object of attention (e.g., sensory stimulation). Our goal was to use an electrophysiological multisite network approach to investigate, in lightly anesthetised rats, the effects of a single psychotomimetic dose (2.5 mg/kg, subcutaneous) of ketamine on sensory stimulus-induced oscillations. Ketamine transiently increased the power of baseline beta/gamma oscillations and decreased sensory-induced beta/gamma oscillations. In addition, it disrupted information transferability in both the somatosensory thalamus and the related cortex and decreased the sensory-induced thalamocortical connectivity in the broadband gamma range. The present findings support the hypothesis that NMDA receptor antagonism disrupts the transfer of perceptual information in the somatosensory cortico-thalamo-cortical system.
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Affiliation(s)
- Yi Qin
- Université de Strasbourg, Strasbourg, France
- INSERM U1114, Neuropsychologie cognitive et physiopathologie de la schizophrénie, Strasbourg, France
- Fédération de Médecine Translationnelle de Strasbourg (FMTS), Faculté de médecine, Strasbourg, France
- Centre de Recherche en Biomédecine de Strasbourg (CRBS), Strasbourg, France
- Netherlands Institute for Neuroscience, The Netherlands
| | - Ali Mahdavi
- Université de Strasbourg, Strasbourg, France
- INSERM U1114, Neuropsychologie cognitive et physiopathologie de la schizophrénie, Strasbourg, France
- Fédération de Médecine Translationnelle de Strasbourg (FMTS), Faculté de médecine, Strasbourg, France
- Centre de Recherche en Biomédecine de Strasbourg (CRBS), Strasbourg, France
- The University of Freiburg, Bernstein Center Freiburg, Freiburg, Germany
| | - Marine Bertschy
- Université de Strasbourg, Strasbourg, France
- INSERM U1114, Neuropsychologie cognitive et physiopathologie de la schizophrénie, Strasbourg, France
- Fédération de Médecine Translationnelle de Strasbourg (FMTS), Faculté de médecine, Strasbourg, France
- Centre de Recherche en Biomédecine de Strasbourg (CRBS), Strasbourg, France
| | - Paul M Anderson
- Dept. Cognitive Neurobiology, Center for Brain Research, Medical University Vienna, Austria
| | - Sofya Kulikova
- National Research University Higher School of Economics, Perm, Russia
| | - Didier Pinault
- Université de Strasbourg, Strasbourg, France
- INSERM U1114, Neuropsychologie cognitive et physiopathologie de la schizophrénie, Strasbourg, France
- Fédération de Médecine Translationnelle de Strasbourg (FMTS), Faculté de médecine, Strasbourg, France
- Centre de Recherche en Biomédecine de Strasbourg (CRBS), Strasbourg, France
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7
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Progressive brain abnormalities in schizophrenia across different illness periods: a structural and functional MRI study. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:2. [PMID: 36604437 PMCID: PMC9816110 DOI: 10.1038/s41537-022-00328-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 11/16/2022] [Indexed: 01/07/2023]
Abstract
Schizophrenia is a chronic brain disorder, and neuroimaging abnormalities have been reported in different stages of the illness for decades. However, when and how these brain abnormalities occur and evolve remains undetermined. We hypothesized structural and functional brain abnormalities progress throughout the illness course at different rates in schizophrenia. A total of 115 patients with schizophrenia were recruited and stratified into three groups of different illness periods: 5-year group (illness duration: ≤5 years), 15-year group (illness duration: 12-18 years), and 25-year group (illness duration: ≥25 years); 230 healthy controls were matched by age and sex to the three groups, respectively. All participants underwent resting-state MRI scanning. Each group of patients with schizophrenia was compared with the corresponding controls in terms of voxel-based morphometry (VBM), fractional anisotropy (FA), global functional connectivity density (gFCD), and sample entropy (SampEn) abnormalities. In the 5-year group we observed only SampEn abnormalities in the putamen. In the 15-year group, we observed VBM abnormalities in the insula and cingulate gyrus and gFCD abnormalities in the temporal cortex. In the 25-year group, we observed FA abnormalities in nearly all white matter tracts, and additional VBM and gFCD abnormalities in the frontal cortex and cerebellum. By using two structural and two functional MRI analysis methods, we demonstrated that individual functional abnormalities occur in limited brain areas initially, functional connectivity and gray matter density abnormalities ensue later in wider brain areas, and structural connectivity abnormalities involving almost all white matter tracts emerge in the third decade of the course in schizophrenia.
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8
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Yurchenko SB. From the origins to the stream of consciousness and its neural correlates. Front Integr Neurosci 2022; 16:928978. [PMID: 36407293 PMCID: PMC9672924 DOI: 10.3389/fnint.2022.928978] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 10/12/2022] [Indexed: 09/22/2023] Open
Abstract
There are now dozens of very different theories of consciousness, each somehow contributing to our understanding of its nature. The science of consciousness needs therefore not new theories but a general framework integrating insights from those, yet not making it a still-born "Frankenstein" theory. First, the framework must operate explicitly on the stream of consciousness, not on its static description. Second, this dynamical account must also be put on the evolutionary timeline to explain the origins of consciousness. The Cognitive Evolution Theory (CET), outlined here, proposes such a framework. This starts with the assumption that brains have primarily evolved as volitional subsystems of organisms, inherited from primitive (fast and random) reflexes of simplest neural networks, only then resembling error-minimizing prediction machines. CET adopts the tools of critical dynamics to account for metastability, scale-free avalanches, and self-organization which are all intrinsic to brain dynamics. This formalizes the stream of consciousness as a discrete (transitive, irreflexive) chain of momentary states derived from critical brain dynamics at points of phase transitions and mapped then onto a state space as neural correlates of a particular conscious state. The continuous/discrete dichotomy appears naturally between the brain dynamics at the causal level and conscious states at the phenomenal level, each volitionally triggered from arousal centers of the brainstem and cognitively modulated by thalamocortical systems. Their objective observables can be entropy-based complexity measures, reflecting the transient level or quantity of consciousness at that moment.
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Kung YC, Li CW, Hsiao FC, Tsai PJ, Chen S, Li MK, Lee HC, Chang CY, Wu CW, Lin CP. Cross-Scale Dynamicity of Entropy and Connectivity in the Sleeping Brain. Brain Connect 2022; 12:835-845. [PMID: 35343241 PMCID: PMC9839343 DOI: 10.1089/brain.2021.0174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Introduction: The concept of local sleep refers to the phenomenon of local brain activity that modifies neural networks during unresponsive global sleep. Such network rewiring may differ across spatial scales; however, the global and local alterations in brain systems remain elusive in human sleep. Materials and Methods: We examined cross-scale changes of brain networks in sleep. Functional magnetic resonance imaging data were acquired from 28 healthy participants during nocturnal sleep. We adopted both metrics of connectivity (functional connectivity [FC] and regional homogeneity [ReHo]) and complexity (multiscale entropy) to explore the global and local functionality of the neural assembly across nonrapid eye movement sleep stages. Results: Long-range FC decreased with sleep depth, whereas local ReHo peaked at the N2 stage and reached its lowest level at the N3 stage. Entropy exhibited a general decline at the local scale (Scale 1) as sleep deepened, whereas the coarse-scale entropy (Scale 3) was consistent across stages. Discussion: The negative correlation between Scale-1 entropy and ReHo reflects the enhanced signal regularity and synchronization in sleep, identifying the information exchange at the local scale. The N2 stage showed a distinctive pattern toward local information processing with scrambled long-distance information exchange, indicating a specific time window for network reorganization. Collectively, the multidimensional metrics indicated an imbalanced global-local relationship among brain functional networks across sleep-wake stages.
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Affiliation(s)
- Yi-Chia Kung
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Chia-Wei Li
- Department of Radiology, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Fan-Chi Hsiao
- Department of Counseling and Industrial/Organizational Psychology, Ming Chuan University, Taoyuan, Taiwan
| | - Pei-Jung Tsai
- Neuroimaging Research Branch, National Institute on Drug Abuse, Baltimore, Maryland, USA
| | - Shuo Chen
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Ming-Kang Li
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | - Hsin-Chien Lee
- Department of Psychiatry, Taipei Medical University Hospital, Taipei, Taiwan
| | - Chun-Yen Chang
- Science Education Center, National Taiwan Normal University, Taipei, Taiwan
| | - Changwei W. Wu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Center, Shuang-Ho Hospital,Taipei Medical University, New Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
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Chen X, Zhou A, Li J, Chen B, Zhou X, Ma H, Lu C, Weng X. Effects of Long-Term Exposure to 2260 m Altitude on Working Memory and Resting-State Activity in the Prefrontal Cortex: A Large-Sample Cross-Sectional Study. Brain Sci 2022; 12:brainsci12091148. [PMID: 36138884 PMCID: PMC9496949 DOI: 10.3390/brainsci12091148] [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: 06/26/2022] [Revised: 08/06/2022] [Accepted: 08/25/2022] [Indexed: 11/16/2022] Open
Abstract
It has been well established that very-high-altitude (>4000 m) environments can affect human cognitive function and brain activity. However, the effects of long-term exposure to moderate altitudes (2000−3000 m) on cognitive function and brain activity are not well understood. In the present cross-sectional study, we utilized an N-back working memory task and resting-state functional near-infrared spectroscopy to examine the effects of two years of exposure to 2260 m altitude on working memory and resting-state brain activity in 208 college students, compared with a control group at the sea level. The results showed that there was no significant change in spatial working memory performance after two years of exposure to 2260 m altitude. In contrast, the analysis of resting-state brain activity revealed changes in functional connectivity patterns in the prefrontal cortex (PFC), with the global efficiency increased and the local efficiency decreased after two years of exposure to 2260 m altitude. These results suggest that long-term exposure to moderate altitudes has no observable effect on spatial working memory performance, while significant changes in functional connectivity and brain network properties could possibly occur to compensate for the effects of mild hypoxic environments. To our knowledge, this study is the first to examine the resting state activity in the PFC associated with working memory in people exposed to moderate altitudes.
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Affiliation(s)
- Xin Chen
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou 510631, China
- School of Psychology, South China Normal University, Guangzhou 510631, China
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
- Research Center of Plateau Brain Science, Tibet University/South China University, Guangzhou 510631, China
| | - Aibao Zhou
- College of Psychology, Northwest Normal University, Lanzhou 730070, China
| | - Junle Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Bing Chen
- Jing Hengyi School of Education, Hangzhou Normal University, Hangzhou 311121, China
| | - Xin Zhou
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 311121, China
| | - Hailin Ma
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa 850012, China
| | - Chunming Lu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Faculty of Psychology, Beijing Normal University, Beijing 100875, China
- Correspondence: (C.L.); (X.W.)
| | - Xuchu Weng
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou 510631, China
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
- Research Center of Plateau Brain Science, Tibet University/South China University, Guangzhou 510631, China
- Correspondence: (C.L.); (X.W.)
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Ji S, Zhang Y, Chen N, Liu X, Li Y, Shao X, Yang Z, Yao Z, Hu B. Shared increased entropy of brain signals across patients with different mental illnesses: A coordinate-based activation likelihood estimation meta-analysis. Brain Imaging Behav 2022; 16:336-343. [PMID: 34997426 DOI: 10.1007/s11682-021-00507-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/15/2021] [Indexed: 11/25/2022]
Abstract
Entropy is a measurement of brain signal complexity. Studies have found increased/decreased entropy of brain signals in psychiatric patients. There is no consistent conclusion regarding the relationship between the entropy of brain signals and mental illness. Therefore, this meta-analysis aimed to identify consistent abnormalities in the brain signal entropy in patients with different mental illnesses. We conducted a systematic search to collect resting-state functional magnetic resonance imaging (rs-fMRI) studies in patients with psychiatric disorders. This work identified 9 eligible rs-fMRI studies, which included a total of 14 experiments, 67 activation foci, and 1383 subjects. We tested the convergence across their findings by using the activation likelihood estimation method. P-value maps were corrected by using cluster-level family-wise error p < 0.05 and permuting 2000 times. Results showed that patients with different psychiatric disorders shared commonly increased entropy of brain signals in the left inferior and middle frontal gyri, and the right fusiform gyrus, cuneus, precuneus. No shared alterations were found in the subcortical regions and cerebellum in the patient group. Our findings suggested that the increased entropy of brain signals in the cortex, not subcortical regions and cerebellum, might have associations with the pathophysiology across mental illnesses. This meta-analysis study provided the first comprehensive understanding of the abnormality in brain signal complexity across patients with different psychiatric disorders.
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Affiliation(s)
- Shanling Ji
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Gansu Province, 730000, Lanzhou, China
| | - Yinghui Zhang
- Mental Health Center Hospital of Guangyuan, Guangyuan, China
| | - Nan Chen
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Gansu Province, 730000, Lanzhou, China
| | - Xia Liu
- School of Computer Science, Qinghai Normal University, Xining, China
| | - Yongchao Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Gansu Province, 730000, Lanzhou, China
| | - Xuexiao Shao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Gansu Province, 730000, Lanzhou, China
| | - Zhengwu Yang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Gansu Province, 730000, Lanzhou, China
| | - Zhijun Yao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Gansu Province, 730000, Lanzhou, China.
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Gansu Province, 730000, Lanzhou, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
- Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors, Chinese Academy of Sciences, Lanzhou, China.
- Engineering Research Center of Open Source Software and Real-Time System, (Lanzhou University), Ministry of Education, Lanzhou, Gansu Province, 730000, China.
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12
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Xin X, Feng Y, Zang Y, Lou Y, Yao K, Gao X. Multivariate Classification of Brain Blood-Oxygen Signal Complexity for the Diagnosis of Children with Tourette Syndrome. Mol Neurobiol 2022; 59:1249-1261. [PMID: 34981418 DOI: 10.1007/s12035-021-02707-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 12/17/2021] [Indexed: 10/19/2022]
Abstract
Tourette syndrome (TS) is a childhood-onset neuropsychiatric disorder characterized by the presence of multiple motor and vocal tics. Because of its varied clinical expressions and lack of reliable diagnostic biomarker, present TS diagnosis still depends on qualitative descriptions of symptoms. Our study aimed to investigate whether the complexity of resting state brain activity can serve as a potential biomarker for TS diagnosis, since it has been used successfully in various neuropsychiatric disorders, including two common TS comorbidities: attention-deficit hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD). In the current study, we used both univariate analysis and multivariate searchlight analysis with both linear and non-linear classification methods to explore the group differences in the complexity of resting state brain blood oxygen level-dependent (BOLD) signals between 25 TS boys without comorbidity and 25 sex, age and educational years matched healthy controls (HCs). We also investigated the relation between symptom severity in TS patients (YGTSS scores) and complexity indices derived from different analysis methods. We found: i) univariate analysis revealed reduced complexity in TS patients in the left cerebellum, left superior frontal gyrus, and left medial frontal gyrus; ii) multivariate analysis with non-linear classification method achieved the highest performance (accuracy: 0.94, sensitivity: 0.96, specificity: 0.92, AUC: 0.95) in bilateral supplementary motor areas; iii) significant correlations were found between complexity index derived from multivariate analysis with non-linear classification method and Tic severity (YGTSS scores) in the left cerebellum (r = 0.523, with YGTSS phonic) and in the right supplementary motor area (r = 0.767, with YGTSS motor). Taken together, these results suggested that complexity of resting state BOLD activity is a highly effective index for differentiating TS patients from normal controls. It has a good potential to be a quantitative biomarker for TS diagnosis.
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Affiliation(s)
- Xiaoyang Xin
- Center for Psychological Sciences, Zhejiang University, Hangzhou, 310027, China
| | - Yixuan Feng
- Eye Center of the 2Nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China.,Zhejiang Provincial Key Lab of Ophthalmology, Hangzhou, 310009, China
| | - Yufeng Zang
- Center for Cognition and Brain Disorders and the Affiliated Hospital, Hangzhou Normal University, Hangzhou, 210015, China
| | - Yuting Lou
- Department of Pediatrics, School of Medicine, the Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China
| | - Ke Yao
- Eye Center of the 2Nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China. .,Zhejiang Provincial Key Lab of Ophthalmology, Hangzhou, 310009, China.
| | - Xiaoqing Gao
- Center for Psychological Sciences, Zhejiang University, Hangzhou, 310027, China.
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13
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Lee YJ, Huang SY, Lin CP, Tsai SJ, Yang AC. Alteration of power law scaling of spontaneous brain activity in schizophrenia. Schizophr Res 2021; 238:10-19. [PMID: 34562833 DOI: 10.1016/j.schres.2021.08.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/04/2021] [Accepted: 08/23/2021] [Indexed: 10/20/2022]
Abstract
Nonlinear dynamical analysis has been used to quantify the complexity of brain signal at temporal scales. Power law scaling is a well-validated method in physics that has been used to describe the dynamics of a system in the frequency domain, ranging from noisy oscillation to complex fluctuations. In this research, we investigated the power-law characteristics in a large-scale resting-state fMRI data of schizophrenia and healthy participants derived from Taiwan Aging and Mental Illness cohort. We extracted the power spectral density (PSD) of resting signal by Fourier transform. Power law scaling of PSD was estimated by determining the slope of the regression line fitting to the logarithm of PSD. t-Test was used to assess the statistical difference in power law scaling between schizophrenia and healthy participants. The significant differences in power law scaling were found in six brain regions. Schizophrenia patients have significantly more positive power law scaling (i.e., more homogenous frequency components) at four brain regions: left precuneus, left medial dorsal nucleus, right inferior frontal gyrus, and right middle temporal gyrus and less positive power law scaling (i.e., more dominant at lower frequency range) in bilateral putamen compared with healthy participants. Moreover, significant correlations of power law scaling with the severity of psychosis were found. These findings suggest that schizophrenia has abnormal brain signal complexity linked to psychotic symptoms. The power law scaling represents the dynamical properties of resting-state fMRI signal may serve as a novel functional brain imaging marker for evaluating patients with mental illness.
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Affiliation(s)
- Yi-Ju Lee
- Taiwan International Graduate Program in Interdisciplinary Neuroscience, National Yang Ming Chiao Tung University and Academia Sinica, Taipei, Taiwan; Laboratory of Precision Psychiatry, Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Su-Yun Huang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Laboratory of Precision Psychiatry, Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Brain Science and Digital Medicine Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Albert C Yang
- Taiwan International Graduate Program in Interdisciplinary Neuroscience, National Yang Ming Chiao Tung University and Academia Sinica, Taipei, Taiwan; Laboratory of Precision Psychiatry, Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Brain Science and Digital Medicine Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.
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14
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Kuang L, Gao W, Wang L, Guo Y, Cao W, Cui D, Jiao Q, Qiu J, Su L, Lu G. Increased resting-state brain entropy of parahippocampal gyrus and dorsolateral prefrontal cortex in manic and euthymic adolescent bipolar disorder. J Psychiatr Res 2021; 143:106-112. [PMID: 34479001 DOI: 10.1016/j.jpsychires.2021.08.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 06/01/2021] [Accepted: 08/17/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Alterations of brain signal complexity may reflect brain functional abnormalities. In adolescent bipolar disorder (ABD) distribution of brain regions showing abnormal complexity in different mood states remains unclear. We aimed to analyze brain entropy (BEN) alteration of functional magnetic resonance imaging (fMRI) signal to observe spatial distribution of complexity in ABD patients, as well as the relationship between this variation and clinical variables. METHODS Resting-state fMRI data were acquired from adolescents with bipolar disorder (BD) who were in manic (n = 19) and euthymic (n = 20) states, and from healthy controls (HCs, n = 17). The differences in BEN among the three groups, and their associations with clinical variables, were examined. RESULTS Compared to HCs, manic and euthymic ABD patients showed increased BEN in right parahippocampal gyrus (PHG) and left dorsolateral prefrontal cortex (DLPFC). There was no significant difference of BEN between the manic and the euthymic ABD groups. In manic ABD patients, right PHG BEN exhibited significantly positive relationship with episode times. CONCLUSIONS Increased BEN in right PHG and left DLPFC in ABD patients may cause dysfunction of corticolimbic circuitry which is important to emotional processing and cognitive control. The positive correlation between PHG BEN and episode times of manic ABD patients further expressed a close association between brain complexity and clinical symptoms. From the perspective of brain temporal dynamics, the present study complements previous findings that have reported corticolimbic dysfunction as an important contributor to the pathophysiology of BD. BEN may provide valuable evidences for understanding the underlying mechanism of ABD.
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Affiliation(s)
- Liangfeng Kuang
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Weijia Gao
- Department of Child Psychology, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Luoyu Wang
- Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, China; Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yongxin Guo
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Weifang Cao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Dong Cui
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Qing Jiao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China.
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Linyan Su
- Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, China
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15
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Gao L, Wu H, Cheng W, Lan B, Ren H, Zhang L, Wang L. Enhanced Descending Corticomuscular Coupling During Hand Grip With Static Force Compared With Enhancing Force. Clin EEG Neurosci 2021; 52:436-443. [PMID: 32611201 DOI: 10.1177/1550059420933149] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The interaction between cortex and muscles under hand motor with different force states has not been quantitatively investigated yet, which to some extent places the optimized movement tasks design for brain-computer interface (BCI) applications in hand motor rehabilitation under uncertainty. Converging evidence has suggested that both the descending corticospinal pathway and ascending sensory feedback pathway are involved in the generation of corticomuscular coupling. The present study aimed to explore the corticomuscular coupling during hand motor task with enhancing force and steady-state force. Twenty healthy subjects performed precision grip with enhancing and static force using the right hand with visual feedback of exerted force. Mutual information and Granger causal connectivity were assessed between electroencephalography (EEG) over primary motor cortex and electromyography (EMG) recordings, and statistically analyzed. The results showed that the mutual information value was significantly larger for static force in the beta and alpha frequency band than enhancing force state. Furthermore, compared with enhancing force, the Granger causal connectivity of descending pathways from cortex to muscle was significantly larger for static force in the beta and high alpha frequency band (10-20 Hz), indicating the connection between the primary motor cortex and muscle was strengthened for static force. In summary, the hand grip with static force resulted in an increasing corticomuscular coupling from EEG over the primary motor cortex to EMG compared with enhancing force, implying more attention was required in the static force state. These results have important implications toward motor rehabilitation therapy design for the recovery of impaired hand motor functions.
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Affiliation(s)
- Lin Gao
- State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.,School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.,Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an, Shaanxi, People's Republic of China
| | - Hongjian Wu
- Key Laboratory of Biomedical Information Engineering of Education Ministry, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.,National Engineering Research Center of Health Care and Medical Devices Xi'an Jiaotong University Branch, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China
| | - Wei Cheng
- State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.,School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China
| | - Beidi Lan
- Department of Structural Heart Disease, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China
| | - Haipeng Ren
- Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an, Shaanxi, People's Republic of China
| | - Lu Zhang
- State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.,School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China
| | - Ling Wang
- State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.,School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China
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16
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Xin X, Long S, Sun M, Gao X. The Application of Complexity Analysis in Brain Blood-Oxygen Signal. Brain Sci 2021; 11:brainsci11111415. [PMID: 34827414 PMCID: PMC8615802 DOI: 10.3390/brainsci11111415] [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: 09/16/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 11/17/2022] Open
Abstract
One of the daunting features of the brain is its physiology complexity, which arises from the interaction of numerous neuronal circuits that operate over a wide range of temporal and spatial scales, enabling the brain to adapt to the constantly changing environment and to perform various cognitive functions. As a reflection of the complexity of brain physiology, the complexity of brain blood-oxygen signal has been frequently studied in recent years. This paper reviews previous literature regarding the following three aspects: (1) whether the complexity of the brain blood-oxygen signal can serve as a reliable biomarker for distinguishing different patient populations; (2) which is the best algorithm for complexity measure? And (3) how to select the optimal parameters for complexity measures. We then discuss future directions for blood-oxygen signal complexity analysis, including improving complexity measurement based on the characteristics of both spatial patterns of brain blood-oxygen signal and latency of complexity itself. In conclusion, the current review helps to better understand complexity analysis in brain blood-oxygen signal analysis and provide useful information for future studies.
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17
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Shen K, McFadden A, McIntosh AR. Signal complexity indicators of health status in clinical EEG. Sci Rep 2021; 11:20192. [PMID: 34642403 PMCID: PMC8511087 DOI: 10.1038/s41598-021-99717-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 09/29/2021] [Indexed: 11/13/2022] Open
Abstract
Brain signal variability changes across the lifespan in both health and disease, likely reflecting changes in information processing capacity related to development, aging and neurological disorders. While signal complexity, and multiscale entropy (MSE) in particular, has been proposed as a biomarker for neurological disorders, most observations of altered signal complexity have come from studies comparing patients with few to no comorbidities against healthy controls. In this study, we examined whether MSE of brain signals was distinguishable across patient groups in a large and heterogeneous set of clinical-EEG data. Using a multivariate analysis, we found unique timescale-dependent differences in MSE across various neurological disorders. We also found MSE to differentiate individuals with non-brain comorbidities, suggesting that MSE is sensitive to brain signal changes brought about by metabolic and other non-brain disorders. Such changes were not detectable in the spectral power density of brain signals. Our findings suggest that brain signal complexity may offer complementary information to spectral power about an individual's health status and is a promising avenue for clinical biomarker development.
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Affiliation(s)
- Kelly Shen
- Rotman Research Institute, Baycrest Centre, 3560 Bathurst Street, Toronto, ON, M6A 2E1, Canada.
| | - Alison McFadden
- Rotman Research Institute, Baycrest Centre, 3560 Bathurst Street, Toronto, ON, M6A 2E1, Canada
| | - Anthony R McIntosh
- Rotman Research Institute, Baycrest Centre, 3560 Bathurst Street, Toronto, ON, M6A 2E1, Canada
- University of Toronto, Toronto, Canada
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18
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Xiang J, Tan Y, Niu Y, Sun J, Zhang N, Li D, Wang B. Analysis of functional MRI signal complexity based on permutation fuzzy entropy in bipolar disorder. Neuroreport 2021; 32:465-471. [PMID: 33657075 DOI: 10.1097/wnr.0000000000001617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Bipolar disorder is a manifestation of an emotional disease and is associated with emotional and cognitive dysfunction. The entropy-based method has been widely used to study the complexity of resting-state functional MRI (rs-fMRI) signals in mental diseases; however, alterations in the brain rs-fMRI signal complexities in bipolar disorder patients remain unclear, and previously used entropy methods are sensitive to noise. Here, we performed a work using permutation fuzzy entropy (PFEN), which has better performance than previously used methods, to analyze the brain complexity of bipolar disorder patients. Based on PFEN research, we obtained brain entropy maps of 49 bipolar disorder patients and 49 normal control, extracted the regions of interest to analyze the complexity of abnormal brain regions and further analyzed the correlation between the PFEN values of abnormal brain regions and the clinical measurement scores. Compared with the values in the normal control group, we found that significantly increased PFEN values mainly appeared in the middle temporal gyrus, angular gyrus, superior occipital gyrus and medial superior frontal gyrus, and the decreased PFEN values were found in the inferior temporal gyrus in bipolar disorder patients. In addition, the PFEN values of the angular gyrus was significantly negatively correlated with clinical scores. These findings improve our understanding of the pathophysiology of bipolar disorder patients.
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Affiliation(s)
- Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
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19
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Tsai HJ, Yang WC, Tsai SJ, Lin CH, Yang AC. Remission of depression is associated with asymmetric hemispheric variation in EEG complexity before antidepressant treatment. J Affect Disord 2021; 281:872-879. [PMID: 33220949 DOI: 10.1016/j.jad.2020.11.041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 09/14/2020] [Accepted: 11/07/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Intense increased alpha activity in the anterior brain has been recognized as one of the biomarkers of depression. This study aimed to explore whether complexity measures of electroencephalogram (EEG) signals vary across the frontal region between patients with or without remission in depression. METHODS Ninety-four patients with moderate-to-severe major depression underwent the experiment. Hilbert-Huang transform was applied to extract individual alpha EEG instantaneous amplitude. Averaged regional complexity (SampEnMean) on frontal and frontal-central areas as well as bilateral frontal areas were assessed according to multiscale entropy between the remitters (n = 26/94, 27.66%) and poor responders (n = 29/94, 30.85%). Standard deviation of regional complexity (SampEnSD) was used as a parameter to test the homogeneity of frontal alpha complexity. RESULTS No significant differences in SampEnMean for the frontal or frontal-central area were observed between the remitters and poor responders. However, the SampEnSD (i.e., regional homogeneity of frontal alpha complexity) significantly increased in the frontal-central area after treatment among the poor responders in comparison to their baseline, whereas the remitters showed an opposite trend. The remitters further showed significantly larger SampEnSD on the left frontal area at baseline, and this lateralization disappeared after antidepressant treatment except for the poor responders. LIMITATIONS This study was limited by a small sample size and without healthy controls. CONCLUSIONS Homogeneity in frontal-central alpha complexity and interhemispheric asymmetry normalization of anterior EEG complexity are associated with antidepressant efficacy, suggesting that homogeneity of dynamical brain activity is a key linked to the successful treatment of major depression.
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Affiliation(s)
- Hsin-Jung Tsai
- Department of Psychiatry, Taipei Veteran General Hospital, Taipei, Taiwan
| | - Wei-Cheng Yang
- Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veteran General Hospital, Taipei, Taiwan; Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Ching-Hua Lin
- Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan.
| | - Albert C Yang
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan; Digital Medicine Center, National Yang-Ming University, Taipei, Taiwan; Brain Medicine Center, Taoyuan Psychiatric Center, Taoyuan City, Taiwan.
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20
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Zhang N, Niu Y, Sun J, An W, Li D, Wei J, Yan T, Xiang J, Wang B. Altered Complexity of Spontaneous Brain Activity in Schizophrenia and Bipolar Disorder Patients. J Magn Reson Imaging 2021; 54:586-595. [PMID: 33576137 DOI: 10.1002/jmri.27541] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 01/22/2021] [Accepted: 01/25/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Schizophrenia (SC) and bipolar disorder (BP) share elements of symptoms and the underlying neural mechanisms for both remain unclear. Recently, the complexity of spontaneous functional MRI (fMRI) signals in brain activity has been investigated in SC and BP using multiscale sample entropy (MSE) with inconsistent results. PURPOSE To perform MSE analysis across five time scales to assess differences in resting-state fMRI signal complexity in SC, BP, and normal controls (NC). STUDY TYPE Retrospective. POPULATION Fifty SC, 49 BP, and 49 NC. FIELD STRENGTH/SEQUENCE A 3 T, T2* weighted echo planar imaging (EPI) sequence. ASSESSMENT The mean MSEs of all gray matter (GM) and of 12 regions of interest (ROIs) were extracted using masks across the five scales. The regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) in these ROIs were also determined and the relationship between the three measures was investigated. The correlations between cognitive assessment scores and MSE values were also explored. STATISTICAL TESTS Bonferroni correction, One-way ANOVA, Spearman rank correlation coefficient (r), Gaussian random field (GRF) correction. RESULTS There were decreased GM MSE values in the patient groups (F = 9.629, P < 0.05). SC and BP patients demonstrated lower complexity than NCs in the calcarine fissure, precuneus, inferior occipital gyrus, lingual gyrus and cerebellum, and higher complexity in the median cingulate, thalamus, hippocampus, middle temporal gyrus and middle frontal gyrus. There were significant differences between SC and BP patients in the precuneus (F = 4.890, P < 0.05) and inferior occipital gyrus (F = 5.820, P < 0.05). Calcarine fissure, cingulate, temporal gyrus, occipital gyrus, hippocampus, precuneus, frontal gyrus, and lingual gyrus MSE values were significantly correlated with both ReHo (r > 0.282, P < 0.05) and ALFF (r > 0.278, P < 0.05). Furthermore, median temporal MSE (r = -0.321, P < 0.05) on scale 3 and (r = -0.307, P < 0.05) on scale 4 and median cingulate MSE (r = -0.337, P < 0.05) on scale 5 was significantly negatively correlated with cognitive assessment scores. DATA CONCLUSION These data highlight different patterns of brain signal intensity complexity in SC and BP. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Nan Zhang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Yan Niu
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Jie Sun
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Weichao An
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Dandan Li
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Jing Wei
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Ting Yan
- Translational Medicine Research Center, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Bin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
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21
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Palix J, Giuliani F, Sierro G, Brandner C, Favrod J. Temporal regularity of cerebral activity at rest correlates with slowness of reaction times in intellectual disability. Clin Neurophysiol 2020; 131:1859-1865. [PMID: 32570200 DOI: 10.1016/j.clinph.2020.04.174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 04/16/2020] [Accepted: 04/27/2020] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Intellectual disability (ID) is described as a general slowness in behavior and an inadequacy in adaptive skills. The present study examines whether behavioral slowness in ID could originate from abnormal complexity in brain signals. METHODS Participants (N = 29) performed a reaction times (RTs) task assessing their individual information processing speeds. Half of the participants had moderate intellectual disability (intelligence quotient (IQ) < 70). Continuous electroencephalogram recording during the resting period was used to quantify brain signal complexity by approximate entropy estimation (ApEn). RESULTS For all participants, a negative correlation between RTs and IQ was found, with longer RTs coinciding with lower IQ. This behavioral slowness in ID was associated with increased temporal regularity in electrocortical brain signals. CONCLUSIONS Behavioral slowness in ID subjects is closely related to lower brain signal complexity. SIGNIFICANCE Brain signal ApEn is shown to correspond with processing speed for the first time: in ID participants, the higher the regularity in brain signals at rest, the slower RTs will be in the active state. ID should be understood as a lack of lability in the cortical transition to the active state, weakening the efficiency of adaptive behavior.
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Affiliation(s)
- Julie Palix
- Research Unit of Legal Psychiatry and Psychology, Department of Psychiatry, University Hospital Centre of Lausanne, Switzerland; Brain Electrophysiology Attention Movement Laboratory, Institute of Psychology, University of Lausanne, Switzerland; La Source School of Nursing, HES-SO University of Applied Sciences and Arts of Western Switzerland, Lausanne, Switzerland.
| | - Fabienne Giuliani
- Consultation of Liaison Psychiatry for Intellectual Disability, Community Psychiatry Service, Department of Psychiatry, University Hospital Centre of Lausanne, Switzerland
| | - Guillaume Sierro
- Brain Electrophysiology Attention Movement Laboratory, Institute of Psychology, University of Lausanne, Switzerland
| | - Catherine Brandner
- Brain Electrophysiology Attention Movement Laboratory, Institute of Psychology, University of Lausanne, Switzerland
| | - Jérôme Favrod
- La Source School of Nursing, HES-SO University of Applied Sciences and Arts of Western Switzerland, Lausanne, Switzerland
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22
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Ilan Y. Overcoming randomness does not rule out the importance of inherent randomness for functionality. J Biosci 2019; 44:132. [PMID: 31894113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Randomness is intrinsic to many natural processes. It is also clear that, under certain conditions, disorders are not associated with functionality. Several examples in which overcoming, suppressing, or combining both randomness and non-randomness is required are drawn from various fields. However, the need to suppress or overcome randomness does not negate its importance under certain conditions and its significance in valid processes and organ functions. Randomness should be acknowledged rather than ignored or suppressed; it can be viewed, at worst, as a disturbing disorder that may be treated to produce order, or, at best, as a 'beneficial disorder' that can be considered as a higher level of functionality.
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Affiliation(s)
- Yaron Ilan
- Department of Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel,
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23
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McDonough IM, Letang SK, Erwin HB, Kana RK. Evidence for Maintained Post-Encoding Memory Consolidation Across the Adult Lifespan Revealed by Network Complexity. ENTROPY 2019. [PMCID: PMC7514376 DOI: 10.3390/e21111072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Memory consolidation is well known to occur during sleep, but might start immediately after encoding new information while awake. While consolidation processes are important across the lifespan, they may be even more important to maintain memory functioning in old age. We tested whether a novel measure of information processing known as network complexity might be sensitive to post-encoding consolidation mechanisms in a sample of young, middle-aged, and older adults. Network complexity was calculated by assessing the irregularity of brain signals within a network over time using multiscale entropy. To capture post-encoding mechanisms, network complexity was estimated using functional magnetic resonance imaging (fMRI) during rest before and after encoding of picture pairs, and subtracted between the two rest periods. Participants received a five-alternative-choice memory test to assess associative memory performance. Results indicated that aging was associated with an increase in network complexity from pre- to post-encoding in the default mode network (DMN). Increases in network complexity in the DMN also were associated with better subsequent memory across all age groups. These findings suggest that network complexity is sensitive to post-encoding consolidation mechanisms that enhance memory performance. These post-encoding mechanisms may represent a pathway to support memory performance in the face of overall memory declines.
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Ilan Y. Overcoming randomness does not rule out the importance of inherent randomness for functionality. J Biosci 2019. [DOI: 10.1007/s12038-019-9958-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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25
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Low I, Kuo PC, Tsai CL, Liu YH, Lin MW, Chao HT, Chen YS, Hsieh JC, Chen LF. Interactions of BDNF Val66Met Polymorphism and Menstrual Pain on Brain Complexity. Front Neurosci 2018; 12:826. [PMID: 30524221 PMCID: PMC6256283 DOI: 10.3389/fnins.2018.00826] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Accepted: 10/23/2018] [Indexed: 12/28/2022] Open
Abstract
The irregularity and uncertainty of neurophysiologic signals across different time scales can be regarded as neural complexity, which is related to the adaptability of the nervous system and the information processing between neurons. We recently reported general loss of brain complexity, as measured by multiscale sample entropy (MSE), at pain-related regions in females with primary dysmenorrhea (PDM). However, it is unclear whether this loss of brain complexity is associated with inter-subject genetic variations. Brain-derived neurotrophic factor (BDNF) is a widely expressed neurotrophin in the brain and is crucial to neural plasticity. The BDNF Val66Met single-nucleotide polymorphism (SNP) is associated with mood, stress, and pain conditions. Therefore, we aimed to examine the interactions of BDNF Val66Met polymorphism and long-term menstrual pain experience on brain complexity. We genotyped BDNF Val66Met SNP in 80 PDM females (20 Val/Val, 31 Val/Met, 29 Met/Met) and 76 healthy female controls (25 Val/Val, 36 Val/Met, 15 Met/Met). MSE analysis was applied to neural source activity estimated from resting-state magnetoencephalography (MEG) signals during pain-free state. We found that brain complexity alterations were associated with the interactions of BDNF Val66Met polymorphism and menstrual pain experience. In healthy female controls, Met carriers (Val/Met and Met/Met) demonstrated lower brain complexity than Val/Val homozygotes in extensive brain regions, suggesting a possible protective role of Val/Val homozygosity in brain complexity. However, after experiencing long-term menstrual pain, the complexity differences between different genotypes in healthy controls were greatly diminished in PDM females, especially in the limbic system, including the hippocampus and amygdala. Our results suggest that pain experience preponderantly affects the effect of BDNF Val66Met polymorphism on brain complexity. The results of the present study also highlight the potential utilization of resting-state brain complexity for the development of new therapeutic strategies in patients with chronic pain.
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Affiliation(s)
- Intan Low
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.,Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Po-Chih Kuo
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Cheng-Lin Tsai
- Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan
| | - Yu-Hsiang Liu
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Ming-Wei Lin
- Institute of Public Health, National Yang-Ming University, Taipei, Taiwan
| | - Hsiang-Tai Chao
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yong-Sheng Chen
- Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan.,Center for Emergent Functional Matter Science, National Chiao Tung University, Hsinchu, Taiwan
| | - Jen-Chuen Hsieh
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.,Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.,Brain Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Li-Fen Chen
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.,Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.,Brain Research Center, National Yang-Ming University, Taipei, Taiwan
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26
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Hager BM, Yang AC, Gutsell JN. Measuring Brain Complexity During Neural Motor Resonance. Front Neurosci 2018; 12:758. [PMID: 30425614 PMCID: PMC6218617 DOI: 10.3389/fnins.2018.00758] [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: 05/31/2018] [Accepted: 10/02/2018] [Indexed: 12/01/2022] Open
Abstract
Background: EEG mu-desynchronization is an index of motor resonance (MR) and is used to study social interaction deficiencies, but finding differences in mu-desynchronization does not reveal how nonlinear brain dynamics are affected during MR. The current study explores how nonlinear brain dynamics change during MR. We hypothesized that the complexity of the mu frequency band (8–13 Hz) changes during MR, and that this change would be frequency specific. Additionally, we sought to determine whether complexity at baseline and changes in complexity during action observation would predict MR and changes in network dynamics. Methods: EEG was recorded from healthy participants (n = 45) during rest and during an action observation task. Baseline brain activity was measured followed by participants observing videos of hands squeezing stress balls. We used multiscale entropy (MSE) to quantify the complexity of the mu rhythm during MR. We then performed post-hoc graph theory analysis to explore whether nonlinear dynamics during MR affect brain network topology. Results: We found significant mu-desynchronization during the action observation task and that mu entropy was significantly increased during the task compared to rest, while gamma, beta, theta, and delta bands showed decreased entropy. Moreover, resting-state entropy was significantly predictive of the degree of mu desynchronization. We also observed a decrease in the clustering coefficient in the mu band only and a significant decrease in global alpha efficiency during action observation. MSE during action observation was strongly correlated with alpha network efficiency. Conclusions: The current findings suggest that the desynchronization of the mu wave during MR results in a local increase of mu entropy in sensorimotor areas, potentially reflecting a release from alpha inhibition. This release from inhibition may be mediated by the baseline MSE in the mu band. The dynamical complexity and network analysis of EEG may provide a useful addition for future studies of MR by incorporating measures of nonlinearity.
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Affiliation(s)
- Brandon M Hager
- Department of Psychology, Brandeis University, Waltham, MA, United States
| | - Albert C Yang
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Jennifer N Gutsell
- Department of Psychology, Neuroscience Program, and Volen National Center for Complex Systems, Brandeis University, Waltham, MA, United States
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Yang AC, Tsai SJ, Lin CP, Peng CK, Huang NE. Frequency and amplitude modulation of resting-state fMRI signals and their functional relevance in normal aging. Neurobiol Aging 2018; 70:59-69. [PMID: 30007165 DOI: 10.1016/j.neurobiolaging.2018.06.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 05/24/2018] [Accepted: 06/04/2018] [Indexed: 01/31/2023]
Abstract
The intrinsic composition and functional relevance of resting-state blood oxygen level-dependent signals are fundamental in research using functional magnetic resonance imaging (fMRI). Using the Hilbert-Huang Transform to estimate high-resolution time-frequency spectra, we investigated the instantaneous frequency and amplitude modulation of resting-state fMRI signals, as well as their functional relevance in a large normal-aging cohort (n = 420, age = 21-89 years). We evaluated the cognitive function of each participant and recorded respiratory signals during fMRI scans. The results showed that the Hilbert-Huang Transform effectively categorized resting-state fMRI power spectra into high (0.087-0.2 Hz), low (0.045-0.087 Hz), and very-low (≤0.045 Hz) frequency bands. The high-frequency power was associated with respiratory activity, and the low-frequency power was associated with cognitive function. Furthermore, within the cognition-related low-frequency band (0.045-0.087 Hz), we discovered that aging was associated with the increased frequency modulation and reduced amplitude modulation of the resting-state fMRI signal. These aging-related changes in frequency and amplitude modulation of resting-state fMRI signals were unaccounted for by the loss of gray matter volume and were consistently identified in the default mode and salience network. These findings indicate that resting-state fMRI signal modulations are dynamic during the normal aging process. In summary, our results refined the functionally related blood oxygen level-dependent frequency band in a considerably narrow band at a low-frequency range (0.045-0.087 Hz) and challenged the current method of resting-fMRI preprocessing by using low-frequency filters with a relatively wide range below 0.1 Hz.
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Affiliation(s)
- Albert C Yang
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan; Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Ching-Po Lin
- Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Chung-Kang Peng
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA
| | - Norden E Huang
- Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan
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Fernández A, Al-Timemy AH, Ferre F, Rubio G, Escudero J. Complexity analysis of spontaneous brain activity in mood disorders: A magnetoencephalography study of bipolar disorder and major depression. Compr Psychiatry 2018; 84:112-117. [PMID: 29734005 DOI: 10.1016/j.comppsych.2018.03.015] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 03/09/2018] [Accepted: 03/10/2018] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND AND PURPOSE The lack of a biomarker for Bipolar Disorder (BD) causes problems in the differential diagnosis with other mood disorders such as major depression (MD), and misdiagnosis frequently occurs. Bearing this in mind, we investigated non-linear magnetoencephalography (MEG) patterns in BD and MD. METHODS Lempel-Ziv Complexity (LZC) was used to evaluate the resting-state MEG activity in a cross-sectional sample of 60 subjects, including 20 patients with MD, 16 patients with BD type-I, and 24 control (CON) subjects. Particular attention was paid to the role of age. The results were aggregated by scalp region. RESULTS Overall, MD patients showed significantly higher LZC scores than BD patients and CONs. Linear regression analyses demonstrated distinct tendencies of complexity progression as a function of age, with BD patients showing a divergent tendency as compared with MD and CON groups. Logistic regressions confirmed such distinct relationship with age, which allowed the classification of diagnostic groups. CONCLUSIONS The patterns of neural complexity in BD and MD showed not only quantitative differences in their non-linear MEG characteristics but also divergent trajectories of progression as a function of age. Moreover, neural complexity patterns in BD patients resembled those previously observed in schizophrenia, thus supporting preceding evidence of common neuropathological processes.
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Affiliation(s)
- Alberto Fernández
- Department of Psychiatry, Faculty of Medicine, Complutense University, Madrid, Spain; Laboratory of Cognitive and Computational Neuroscience, Centre for Biomedical Technology (CTB), Technical University and Complutense University, Madrid, Spain.
| | - Ali H Al-Timemy
- Biomedical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad, Iraq; Centre for Robotics and Neural Systems (CRNS), Cognitive Institute, Plymouth University, PL4 8AA, United Kingdom
| | - Francisco Ferre
- Department of Psychiatry, Faculty of Medicine, Complutense University, Madrid, Spain; Psychiatry Department, Gregorio Marañón University Hospital, Madrid, Spain
| | - Gabriel Rubio
- Department of Psychiatry, Faculty of Medicine, Complutense University, Madrid, Spain; Psychiatry Department, 12 de Octubre University Hospital, Madrid, Spain
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh EH9 3FB, United Kingdom
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Yang AC, Tsai SJ, Lin CP, Peng CK. A Strategy to Reduce Bias of Entropy Estimates in Resting-State fMRI Signals. Front Neurosci 2018; 12:398. [PMID: 29950971 PMCID: PMC6008384 DOI: 10.3389/fnins.2018.00398] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 05/23/2018] [Indexed: 01/07/2023] Open
Abstract
Complexity analysis of resting-state blood oxygen level-dependent (BOLD) signals using entropy methods has attracted considerable attention. However, investigation on the bias of entropy estimates in resting-state functional magnetic resonance imaging (fMRI) signals and a general strategy for selecting entropy parameters is lacking. In this paper, we present a minimizing error approach to reduce the bias of sample entropy (SampEn) and multiscale entropy (MSE) in resting-state fMRI data. The strategy explored a range of parameters that minimized the relative error of SampEn of BOLD signals in cerebrospinal fluids where minimal physiologic information was present, and applied these parameters to calculate SampEn of BOLD signals in gray matter regions. We examined the effect of various parameters on the results of SampEn and MSE analyses of a large normal aging adult cohort (354 healthy subjects aged 21-89 years). The results showed that a tradeoff between pattern length m and tolerance factor r was necessary to maintain the accuracy of SampEn estimates. Furthermore, an increased relative error of SampEn was associated with an increased coefficient of variation in voxel-wise statistics. Overall, the parameters m = 1 and r = 0.20-0.45 provided reliable MSE estimates in short resting-state fMRI signals. For a single-scale SampEn analysis, a wide range of parameters was available with data lengths of at least 97 time points. This study provides a minimization error strategy for future studies on the non-linear analysis of resting-state fMRI signals to account for the bias of entropy estimates.
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Affiliation(s)
- Albert C. Yang
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, United States
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Chung-Kang Peng
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, United States
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Shan ZY, Finegan K, Bhuta S, Ireland T, Staines DR, Marshall-Gradisnik SM, Barnden LR. Brain function characteristics of chronic fatigue syndrome: A task fMRI study. Neuroimage Clin 2018; 19:279-286. [PMID: 30035022 PMCID: PMC6051500 DOI: 10.1016/j.nicl.2018.04.025] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Revised: 03/14/2018] [Accepted: 04/22/2018] [Indexed: 12/15/2022]
Abstract
The mechanism underlying neurological dysfunction in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) is yet to be established. This study investigated the temporal complexity of blood oxygenation level dependent (BOLD) changes in response to the Stroop task in CFS patients. 43 CFS patients (47.4 ± 11.8 yrs) and 26 normal controls (NCs, 43.4 ± 13.9 yrs) were included in this study. Their mental component summary (MCS) and physical component summary (PCS) from the 36-item Short Form Health Survey (SF-36) questionnaire were recorded. Their Stroop colour-word task performance was measured by accuracy and response time (RT). The BOLD changes associated with the Stroop task were evaluated using a 2-level general linear model approach. The temporal complexity of the BOLD responses, a measure of information capacity and thus adaptability to a challenging environment, in each activated region was measured by sample entropy (SampEn). The CFS patients showed significantly longer RTs than the NCs (P < 0.05) but no significant difference in accuracy. One sample t-tests for the two groups (Family wise error adjusted PFWE < 0.05) showed more BOLD activation regions in the CFS, although a two sample group comparison did not show significant difference. BOLD SampEns in ten regions were significantly lower (FDR-q < 0.05) in CFS patients. BOLD SampEns in 15 regions were significantly associated with PCS (FDR-q < 0.05) and in 9 regions were associated with MCS (FDR-q < 0.05) across all subjects. SampEn of the BOLD signal in the medioventral occipital cortex could explain 40% and 31% of the variance in the SF-36 PCS and MCS scores, and those in the precentral gyrus could explain an additional 16% and 7% across all subjects. This is the first study to investigate BOLD signal SampEn in response to tasks in CFS. The results suggest the brain responds differently to a cognitive challenge in patients with CFS, with recruitment of wider regions to compensate for lower information capacity.
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Affiliation(s)
- Zack Y Shan
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD 4222, Australia.
| | - Kevin Finegan
- Medical Imaging Department, Gold Coast University Hospital, Parklands, QLD 4215, Australia
| | - Sandeep Bhuta
- Medical Imaging Department, Gold Coast University Hospital, Parklands, QLD 4215, Australia
| | - Timothy Ireland
- Medical Imaging Department, Gold Coast University Hospital, Parklands, QLD 4215, Australia
| | - Donald R Staines
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD 4222, Australia
| | - Sonya M Marshall-Gradisnik
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD 4222, Australia
| | - Leighton R Barnden
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD 4222, Australia
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Intrinsic, task-evoked and absolute gamma synchrony during cognitive processing in first onset schizophrenia. J Psychiatr Res 2018; 99:10-21. [PMID: 29407283 DOI: 10.1016/j.jpsychires.2017.12.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Revised: 10/27/2017] [Accepted: 12/07/2017] [Indexed: 11/24/2022]
Abstract
Cognitive deficits present from the first onset of schizophrenia are thought to arise from a core problem in neural synchrony. This is the first study to characterize the profile of gamma (30-100 Hz) synchrony (rather than power) and behavioral performance during higher-order cognitive processing in schizophrenia. Gamma synchrony was acquired from the EEG, and elicited by a Continuous Performance Test (CPT). We quantitated synchrony for regions associated with the fronto-parietal attention and visual networks for 59 young people with First Onset Schizophrenia (FOS) and 59 matched controls, facilitated by the BRAINnet.net data sharing initiative. We compared groups on gamma synchrony for intrinsic (pre-stimulus), task-evoked change (relative to baseline) and absolute (not relative to baseline) measures. Relationships between synchrony and CPT accuracy, symptoms and functioning were also assessed. FOS showed a reduced ability to modulate task-evoked changes in gamma synchrony, in the context of generally higher intrinsic and absolute synchrony, particularly in frontal regions. These gamma synchrony abnormalities in FOS were associated with performance on the CPT, but not with symptoms or functioning. Task-relevant changes in synchrony may be constrained by an overall excess of intrinsic background synchrony that is unrelated to specific task demands and this relates to cognitive performance. Results are in line with theoretical accounts of gamma synchrony as a core abnormality in schizophrenia, affecting functional connectivity in central executive circuits and causing cognitive symptoms. This study is the first to demonstrate that these gamma synchrony abnormalities are not limited to perceptual or lower-order cognitive processing.
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Low I, Wei SY, Lee PS, Li WC, Lee LC, Hsieh JC, Chen LF. Neuroimaging Studies of Primary Dysmenorrhea. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1099:179-199. [DOI: 10.1007/978-981-13-1756-9_16] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis. ENTROPY 2017. [DOI: 10.3390/e19120680] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Jia Y, Gu H, Luo Q. Sample entropy reveals an age-related reduction in the complexity of dynamic brain. Sci Rep 2017; 7:7990. [PMID: 28801672 PMCID: PMC5554148 DOI: 10.1038/s41598-017-08565-y] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 07/13/2017] [Indexed: 12/16/2022] Open
Abstract
Dynamic reconfiguration of the human brain is characterized by the nature of complexity. The purpose of this study was to measure such complexity and also analyze its association with age. We modeled the dynamic reconfiguration process by dynamic functional connectivity, which was established by resting-state functional magnetic resonance imaging (fMRI) data, and we measured complexity within the dynamic functional connectivity by sample entropy (SampEn). A brainwide map of SampEn in healthy subjects shows larger values in the caudate, the olfactory gyrus, the amygdala, and the hippocampus, and lower values in primary sensorimotor and visual areas. Association analysis in healthy subjects indicated that SampEn of the amygdala-cortical connectivity decreases with advancing age. Such age-related loss of SampEn, however, disappears in patients with schizophrenia. These findings suggest that SampEn of the dynamic functional connectivity is a promising indicator of normal aging.
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Affiliation(s)
- Yanbing Jia
- School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, 200092, P. R. China
| | - Huaguang Gu
- School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, 200092, P. R. China.
| | - Qiang Luo
- School of Life Sciences, Fudan University, Shanghai, 200433, P. R. China. .,Institute of Science and Technology of Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, P. R. China.
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Birur B, Kraguljac NV, Shelton RC, Lahti AC. Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature. NPJ SCHIZOPHRENIA 2017; 3:15. [PMID: 28560261 PMCID: PMC5441538 DOI: 10.1038/s41537-017-0013-9] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Revised: 01/17/2017] [Accepted: 01/24/2017] [Indexed: 12/18/2022]
Abstract
Since Emil Kraepelin's conceptualization of endogenous psychoses as dementia praecox and manic depression, the separation between primary psychotic disorders and primary affective disorders has been much debated. We conducted a systematic review of case-control studies contrasting magnetic resonance imaging studies in schizophrenia and bipolar disorder. A literature search in PubMed of studies published between January 2005 and December 2016 was conducted, and 50 structural, 29 functional, 7 magnetic resonance spectroscopy, and 8 combined imaging and genetic studies were deemed eligible for systematic review. Structural neuroimaging studies suggest white matter integrity deficits that are consistent across the illnesses, while gray matter reductions appear more widespread in schizophrenia compared to bipolar disorder. Spectroscopy studies in cortical gray matter report evidence of decreased neuronal integrity in both disorders. Functional neuroimaging studies typically report similar functional architecture of brain networks in healthy controls and patients across the psychosis spectrum, but find differential extent of alterations in task related activation and resting state connectivity between illnesses. The very limited imaging-genetic literature suggests a relationship between psychosis risk genes and brain structure, and possible gene by diagnosis interaction effects on functional imaging markers. While the existing literature suggests some shared and some distinct neural markers in schizophrenia and bipolar disorder, it will be imperative to conduct large, well designed, multi-modal neuroimaging studies in medication-naïve first episode patients that will be followed longitudinally over the course of their illness in an effort to advance our understanding of disease mechanisms.
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Affiliation(s)
- Badari Birur
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL USA
| | - Nina Vanessa Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL USA
| | - Richard C. Shelton
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL USA
| | - Adrienne Carol Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL USA
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