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Hernandez H, Baez S, Medel V, Moguilner S, Cuadros J, Santamaria-Garcia H, Tagliazucchi E, Valdes-Sosa PA, Lopera F, OchoaGómez JF, González-Hernández A, Bonilla-Santos J, Gonzalez-Montealegre RA, Aktürk T, Yıldırım E, Anghinah R, Legaz A, Fittipaldi S, Yener GG, Escudero J, Babiloni C, Lopez S, Whelan R, Lucas AAF, García AM, Huepe D, Caterina GD, Soto-Añari M, Birba A, Sainz-Ballesteros A, Coronel C, Herrera E, Abasolo D, Kilborn K, Rubido N, Clark R, Herzog R, Yerlikaya D, Güntekin B, Parra MA, Prado P, Ibanez A. Brain health in diverse settings: How age, demographics and cognition shape brain function. Neuroimage 2024; 295:120636. [PMID: 38777219 DOI: 10.1016/j.neuroimage.2024.120636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 04/17/2024] [Accepted: 05/04/2024] [Indexed: 05/25/2024] Open
Abstract
Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.
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Affiliation(s)
- Hernan Hernandez
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | - Sandra Baez
- Universidad de los Andes, Bogota, Colombia; Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland
| | - Vicente Medel
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | - Sebastian Moguilner
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Harvard Medical School, Boston, MA, USA
| | - Jhosmary Cuadros
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile; Grupo de Bioingeniería, Decanato de Investigación, Universidad Nacional Experimental del Táchira, San Cristóbal 5001, Venezuela
| | - Hernando Santamaria-Garcia
- Pontificia Universidad Javeriana (PhD Program in Neuroscience) Bogotá, San Ignacio, Colombia; Center of Memory and Cognition Intellectus, Hospital Universitario San Ignacio Bogotá, San Ignacio, Colombia
| | - Enzo Tagliazucchi
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; University of Buenos Aires, Argentina
| | - Pedro A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Sciences, University of Electronic Sciences Technology of China, Chengdu, China; Cuban Neuroscience Center, La Habana, Cuba
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, University of Antioquia, Medellín, Colombia
| | | | | | | | | | - Tuba Aktürk
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Ebru Yıldırım
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Renato Anghinah
- Reference Center of Behavioural Disturbances and Dementia, School of Medicine, University of Sao Paulo, Sao Paulo, Brazil; Traumatic Brain Injury Cognitive Rehabilitation Out-Patient Center, University of Sao Paulo, Sao Paulo, Brazil
| | - Agustina Legaz
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Sol Fittipaldi
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Görsev G Yener
- Faculty of Medicine, Izmir University of Economics, 35330, Izmir, Turkey; Brain Dynamics Multidisciplinary Research Center, Dokuz Eylul University, Izmir, Turkey; Izmir Biomedicine and Genome Center, Izmir, Turkey
| | - Javier Escudero
- School of Engineering, Institute for Imaging, Data and Communications, University of Edinburgh, Scotland, UK
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino, Cassino, (FR), Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy
| | - Robert Whelan
- Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; Department of Legal Medicine, Psychiatry and Pathology at the Complutense University of Madrid, Madrid, Spain
| | - Alberto A Fernández Lucas
- Department of Legal Medicine, Psychiatry and Pathology at the Complutense University of Madrid, Madrid, Spain
| | - Adolfo M García
- Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; Cognitive Neuroscience Center, Universidad de San Andréss, Buenos Aires, Argentina; Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - David Huepe
- Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez
| | - Gaetano Di Caterina
- Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
| | | | - Agustina Birba
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | | | - Carlos Coronel
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Universidad de Valparaíso, Valparaíso, Chile
| | - Eduar Herrera
- Departamento de Estudios Psicológicos, Universidad ICESI, Cali, Colombia
| | - Daniel Abasolo
- Centre for Biomedical Engineering, School of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Kerry Kilborn
- School of Psychology, University of Glasgow, Glasgow, Scotland, UK
| | - Nicolás Rubido
- Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen, AB24 3UE, UK
| | - Ruaridh Clark
- Centre for Signal and Image Processing, Department of Electronic and Electrical Engineering, University of Strathclyde, UK
| | - Ruben Herzog
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, Paris 75013, France
| | - Deniz Yerlikaya
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Bahar Güntekin
- Health Sciences and Technology Research Institute (SABITA), Istanbul Medipol University, Istanbul, Turkey; Department of Biophysics, School of Medicine, Istanbul Medipol University, Turkey
| | - Mario A Parra
- Department of Psychological Sciences and Health, University of Strathclyde, United Kingdom and Associate Researcher of the Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Pavel Prado
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Agustin Ibanez
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Global Brain Health Institute, University of California San Francisco, San Francisco, CA, USA; Cognitive Neuroscience Center, Universidad de San Andrés and Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina; Trinity College Dublin, The University of Dublin, Dublin, Ireland.
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Brinkmann BH. Technical Considerations in EEG Source Imaging. J Clin Neurophysiol 2024; 41:2-7. [PMID: 38181382 DOI: 10.1097/wnp.0000000000001029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2024] Open
Abstract
SUMMARY EEG source imaging is an established technique for identifying the origin of interictal and ictal epileptiform discharges in patients with epilepsy, and it is an important tool in neurophysiology research. Accurate and reliable EEG source imaging requires appropriate choices of how the head, skull, and scalp are modeled, and understanding of the different approaches to modeling is important to guide these choices. Similarly, numerous different approaches to modeling the electrical sources within the brain exist, and appropriate understanding of the strengths and limitations of each are essential to obtaining accurate, reliable, and interpretable solutions. This review aims to describe the essential theoretical basis for these head and source models while also discussing the practical implications of each in clinical or research applications.
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Affiliation(s)
- Benjamin H Brinkmann
- Departments of Neurology and Physiology and Biomedical Engineering, Mayo Clinic, Alfred 9-441C, SMH; 200 First Street SW, Rochester, Minnesota, U.S.A
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Burd SG, Lebedeva AV, Rubleva YV, Pantina NV, Efimenko AP, Kovaleva II. [EEG changes in patients with Alzheimer's disease]. Zh Nevrol Psikhiatr Im S S Korsakova 2024; 124:72-76. [PMID: 38696154 DOI: 10.17116/jnevro202412404272] [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: 05/23/2024]
Abstract
The prevalence of cognitive impairment is steadily increasing compared to previous years. According to the World Health Organization, the number of people living with dementia will increase reaching 82 million in 2030 and 152 million in 2050. The most common cause is Alzheimer's disease (AD). The pathophysiological process in AD begins several years before the onset of clinical symptoms; so identifying it at an early stage would likely improve the clinical prognosis. The article presents EEG changes in patients with AD, and discusses the possibility of using EEG as a screening method for examining patients with cognitive impairment.
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Affiliation(s)
- S G Burd
- Federal Center of Brain Research and Neurotechnologies, Moscow, Russia
- Pirogov Russian National Research Medical University, Moscow, Russia
- Scientific and Practical Center for Child Psychoneurology, Moscow, Russia
| | - A V Lebedeva
- Federal Center of Brain Research and Neurotechnologies, Moscow, Russia
- Pirogov Russian National Research Medical University, Moscow, Russia
| | - Yu V Rubleva
- Federal Center of Brain Research and Neurotechnologies, Moscow, Russia
| | - N V Pantina
- Federal Center of Brain Research and Neurotechnologies, Moscow, Russia
| | - A P Efimenko
- Federal Center of Brain Research and Neurotechnologies, Moscow, Russia
| | - I I Kovaleva
- Federal Center of Brain Research and Neurotechnologies, Moscow, Russia
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Katayama O, Stern Y, Habeck C, Lee S, Harada K, Makino K, Tomida K, Morikawa M, Yamaguchi R, Nishijima C, Misu Y, Fujii K, Kodama T, Shimada H. Neurophysiological markers in community-dwelling older adults with mild cognitive impairment: an EEG study. Alzheimers Res Ther 2023; 15:217. [PMID: 38102703 PMCID: PMC10722716 DOI: 10.1186/s13195-023-01368-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 12/05/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Neurodegeneration and structural changes in the brain due to amyloid deposition have been observed even in individuals with mild cognitive impairment (MCI). EEG measurement is considered an effective tool because it is noninvasive, has few restrictions on the measurement environment, and is simple and easy to use. In this study, we investigated the neurophysiological characteristics of community-dwelling older adults with MCI using EEG. METHODS Demographic characteristics, cognitive function, physical function, resting-state MRI and electroencephalogram (rs-EEG), event-related potentials (ERPs) during Simon tasks, and task proportion of correct responses and reaction times (RTs) were obtained from 402 healthy controls (HC) and 47 MCI participants. We introduced exact low-resolution brain electromagnetic tomography-independent component analysis (eLORETA-ICA) to assess the rs-EEG network in community-dwelling older adults with MCI. RESULTS A lower proportion of correct responses to the Simon task and slower RTs were observed in the MCI group (p < 0.01). Despite no difference in brain volume between the HC and MCI groups, significant decreases in dorsal attention network (DAN) activity (p < 0.05) and N2 amplitude of ERP (p < 0.001) were observed in the MCI group. Moreover, DAN activity demonstrated a correlation with education (Rs = 0.32, p = 0.027), global cognitive function (Rs = 0.32, p = 0.030), and processing speed (Rs = 0.37, p = 0.010) in the MCI group. The discrimination accuracy for MCI with the addition of the eLORETA-ICA network ranged from 0.7817 to 0.7929, and the area under the curve ranged from 0.8492 to 0.8495. CONCLUSIONS The eLORETA-ICA approach of rs-EEG using noninvasive and relatively inexpensive EEG demonstrates specific changes in elders with MCI. It may provide a simple and valid assessment method with few restrictions on the measurement environment and may be useful for early detection of MCI in community-dwelling older adults.
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Affiliation(s)
- Osamu Katayama
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan.
- Japan Society for the Promotion of Science, Chiyoda-Ku, Tokyo, 102-0083, Japan.
- Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA.
- Department of Physical Therapy, Graduate School of Health Sciences, Kyoto Tachibana University, 34 Yamada-Cho, Oyake, Yamashina-Ku, Kyoto, 607-8175, Japan.
| | - Yaakov Stern
- Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA
| | - Christian Habeck
- Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA
| | - Sangyoon Lee
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Kenji Harada
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Keitaro Makino
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Kouki Tomida
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Masanori Morikawa
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Ryo Yamaguchi
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Chiharu Nishijima
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Yuka Misu
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Kazuya Fujii
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
| | - Takayuki Kodama
- Department of Physical Therapy, Graduate School of Health Sciences, Kyoto Tachibana University, 34 Yamada-Cho, Oyake, Yamashina-Ku, Kyoto, 607-8175, Japan
| | - Hiroyuki Shimada
- Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-Cho, Obu City, Aichi, 474-8511, Japan
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Wei Y, Wang X, Luo R, Mai X, Li S, Meng J. Decoding movement frequencies and limbs based on steady-state movement-related rhythms from noninvasive EEG. J Neural Eng 2023; 20:066019. [PMID: 37816342 DOI: 10.1088/1741-2552/ad01de] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 10/10/2023] [Indexed: 10/12/2023]
Abstract
Objective.Decoding different types of movements noninvasively from electroencephalography (EEG) is an essential topic in neural engineering, especially in brain-computer interface. Although the widely used sensorimotor rhythm (SMR) is efficient in limb decoding, it lacks efficacy in decoding movement frequencies. Accumulating evidence supports the notion that the movement frequency is encoded in the steady-state movement-related rhythm (SSMRR). Our study has two primary objectives: firstly, to investigate the spatial-spectral representation of SSMRR in EEG during voluntary movements; secondly, to assess whether movement frequencies and limbs can be effectively decoded based on SSMRR.Approach.To comprehensively examine the representation of SSMRR, we investigated the frequency characteristics and spatial patterns associated with various rhythmic finger movements. Coherence analysis was performed between the sensor or source domain EEG and finger movements recorded by data gloves. A fusion model based on spectral SNR features and filter-bank common spatial pattern features was utilized to decode movement frequencies and limbs.Main results.At the group-level, sensor domain, and source domain coherence maps demonstrated that the accurate movement frequency (f0) and its first harmonic (f1) were encoded in the contralateral motor cortex. For the four-class classification, including two movement frequencies for both hands, the decoding accuracies for externally paced and internally paced movements were 73.14 ± 15.86% and 66.30 ± 17.26% (averaged across ten subjects, chance levels at 31.05% and 30.96%). Notably, the average results of five subjects with the highest decoding accuracies reached 87.21 ± 7.44% and 80.44 ± 7.99%.Significance.Our results verified the EEG representation of SSMRR and proved that the movement frequency and limb could be effectively decoded based on spatial-spectral features extracted from SSMRR. We suggest that SSMRR can serve as a complement to SMR to expand the range of decodable movement types and the approaches of limb decoding.
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Affiliation(s)
- Yuxuan Wei
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Xu Wang
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Ruijie Luo
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Ximing Mai
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Songwei Li
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Jianjun Meng
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, People's Republic of China
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Aoki Y, Kazui H, Pascual-Marqui RD, Bruña R, Yoshiyama K, Wada T, Kanemoto H, Suzuki Y, Suehiro T, Satake Y, Yamakawa M, Hata M, Canuet L, Ishii R, Iwase M, Ikeda M. Normalized Power Variance: A new Field Orthogonal to Power in EEG Analysis. Clin EEG Neurosci 2023; 54:611-619. [PMID: 35345930 DOI: 10.1177/15500594221088736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
To date, electroencephalogram (EEG) has been used in the diagnosis of epilepsy, dementia, and disturbance of consciousness via the inspection of EEG waves and identification of abnormal electrical discharges and slowing of basic waves. In addition, EEG power analysis combined with a source estimation method like exact-low-resolution-brain-electromagnetic-tomography (eLORETA), which calculates the power of cortical electrical activity from EEG data, has been widely used to investigate cortical electrical activity in neuropsychiatric diseases. However, the recently developed field of mathematics "information geometry" indicates that EEG has another dimension orthogonal to power dimension - that of normalized power variance (NPV). In addition, by introducing the idea of information geometry, a significantly faster convergent estimator of NPV was obtained. Research into this NPV coordinate has been limited thus far. In this study, we applied this NPV analysis of eLORETA to idiopathic normal pressure hydrocephalus (iNPH) patients prior to a cerebrospinal fluid (CSF) shunt operation, where traditional power analysis could not detect any difference associated with CSF shunt operation outcome. Our NPV analysis of eLORETA detected significantly higher NPV values at the high convexity area in the beta frequency band between 17 shunt responders and 19 non-responders. Considering our present and past research findings about NPV, we also discuss the advantage of this application of NPV representing a sensitive early warning signal of cortical impairment. Overall, our findings demonstrated that EEG has another dimension - that of NPV, which contains a lot of information about cortical electrical activity that can be useful in clinical practice.
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Affiliation(s)
- Yasunori Aoki
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
- Department of Psychiatry, Nippon Life Hospital, Osaka, Japan
| | - Hiroaki Kazui
- Department of Neuropsychiatry, Kochi Medical School, Kochi University, Kochi, Japan
| | - Roberto D Pascual-Marqui
- The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland
| | - Ricardo Bruña
- UCM-UPM Centre for Biomedical Technology, Laboratory of Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Electrical Engineering, La Laguna University, Tenerife, Spain
| | - Kenji Yoshiyama
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Tamiki Wada
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Hideki Kanemoto
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Yukiko Suzuki
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Takashi Suehiro
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Yuto Satake
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Maki Yamakawa
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Masahiro Hata
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Leonides Canuet
- Neurology department, Nuestra Senora del Rosario hospital, Madrid, Spain
| | - Ryouhei Ishii
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
- Graduate School of Comprehensive Rehabilitation, Osaka Prefecture University, Osaka, Japan
| | - Masao Iwase
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Manabu Ikeda
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
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Jafari M, Shaabani M, Hosseini SR, Ashayeri H, Bakhshi E, Haghgoo HA. Modification of cortical electrical activity in stroke survivors with abnormal subjective visual vertical: An eLORETA study. Heliyon 2023; 9:e22194. [PMID: 38027645 PMCID: PMC10661540 DOI: 10.1016/j.heliyon.2023.e22194] [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: 05/31/2022] [Revised: 09/16/2023] [Accepted: 11/06/2023] [Indexed: 12/01/2023] Open
Abstract
Objectives Balance impairment is among the main complications of stroke. The gravity-based subjective vertical (SV) is considered an important reference for upright posture and navigation affected by stroke. The correlation between injury location and pathological perception of verticality remains controversial. This study aimed to evaluate the cortico-cortical network of vertical perception among patients with the right hemisphere stroke and abnormal visual-vertical perception compared with healthy individuals. Materials and methods This observational cross-sectional study included 40 patients with the right hemisphere stroke and 35 healthy participants. All patients had abnormal visual-vertical perception. The EEG connectivity analysis was conducted through the exact low-resolution brain electromagnetic tomography analysis (eLORETA). Results Stroke survivors manifested a power spectral density that reduced within the beta-2 frequency band in the left hemisphere and increased within the beta-3 frequency band in the right hemisphere compared with controls (p < 0.01). The lagged-phase synchronization was increased within alpha-1, beta-2, and beta-3 bands and decreased in stroke survivors compared with controls in the vestibular network involved in visual-vertical perception (p < 0.01). Conclusion The results of this study demonstrated variations in the function and functional connectivity of cortical areas involved in the visual-vertical perception that are mainly located in the vestibular cortex.
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Affiliation(s)
- Meymaneh Jafari
- Department of Audiology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Moslem Shaabani
- Department of Audiology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Seyed Ruhollah Hosseini
- Department of Psychology, Faculty of Education Sciences and Psychology, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Hassan Ashayeri
- Rehabilitation Research Center, Department of Basic Sciences, School of Rehabilitation Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Enayatollah Bakhshi
- Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Hojjat Allah Haghgoo
- Department of Occupational Therapy. University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
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Ma M, Li Y, Shao Y, Weng X. Effect of total sleep deprivation on effective EEG connectivity for young male in resting-state networks in different eye states. Front Neurosci 2023; 17:1204457. [PMID: 37928738 PMCID: PMC10620317 DOI: 10.3389/fnins.2023.1204457] [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: 04/12/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
Background Many studies have investigated the effect of total sleep deprivation (TSD) on resting-state functional networks, especially the default mode network (DMN) and sensorimotor network (SMN), using functional connectivity. While it is known that the activities of these networks differ based on eye state, it remains unclear how TSD affects them in different eye states. Therefore, we aimed to examine the effect of TSD on DMN and SMN in different eye states using effective functional connectivity via isolated effective coherence (iCoh) in exact low-resolution brain electromagnetic tomography (eLORETA). Methods Resting-state electroencephalogram (EEG) signals were collected from 24 male college students, and each participant completed a psychomotor vigilance task (PVT) while behavioral data were acquired. Each participant underwent 36-h TSD, and the data were acquired in two sleep-deprivation times (rested wakefulness, RW: 0 h; and TSD: 36 h) and two eye states (eyes closed, EC; and eyes open, EO). Changes in neural oscillations and effective connectivity were compared based on paired t-test. Results The behavioral results showed that PVT reaction time was significantly longer in TSD compared with that of RW. The EEG results showed that in the EO state, the activity of high-frequency bands in the DMN and SMN were enhanced compared to those of the EC state. Furthermore, when compared with the DMN and SMN of RW, in TSD, the activity of DMN was decreased, and SMN was increased. Moreover, the changed effective connectivity in the DMN and SMN after TSD was positively correlated with an increased PVT reaction time. In addition, the effective connectivity in the different network (EO-EC) of the SMN was reduced in the β band after TSD compared with that of RW. Conclusion These findings indicate that TSD impairs alertness and sensory information input in the SMN to a greater extent in an EO than in an EC state.
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Affiliation(s)
- Mengke Ma
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yutong Li
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing, China
- Key Laboratory for Biomechanics and Mechanobiology of the Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Xiechuan Weng
- Department of Neuroscience, Beijing Institute of Basic Medical Sciences, Beijing, China
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9
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Chaudhari A, Wang X, Wu A, Liu H. Repeated Transcranial Photobiomodulation with Light-Emitting Diodes Improves Psychomotor Vigilance and EEG Networks of the Human Brain. Bioengineering (Basel) 2023; 10:1043. [PMID: 37760145 PMCID: PMC10525861 DOI: 10.3390/bioengineering10091043] [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: 07/10/2023] [Revised: 08/16/2023] [Accepted: 08/29/2023] [Indexed: 09/29/2023] Open
Abstract
Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group's singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes.
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Affiliation(s)
| | | | | | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd, Arlington, TX 76019, USA; (A.C.); (X.W.); (A.W.)
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10
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Irie S, Tachibana A, Matsuo A. Association between Reaction Times in the Joint Simon Task and Personality Traits. Brain Sci 2023; 13:1207. [PMID: 37626563 PMCID: PMC10452160 DOI: 10.3390/brainsci13081207] [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: 07/27/2023] [Revised: 08/10/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023] Open
Abstract
Joint go and no-go effects (joint Simon effects; JSEs) are considered to have a stimulus-response compatibility effect on joint reaction time tasks (joint Simon task) caused by the presence of other people. Additionally, JSEs are known to be associated with various social factors and are therefore a potential clinical marker for communicative function; however, the relationship with the personality that is associated with communication skills remains unclear. In this study, we focused on the association between JSE and personality traits. Thirty Japanese participants (fifteen women) were recruited. First, personality trait scores were obtained using the Japanese version of the ten-item personality inventory before the experiment. Second, we measured reaction times in the joint Simon task and single go and no-go tasks with the go signal presented on the congruent and incongruent sides. At last, we analyzed the association between reaction times and personality traits by using Spearman's correlation analysis. As a result, we observed two pairs with significant correlations: JSE and neuroticism and short reaction times in the joint condition and agreeableness. In conclusion, we identified potential psychological markers associated with the joint Simon task. These findings may lead to an additional hypothesis regarding the neurobiological mechanisms of JSEs.
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Affiliation(s)
- Shun Irie
- Division for Smart Healthcare Research, Dokkyo Medical University, Tochigi 321-0293, Japan
| | | | - Akiko Matsuo
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 113-8654, Japan;
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11
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Caravaglios G, Muscoso EG, Blandino V, Di Maria G, Gangitano M, Graziano F, Guajana F, Piccoli T. EEG Resting-State Functional Networks in Amnestic Mild Cognitive Impairment. Clin EEG Neurosci 2023; 54:36-50. [PMID: 35758261 DOI: 10.1177/15500594221110036] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background. Alzheimer's cognitive-behavioral syndrome is the result of impaired connectivity between nerve cells, due to misfolded proteins, which accumulate and disrupt specific brain networks. Electroencephalography, because of its excellent temporal resolution, is an optimal approach for assessing the communication between functionally related brain regions. Objective. To detect and compare EEG resting-state networks (RSNs) in patients with amnesic mild cognitive impairment (aMCI), and healthy elderly (HE). Methods. We recruited 125 aMCI patients and 70 healthy elderly subjects. One hundred and twenty seconds of artifact-free EEG data were selected and compared between patients with aMCI and HE. We applied standard low-resolution brain electromagnetic tomography (sLORETA)-independent component analysis (ICA) to assess resting-state networks. Each network consisted of a set of images, one for each frequency (delta, theta, alpha1/2, beta1/2). Results. The functional ICA analysis revealed 17 networks common to groups. The statistical procedure demonstrated that aMCI used some networks differently than HE. The most relevant findings were as follows. Amnesic-MCI had: i) increased delta/beta activity in the superior frontal gyrus and decreased alpha1 activity in the paracentral lobule (ie, default mode network); ii) greater delta/theta/alpha/beta in the superior frontal gyrus (i.e, attention network); iii) lower alpha in the left superior parietal lobe, as well as a lower delta/theta and beta, respectively in post-central, and in superior frontal gyrus(ie, attention network). Conclusions. Our study confirms sLORETA-ICA method is effective in detecting functional resting-state networks, as well as between-groups connectivity differences. The findings provide support to the Alzheimer's network disconnection hypothesis.
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Affiliation(s)
- G Caravaglios
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - E G Muscoso
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - V Blandino
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - G Di Maria
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - M Gangitano
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - F Graziano
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - F Guajana
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - T Piccoli
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
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12
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Perez TM, Glue P, Adhia DB, Navid MS, Zeng J, Dillingham P, Smith M, Niazi IK, Young CK, De Ridder D. Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders. Trials 2022; 23:949. [DOI: 10.1186/s13063-022-06863-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/22/2022] [Indexed: 11/18/2022] Open
Abstract
Abstract
Background
The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.
Methods
We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms – Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale – Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.
Discussion
This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.
Trial registration
Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.
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Meijs H, Prentice A, Lin BD, De Wilde B, Van Hecke J, Niemegeers P, van Eijk K, Luykx JJ, Arns M. A polygenic-informed approach to a predictive EEG signature empowers antidepressant treatment prediction: A proof-of-concept study. Eur Neuropsychopharmacol 2022; 62:49-60. [PMID: 35896057 DOI: 10.1016/j.euroneuro.2022.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 07/05/2022] [Accepted: 07/08/2022] [Indexed: 11/04/2022]
Abstract
The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG signatures may help predict antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a brain network in a large cohort (N=1,123), and discover it is sex-specifically (male patients, N=617) associated with polygenic risk score (PRS) of antidepressant response. Subsequently, we demonstrate in three independent datasets the utility of the network in predicting response to antidepressant medication (male, N=232) as well as repetitive transcranial magnetic stimulation (rTMS) and concurrent psychotherapy (male, N=95). This network significantly improves a treatment response prediction model with age and baseline severity data (area under the curve, AUC=0.623 for medicaton; AUC=0.719 for rTMS). A predictive model for MDD patients, aimed at increasing the likelihood of being a responder to antidepressants or rTMS and concurrent psychotherapy based on only this network, yields a positive predictive value (PPV) of 69% for medication and 77% for rTMS. Finally, blinded out-of-sample validation of the network as predictor for psychotherapy response in another independent dataset (male, N=50) results in a within-subsample response rate of 50% (improvement of 56%). Overall, the findings provide a first proof-of-concept of a combined genetic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders, and should encourage researchers to incorporate genetic information, such as PRS, in their search for clinically relevant neuroimaging biomarkers.
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Affiliation(s)
- Hannah Meijs
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands; GGNet Mental Health, Warnsveld, the Netherlands.
| | - Amourie Prentice
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Bochao D Lin
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Bieke De Wilde
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Jan Van Hecke
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Peter Niemegeers
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Kristel van Eijk
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Jurjen J Luykx
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands; GGNet Mental Health, Warnsveld, the Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Martijn Arns
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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14
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Ferreri F, Francesca M, Fabrizio V, Manzo N, Maria C, Elda J, Rossini PM. EEG, ERPs, and EROs in patients with neurodegenerative dementing disorders: A window into the cortical neurophysiology of cognition and behavior. Int J Psychophysiol 2022; 181:85-94. [PMID: 36055410 DOI: 10.1016/j.ijpsycho.2022.08.005] [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: 05/11/2022] [Revised: 07/20/2022] [Accepted: 08/18/2022] [Indexed: 10/31/2022]
Abstract
In the human brain, physiological aging is characterized by progressive neuronal loss, leading to disruption of synapses and to a degree of failure in neurotransmission and information flow. However, there is increasing evidence to support the notion that the aged brain has a remarkable level of resilience (i.s. ability to reorganize itself), with the aim of preserving its physiological activity. It is therefore of paramount interest to develop objective markers able to characterize the biological processes underlying brain aging in the intact human, and to distinguish them from brain degeneration associated to age-related neurological progressive diseases like Alzheimer's disease. EEG, alone and combined with transcranial magnetic stimulation (TMS-EEG), is particularly suited to this aim, due to the functional nature of the information provided, and thanks to the ease with which it can be integrated in ecological scenarios including behavioral tasks. In this review, we aimed to provide the reader with updated information about the role of modern methods of EEG and TMS-EEG analysis in the investigation of physiological brain aging and Alzheimer's disease. In particular, we focused on data about cortical connectivity obtained by using readouts such graph theory network brain organization and architecture, and transcranial evoked potentials (TEPs) during TMS-EEG. Overall, findings in the literature support an important potential contribution of such neurophysiological techniques to the understanding of the mechanisms underlying normal brain aging and the early (prodromal/pre-symptomatic) stages of dementia.
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Affiliation(s)
- Florinda Ferreri
- Unit of Neurology, Unit of Clinical Neurophysiology and Study Center of Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy; Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Miraglia Francesca
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy; Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy.
| | - Vecchio Fabrizio
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy; Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy
| | - Nicoletta Manzo
- IRCCS San Camillo Hospital, Via Alberoni 70, 30126 Lido di Venezia, Venice, Italy
| | - Cotelli Maria
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di DioFatebenefratelli, Brescia, Italy
| | - Judica Elda
- Department of Neurorehabilitation Sciences, Casa Cura Policlinico, Milano, Italy
| | - Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy
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15
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Mathew J, Adhia DB, Smith ML, De Ridder D, Mani R. Source localized infraslow neurofeedback training in people with chronic painful knee osteoarthritis: A randomized, double-blind, sham-controlled feasibility clinical trial. Front Neurosci 2022; 16:899772. [PMID: 35968375 PMCID: PMC9366917 DOI: 10.3389/fnins.2022.899772] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 07/01/2022] [Indexed: 11/15/2022] Open
Abstract
Persistent pain is a key symptom in people living with knee osteoarthritis (KOA). Infra-slow Neurofeedback (ISF-NF) training is a recent development focusing on modulating cortical slow-wave activity to improve pain outcomes. A parallel, two-armed double-blinded, randomized sham-controlled, feasibility clinical trial aimed to determine the feasibility and safety of a novel electroencephalography-based infraslow fluctuation neurofeedback (EEG ISF-NF) training in people with KOA and determine the variability of clinical outcomes and EEG changes following NF training. Eligible participants attended nine 30-min ISF-NF training sessions involving three cortical regions linked to pain. Feasibility measures were monitored during the trial period. Pain and functional outcomes were measured at baseline, post-intervention, and follow-up after 2 weeks. Resting-state EEG was recorded at baseline and immediate post-intervention. Participants were middle-aged (61.7 ± 7.6 years), New Zealand European (90.5%), and mostly females (62%) with an average knee pain duration of 4 ± 3.4 years. The study achieved a retention rate of 91%, with 20/22 participants completing all the sessions. Participants rated high levels of acceptance and “moderate to high levels of perceived effectiveness of the training.” No serious adverse events were reported during the trial. Mean difference (95% CI) for clinical pain and function measures are as follows for pain severity [active: 0.89 ± 1.7 (−0.27 to 2.0); sham: 0.98 ± 1.1 (0.22–1.7)], pain interference [active: 0.75 ± 2.3 (−0.82 to 2.3); Sham: 0.89 ± 2.1 (−0.60 to 2.4)], pain unpleasantness [active: 2.6 ± 3.7 (0.17–5.1); sham: 2.8 ± 3 (0.62–5.0)] and physical function [active: 6.2 ± 13 (−2.6 to 15); sham: 1.6 ± 12 (−6.8 to 10)]. EEG sources demonstrated frequency-specific neuronal activity, functional connectivity, and ISF ratio changes following NF training. The findings of the study indicated that the ISF-NF training is a feasible, safe, and acceptable intervention for pain management in people with KOA, with high levels of perceived effectiveness. The study also reports the variability in clinical, brain activity, and connectivity changes following training.
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Affiliation(s)
- Jerin Mathew
- Centre for Health, Activity, and Rehabilitation Research, School of Physiotherapy, University of Otago, Dunedin, New Zealand
- Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
- *Correspondence: Jerin Mathew,
| | - Divya Bharatkumar Adhia
- Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | | | - Dirk De Ridder
- Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - Ramakrishnan Mani
- Centre for Health, Activity, and Rehabilitation Research, School of Physiotherapy, University of Otago, Dunedin, New Zealand
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16
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Shan X, Li J, Zeng L, Wang H, Yang T, Shao Y, Yu M. Motor Imagery-Related Changes of Neural Oscillation in Unilateral Lower Limb Amputation. Front Neurosci 2022; 16:799995. [PMID: 35663556 PMCID: PMC9160601 DOI: 10.3389/fnins.2022.799995] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 05/02/2022] [Indexed: 12/02/2022] Open
Abstract
An amputation is known to seriously affect patient quality of life. This study aimed to investigate changes in neural activity in amputees during the postoperative period using neural electrophysiological techniques. In total, 14 patients with left lower limb amputation and 18 healthy participants were included in our study. All participants were required to perform motor imagery paradigm tasks while electroencephalogram (EEG) data were recorded. Data analysis results indicated that the beta frequency band showed significantly decreased oscillatory activity in motor imaging-related brain regions such as the frontal lobe and the precentral and postcentral gyri in amputees. Furthermore, the functional independent component analysis (fICA) value of neural oscillation negatively correlated with the C4 electrode power value of the motor imagery task in amputees (p < 0.05). Therefore, changes in neural oscillations and beta frequency band in motor imagery regions may be related to brain remodeling in amputees.
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Affiliation(s)
- Xinying Shan
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Jialu Li
- School of Psychology, University of Leeds, Leeds, United Kingdom
| | - Lingjing Zeng
- School of Psychology, University of Leeds, Leeds, United Kingdom
| | - Haiteng Wang
- School of Psychology, Beijing Sport University, Beijing, China
| | - Tianyi Yang
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing, China
- *Correspondence: Yongcong Shao,
| | - Mengsun Yu
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Mengsun Yu,
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17
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Wang Y, Li J, Zeng L, Wang H, Yang T, Shao Y, Weng X. Open Eyes Increase Neural Oscillation and Enhance Effective Brain Connectivity of the Default Mode Network: Resting-State Electroencephalogram Research. Front Neurosci 2022; 16:861247. [PMID: 35573310 PMCID: PMC9092973 DOI: 10.3389/fnins.2022.861247] [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: 01/24/2022] [Accepted: 04/05/2022] [Indexed: 11/13/2022] Open
Abstract
The default mode network (DMN) has a unique activity pattern in the resting brain. Studies on resting-state brain activity are helpful to identify various brain dynamic characteristics of patients with mental diseases and those of healthy people. The brain produces a series of changes in different eye states. However, the relationship between eye states and the DMN, which is closely related to the resting state, has not been widely examined. This study recruited 42 healthy students aged 17–22. Participants completed the Profile of Mood States questionnaire. Thereafter, the electroencephalogram data was collected with the patients’ eyes open and closed. Changes in neural oscillation and the DMN’s information transmission during different eye openness states were compared. The results showed that the neural oscillation activities of the parietal-occipital network such as the superior parietal lobule and precuneus were significantly enhanced in the eyes open state. In addition, the effective connectivity within the DMN was enhanced during opened eyes, especially from the left precuneus to the left posterior cingulate cortex, and this connectivity was negatively correlated with the Vigor-Activity mood state in the eyes open state. The activity of the DMN in the resting-state is regulated by eye states, which may relate to mood and emotional perception.
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Affiliation(s)
- Yi Wang
- Department of Physical Education, Renmin University of China, Beijing, China.,School of Life Sciences and Technology, Harbin Institute of Technology, Harbin, China
| | - Jialu Li
- School of Psychology, University of Leeds, Leeds, United Kingdom
| | - Lingjing Zeng
- School of Psychology, University of Leeds, Leeds, United Kingdom
| | - Haiteng Wang
- School of Psychology, Beijing Sport University, Beijing, China
| | - Tianyi Yang
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing, China
| | - Xiechuan Weng
- Beijing Institute of Basic Medical Sciences, Beijing, China
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18
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Li Z, Huang J, Wei W, Jiang S, Liu H, Luo H, Ruan J. EEG Oscillatory Networks in Peri-Ictal Period of Absence Epilepsy. Front Neurol 2022; 13:825225. [PMID: 35547382 PMCID: PMC9081722 DOI: 10.3389/fneur.2022.825225] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/28/2022] [Indexed: 11/15/2022] Open
Abstract
Objective To investigate the dynamical brain network changes before and after an absence seizure episode in absence epilepsy (AE). Methods 21 AE patients with a current high frequency of seizures and 21 sex- and age-matched health control (HC) who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were included. Each included subject underwent a 2-h and 19-channel video EEG examination. For AE patients, five epochs of 10-s EEG data in inter-ictal, pre-ictal, and post-ictal states were collected. For the HC group, five 10-s resting-state EEG epochs were extracted. Functional independent components analysis (ICA) was carried out using the LORETA KEY tool. Results Compared with the resting-state EEG data of the HC group, the EEG data from AE patients during inter-ictal periods showed decreased alpha oscillations in regions involving the superior frontal gyrus (SFG) (BA11). From inter-ictal to pre-ictal, SFG (BA10) showed maximum decreased delta oscillations. Additionally, from pre-ictal to post-ictal, superior temporal gyrus (STG) (BA 22) presented maximum increased neural activity in the alpha band. Moreover, compared with inter-ictal EEG, post-ictal EEG showed significantly decreased theta activity in SFG (BA8). Conclusion The changes in SFG alpha oscillations are the key brain network differences between inter-ictal EEG of AE patients and resting-state EEG of HCs. The brain networks of EEG oscillatory during peri-ictal episodes are mainly involving SFG and STG. Our study suggests that altered EEG brain networks dynamics exist between inter-ictal EEG of AE patients and resting-state EEG of HCs and between pre- and post-ictal EEG in AE patients.
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Affiliation(s)
- Zhiye Li
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.,Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Jialing Huang
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.,Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Wei Wei
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.,Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Sili Jiang
- Department of Neurology, Suining Central Hospital, Suining, China
| | - Hong Liu
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.,Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Hua Luo
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.,Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Jianghai Ruan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.,Laboratory of Neurological Diseases and Brain Function, Luzhou, China
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19
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Wang X, Wanniarachchi H, Wu A, Liu H. Combination of Group Singular Value Decomposition and eLORETA Identifies Human EEG Networks and Responses to Transcranial Photobiomodulation. Front Hum Neurosci 2022; 16:853909. [PMID: 35620152 PMCID: PMC9127055 DOI: 10.3389/fnhum.2022.853909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Transcranial Photobiomodulation (tPBM) has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram (EEG) networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm2. In data processing, a novel methodology by combining group singular value decomposition (gSVD) with the exact low-resolution brain electromagnetic tomography (eLORETA) was implemented and performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components (PCs) projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band (delta, theta, alpha, beta and gamma) were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes.
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20
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Rossini PM, Miraglia F, Vecchio F, Di Iorio R, Iodice F, Cotelli M. General principles of brain electromagnetic rhythmic oscillations and implications for neuroplasticity. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:221-237. [PMID: 35034737 DOI: 10.1016/b978-0-12-819410-2.00012-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Neuro-plasticity describes the ability of the brain in achieving novel functions, either by transforming its internal connectivity, or by changing the elements of which it is made, meaning that, only those changes, that affect both structural and functional aspects of the system, can be defined as "plastic." The concept of plasticity can be applied to molecular as well as to environmental events that can be recognized as the basic mechanism by which our brain reacts to the internal and external stimuli. When considering brain plasticity within a clinical context-that is the process linked with changes of brain functions following a lesion- the term "reorganization" is somewhat synonymous, referring to the specific types of structural/functional modifications observed as axonal sprouting, long-term synaptic potentiation/inhibition or to the plasticity related genomic responses. Furthermore, brain rewires during maturation, and aging thus maintaining a remarkable learning capacity, allowing it to acquire a wide range of skills, from motor actions to complex abstract reasoning, in a lifelong expression. In this review, the contribution on the "neuroplasticity" topic coming from advanced analysis of EEG rhythms is put forward.
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Affiliation(s)
- Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy.
| | - Francesca Miraglia
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy
| | - Fabrizio Vecchio
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy; Department of Technical and Applied Sciences, eCampus University, Novedrate (Como), Italy
| | | | - Francesco Iodice
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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21
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Costa C, Vecchio F, Romoli M, Miraglia F, Cesarini EN, Alù F, Calabresi P, Rossini PM. Cognitive Decline Risk Stratification in People with Late-Onset Epilepsy of Unknown Etiology: An Electroencephalographic Connectivity and Graph Theory Pilot Study. J Alzheimers Dis 2021; 88:893-901. [PMID: 34842184 DOI: 10.3233/jad-210350] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND Although people with late onset epilepsy of unknown etiology (LOEU) are at higher risk of cognitive decline compared to the general population, we still lack affordable tools to predict and stratify their risk of dementia. OBJECTIVE This pilot-study investigates the potential application of electroencephalography (EEG) network small-world (SW) properties in predicting cognitive decline among patients with LOEU. METHODS People diagnosed with LOEU and normal cognitive examination at the time of epilepsy diagnosis were included. Cerebrospinal fluid biomarkers, brain imaging, and neuropsychological assessment were performed at the time of epilepsy diagnosis. Baseline EEG was analyzed for SW properties. Patients were followed-up over time with neuropsychological testing to define the trajectory of cognitive decline. RESULTS Over 5.1 years of follow-up, among 24 patients diagnosed with LOEU, 62.5% were female, mean age was 65.3 years, thirteen developed mild cognitive impairment (MCI), and four developed dementia. Patients with LOEU developing MCI had lower values of SW coefficients in the delta (p = 0.03) band and higher SW values in the alpha frequency bands (p = 0.02) compared to patients having normal cognition at last follow-up. The two separate ANOVAs, for low and alpha bands, confirmed an interaction between SW and cognitive decline at follow-up. A similar gradient was confirmed for patients developing dementia compared to those with normal cognitive function as well as to those developing MCI. CONCLUSION Baseline EEG analysis through SW is worth investigating as an affordable, widely available tool to stratify LOEU patients for their risk of cognitive decline.
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Affiliation(s)
- Cinzia Costa
- Neurology Clinic, S. Maria della Misericordia Hospital -University of Perugia, Perugia, Italy
| | - Fabrizio Vecchio
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilition, IRCCS San Raffaele Roma, Roma, Italy.,eCampus University, Novedrate (Como), Italy
| | - Michele Romoli
- Neurology Clinic, S. Maria della Misericordia Hospital -University of Perugia, Perugia, Italy.,UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore C.A. Pizzardi, Bologna, Italy
| | - Francesca Miraglia
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilition, IRCCS San Raffaele Roma, Roma, Italy
| | - Elena Nardi Cesarini
- Neurology Clinic, S. Maria della Misericordia Hospital -University of Perugia, Perugia, Italy.,UOC Neurologia, Ospedale di Senigallia, Senigallia, Italy
| | - Francesca Alù
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilition, IRCCS San Raffaele Roma, Roma, Italy
| | - Paolo Calabresi
- Neurologia, DipartimentoNeuroscienze, Università Cattolica del Sacro Cuore, Roma, Italy.,Neurologia, Fondazione Policlinico Universitario"A. Gemelli" IRCCS, Roma, Italy
| | - Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilition, IRCCS San Raffaele Roma, Roma, Italy
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22
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Zhou Y, Liu Z, Sun Y, Zhang H, Ruan J. Altered EEG Brain Networks in Patients with Acute Peripheral Herpes Zoster. J Pain Res 2021; 14:3429-3436. [PMID: 34754236 PMCID: PMC8570286 DOI: 10.2147/jpr.s329068] [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: 07/14/2021] [Accepted: 10/22/2021] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE To investigate whether the brain networks changed in patients with acute peripheral herpes zoster (HZ). METHODS We reviewed the EEG database in Jianyang People's Hospital. Patients with acute HZ (n=71) were enrolled from January 2016 to December 2020. Each included subject underwent a ten-minute and 16-channel EEG examination. Five epochs of 10-second EEG data in resting-state were collected from each HZ patient. Five 10-second resting-state EEG epochs from sex- and age-matched healthy controls (HC, n=71) who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were collected. Brain network and graph theory analysis based on phase locking value parameter and functional ICA were performed using a self-writing Matlab code and the LORETA KEY tool. RESULTS Compared with the HC group, the HZ patients showed significant altered brain networks. The graph theory analysis revealed that the clustering coefficient and local efficiency of full band in HZ patients were lower than those in HC group (P<0.05). In beta band, the global efficiency and local efficiency of HZ patients group decreased, compared with healthy group (P<0.05). The functional ICA showed that three components showed significant differences between the two groups. In component 2, HZ patients showed excess superior frontal gyrus (BA10) neuro oscillation in delta band and less medial frontal gyrus (BA 11) neuro oscillation in beta and gamma bands than that in HCs. And for component 3, the alpha band of the HZ patients presented increased neuro activities in superior frontal gyrus (BA 11) and decreased neuro activities in occipital lobe (BA 18). In component 4, the inferior frontal gyrus (BA 47) showed excess activity in the left hemisphere and reduced activity in the right hemisphere in delta band, compared with HC group. CONCLUSION Altered brain networks exist in resting-state EEG data of patients with acute HZ. The changes of EEG brain networks in HZ patients are characterized by decreased global efficiency and local efficiency in beta band. Moreover, the spontaneous oscillation of some brain regions involving pain management and the connectivity of default mode network changed in HZ patients. Our study provided novel understanding of HZ from an electrophysiological view, and led to converging evidence for treatment of HZ with neural regulation in future.
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Affiliation(s)
- Yan Zhou
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China
- Department of Neurology, Jianyang People’s Hospital, Jianyang, 641400, People’s Republic of China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, People’s Republic of China
| | - Zhenqin Liu
- Department of Dermatology, Jianyang People’s Hospital, Jianyang, 641400, People’s Republic of China
| | - Yuanmei Sun
- Department of Dermatology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, 400010, People’s Republic of China
| | - Hao Zhang
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, People’s Republic of China
| | - Jianghai Ruan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, People’s Republic of China
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23
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Snyder DB, Schmit BD, Hyngstrom AS, Beardsley SA. Electroencephalography resting-state networks in people with Stroke. Brain Behav 2021; 11:e02097. [PMID: 33759382 PMCID: PMC8119848 DOI: 10.1002/brb3.2097] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 01/30/2021] [Accepted: 02/04/2021] [Indexed: 12/21/2022] Open
Abstract
INTRODUCTION The purpose of this study was to characterize resting-state cortical networks in chronic stroke survivors using electroencephalography (EEG). METHODS Electroencephalography data were collected from 14 chronic stroke and 11 neurologically intact participants while they were in a relaxed, resting state. EEG power was normalized to reduce bias and used as an indicator of network activity. Correlations of orthogonalized EEG activity were used as a measure of functional connectivity between cortical regions. RESULTS We found reduced cortical activity and connectivity in the alpha (p < .05; p = .05) and beta (p < .05; p = .03) bands after stroke while connectivity in the gamma (p = .031) band increased. Asymmetries, driven by a reduction in the lesioned hemisphere, were also noted in cortical activity (p = .001) after stroke. CONCLUSION These findings suggest that stroke lesions cause a network alteration to more local (higher frequency), asymmetric networks. Understanding changes in cortical networks after stroke could be combined with controllability models to identify (and target) alternate brain network states that reduce functional impairment.
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Affiliation(s)
- Dylan B Snyder
- Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
| | - Brian D Schmit
- Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - Scott A Beardsley
- Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
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24
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Using Tools for the Analysis of the Mental Activity of Programmers. Brain Inform 2021. [DOI: 10.1007/978-3-030-86993-9_30] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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25
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Huizeling E, Wang H, Holland C, Kessler K. Age-Related Changes in Attentional Refocusing during Simulated Driving. Brain Sci 2020; 10:brainsci10080530. [PMID: 32784739 PMCID: PMC7465308 DOI: 10.3390/brainsci10080530] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 08/03/2020] [Accepted: 08/05/2020] [Indexed: 12/15/2022] Open
Abstract
We recently reported that refocusing attention between temporal and spatial tasks becomes more difficult with increasing age, which could impair daily activities such as driving (Callaghan et al., 2017). Here, we investigated the extent to which difficulties in refocusing attention extend to naturalistic settings such as simulated driving. A total of 118 participants in five age groups (18–30; 40–49; 50–59; 60–69; 70–91 years) were compared during continuous simulated driving, where they repeatedly switched from braking due to traffic ahead (a spatially focal yet temporally complex task) to reading a motorway road sign (a spatially more distributed task). Sequential-Task (switching) performance was compared to Single-Task performance (road sign only) to calculate age-related switch-costs. Electroencephalography was recorded in 34 participants (17 in the 18–30 and 17 in the 60+ years groups) to explore age-related changes in the neural oscillatory signatures of refocusing attention while driving. We indeed observed age-related impairments in attentional refocusing, evidenced by increased switch-costs in response times and by deficient modulation of theta and alpha frequencies. Our findings highlight virtual reality (VR) and Neuro-VR as important methodologies for future psychological and gerontological research.
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Affiliation(s)
- Eleanor Huizeling
- Aston Neuroscience Institute, Aston University, Birmingham B4 7ET, UK;
- Aston Research Centre for Healthy Ageing, Aston University, Birmingham B4 7ET, UK;
- Correspondence: (E.H.); (K.K.)
| | - Hongfang Wang
- Aston Neuroscience Institute, Aston University, Birmingham B4 7ET, UK;
| | - Carol Holland
- Aston Research Centre for Healthy Ageing, Aston University, Birmingham B4 7ET, UK;
| | - Klaus Kessler
- Aston Neuroscience Institute, Aston University, Birmingham B4 7ET, UK;
- Aston Research Centre for Healthy Ageing, Aston University, Birmingham B4 7ET, UK;
- Correspondence: (E.H.); (K.K.)
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26
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Simões M, Abreu R, Direito B, Sayal A, Castelhano J, Carvalho P, Castelo-Branco M. How much of the BOLD-fMRI signal can be approximated from simultaneous EEG data: relevance for the transfer and dissemination of neurofeedback interventions. J Neural Eng 2020; 17:046007. [DOI: 10.1088/1741-2552/ab9a98] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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27
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Early diagnosis of Alzheimer’s disease: the role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts. Clin Neurophysiol 2020; 131:1287-1310. [DOI: 10.1016/j.clinph.2020.03.003] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 03/01/2020] [Accepted: 03/02/2020] [Indexed: 02/06/2023]
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28
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Zhou S, Lithfous S, Després O, Pebayle T, Bi X, Dufour A. Involvement of Frontal Functions in Pain Tolerance in Aging: Evidence From Neuropsychological Assessments and Gamma-Band Oscillations. Front Aging Neurosci 2020; 12:131. [PMID: 32536860 PMCID: PMC7266988 DOI: 10.3389/fnagi.2020.00131] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2019] [Accepted: 04/20/2020] [Indexed: 11/13/2022] Open
Abstract
Reduced pain tolerance may be one of the possible explanations for high prevalence of chronic pain among older people. We hypothesized that age-related alterations in pain tolerance are associated with functioning deterioration of the frontal cortex during normal aging. Twenty-one young and 41 elderly healthy participants underwent a tonic heat pain test, during which cerebral activity was recorded using electroencephalography (EEG). Elderly participants were divided into two subgroups according to their scores on executive tests, high performers (HPs; n = 21) and low performers (LPs; n = 20). Pain measures [exposure times (ETs) and perceived pain ratings] and cerebral activity were compared among the three groups. ETs were significantly lower in elderly LPs than in young participants and elderly HPs. Electroencephalographic analyses showed that gamma-band oscillations (GBOs) were significantly increased in pain state for all subjects, especially in the frontal sites. Source analysis showed that GBO increase in elderly LPs was contributed not only by frontal but also by central, parietal, and occipital regions. These findings suggest that better preservation of frontal functions may result in better pain tolerance by elderly subjects.
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Affiliation(s)
- Shu Zhou
- Laboratoire de Neurosciences Cognitives et Adaptatives, UMR 7364 - Université de Strasbourg - CNRS, Strasbourg, France.,Department of Neurology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Ségolène Lithfous
- Laboratoire de Neurosciences Cognitives et Adaptatives, UMR 7364 - Université de Strasbourg - CNRS, Strasbourg, France
| | - Olivier Després
- Laboratoire de Neurosciences Cognitives et Adaptatives, UMR 7364 - Université de Strasbourg - CNRS, Strasbourg, France
| | - Thierry Pebayle
- Centre d'Investigations Neurocognitives et Neurophysiologiques, UMS 3489 - Université de Strasbourg - CNRS, Strasbourg, France
| | - Xiaoying Bi
- Department of Neurology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - André Dufour
- Laboratoire de Neurosciences Cognitives et Adaptatives, UMR 7364 - Université de Strasbourg - CNRS, Strasbourg, France.,Centre d'Investigations Neurocognitives et Neurophysiologiques, UMS 3489 - Université de Strasbourg - CNRS, Strasbourg, France
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Rossini PM, Miraglia F, Alù F, Cotelli M, Ferreri F, Di Iorio R, Iodice F, Vecchio F. Neurophysiological Hallmarks of Neurodegenerative Cognitive Decline: The Study of Brain Connectivity as A Biomarker of Early Dementia. J Pers Med 2020; 10:E34. [PMID: 32365890 PMCID: PMC7354555 DOI: 10.3390/jpm10020034] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/26/2020] [Accepted: 04/27/2020] [Indexed: 02/07/2023] Open
Abstract
Neurodegenerative processes of various types of dementia start years before symptoms, but the presence of a "neural reserve", which continuously feeds and supports neuroplastic mechanisms, helps the aging brain to preserve most of its functions within the "normality" frame. Mild cognitive impairment (MCI) is an intermediate stage between dementia and normal brain aging. About 50% of MCI subjects are already in a stage that is prodromal-to-dementia and during the following 3 to 5 years will develop clinically evident symptoms, while the other 50% remains at MCI or returns to normal. If the risk factors favoring degenerative mechanisms are modified during early stages (i.e., in the prodromal), the degenerative process and the loss of abilities in daily living activities will be delayed. It is therefore extremely important to have biomarkers able to identify-in association with neuropsychological tests-prodromal-to-dementia MCI subjects as early as possible. MCI is a large (i.e., several million in EU) and substantially healthy population; therefore, biomarkers should be financially affordable, largely available and non-invasive, but still accurate in their diagnostic prediction. Neurodegeneration initially affects synaptic transmission and brain connectivity; methods exploring them would represent a 1st line screening. Neurophysiological techniques able to evaluate mechanisms of synaptic function and brain connectivity are attracting general interest and are described here. Results are quite encouraging and suggest that by the application of artificial intelligence (i.e., learning-machine), neurophysiological techniques represent valid biomarkers for screening campaigns of the MCI population.
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Affiliation(s)
- Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy; (F.M.); (F.A.); (F.I.); (F.V.)
| | - Francesca Miraglia
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy; (F.M.); (F.A.); (F.I.); (F.V.)
| | - Francesca Alù
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy; (F.M.); (F.A.); (F.I.); (F.V.)
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di DioFatebenefratelli, 25125 Brescia, Italy;
| | - Florinda Ferreri
- Department of Neuroscience, Unit of Neurology and Neurophysiology, University of Padua, 35100 Padua, Italy;
- Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, 70100 Kuopio, Finland
| | - Riccardo Di Iorio
- Neurology Unit, IRCCS Polyclinic A. Gemelli Foundation, 00168 Rome, Italy;
| | - Francesco Iodice
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy; (F.M.); (F.A.); (F.I.); (F.V.)
- Neurology Unit, IRCCS Polyclinic A. Gemelli Foundation, 00168 Rome, Italy;
| | - Fabrizio Vecchio
- Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy; (F.M.); (F.A.); (F.I.); (F.V.)
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30
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Kamarajan C, Ardekani BA, Pandey AK, Chorlian DB, Kinreich S, Pandey G, Meyers JL, Zhang J, Kuang W, Stimus AT, Porjesz B. Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures. Behav Sci (Basel) 2020; 10:bs10030062. [PMID: 32121585 PMCID: PMC7139327 DOI: 10.3390/bs10030062] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 02/26/2020] [Accepted: 02/28/2020] [Indexed: 12/16/2022] Open
Abstract
: Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD.
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Affiliation(s)
- Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
- Correspondence: ; Tel.: +1-718-270-2913
| | - Babak A. Ardekani
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA;
- Department of Psychiatry, NYU School of Medicine, New York, NY 10016, USA
| | - Ashwini K. Pandey
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - David B. Chorlian
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - Sivan Kinreich
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - Gayathri Pandey
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - Jacquelyn L. Meyers
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - Jian Zhang
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - Weipeng Kuang
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - Arthur T. Stimus
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA; (A.K.P.); (D.B.C.); (S.K.); (G.P.); (J.L.M.); (J.Z.); (W.K.); (A.T.S.); (B.P.)
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Schneider L, Seeger V, Timmermann L, Florin E. Electrophysiological resting state networks of predominantly akinetic-rigid Parkinson patients: Effects of dopamine therapy. NEUROIMAGE-CLINICAL 2020; 25:102147. [PMID: 31954989 PMCID: PMC6965744 DOI: 10.1016/j.nicl.2019.102147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 11/21/2019] [Accepted: 12/21/2019] [Indexed: 11/25/2022]
Abstract
Analysis of whole-brain frequency-specific resting state networks with EEG. Comparison of dopamine medication ON and OFF state in Parkinson patients. Parkinson patients show distinct frequency-specific network alterations. Motor network at beta frequencies is re-instated after dopamine medication.
Parkinson's disease (PD) causes both motor and non-motor symptoms, which can partially be reversed by dopamine therapy. These symptoms as well as the effect of dopamine may be explained by distinct alterations in whole-brain architecture. We used functional connectivity (FC) and in particular resting state network (RSN) analysis to identify such whole-brain alterations in a frequency-specific manner. In addition, we hypothesized that standard dopaminergic medication would have a normalizing effect on these whole brain alterations. We recorded resting-state EEGs of 19 PD patients in the medical OFF and ON states, and of 12 healthy age-matched controls. The PD patients were either of akinetic-rigid or mixed subtype. We extracted RSNs with independent component analysis in the source space for five frequency bands. Within the sensorimotor network (SMN) the supplementary motor area (SMA) showed decreased FC in the OFF state compared to healthy controls. This finding was reversed after dopamine administration. Furthermore, in the OFF state no stable SMN beta component could be identified. The default mode network showed alterations due to PD independent of the medication state. The visual network was altered in the OFF state, and reinstated to a pattern similar to healthy controls by medication. In conclusion, PD causes distinct RSN alterations, which are partly reversed after levodopa administration. The changes within the SMN are of particular interest, because they broaden the pathophysiological understanding of PD. Our results identify the SMA as a central network hub affected in PD and a crucial effector of dopamine therapy.
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Affiliation(s)
- Lukas Schneider
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany
| | - Valentin Seeger
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany; Department of Neurology, University Hospital Marburg, Baldingerstrasse, 35043 Marburg, Germany
| | - Esther Florin
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Germany.
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32
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Vlcek P, Bares M, Novak T, Brunovsky M. Baseline Difference in Quantitative Electroencephalography Variables Between Responders and Non-Responders to Low-Frequency Repetitive Transcranial Magnetic Stimulation in Depression. Front Psychiatry 2020; 11:83. [PMID: 32174854 PMCID: PMC7057228 DOI: 10.3389/fpsyt.2020.00083] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 02/03/2020] [Indexed: 12/13/2022] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depressive disorder, with outcomes approaching 45-55% response and 30-40% remission. Eligible predictors of treatment outcome, however, are still lacking. Few studies have investigated quantitative electroencephalography (QEEG) parameters as predictors of rTMS treatment outcome and none of them have addressed the source localization techniques to predict the response to low-frequency rTMS (LF rTMS). We investigated electrophysiological differences based on scalp EEG data and inverse solution method, exact low-resolution brain electromagnetic tomography (eLORETA), between responders and non-responders to LF rTMS in resting brain activity recorded prior to the treatment. Twenty-five unmedicated depressive patients (mean age of 45.7 years, 20 females) received a 4-week treatment of LF rTMS (1 Hz; 20 sessions per 600 pulses; 100% of the motor threshold) over the right dorsolateral prefrontal cortex. Comparisons between responders (≥50% reduction in Montgomery-Åsberg Depression Rating Scale score) and non-responders were made at baseline for measures of eLORETA current density, spectral absolute power, and inter-hemispheric and intra-hemispheric EEG asymmetry. Responders were found to have lower current source densities in the alpha-2 and beta-1 frequency bands bilaterally (with predominance on the left side) in the inferior, medial, and middle frontal gyrus, precentral gyrus, cingulate gyrus, anterior cingulate, and insula. The most pronounced difference was found in the left middle frontal gyrus for alpha-2 and beta-1 bands (p < 0.05). Using a spectral absolute power analysis, we found a negative correlation between the absolute power in beta and theta frequency bands on the left frontal electrode F7 and the change in depressive symptomatology. None of the selected asymmetries significantly differentiated responders from non-responders in any frequency band. Pre-treatment reduction of alpha-2 and beta-1 sources, but not QEEG asymmetry, was found in patients with major depressive disorder who responded to LF rTMS treatment. Prospective trials with larger groups of subjects are needed to further validate these findings.
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Affiliation(s)
- Premysl Vlcek
- National Institute of Mental Health, Klecany, Czechia.,Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Martin Bares
- National Institute of Mental Health, Klecany, Czechia.,Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Tomas Novak
- National Institute of Mental Health, Klecany, Czechia.,Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Martin Brunovsky
- National Institute of Mental Health, Klecany, Czechia.,Third Faculty of Medicine, Charles University, Prague, Czechia
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Gerrits B, Vollebregt MA, Olbrich S, van Dijk H, Palmer D, Gordon E, Pascual-Marqui R, Kessels RPC, Arns M. Probing the "Default Network Interference Hypothesis" With EEG: An RDoC Approach Focused on Attention. Clin EEG Neurosci 2019; 50:404-412. [PMID: 31322000 DOI: 10.1177/1550059419864461] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Studies have shown that specific networks (default mode network [DMN] and task positive network [TPN]) activate in an anticorrelated manner when sustaining attention. Related EEG studies are scarce and often lack behavioral validation. We performed independent component analysis (ICA) across different frequencies (source-level), using eLORETA-ICA, to extract brain-network activity during resting-state and sustained attention. We applied ICA to the voxel domain, similar to functional magnetic resonance imaging methods of analyses. The obtained components were contrasted and correlated to attentional performance (omission errors) in a large sample of healthy subjects (N = 1397). We identified one component that robustly correlated with inattention and reflected an anticorrelation of delta activity in the anterior cingulate and precuneus, and delta and theta activity in the medial prefrontal cortex and with alpha and gamma activity in medial frontal regions. We then compared this component between optimal and suboptimal attentional performers. For the latter group, we observed a greater change in component loading between resting-state and sustained attention than for the optimal performers. Following the National Institute of Mental Health Research Domain Criteria (RDoC) approach, we prospectively replicated and validated these findings in subjects with attention deficit/hyperactivity disorder. Our results provide further support for the "default mode interference hypothesis."
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Affiliation(s)
- Berrie Gerrits
- 1 Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands.,2 Research Institute Brainclinics, Nijmegen, the Netherlands
| | - Madelon A Vollebregt
- 2 Research Institute Brainclinics, Nijmegen, the Netherlands.,3 Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Sebastian Olbrich
- 2 Research Institute Brainclinics, Nijmegen, the Netherlands.,4 Department for Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, Zurich, Switzerland
| | | | - Donna Palmer
- 5 Brain Resource Inc, Sydney, New South Wales, Australia
| | | | - Roberto Pascual-Marqui
- 7 The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland.,8 Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
| | - Roy P C Kessels
- 1 Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands.,9 Department of Medical Psychology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Martijn Arns
- 2 Research Institute Brainclinics, Nijmegen, the Netherlands.,10 Department of Experimental Psychology, Utrecht University, Utrecht, The Netherlands.,11 neuroCare Group, Munich, Germany
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34
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Kodama T, Katayama O, Nakano H, Ueda T, Murata S. Treatment of Medial Medullary Infarction Using a Novel iNems Training: A Case Report and Literature Review. Clin EEG Neurosci 2019; 50:429-435. [PMID: 30955363 DOI: 10.1177/1550059419840246] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Objective. We describe the case of a 66-year-old Japanese male patient who developed medial medullary infarction along with severe motor paralysis and intense numbness of the left arm, pain catastrophizing, and abnormal physical sensation. We further describe his recovery using a new imagery neurofeedback-based multisensory systems (iNems) training method. Clinical Course and Intervention. The patient underwent physical therapy for the rehabilitation of motor paralysis and numbness of the paralyzed upper limbs; in addition, we implemented iNems training using EEG activity, which aims to synchronize movement intent (motor imagery) with sensory information (feedback visual information). Results. Considerable improvement in motor function, pain catastrophizing, representation of the body in the brain, and abnormal physical sensations was accomplished with iNems training. Furthermore, iNems training improved the neural activity of the default mode network at rest and the sensorimotor region when the movement was intended. Conclusions. The newly developed iNems could prove a novel, useful tool for neurorehabilitation considering that both behavioral and neurophysiological changes were observed in our case.
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Affiliation(s)
- Takayuki Kodama
- 1 Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Osamu Katayama
- 2 Department of Rehabilitation, Watanabe Hospital, Aichi, Japan
| | - Hideki Nakano
- 3 Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Tomohiro Ueda
- 1 Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Shin Murata
- 1 Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
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35
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Rossini P, Di Iorio R, Bentivoglio M, Bertini G, Ferreri F, Gerloff C, Ilmoniemi R, Miraglia F, Nitsche M, Pestilli F, Rosanova M, Shirota Y, Tesoriero C, Ugawa Y, Vecchio F, Ziemann U, Hallett M. Methods for analysis of brain connectivity: An IFCN-sponsored review. Clin Neurophysiol 2019; 130:1833-1858. [DOI: 10.1016/j.clinph.2019.06.006] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 05/08/2019] [Accepted: 06/18/2019] [Indexed: 01/05/2023]
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36
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Tait L, Stothart G, Coulthard E, Brown JT, Kazanina N, Goodfellow M. Network substrates of cognitive impairment in Alzheimer’s Disease. Clin Neurophysiol 2019; 130:1581-1595. [DOI: 10.1016/j.clinph.2019.05.027] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 03/26/2019] [Accepted: 05/17/2019] [Indexed: 12/28/2022]
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Jia H, Yu D. Attenuated long-range temporal correlations of electrocortical oscillations in patients with autism spectrum disorder. Dev Cogn Neurosci 2019; 39:100687. [PMID: 31377569 PMCID: PMC6969363 DOI: 10.1016/j.dcn.2019.100687] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 06/24/2019] [Accepted: 07/26/2019] [Indexed: 11/30/2022] Open
Abstract
The LRTCs of beta and low-gamma oscillations were significantly attenuated in ASD patients compared to TD participants. The regions with attenuated LRTCs were mainly located in certain social functions related cortical networks. ASD is associated with highly volatile neuronal states of electrocortical oscillations.
The aim of this study was to investigate the long-range temporal correlations (LRTCs) of instantaneous amplitude of electrocortical oscillations in patients with autism spectrum disorder (ASD). Using the resting-state electroencephalography (EEG) of 15 patients with ASD (aged between 5˜18 years, mean age = 11.6 years, SD = 4.4 years) and 18 typical developing (TD) people (aged between 5˜18 years, mean age = 8.9 years, SD = 2.4 years), we estimated the LRTCs of neuronal oscillations amplitude of 84 predefined cortical regions of interest using detrended fluctuation analysis (DFA) after confirming the presence of scale invariance. We found that the DFA exponents of instantaneous amplitude of beta and low-gamma oscillations were significantly attenuated in patients with ASD compared to TD participants. Moreover, the regions with attenuated DFA exponent were mainly located in social functions related cortical networks, including the default mode network (DMN), the mirror neuron system (MNS) and the salience network (SN). These findings suggest that ASD is associated with highly volatile neuronal states of electrocortical oscillations, which may be related to social and cognitive dysfunction in patients with ASD.
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Affiliation(s)
- Huibin Jia
- Key Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, Jiangsu, China
| | - Dongchuan Yu
- Key Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, Jiangsu, China.
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38
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da Silva Junior M, de Freitas RC, dos Santos WP, da Silva WWA, Rodrigues MCA, Conde EFQ. Exploratory study of the effect of binaural beat stimulation on the EEG activity pattern in resting state using artificial neural networks. COGN SYST RES 2019. [DOI: 10.1016/j.cogsys.2018.11.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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39
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Aoki Y, Kazui H, Pascual-Marqui RD, Ishii R, Yoshiyama K, Kanemoto H, Suzuki Y, Sato S, Azuma S, Suehiro T, Matsumoto T, Hata M, Canuet L, Iwase M, Ikeda M. EEG Resting-State Networks Responsible for Gait Disturbance Features in Idiopathic Normal Pressure Hydrocephalus. Clin EEG Neurosci 2019; 50:210-218. [PMID: 30417664 DOI: 10.1177/1550059418812156] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric disease characterized by gait disturbance, cognitive dysfunction, and urinary incontinence that affects a large population of elderly people. These symptoms, especially gait disturbance, can potentially be improved by cerebrospinal fluid (CSF) drainage, which is more effective if performed at an early stage of the disease. However, the neurophysiological mechanisms of these symptoms and their recovery by CSF drainage are poorly understood. In this study, using exact low-resolution brain electromagnetic tomography-independent component analysis (eLORETA-ICA) with electroencephalography (EEG) data, we assessed activities of five EEG resting-state networks (EEG-RSNs) in 58 iNPH patients before and after drainage of CSF by lumbar puncture (CSF tapping). In addition, we assessed correlations of changes in these five EEG-RSNs activities with CSF tapping-induced changes in iNPH symptoms. The results reveal that compared with 80 healthy controls, iNPH patients had significantly decreased activities in the occipital alpha rhythm, visual perception network, and self-referential network before CSF tapping. Furthermore, CSF tapping-induced changes in occipital alpha activity correlated with changes in postural sway and frontal lobe function. Changes in visual perception network activity correlated with changes in gait speed. In addition, changes in memory perception network activity correlated with changes in Parkinsonian gait features. These results indicate a recruitment of cognitive networks in gait control, and involvement of the occipital alpha activity in cognitive dysfunction in iNPH patients. Based on these findings, eLORETA-ICA with EEG data can be considered a noninvasive, useful tool for detection of EEG-RSN activities and for understanding the neurophysiological mechanisms underlying this disease.
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Affiliation(s)
- Yasunori Aoki
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.,2 Department of Psychiatry, Nippon Life Hospital, Osaka, Japan
| | - Hiroaki Kazui
- 3 Department of Neuropsychiatry, Kochi University, Kochi, Japan
| | - Roberto D Pascual-Marqui
- 4 The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland.,5 Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
| | - Ryouhei Ishii
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Kenji Yoshiyama
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Hideki Kanemoto
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.,6 Department of Psychiatry, Mizuma Hospital, Osaka, Japan.,7 Cognitive Reserve Research Center, Osaka Kawasaki Rehabilitation University, Osaka, Japan
| | - Yukiko Suzuki
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Shunsuke Sato
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Shingo Azuma
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Takashi Suehiro
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Takuya Matsumoto
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Masahiro Hata
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Leonides Canuet
- 8 Department of Clinical Psychology and Psychobiology, La Laguna University, Tenerife, Spain
| | - Masao Iwase
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Manabu Ikeda
- 1 Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
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40
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Electrophysiological assessment methodology of sensory processing dysfunction in schizophrenia and dementia of the Alzheimer type. Neurosci Biobehav Rev 2019; 97:70-84. [DOI: 10.1016/j.neubiorev.2018.09.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 09/04/2018] [Accepted: 09/05/2018] [Indexed: 12/26/2022]
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Fleischmann R, Traenkner S, Kraft A, Schmidt S, Schreiber SJ, Brandt SA. Delirium is associated with frequency band specific dysconnectivity in intrinsic connectivity networks: preliminary evidence from a large retrospective pilot case-control study. Pilot Feasibility Stud 2019; 5:2. [PMID: 30631448 PMCID: PMC6322230 DOI: 10.1186/s40814-018-0388-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 12/17/2018] [Indexed: 12/25/2022] Open
Abstract
Background Pathophysiological concepts in delirium are not sufficient to define objective biomarkers suited to improve clinical approaches. Advances in neuroimaging have revalued electroencephalography (EEG) as a tool to assess oscillatory network activity in neuropsychiatric disease. Yet, research in the field is limited to small populations and largely confined to postoperative delirium, which impedes generalizability of findings and planning of prospective studies in other populations. This study aimed to assess effect sizes of connectivity measures in a large mixed population to demonstrate that there are measurable EEG differences between delirium and control patients. Methods This retrospective pilot study investigated EEG measures as biomarkers in delirium using a case-control design including patients diagnosed with delirium (DSM-5 criteria) and age-/gender-matched controls drawn from a database of 9980 patients (n = 129 and 414, respectively). Assessors were not blinded for groups. Power spectra and connectivity estimates, using the weighted phase log index, of continuous EEG data were compared between conditions. Alterations of information flow through nodes of intrinsic connectivity networks (ICN; default mode, salience, and executive control network) were evaluated in source space using betweenness centrality. This was done frequency specific and network nodes were defined by the multimodal human cerebral cortex parcellation based on human connectome project data. Results Delirium and control patients exhibited distinct EEG power, connectivity, and network characteristics (F(72,540) = 70.3, p < .001; F(493,1079) = 2.69, p < .001; and F(718,2159) = 1.14, p = .007, respectively). Connectivity analyses revealed global alpha and regional beta band disconnectivity that was accompanied by theta band hyperconnectivity in delirious patients. Source and network analyses yielded that these changes are not specific to single intrinsic connectivity networks but affect multiple nodes of networks engaged in level of consciousness, attention, working memory, executive control, and salience detection. Effect sizes were medium to strong in this mixed population of delirious patients. Conclusions We quantified effect sizes for EEG connectivity and network analyses to be expected in delirium. This study implicates that theta band hyperconnectivity and alpha band disconnectivity may be essential mechanisms in the pathophysiology of delirium. Upcoming prospective studies will build upon these results and evaluate the clinical utility of identified EEG measures as therapeutic and prognostic biomarkers. Electronic supplementary material The online version of this article (10.1186/s40814-018-0388-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Robert Fleischmann
- 1Vision and Motor System Research Group, Department of Neurology, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany.,2Department of Neurology, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Steffi Traenkner
- 1Vision and Motor System Research Group, Department of Neurology, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Antje Kraft
- 1Vision and Motor System Research Group, Department of Neurology, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Sein Schmidt
- 1Vision and Motor System Research Group, Department of Neurology, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Stephan J Schreiber
- 3Department of Neurology, Asklepios Fachklinikum Brandenburg, 14772 Brandenburg an der Havel, Brandenburg Germany
| | - Stephan A Brandt
- 1Vision and Motor System Research Group, Department of Neurology, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
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Katayama O, Tsukamoto T, Osumi M, Kodama T, Morioka S. Neural Mechanism of Altered Limb Perceptions Caused by Temporal Sensorimotor Incongruence. Front Behav Neurosci 2018; 12:282. [PMID: 30515087 PMCID: PMC6255791 DOI: 10.3389/fnbeh.2018.00282] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 11/05/2018] [Indexed: 12/30/2022] Open
Abstract
Previous studies have demonstrated that patients with strokes or pathological pain suffer distorted limb ownership and an inability to perceive their affected limbs as a part of their bodies. These disturbances are apparent in experiments showing time delays between motor commands and visual feedback. The experimental paradigm manipulating temporal delay is considered possible to clarify, in detail, the degree of altered limb perception, peculiarity and movement disorders that are caused by temporal sensorimotor incongruence. However, the neural mechanisms of these body perceptions, peculiarity and motor control remain unknown. In this experiment, we used exact low-resolution brain electromagnetic tomography (eLORETA) with independent component analysis (ICA) to clarify the neural mechanisms of altered limb perceptions caused by temporal sensorimotor incongruence. Seventeen healthy participants were recruited, and temporal sensorimotor incongruence was systematically evoked using a visual feedback delay system. Participants periodically extended their right wrists while viewing video images of their hands that were delayed by 0, 150, 250, 350 and 600 ms. To investigate neural mechanisms, altered limb perceptions were then rated using the 7-point Likert scale and brain activities were concomitantly examined with electroencephalographic (EEG) analyses using eLORETA-ICA. These experiments revealed that peculiarities are caused prior to perceptions of limb loss and heaviness. Moreover, we show that supplementary motor and parietal association areas are involved in changes of peculiarity, limb loss, heaviness and movement accuracy due to temporal sensorimotor incongruence. We suggest that abnormalities in these areas contribute to neural mechanisms that modify altered limb perceptions and movement accuracy.
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Affiliation(s)
- Osamu Katayama
- Department of Neurorehabilitation, Graduate School of Health Sciences, Kio University, Nara, Japan.,Department of Rehabilitation, Watanabe Hospital, Aichi, Japan
| | - Tatsuya Tsukamoto
- Department of Undergraduate School of Health Sciences, Kio University, Nara, Japan
| | - Michihiro Osumi
- Department of Neurorehabilitation, Graduate School of Health Sciences, Kio University, Nara, Japan.,Department of Neurorehabilitation Research Center, Kio University, Nara, Japan
| | - Takayuki Kodama
- Department of Physical Therapy, Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Shu Morioka
- Department of Neurorehabilitation, Graduate School of Health Sciences, Kio University, Nara, Japan.,Department of Neurorehabilitation Research Center, Kio University, Nara, Japan
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43
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Kazemi R, Rostami R, Khomami S, Baghdadi G, Rezaei M, Hata M, Aoki Y, Ishii R, Iwase M, Fitzgerald PB. Bilateral Transcranial Magnetic Stimulation on DLPFC Changes Resting State Networks and Cognitive Function in Patients With Bipolar Depression. Front Hum Neurosci 2018; 12:356. [PMID: 30233346 PMCID: PMC6135217 DOI: 10.3389/fnhum.2018.00356] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 08/20/2018] [Indexed: 01/13/2023] Open
Abstract
Introduction: Bipolar patients have abnormalities in cognitive functions and emotional processing. Two resting state networks (RSNs), the default mode network (DMN) and the sensorimotor network (SMN), play a decisive role in these two functions. Dorsolateral prefrontal cortex (DLPFC) is one of the main areas in the central executive network (CEN), which is linked to the activities of each of the two networks. Studies have found DLPFC abnormalities in both hemispheres of patients with bipolar depression. We hypothesized that the bilateral repetitive transcranial magnetic stimulation (rTMS) of DLPFC would produce changes in the activity of both the SMN and DMN as well as relevant cognitive function in patients with bipolar depression that responded to treatment. Methods: 20 patients with bipolar depression underwent 10 sessions of 1 Hz rTMS on right DLPFC with subsequent 10 Hz rTMS on left DLPFC. Changes in electroencephalography resting networks between pre and post rTMS were evaluated utilizing low-resolution electromagnetic tomography (eLORETA). Depression symptom was assessed using the Beck Depression Inventory (BDI-II) and cognitive function was assessed by Verbal Fluency Test (VFT), Rey Auditory Verbal Learning Test (RAVLT), Stroop Test, and Wisconsin Card Sorting Test (WCST). Results: Responders to rTMS showed significantly lower DMN activity at baseline and a significant decrease in SMN connectivity after treatment. Non-responders did not significantly differ from the control group at the baseline and they showed higher activity in the SMN, visual network, and visual perception network compared to control group following treatment. Bilateral rTMS resulted in significant changes in the executive functions, verbal memory, and depression symptoms. No significant changes were observed in selective attention and verbal fluency. Conclusion: Bilateral stimulation of DLPFC, as the main node of CEN, results in changes in the activity of the SMN and consequently improves verbal memory and executive functions in patients with bipolar depression.
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Affiliation(s)
- Reza Kazemi
- Cognitive Lab, Department of Psychology, University of Tehran, Tehran, Iran.,Atieh Clinical Neuroscience Center, Tehran, Iran
| | - Reza Rostami
- Department of Psychology, University of Tehran, Tehran, Iran
| | - Sanaz Khomami
- Cognitive Lab, Department of Psychology, University of Tehran, Tehran, Iran
| | - Golnaz Baghdadi
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Mehdi Rezaei
- Behavioral Sciences Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Masahiro Hata
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Yasunori Aoki
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Ryouhei Ishii
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Masao Iwase
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Paul B Fitzgerald
- Epworth Healthcare, Epworth Clinic Camberwell, Victoria Australia and Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University, Melbourne, VIC, Australia
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44
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Li L, Babawale O, Yennu A, Trowbridge C, Hulla R, Gatchel RJ, Liu H. Whole-cortical graphical networks at wakeful rest in young and older adults revealed by functional near-infrared spectroscopy. NEUROPHOTONICS 2018; 5:035004. [PMID: 30137882 PMCID: PMC6063133 DOI: 10.1117/1.nph.5.3.035004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 07/02/2018] [Indexed: 05/17/2023]
Abstract
A good understanding of age-dependent changes and modifications in brain networks is crucial for fully exploring the effects of aging on the human brain. Few reports have been found in studies of functional brain networks using functional near-infrared spectroscopy (fNIRS). Moreover, little is known about the feasibility of using fNIRS to assess age-related changes in brain connectomes. This study applied whole brain fNIRS measurement, combined with graph theory analysis, to assess the age-dependent changes in resting-state brain networks. Five to eight minutes of resting-state brain hemodynamic signals were recorded from 48 participants (18 young adults and 30 older adults) with 133 optical channels covering the majority of the cortical regions. Both local and global graph metrics were computed to identify the age-related changes of topographical brain networks. Older adults showed an overall decline of both global and local efficiency compared to young adults, as well as the decline of small-worldness. In addition, young adults showed the abundance of hubs in the prefrontal cortex, whereas older adults revealed the hub shifts to the sensorimotor cortex. These obvious shifts of hubs may potentially indicate decreases of the decision-making, memory, and other high-order functions as people age. Our results showed consistent findings with published literature and also demonstrated the feasibility of whole-head fNIRS measurements to assess age-dependent changes in resting-state brain networks.
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Affiliation(s)
- Lin Li
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
- University of California at Los Angeles, David Geffen School of Medicine, Department of Neurology, Los Angeles, California, United States
| | - Olajide Babawale
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
| | - Amarnath Yennu
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
- Stanford University School of Medicine, Department of Neurology, Stanford, California, United States
| | - Cynthia Trowbridge
- University of Texas at Arlington, Department of Kinesiology, Arlington, Texas, United States
| | - Ryan Hulla
- University of Texas at Arlington, College of Science, Department of Psychology, Arlington, Texas, United States
| | - Robert J. Gatchel
- University of Texas at Arlington, College of Science, Department of Psychology, Arlington, Texas, United States
| | - Hanli Liu
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
- Address all correspondence to: Hanli Liu, E-mail:
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45
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Hindriks R, Micheli C, Bosman CA, Oostenveld R, Lewis C, Mantini D, Fries P, Deco G. Source-reconstruction of the sensorimotor network from resting-state macaque electrocorticography. Neuroimage 2018; 181:347-358. [PMID: 29886144 DOI: 10.1016/j.neuroimage.2018.06.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 06/01/2018] [Accepted: 06/04/2018] [Indexed: 10/28/2022] Open
Abstract
The discovery of hemodynamic (BOLD-fMRI) resting-state networks (RSNs) has brought about a fundamental shift in our thinking about the role of intrinsic brain activity. The electrophysiological underpinnings of RSNs remain largely elusive and it has been shown only recently that electric cortical rhythms are organized into the same RSNs as hemodynamic signals. Most electrophysiological studies into RSNs use magnetoencephalography (MEG) or scalp electroencephalography (EEG), which limits the spatial resolution with which electrophysiological RSNs can be observed. Due to their close proximity to the cortical surface, electrocorticographic (ECoG) recordings can potentially provide a more detailed picture of the functional organization of resting-state cortical rhythms, albeit at the expense of spatial coverage. In this study we propose using source-space spatial independent component analysis (spatial ICA) for identifying generators of resting-state cortical rhythms as recorded with ECoG and for reconstructing their functional connectivity. Network structure is assessed by two kinds of connectivity measures: instantaneous correlations between band-limited amplitude envelopes and oscillatory phase-locking. By simulating rhythmic cortical generators, we find that the reconstruction of oscillatory phase-locking is more challenging than that of amplitude correlations, particularly for low signal-to-noise levels. Specifically, phase-lags can both be over- and underestimated, which troubles the interpretation of lag-based connectivity measures. We illustrate the methodology on somatosensory beta rhythms recorded from a macaque monkey using ECoG. The methodology decomposes the resting-state sensorimotor network into three cortical generators, distributed across primary somatosensory and primary and higher-order motor areas. The generators display significant and reproducible amplitude correlations and phase-locking values with non-zero lags. Our findings illustrate the level of spatial detail attainable with source-projected ECoG and motivates wider use of the methodology for studying resting-state as well as event-related cortical dynamics in macaque and human.
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Affiliation(s)
- R Hindriks
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Spain; Department of Mathematics, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - C Micheli
- Institut des Sciences Cognitives Marc Jeannerod, UMR 5304, CNRS, Bron, France; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525, EN Nijmegen, the Netherlands
| | - C A Bosman
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525, EN Nijmegen, the Netherlands; Cognitive and System Neuroscience Group, Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, 1098, XH, Amsterdam, the Netherlands
| | - R Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525, EN Nijmegen, the Netherlands
| | - C Lewis
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt, Germany
| | - D Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Tervuursevest 101, 3001, Leuven, Belgium; Functional Neuroimaging Laboratory, IRCCS San Camillo Hospital, via Alberoni 70, 30126, Venice Lido, Italy
| | - P Fries
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525, EN Nijmegen, the Netherlands; Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt, Germany
| | - G Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Spain; Instituci Catalana de la Recerca i Estudis Avanats (ICREA), Universitat Pompeu Fabra, Spain
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46
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Ghaderi AH, Andevari MN, Sowman PF. Evidence for a Resting State Network Abnormality in Adults Who Stutter. Front Integr Neurosci 2018; 12:16. [PMID: 29755328 PMCID: PMC5934488 DOI: 10.3389/fnint.2018.00016] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 04/10/2018] [Indexed: 01/21/2023] Open
Abstract
Neural network-based investigations of stuttering have begun to provide a possible integrative account for the large number of brain-based anomalies associated with stuttering. Here we used resting-state EEG to investigate functional brain networks in adults who stutter (AWS). Participants were 19 AWS and 52 age-, and gender-matched normally fluent speakers. EEGs were recorded and connectivity matrices were generated by LORETA in the theta (4-8 Hz), alpha (8-12 Hz), beta1 (12-20 Hz), and beta2 (20-30 Hz) bands. Small-world propensity (SWP), shortest path, and clustering coefficients were computed for weighted graphs. Minimum spanning tree analysis was also performed and measures were compared by non-parametric permutation test. The results show that small-world topology was evident in the functional networks of all participants. Three graph indices (diameter, clustering coefficient, and shortest path) exhibited significant differences between groups in the theta band and one [maximum betweenness centrality (BC)] measure was significantly different between groups in the beta2 band. AWS show higher BC than control in right temporal and inferior frontal areas and lower BC in the right primary motor cortex. Abnormal functional networks during rest state suggest an anomaly of DMN activity in AWS. Furthermore, functional segregation/integration deficits in the theta network are evident in AWS. These deficits reinforce the hypothesis that there is a neural basis for abnormal executive function in AWS. Increased beta2 BC in the right speech-motor related areas confirms previous evidence that right audio-speech areas are over-activated in AWS. Decreased beta2 BC in the right primary motor cortex is discussed in relation to abnormal neural mechanisms associated with time perception in AWS.
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Affiliation(s)
- Amir H. Ghaderi
- Cognitive Neuroscience Laboratory, University of Tabriz, Tabriz, Iran
- Iranian Neuro-wave Laboratory, Center of Isfahan, Isfahan, Iran
| | - Masoud N. Andevari
- Iranian Neuro-wave Laboratory, Center of Isfahan, Isfahan, Iran
- Department of Physics, School of Basic Science, Babol Noshirvani University of Technology, Babol, Iran
| | - Paul F. Sowman
- Department of Cognitive Science, Faculty of Human Sciences, Macquarie University, Sydney, NSW, Australia
- ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, NSW, Australia
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47
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Jonmohamadi Y, Muthukumaraswamy SD. Multi-band component analysis for EEG artifact removal and source reconstruction with application to gamma-band activity. Biomed Phys Eng Express 2018. [DOI: 10.1088/2057-1976/aab0ce] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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48
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Liu Q, Ganzetti M, Wenderoth N, Mantini D. Detecting Large-Scale Brain Networks Using EEG: Impact of Electrode Density, Head Modeling and Source Localization. Front Neuroinform 2018; 12:4. [PMID: 29551969 PMCID: PMC5841019 DOI: 10.3389/fninf.2018.00004] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2017] [Accepted: 01/22/2018] [Indexed: 11/13/2022] Open
Abstract
Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis.
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Affiliation(s)
- Quanying Liu
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland.,Laboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Department of Control and Dynamical Systems, California Institute of Technology, Pasadena, CA, United States
| | - Marco Ganzetti
- Laboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland.,Laboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium
| | - Dante Mantini
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland.,Laboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
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49
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Ikeda S, Ishii R, Canuet L, Pascual-Marqui RD. Source estimation of epileptic activity using eLORETA kurtosis analysis. BMJ Case Rep 2017; 2017:bcr-2017-222123. [PMID: 29146728 PMCID: PMC5699115 DOI: 10.1136/bcr-2017-222123] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Exact low-resolution brain electromagnetic tomography (eLORETA) is a technique for three-dimensional representation of the distribution of sources of electrical activity in the brain. Kurtosis analysis allows for identification of spiky activity in the brain. To evaluate the reliability of eLORETA kurtosis analysis, the results of the analysis were compared with those of equivalent current dipole (ECD) and synthetic aperture magnetometry (SAM) kurtosis analysis of magnetoencephalography (MEG) data in a patient with epilepsy with elementary visual seizures in a 6-year follow-up. The results of electroencephalography (EEG) eLORETA kurtosis analysis indicative of a right superior temporal spike source partially overlapped with MEG ECD/SAM kurtosis results in all recordings, with a total overlapping at the end of the follow-up period. Overall findings suggest that eLORETA kurtosis analysis of EEG data may aid in the localisation of spike activity sources in patients with epilepsy.
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Affiliation(s)
- Shunichiro Ikeda
- Department of Neuropsychiatry, Kansai Medical University,, Osaka, Japan.,University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Ryouhei Ishii
- Department of Psychiatry and Clinical Neuroscience, Osaka University Graduate School of Medicine, Suita, Japan
| | - Leonides Canuet
- UCM-UPM Centre for Biomedical Technology, Department of Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid,, Spain
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50
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Vecchio F, Miraglia F, Maria Rossini P. Connectome: Graph theory application in functional brain network architecture. Clin Neurophysiol Pract 2017; 2:206-213. [PMID: 30214997 PMCID: PMC6123924 DOI: 10.1016/j.cnp.2017.09.003] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Revised: 07/28/2017] [Accepted: 09/06/2017] [Indexed: 12/20/2022] Open
Abstract
Network science and graph theory applications can help in understanding how human cognitive functions are linked to neuronal network structure. The present review focuses on pivotal recent studies regarding graph theory application on functional dynamic connectivity investigated by electroencephalographic (EEG) analysis. Graph analysis applications represent an interesting probe to analyze the distinctive features of real life by focusing on functional connectivity networks. Application of graph theory to patient data might provide more insight into the pathophysiological processes underlying brain disconnection. Graph theory might aid in monitoring the impact of eventual pharmacological and rehabilitative treatments.
Network science and graph theory applications have recently spread widely to help in understanding how human cognitive functions are linked to neuronal network structure, thus providing a conceptual frame that can help in reducing the analytical brain complexity and underlining how network topology can be used to characterize and model vulnerability and resilience to brain disease and dysfunction. The present review focuses on few pivotal recent studies of our research team regarding graph theory application in functional dynamic connectivity investigated by electroencephalographic (EEG) analysis. The article is divided into two parts. The first describes the methodological approach to EEG functional connectivity data analysis. In the second part, network studies of physiological aging and neurological disorders are explored, with a particular focus on epilepsy and neurodegenerative dementias, such as Alzheimer's disease.
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Affiliation(s)
- Fabrizio Vecchio
- Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy
| | - Francesca Miraglia
- Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy.,Institute of Neurology, Dept. Geriatrics, Neuroscience & Orthopedics, Catholic University, Policlinic A. Gemelli, Rome, Italy
| | - Paolo Maria Rossini
- Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy.,Institute of Neurology, Dept. Geriatrics, Neuroscience & Orthopedics, Catholic University, Policlinic A. Gemelli, Rome, Italy
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