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Dallasta I, Marsh EB. Poststroke Cognitive Decline: Is Functional Connectivity the Key to Tangible Therapeutic Targets? Stroke 2024; 55:1412-1415. [PMID: 38293808 DOI: 10.1161/strokeaha.123.044290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Affiliation(s)
- Isabella Dallasta
- Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD
| | - Elisabeth B Marsh
- Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD
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Bonassi G, Zhao M, Samogin J, Mantini D, Marchese R, Contrino L, Tognetti P, Putzolu M, Botta A, Pelosin E, Avanzino L. Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study. SENSORS (BASEL, SWITZERLAND) 2024; 24:2875. [PMID: 38732980 PMCID: PMC11086305 DOI: 10.3390/s24092875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/24/2024] [Accepted: 04/29/2024] [Indexed: 05/13/2024]
Abstract
Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, β, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and β bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, β ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.
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Affiliation(s)
- Gaia Bonassi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genoa, Italy;
| | - Mingqi Zhao
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001 Leuven, Belgium; (M.Z.); (J.S.); (D.M.)
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Jessica Samogin
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001 Leuven, Belgium; (M.Z.); (J.S.); (D.M.)
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001 Leuven, Belgium; (M.Z.); (J.S.); (D.M.)
| | - Roberta Marchese
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
| | - Luciano Contrino
- S.C. Medicina Fisica e Riabilitazione Ospedaliera, Azienda Sanitaria Locale Chiavarese, 16043 Chiavari, Italy; (L.C.); (P.T.)
| | - Paola Tognetti
- S.C. Medicina Fisica e Riabilitazione Ospedaliera, Azienda Sanitaria Locale Chiavarese, 16043 Chiavari, Italy; (L.C.); (P.T.)
| | - Martina Putzolu
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Viale Benedetto XV 3, 16132 Genoa, Italy;
| | - Alessandro Botta
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
| | - Elisa Pelosin
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genoa, Italy;
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
| | - Laura Avanzino
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Viale Benedetto XV 3, 16132 Genoa, Italy;
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Della Vedova G, Proverbio AM. Neural signatures of imaginary motivational states: desire for music, movement and social play. Brain Topogr 2024:10.1007/s10548-024-01047-1. [PMID: 38625520 DOI: 10.1007/s10548-024-01047-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 03/12/2024] [Indexed: 04/17/2024]
Abstract
The literature has demonstrated the potential for detecting accurate electrical signals that correspond to the will or intention to move, as well as decoding the thoughts of individuals who imagine houses, faces or objects. This investigation examines the presence of precise neural markers of imagined motivational states through the combining of electrophysiological and neuroimaging methods. 20 participants were instructed to vividly imagine the desire to move, listen to music or engage in social activities. Their EEG was recorded from 128 scalp sites and analysed using individual standardized Low-Resolution Brain Electromagnetic Tomographies (LORETAs) in the N400 time window (400-600 ms). The activation of 1056 voxels was examined in relation to the 3 motivational states. The most active dipoles were grouped in eight regions of interest (ROI), including Occipital, Temporal, Fusiform, Premotor, Frontal, OBF/IF, Parietal, and Limbic areas. The statistical analysis revealed that all motivational imaginary states engaged the right hemisphere more than the left hemisphere. Distinct markers were identified for the three motivational states. Specifically, the right temporal area was more relevant for "Social Play", the orbitofrontal/inferior frontal cortex for listening to music, and the left premotor cortex for the "Movement" desire. This outcome is encouraging in terms of the potential use of neural indicators in the realm of brain-computer interface, for interpreting the thoughts and desires of individuals with locked-in syndrome.
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Affiliation(s)
- Giada Della Vedova
- Cognitive Electrophysiology lab, Dept. of Psychology, University of Milano, Bicocca, Italy
| | - Alice Mado Proverbio
- Cognitive Electrophysiology lab, Dept. of Psychology, University of Milano, Bicocca, Italy.
- NeuroMI, Milan Center for Neuroscience, Milan, Italy.
- Department of Psychology of University of Milano-Bicocca, Piazza dell'Ateneo nuovo 1, Milan, 20162, Italy.
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Proverbio AM, Cesati F. Neural correlates of recalled sadness, joy, and fear states: a source reconstruction EEG study. Front Psychiatry 2024; 15:1357770. [PMID: 38638416 PMCID: PMC11024723 DOI: 10.3389/fpsyt.2024.1357770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 03/18/2024] [Indexed: 04/20/2024] Open
Abstract
Introduction The capacity to understand the others' emotional states, particularly if negative (e.g. sadness or fear), underpins the empathic and social brain. Patients who cannot express their emotional states experience social isolation and loneliness, exacerbating distress. We investigated the feasibility of detecting non-invasive scalp-recorded electrophysiological signals that correspond to recalled emotional states of sadness, fear, and joy for potential classification. Methods The neural activation patterns of 20 healthy and right-handed participants were studied using an electrophysiological technique. Analyses were focused on the N400 component of Event-related potentials (ERPs) recorded during silent recall of subjective emotional states; Standardized weighted Low-resolution Electro-magnetic Tomography (swLORETA) was employed for source reconstruction. The study classified individual patterns of brain activation linked to the recollection of three distinct emotional states into seven regions of interest (ROIs). Results Statistical analysis (ANOVA) of the individual magnitude values revealed the existence of a common emotional circuit, as well as distinct brain areas that were specifically active during recalled sad, happy and fearful states. In particular, the right temporal and left superior frontal areas were more active for sadness, the left limbic region for fear, and the right orbitofrontal cortex for happy affective states. Discussion In conclusion, this study successfully demonstrated the feasibility of detecting scalp-recorded electrophysiological signals corresponding to internal and subjective affective states. These findings contribute to our understanding of the emotional brain, and have potential applications for future BCI classification and identification of emotional states in LIS patients who may be unable to express their emotions, thus helping to alleviate social isolation and sense of loneliness.
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Affiliation(s)
- Alice Mado Proverbio
- Cognitive Electrophysiology Lab, Department of Psychology, University of Milano-Bicocca, Milan, Italy
- NEURO-MI Milan Center for Neuroscience, Milan, Italy
| | - Federico Cesati
- Cognitive Electrophysiology Lab, Department of Psychology, University of Milano-Bicocca, Milan, Italy
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Arjmandi-Rad S, Vestergaard Nieland JD, Goozee KG, Vaseghi S. The effects of different acetylcholinesterase inhibitors on EEG patterns in patients with Alzheimer's disease: A systematic review. Neurol Sci 2024; 45:417-430. [PMID: 37843690 DOI: 10.1007/s10072-023-07114-y] [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: 06/21/2023] [Accepted: 10/01/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common type of dementia. The early diagnosis of AD is an important factor for the control of AD progression. Electroencephalography (EEG) can be used for early diagnosis of AD. Acetylcholinesterase inhibitors (AChEIs) are also used for the amelioration of AD symptoms. In this systematic review, we reviewed the effect of different AChEIs including donepezil, rivastigmine, tacrine, physostigmine, and galantamine on EEG patterns in patients with AD. METHODS PubMed electronic database was searched and 122 articles were found. After removal of unrelated articles, 24 articles were selected for the present study. RESULTS AChEIs can decrease beta, theta, and delta frequency bands in patients with AD. However, conflicting results were found for alpha band. Some studies have shown increased alpha frequency, while others have shown decreased alpha frequency following treatment with AChEIs. The only difference was the type of drug. CONCLUSIONS We found that studies reporting the decreased alpha frequency used donepezil and galantamine, while studies reporting the increased alpha frequency used rivastigmine and tacrine. It was suggested that future studies should focus on the effect of different AChEIs on EEG bands, especially alpha frequency in patients with AD, to compare their effects and find the reason for their different influence on EEG patterns. Also, differences between the effects of AChEIs on oligodendrocyte differentiation and myelination may be another important factor. This is the first article investigating the effect of different AChEIs on EEG patterns in patients with AD.
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Affiliation(s)
- Shirin Arjmandi-Rad
- Institute for Cognitive & Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | | | - Kathryn G Goozee
- KaRa Institute of Neurological Diseases Pty Ltd, Macquarie, NSW, Australia
- Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Salar Vaseghi
- Cognitive Neuroscience Lab, Medicinal Plants Research Center, Institute of Medicinal Plants, ACECR, Karaj, Iran.
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Gorgoni M, Cenani J, Scarpelli S, D'Atri A, Alfonsi V, Annarumma L, Pietrogiacomi F, Ferrara M, Marra C, Rossini PM, De Gennaro L. The role of the sleep K-complex on the conversion from mild cognitive impairment to Alzheimer's disease. J Sleep Res 2024; 33:e14046. [PMID: 37718942 DOI: 10.1111/jsr.14046] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 07/24/2023] [Accepted: 08/29/2023] [Indexed: 09/19/2023]
Abstract
The present literature points to an alteration of the human K-complex during non-rapid eye movement sleep in Alzheimer's disease. Nevertheless, the few findings on the K-complex changes in mild cognitive impairment and their possible predictive role on the Alzheimer's disease conversion show mixed findings, lack of replication, and a main interest for the frontal region. The aim of the present study was to assess K-complex measures in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease over different cortical regions, comparing them with healthy controls and stable amnesic mild cognitive impairment. We assessed baseline K-complex density, amplitude, area under the curve and overnight changes in frontal, central and parietal midline derivations of 12 amnesic mild cognitive impairment subsequently converted in Alzheimer's disease, 12 stable amnesic mild cognitive impairment and 12 healthy controls. We also assessed delta electroencephalogram power, to determine if K-complex alterations in amnesic mild cognitive impairment occur with modification of the electroencephalogram power in the frequency range of the slow-wave activity. We found a reduced parietal K-complex density in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease compared with stable amnesic mild cognitive impairment and healthy controls, without changes in K-complex morphology and overnight modulation. Both amnesic mild cognitive impairment groups showed decreased slow-wave sleep percentage compared with healthy controls. No differences between groups were observed in slow-wave activity power. Our findings suggest that K-complex alterations in mild cognitive impairment may be observed earlier in parietal regions, likely mirroring the topographical progression of Alzheimer's disease-related brain pathology, and express a frontal predominance only in a full-blown phase of Alzheimer's disease. Consistently with previous results, such K-complex modification occurs in the absence of significant electroencephalogram power changes in the slow oscillations range.
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Affiliation(s)
- Maurizio Gorgoni
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Body and Action Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Jessica Cenani
- Department of Psychology, Sapienza University of Rome, Rome, Italy
| | - Serena Scarpelli
- Department of Psychology, Sapienza University of Rome, Rome, Italy
| | - Aurora D'Atri
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | | | | | | | - Michele Ferrara
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Camillo Marra
- Institute of Neurology, Catholic University, Rome, Italy
| | - Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy
| | - Luigi De Gennaro
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Body and Action Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
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Kopčanová M, Tait L, Donoghue T, Stothart G, Smith L, Flores-Sandoval AA, Davila-Perez P, Buss S, Shafi MM, Pascual-Leone A, Fried PJ, Benwell CSY. Resting-state EEG signatures of Alzheimer's disease are driven by periodic but not aperiodic changes. Neurobiol Dis 2024; 190:106380. [PMID: 38114048 DOI: 10.1016/j.nbd.2023.106380] [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: 07/13/2023] [Revised: 11/30/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023] Open
Abstract
Electroencephalography (EEG) has shown potential for identifying early-stage biomarkers of neurocognitive dysfunction associated with dementia due to Alzheimer's disease (AD). A large body of evidence shows that, compared to healthy controls (HC), AD is associated with power increases in lower EEG frequencies (delta and theta) and decreases in higher frequencies (alpha and beta), together with slowing of the peak alpha frequency. However, the pathophysiological processes underlying these changes remain unclear. For instance, recent studies have shown that apparent shifts in EEG power from high to low frequencies can be driven either by frequency specific periodic power changes or rather by non-oscillatory (aperiodic) changes in the underlying 1/f slope of the power spectrum. Hence, to clarify the mechanism(s) underlying the EEG alterations associated with AD, it is necessary to account for both periodic and aperiodic characteristics of the EEG signal. Across two independent datasets, we examined whether resting-state EEG changes linked to AD reflect true oscillatory (periodic) changes, changes in the aperiodic (non-oscillatory) signal, or a combination of both. We found strong evidence that the alterations are purely periodic in nature, with decreases in oscillatory power at alpha and beta frequencies (AD < HC) leading to lower (alpha + beta) / (delta + theta) power ratios in AD. Aperiodic EEG features did not differ between AD and HC. By replicating the findings in two cohorts, we provide robust evidence for purely oscillatory pathophysiology in AD and against aperiodic EEG changes. We therefore clarify the alterations underlying the neural dynamics in AD and emphasize the robustness of oscillatory AD signatures, which may further be used as potential prognostic or interventional targets in future clinical investigations.
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Affiliation(s)
- Martina Kopčanová
- Division of Psychology, School of Humanities, Social Sciences and Law, University of Dundee, Dundee, UK.
| | - Luke Tait
- Centre for Systems Modelling and Quantitative Biomedicine, School of Medical and Dental Sciences, University of Birmingham, UK; Cardiff University Brain Research Imaging Centre, Cardiff, UK
| | - Thomas Donoghue
- Department of Biomedical Engineering, Columbia University, New York, USA
| | | | - Laura Smith
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Aimee Arely Flores-Sandoval
- Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, 10117 Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Paula Davila-Perez
- Rey Juan Carlos University Hospital (HURJC), Department of Clinical Neurophysiology, Móstoles, Madrid, Spain; Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
| | - Stephanie Buss
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, MA, USA; Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, United States of America
| | - Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Christopher S Y Benwell
- Division of Psychology, School of Humanities, Social Sciences and Law, University of Dundee, Dundee, UK
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Fide E, Yerlikaya D, Güntekin B, Babiloni C, Yener GG. Coherence in event-related EEG oscillations in patients with Alzheimer's disease dementia and amnestic mild cognitive impairment. Cogn Neurodyn 2023; 17:1621-1635. [PMID: 37974589 PMCID: PMC10640558 DOI: 10.1007/s11571-022-09920-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 11/02/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Objectives Working memory performances are based on brain functional connectivity, so that connectivity may be deranged in individuals with mild cognitive impairment (MCI) and patients with dementia due to Alzheimer's disease (ADD). Here we tested the hypothesis of abnormal functional connectivity as revealed by the imaginary part of coherency (ICoh) at electrode pairs from event-related electroencephalographic oscillations in ADD and MCI patients. Methods The study included 43 individuals with MCI, 43 with ADD, and 68 demographically matched healthy controls (HC). Delta, theta, alpha, beta, and gamma bands event-related ICoh was measured during an oddball paradigm. Inter-hemispheric, midline, and intra-hemispheric ICoh values were compared in ADD, MCI, and HC groups. Results The main results of the present study can be summarized as follows: (1) A significant increase of midline frontal and temporal theta coherence in the MCI group as compared to the HC group; (2) A significant decrease of theta, delta, and alpha intra-hemispheric coherence in the ADD group as compared to the HC and MCI groups; (3) A significant decrease of theta midline coherence in the ADD group as compared to the HC and MCI groups; (4) Normal inter-hemispheric coherence in the ADD and MCI groups. Conclusions Compared with the MCI and HC, the ADD group showed disrupted event-related intra-hemispheric and midline low-frequency band coherence as an estimate of brain functional dysconnectivity underlying disabilities in daily living. Brain functional connectivity during attention and short memory demands is relatively resilient in elderly subjects even with MCI (with preserved abilities in daily activities), and it shows reduced efficiency at multiple operating oscillatory frequencies only at an early stage of ADD. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09920-0.
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Affiliation(s)
- Ezgi Fide
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Deniz Yerlikaya
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
- REMER Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, Italy
- Hospital San Raffaele of Cassino, Cassino, Italy
| | - 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
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Scheijbeler EP, de Haan W, Stam CJ, Twisk JWR, Gouw AA. Longitudinal resting-state EEG in amyloid-positive patients along the Alzheimer's disease continuum: considerations for clinical trials. Alzheimers Res Ther 2023; 15:182. [PMID: 37858173 PMCID: PMC10585755 DOI: 10.1186/s13195-023-01327-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 10/06/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND To enable successful inclusion of electroencephalography (EEG) outcome measures in Alzheimer's disease (AD) clinical trials, we retrospectively mapped the progression of resting-state EEG measures over time in amyloid-positive patients with mild cognitive impairment (MCI) or dementia due to AD. METHODS Resting-state 21-channel EEG was recorded in 148 amyloid-positive AD patients (MCI, n = 88; dementia due to AD, n = 60). Two or more EEG recordings were available for all subjects. We computed whole-brain and regional relative power (i.e., theta (4-8 Hz), alpha1 (8-10 Hz), alpha2 (10-13 Hz), beta (13-30 Hz)), peak frequency, signal variability (i.e., theta permutation entropy), and functional connectivity values (i.e., alpha and beta corrected amplitude envelope correlation, theta phase lag index, weighted symbolic mutual information, inverted joint permutation entropy). Whole-group linear mixed effects models were used to model the development of EEG measures over time. Group-wise analysis was performed to investigate potential differences in change trajectories between the MCI and dementia subgroups. Finally, we estimated the minimum sample size required to detect different treatment effects (i.e., 50% less deterioration, stabilization, or 50% improvement) on the development of EEG measures over time, in hypothetical clinical trials of 1- or 2-year duration. RESULTS Whole-group analysis revealed significant regional and global oscillatory slowing over time (i.e., increased relative theta power, decreased beta power), with strongest effects for temporal and parieto-occipital regions. Disease severity at baseline influenced the EEG measures' rates of change, with fastest deterioration reported in MCI patients. Only AD dementia patients displayed a significant decrease of the parieto-occipital peak frequency and theta signal variability over time. We estimate that 2-year trials, focusing on amyloid-positive MCI patients, require 36 subjects per arm (2 arms, 1:1 randomization, 80% power) to detect a stabilizing treatment effect on temporal relative theta power. CONCLUSIONS Resting-state EEG measures could facilitate early detection of treatment effects on neuronal function in AD patients. Their sensitivity depends on the region-of-interest and disease severity of the study population. Conventional spectral measures, particularly recorded from temporal regions, present sensitive AD treatment monitoring markers.
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Affiliation(s)
- Elliz P Scheijbeler
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands.
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands.
| | - Willem de Haan
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
| | - Cornelis J Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Jos W R Twisk
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
| | - Alida A Gouw
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
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10
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Flores-Sandoval AA, Davila-Pérez P, Buss SS, Donohoe K, O'Connor M, Shafi MM, Pascual-Leone A, Benwell CSY, Fried PJ. Spectral power ratio as a measure of EEG changes in mild cognitive impairment due to Alzheimer's disease: a case-control study. Neurobiol Aging 2023; 130:50-60. [PMID: 37459658 PMCID: PMC10614059 DOI: 10.1016/j.neurobiolaging.2023.05.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/12/2023] [Accepted: 05/17/2023] [Indexed: 08/13/2023]
Abstract
Adopting preventive strategies in individuals with subclinical Alzheimer's disease (AD) has the potential to delay dementia onset and reduce healthcare costs. Thus, it is extremely important to identify inexpensive, scalable, sensitive, and specific markers to track disease progression. The electroencephalography spectral power ratio (SPR: the fast to slow spectral power ratio), a measure of the shift in power distribution from higher to lower frequencies, holds potential for aiding clinical practice. The SPR is altered in patients with AD, correlates with cognitive functions, and can be easily implemented in clinical settings. However, whether the SPR is sensitive to pathophysiological changes in the prodromal stage of AD is unclear. We explored the SPR of individuals diagnosed with amyloid-positive amnestic mild cognitive impairment (Aβ+aMCI) and its association with both cognitive function and amyloid load. The SPR was lower in Aβ+aMCI than in the cognitively unimpaired individuals and correlated with executive function scores but not with amyloid load. Hypothesis-generating analyses suggested that aMCI participants with a lower SPR had an increased probability of a positive amyloid positron emission tomography. Future research may explore the potential of this measure to classify aMCI individuals according to their AD biomarker status.
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Affiliation(s)
- Aimee A Flores-Sandoval
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, 10117 Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Paula Davila-Pérez
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Department of Clinical Neurophysiology, Hospital Universitario Rey Juan Carlos, Móstoles, Spain; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Stephanie S Buss
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Kevin Donohoe
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Margaret O'Connor
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, MA, USA; Hinda and Arthur Marcus Institute for Aging Research, and Deanna and Sidney Wolk Center for Memory Health, Hebrew Senior Life, Boston, MA, USA
| | - Christopher S Y Benwell
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Division of Psychology, School of Humanities, Social Sciences and Law, University of Dundee, Dundee, UK
| | - Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.
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11
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Kopčanová M, Tait L, Donoghue T, Stothart G, Smith L, Sandoval AAF, Davila-Perez P, Buss S, Shafi MM, Pascual-Leone A, Fried PJ, Benwell CS. Resting-state EEG signatures of Alzheimer's disease are driven by periodic but not aperiodic changes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.11.544491. [PMID: 37398162 PMCID: PMC10312609 DOI: 10.1101/2023.06.11.544491] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Electroencephalography (EEG) has shown potential for identifying early-stage biomarkers of neurocognitive dysfunction associated with dementia due to Alzheimer's disease (AD). A large body of evidence shows that, compared to healthy controls (HC), AD is associated with power increases in lower EEG frequencies (delta and theta) and decreases in higher frequencies (alpha and beta), together with slowing of the peak alpha frequency. However, the pathophysiological processes underlying these changes remain unclear. For instance, recent studies have shown that apparent shifts in EEG power from high to low frequencies can be driven either by frequency specific periodic power changes or rather by non-oscillatory (aperiodic) changes in the underlying 1/f slope of the power spectrum. Hence, to clarify the mechanism(s) underlying the EEG alterations associated with AD, it is necessary to account for both periodic and aperiodic characteristics of the EEG signal. Across two independent datasets, we examined whether resting-state EEG changes linked to AD reflect true oscillatory (periodic) changes, changes in the aperiodic (non-oscillatory) signal, or a combination of both. We found strong evidence that the alterations are purely periodic in nature, with decreases in oscillatory power at alpha and beta frequencies (AD < HC) leading to lower (alpha + beta) / (delta + theta) power ratios in AD. Aperiodic EEG features did not differ between AD and HC. By replicating the findings in two cohorts, we provide robust evidence for purely oscillatory pathophysiology in AD and against aperiodic EEG changes. We therefore clarify the alterations underlying the neural dynamics in AD and emphasise the robustness of oscillatory AD signatures, which may further be used as potential prognostic or interventional targets in future clinical investigations.
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Affiliation(s)
- Martina Kopčanová
- Division of Psychology, School of Humanities, Social Sciences and Law, University of Dundee, Dundee, UK
| | - Luke Tait
- Centre for Systems Modelling and Quantitative Biomedicine, School of Medical and Dental Sciences, University of Birmingham, UK
- Cardiff University Brain Research Imaging Centre, Cardiff, UK
| | - Thomas Donoghue
- Department of Biomedical Engineering, Columbia University, New York, USA
| | | | - Laura Smith
- School of Psychology, University of Kent, Kent, UK
| | - Aimee Arely Flores Sandoval
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, 10117, Berlin, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Paula Davila-Perez
- Rey Juan Carlos University Hospital (HURJC), Department of Clinical Neurophysiology, Móstoles, Madrid, Spain
- Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
| | - Stephanie Buss
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
| | - Mouhsin M. Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston MA
| | - Peter J. Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
| | - Christopher S.Y. Benwell
- Division of Psychology, School of Humanities, Social Sciences and Law, University of Dundee, Dundee, UK
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12
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Inamoto T, Ueda M, Ueno K, Shiroma C, Morita R, Naito Y, Ishii R. Motor-Related Mu/Beta Rhythm in Older Adults: A Comprehensive Review. Brain Sci 2023; 13:brainsci13050751. [PMID: 37239223 DOI: 10.3390/brainsci13050751] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/23/2023] [Accepted: 04/28/2023] [Indexed: 05/28/2023] Open
Abstract
Mu rhythm, also known as the mu wave, occurs on sensorimotor cortex activity at rest, and the frequency range is defined as 8-13Hz, the same frequency as the alpha band. Mu rhythm is a cortical oscillation that can be recorded from the scalp over the primary sensorimotor cortex by electroencephalogram (EEG) and magnetoencephalography (MEG). The subjects of previous mu/beta rhythm studies ranged widely from infants to young and older adults. Furthermore, these subjects were not only healthy people but also patients with various neurological and psychiatric diseases. However, very few studies have referred to the effect of mu/beta rhythm with aging, and there was no literature review about this theme. It is important to review the details of the characteristics of mu/beta rhythm activity in older adults compared with young adults, focusing on age-related mu rhythm changes. By comprehensive review, we found that, compared with young adults, older adults showed mu/beta activity change in four characteristics during voluntary movement, increased event-related desynchronization (ERD), earlier beginning and later end, symmetric pattern of ERD and increased recruitment of cortical areas, and substantially reduced beta event-related desynchronization (ERS). It was also found that mu/beta rhythm patterns of action observation were changing with aging. Future work is needed in order to investigate not only the localization but also the network of mu/beta rhythm in older adults.
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Affiliation(s)
- Takashi Inamoto
- Graduate School of Comprehensive Rehabilitation, Osaka Prefecture University, Osaka 583-8555, Japan
- Faculty of Health Sciences, Kansai University of Health Sciences, Osaka 590-0482, Japan
| | - Masaya Ueda
- Graduate School of Rehabilitation Science, Osaka Metropolitan University, Osaka 583-8555, Japan
| | - Keita Ueno
- Graduate School of Rehabilitation Science, Osaka Metropolitan University, Osaka 583-8555, Japan
| | - China Shiroma
- Graduate School of Rehabilitation Science, Osaka Metropolitan University, Osaka 583-8555, Japan
| | - Rin Morita
- Graduate School of Rehabilitation Science, Osaka Metropolitan University, Osaka 583-8555, Japan
| | - Yasuo Naito
- Graduate School of Rehabilitation Science, Osaka Metropolitan University, Osaka 583-8555, Japan
| | - Ryouhei Ishii
- Graduate School of Rehabilitation Science, Osaka Metropolitan University, Osaka 583-8555, Japan
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
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13
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Victorino DB, Faber J, Pinheiro DJLL, Scorza FA, Almeida ACG, Costa ACS, Scorza CA. Toward the Identification of Neurophysiological Biomarkers for Alzheimer's Disease in Down Syndrome: A Potential Role for Cross-Frequency Phase-Amplitude Coupling Analysis. Aging Dis 2023; 14:428-449. [PMID: 37008053 PMCID: PMC10017148 DOI: 10.14336/ad.2022.0906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 09/06/2022] [Indexed: 11/18/2022] Open
Abstract
Cross-frequency coupling (CFC) mechanisms play a central role in brain activity. Pathophysiological mechanisms leading to many brain disorders, such as Alzheimer's disease (AD), may produce unique patterns of brain activity detectable by electroencephalography (EEG). Identifying biomarkers for AD diagnosis is also an ambition among research teams working in Down syndrome (DS), given the increased susceptibility of people with DS to develop early-onset AD (DS-AD). Here, we review accumulating evidence that altered theta-gamma phase-amplitude coupling (PAC) may be one of the earliest EEG signatures of AD, and therefore may serve as an adjuvant tool for detecting cognitive decline in DS-AD. We suggest that this field of research could potentially provide clues to the biophysical mechanisms underlying cognitive dysfunction in DS-AD and generate opportunities for identifying EEG-based biomarkers with diagnostic and prognostic utility in DS-AD.
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Affiliation(s)
- Daniella B Victorino
- Discipline of Neuroscience, Department of Neurology and Neurosurgery, Federal University of São Paulo / Paulista Medical School, São Paulo, SP, Brazil.
| | - Jean Faber
- Discipline of Neuroscience, Department of Neurology and Neurosurgery, Federal University of São Paulo / Paulista Medical School, São Paulo, SP, Brazil.
| | - Daniel J. L. L Pinheiro
- Discipline of Neuroscience, Department of Neurology and Neurosurgery, Federal University of São Paulo / Paulista Medical School, São Paulo, SP, Brazil.
| | - Fulvio A Scorza
- Discipline of Neuroscience, Department of Neurology and Neurosurgery, Federal University of São Paulo / Paulista Medical School, São Paulo, SP, Brazil.
| | - Antônio C. G Almeida
- Department of Biosystems Engineering, Federal University of São João Del Rei, Minas Gerais, MG, Brazil.
| | - Alberto C. S Costa
- Division of Psychiatry, Case Western Reserve University, Cleveland, OH, United States.
- Department of Macromolecular Science and Engineering, Case Western Reserve University, Cleveland, OH, United States.
| | - Carla A Scorza
- Discipline of Neuroscience, Department of Neurology and Neurosurgery, Federal University of São Paulo / Paulista Medical School, São Paulo, SP, Brazil.
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14
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Regional spectral ratios as potential neural markers to identify mild cognitive impairment related to Alzheimer's disease. Acta Neuropsychiatr 2023; 35:118-122. [PMID: 35634747 DOI: 10.1017/neu.2022.18] [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] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Alzheimer's disease (AD) has prolonged asymptomatic or mild symptomatic periods. Given that there is an increase in treatment options and that early intervention could modify the disease course, it is desirable to devise biological indices that may differentiate AD and nonAD at mild cognitive impairment (MCI) stage. METHODS Based on two well-acknowledged observations of background slowing (attenuation in alpha power and enhancement in theta and delta powers) and early involvement of posterior cingulate cortex (PCC, a neural hub of default-mode network), this study devised novel neural markers, namely, spectral ratios of alpha1 to delta and alpha1 to theta in the PCC. RESULTS We analysed 46 MCI patients, with 22 ADMCI and 24 nonADMCI who were matched in age, education, and global cognitive capability. Concordant with the prediction, the regional spectral ratios were lower in the ADMCI group, suggesting its clinical application potential. CONCLUSION Previous research has verified that neural markers derived from clinical electroencephalography may be informative in differentiating AD from other neurological conditions. We believe that the spectral ratios in the neural hubs that show early pathological changes can enrich the instrumental assessment of brain dysfunctions at the MCI (or pre-clinical) stage.
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15
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Liu M, Liu B, Ye Z, Wu D. Bibliometric analysis of electroencephalogram research in mild cognitive impairment from 2005 to 2022. Front Neurosci 2023; 17:1128851. [PMID: 37021134 PMCID: PMC10067679 DOI: 10.3389/fnins.2023.1128851] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/06/2023] [Indexed: 03/22/2023] Open
Abstract
BackgroundElectroencephalogram (EEG), one of the most commonly used non-invasive neurophysiological examination techniques, advanced rapidly between 2005 and 2022, particularly when it was used for the diagnosis and prognosis of mild cognitive impairment (MCI). This study used a bibliometric approach to synthesize the knowledge structure and cutting-edge hotspots of EEG application in the MCI.MethodsRelated publications in the Web of Science Core Collection (WosCC) were retrieved from inception to 30 September 2022. CiteSpace, VOSviewer, and HistCite software were employed to perform bibliographic and visualization analyses.ResultsBetween 2005 and 2022, 2,905 studies related to the application of EEG in MCI were investigated. The United States had the highest number of publications and was at the top of the list of international collaborations. In terms of total number of articles, IRCCS San Raffaele Pisana ranked first among institutions. The Clinical Neurophysiology published the greatest number of articles. The author with the highest citations was Babiloni C. In descending order of frequency, keywords with the highest frequency were “EEG,” “mild cognitive impairment,” and “Alzheimer’s disease”.ConclusionThe application of EEG in MCI was investigated using bibliographic analysis. The research emphasis has shifted from examining local brain lesions with EEG to neural network mechanisms. The paradigm of big data and intelligent analysis is becoming more relevant in EEG analytical methods. The use of EEG to link MCI to other related neurological disorders, and to evaluate new targets for diagnosis and treatment, has become a new research trend. The above-mentioned findings have implications in the future research on the application of EEG in MCI.
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Affiliation(s)
- Mingrui Liu
- Department of Rehabilitation, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Baohu Liu
- Department of Rehabilitation, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zelin Ye
- Department of Cardiovascular, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Dongyu Wu
- Department of Rehabilitation, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- *Correspondence: Dongyu Wu,
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16
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Cesnaite E, Steinfath P, Jamshidi Idaji M, Stephani T, Kumral D, Haufe S, Sander C, Hensch T, Hegerl U, Riedel-Heller S, Röhr S, Schroeter ML, Witte AV, Villringer A, Nikulin VV. Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age. Neuroimage 2023; 268:119810. [PMID: 36587708 DOI: 10.1016/j.neuroimage.2022.119810] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 12/31/2022] Open
Abstract
While many structural and biochemical changes in the brain have previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.
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Affiliation(s)
- Elena Cesnaite
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Paul Steinfath
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany
| | - Mina Jamshidi Idaji
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany; Machine Learning Group, Technical University Berlin, Berlin, Germany
| | - Tilman Stephani
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany
| | - Deniz Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg im Breisgau, Germany; Institute of Psychology, Clinical Psychology and Psychotherapy Unit, University of Freiburg, Freiburg im Breisgau, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; IUBH International University, Erfurt, Germany
| | - Ulrich Hegerl
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Department of Psychiatry, Psychosomatics and Psychotherapy, Goethe University Frankfurt, Frankfurt, Germany
| | - Steffi Riedel-Heller
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
| | - Susanne Röhr
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany; Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Matthias L Schroeter
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - A Veronica Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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17
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Jiao B, Li R, Zhou H, Qing K, Liu H, Pan H, Lei Y, Fu W, Wang X, Xiao X, Liu X, Yang Q, Liao X, Zhou Y, Fang L, Dong Y, Yang Y, Jiang H, Huang S, Shen L. Neural biomarker diagnosis and prediction to mild cognitive impairment and Alzheimer's disease using EEG technology. Alzheimers Res Ther 2023; 15:32. [PMID: 36765411 PMCID: PMC9912534 DOI: 10.1186/s13195-023-01181-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 02/06/2023] [Indexed: 02/12/2023]
Abstract
BACKGROUND Electroencephalogram (EEG) has emerged as a non-invasive tool to detect the aberrant neuronal activity related to different stages of Alzheimer's disease (AD). However, the effectiveness of EEG in the precise diagnosis and assessment of AD and its preclinical stage, amnestic mild cognitive impairment (MCI), has yet to be fully elucidated. In this study, we aimed to identify key EEG biomarkers that are effective in distinguishing patients at the early stage of AD and monitoring the progression of AD. METHODS A total of 890 participants, including 189 patients with MCI, 330 patients with AD, 125 patients with other dementias (frontotemporal dementia, dementia with Lewy bodies, and vascular cognitive impairment), and 246 healthy controls (HC) were enrolled. Biomarkers were extracted from resting-state EEG recordings for a three-level classification of HC, MCI, and AD. The optimal EEG biomarkers were then identified based on the classification performance. Random forest regression was used to train a series of models by combining participants' EEG biomarkers, demographic information (i.e., sex, age), CSF biomarkers, and APOE phenotype for assessing the disease progression and individual's cognitive function. RESULTS The identified EEG biomarkers achieved over 70% accuracy in the three-level classification of HC, MCI, and AD. Among all six groups, the most prominent effects of AD-linked neurodegeneration on EEG metrics were localized at parieto-occipital regions. In the cross-validation predictive analyses, the optimal EEG features were more effective than the CSF + APOE biomarkers in predicting the age of onset and disease course, whereas the combination of EEG + CSF + APOE measures achieved the best performance for all targets of prediction. CONCLUSIONS Our study indicates that EEG can be used as a useful screening tool for the diagnosis and disease progression evaluation of MCI and AD.
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Affiliation(s)
- Bin Jiao
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China ,grid.216417.70000 0001 0379 7164National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China ,grid.216417.70000 0001 0379 7164Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China ,Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China ,grid.216417.70000 0001 0379 7164Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Rihui Li
- grid.168010.e0000000419368956Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA USA ,Brainup Institute of Science and Technology, Chongqing, China
| | - Hui Zhou
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Kunqiang Qing
- Brainup Institute of Science and Technology, Chongqing, China
| | - Hui Liu
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Hefu Pan
- Brainup Institute of Science and Technology, Chongqing, China
| | - Yanqin Lei
- Brainup Institute of Science and Technology, Chongqing, China
| | - Wenjin Fu
- Brainup Institute of Science and Technology, Chongqing, China
| | - Xiaoan Wang
- Brainup Institute of Science and Technology, Chongqing, China
| | - Xuewen Xiao
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xixi Liu
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qijie Yang
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xinxin Liao
- grid.216417.70000 0001 0379 7164Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, China
| | - Yafang Zhou
- grid.216417.70000 0001 0379 7164Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, China
| | - Liangjuan Fang
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yanbin Dong
- Brainup Institute of Science and Technology, Chongqing, China
| | - Yuanhao Yang
- grid.1003.20000 0000 9320 7537Mater Research Institute, The University of Queensland, Woolloongabba, Queensland 4102 Australia
| | - Haiyan Jiang
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Sha Huang
- grid.216417.70000 0001 0379 7164Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China. .,National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China. .,Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China. .,Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China. .,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China. .,Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, Changsha, China.
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18
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Giustiniani A, Danesin L, Bozzetto B, Macina A, Benavides-Varela S, Burgio F. Functional changes in brain oscillations in dementia: a review. Rev Neurosci 2023; 34:25-47. [PMID: 35724724 DOI: 10.1515/revneuro-2022-0010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/16/2022] [Indexed: 01/11/2023]
Abstract
A growing body of evidence indicates that several characteristics of electroencephalography (EEG) and magnetoencephalography (MEG) play a functional role in cognition and could be linked to the progression of cognitive decline in some neurological diseases such as dementia. The present paper reviews previous studies investigating changes in brain oscillations associated to the most common types of dementia, namely Alzheimer's disease (AD), frontotemporal degeneration (FTD), and vascular dementia (VaD), with the aim of identifying pathology-specific patterns of alterations and supporting differential diagnosis in clinical practice. The included studies analysed changes in frequency power, functional connectivity, and event-related potentials, as well as the relationship between electrophysiological changes and cognitive deficits. Current evidence suggests that an increase in slow wave activity (i.e., theta and delta) as well as a general reduction in the power of faster frequency bands (i.e., alpha and beta) characterizes AD, VaD, and FTD. Additionally, compared to healthy controls, AD exhibits alteration in latencies and amplitudes of the most common event related potentials. In the reviewed studies, these changes generally correlate with performances in many cognitive tests. In conclusion, particularly in AD, neurophysiological changes can be reliable early markers of dementia.
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Affiliation(s)
| | - Laura Danesin
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
| | | | - AnnaRita Macina
- Department of Developmental Psychology and Socialization, University of Padua, via Venezia 8, 35131 Padova, Italy
| | - Silvia Benavides-Varela
- Department of Developmental Psychology and Socialization, University of Padua, via Venezia 8, 35131 Padova, Italy.,Department of Neuroscience, University of Padova, 35128 Padova, Italy.,Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Francesca Burgio
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
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19
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Fide E, Polat H, Yener G, Özerdem MS. Effects of Pharmacological Treatments in Alzheimer's Disease: Permutation Entropy-Based EEG Complexity Study. Brain Topogr 2023; 36:106-118. [PMID: 36399219 DOI: 10.1007/s10548-022-00927-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 11/03/2022] [Indexed: 11/19/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative brain disease affecting cognitive and physical functioning. The currently available pharmacological treatments for AD mainly contain cholinesterase inhibitors (AChE-I) and N-methyl-D-aspartic acid (NMDA) receptor antagonists (i.e., memantine). Because brain signals have complex nonlinear dynamics, there has been an increase in interest in researching complexity changes in the time series of brain signals in individuals with AD. In this study, we explore the electroencephalographic (EEG) complexity for making better observation of pharmacological therapy-based treatment effects on AD patients using the permutation entropy (PE) method. We examined EEG sub-band (delta, theta, alpha, beta, and gamma) complexity in de-novo, monotherapy (AChE-I), dual therapy (AChE-I and memantine) receiving AD participants compared with healthy elderly controls. We showed that each frequency band depicts its own complexity profile, which is regionally altered between groups. These alterations were also found to be associated with global cognitive scores. Overall, our findings indicate that entropy measures could be useful to show medication effects in AD.
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Affiliation(s)
- Ezgi Fide
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Hasan Polat
- Department of Electrical and Energy, Bingöl University, Selahaddin-i Eyyübi Mah. Aydınlık Cad No: 1, 12000, Bingöl, Turkey.
| | - Görsev Yener
- Brain Dynamics Multidisciplinary Research Center, Izmir, Turkey.,Faculty of Medicine, Izmir University of Economics, Izmir, Turkey.,International Biomedicine and Genome Institute, Izmir, Turkey
| | - Mehmet Siraç Özerdem
- Department of Electrical and Electronics Engineering, Dicle University, Diyarbakır, Turkey
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20
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Simfukwe C, Youn YC, Kim MJ, Paik J, Han SH. CNN for a Regression Machine Learning Algorithm for Predicting Cognitive Impairment Using qEEG. Neuropsychiatr Dis Treat 2023; 19:851-863. [PMID: 37077704 PMCID: PMC10106803 DOI: 10.2147/ndt.s404528] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 04/05/2023] [Indexed: 04/21/2023] Open
Abstract
Purpose Electroencephalogram (EEG) signals give detailed information on the electrical brain activities occurring in the cerebral cortex. They are used to study brain-related disorders such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). Brain signals obtained using an EEG machine can be a neurophysiological biomarker for early diagnosis of dementia through quantitative EEG (qEEG) analysis. This paper proposes a machine learning methodology to detect MCI and AD from qEEG time-frequency (TF) images of the subjects in an eyes-closed resting state (ECR). Participants and Methods The dataset consisted of 16,910 TF images from 890 subjects: 269 healthy controls (HC), 356 MCI, and 265 AD. First, EEG signals were transformed into TF images using a Fast Fourier Transform (FFT) containing different event-rated changes of frequency sub-bands preprocessed from the EEGlab toolbox in the MATLAB R2021a environment software. The preprocessed TF images were applied in a convolutional neural network (CNN) with adjusted parameters. For classification, the computed image features were concatenated with age data and went through the feed-forward neural network (FNN). Results The trained models', HC vs MCI, HC vs AD, and HC vs CASE (MCI + AD), performance metrics were evaluated based on the test dataset of the subjects. The accuracy, sensitivity, and specificity were evaluated: HC vs MCI was 83%, 93%, and 73%, HC vs AD was 81%, 80%, and 83%, and HC vs CASE (MCI + AD) was 88%, 80%, and 90%, respectively. Conclusion The proposed models trained with TF images and age can be used to assist clinicians as a biomarker in detecting cognitively impaired subjects at an early stage in clinical sectors.
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Affiliation(s)
- Chanda Simfukwe
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, South Korea
| | - Young Chul Youn
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, South Korea
- Correspondence: Young Chul Youn; Su-Hyun Han, Department of Neurology, Chung-Ang University Hospital, Seoul, Republic of Korea, Email ;
| | - Min-Jae Kim
- Department of Image, Chung-Ang University, Seoul, South Korea
| | - Joonki Paik
- Department of Image, Chung-Ang University, Seoul, South Korea
| | - Su-Hyun Han
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, South Korea
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21
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Dang M, Sang F, Long S, Chen Y. The Aging Patterns of Brain Structure, Function, and Energy Metabolism. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1419:85-97. [PMID: 37418208 DOI: 10.1007/978-981-99-1627-6_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]
Abstract
The normal aging process brings changes in brain structure, function, and energy metabolism, which are presumed to contribute to the age-related decline in brain function and cognitive ability. This chapter aims to summarize the aging patterns of brain structure, function, and energy metabolism to distinguish them from the pathological changes associated with neurodegenerative diseases and explore protective factors in aging. We first described the normal atrophy pattern of cortical gray matter with age, which is negatively affected by some neurodegenerative diseases and is protected by a healthy lifestyle, such as physical exercise. Next, we summarized the main types of age-related white matter lesions, including white matter atrophy and hyperintensity. Age-related white matter changes mainly occurred in the frontal lobe, and white matter lesions in posterior regions may be an early sign of Alzheimer's disease. In addition, the relationship between brain activity and various cognitive functions during aging was discussed based on electroencephalography, magnetoencephalogram, and functional magnetic resonance imaging. An age-related reduction in occipital activity is coupled with increased frontal activity, which supports the posterior-anterior shift in aging (PASA) theory. Finally, we discussed the relationship between amyloid-β deposition and tau accumulation in the brain, as pathological manifestations of neurodegenerative disease and aging.
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Affiliation(s)
- Mingxi Dang
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing, China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Centre, Beijing Normal University, Beijing, China
| | - Feng Sang
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing, China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Centre, Beijing Normal University, Beijing, China
| | - Shijie Long
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing, China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Centre, Beijing Normal University, Beijing, China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing, China.
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Centre, Beijing Normal University, Beijing, China.
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22
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Del Percio C, Lopez S, Noce G, Lizio R, Tucci F, Soricelli A, Ferri R, Nobili F, Arnaldi D, Famà F, Buttinelli C, Giubilei F, Marizzoni M, Güntekin B, Yener G, Stocchi F, Vacca L, Frisoni GB, Babiloni C. What a Single Electroencephalographic (EEG) Channel Can Tell us About Alzheimer's Disease Patients With Mild Cognitive Impairment. Clin EEG Neurosci 2023; 54:21-35. [PMID: 36413420 DOI: 10.1177/15500594221125033] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; www.pdwaves.eu). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries.
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Affiliation(s)
- Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy
| | | | | | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy
| | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Flavio Nobili
- Clinica neurologica, 9246IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), 27212Università di Genova, Italy
| | - Dario Arnaldi
- Clinica neurologica, 9246IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), 27212Università di Genova, Italy
| | - Francesco Famà
- Clinica neurologica, 9246IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, 9311Sapienza University of Rome, Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, 9311Sapienza University of Rome, Rome, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, 218502Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab., 218502Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Izmir University of Economics, Faculty of Medicine, Izmir, Turkey
| | | | | | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and 27212University of Geneva, Geneva, Switzerland
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", 9311Sapienza University of Rome, Rome, Italy.,Hospital San Raffaele Cassino, Cassino (FR), Italy
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23
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Thapa N, Yang JG, Bae S, Kim GM, Park HJ, Park H. Effect of Electrical Muscle Stimulation and Resistance Exercise Intervention on Physical and Brain Function in Middle-Aged and Older Women. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:101. [PMID: 36612423 PMCID: PMC9819342 DOI: 10.3390/ijerph20010101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 06/17/2023]
Abstract
This study investigated the effectiveness of electrical muscle stimulation (EMS) with resistance exercise training (ERT) and resistance exercise training (RT) on physical and brain function in middle-aged and older women. Method: Forty-eight participants were randomly allocated into three groups: (i) ERT (n = 16), (ii) RT (n = 16), and (iii) control group (n = 16). The intervention session was 50 min long and performed three times/week for four weeks. The ERT group performed quadriceps setting, straight leg raises, and ankle pump exercises while constantly receiving EMS on their quadriceps muscle on both legs. The RT group performed the same exercise without EMS. Physical function was measured using skeletal muscle mass index (SMI), handgrip strength, gait speed, five times sit-to-stand test (FTSS) and timed up-and-go test (TUG). Brain function was assessed with electroencephalogram measurement of whole brain activity. Results: After four-week intervention, significant improvements were observed in SMI (p < 0.01), phase angle (p < 0.05), and gait speed (p < 0.05) in the ERT group compared to the control group. ERT also increased muscle strength (p < 0.05) and mobility in lower limbs as observed in FTSS and TUG tests (p < 0.05) at post-intervention compared to the baseline. In the ERT group, significant positive changes were observed in Beta1 band power, Theta band power, and Alpha1 band whole brain connectivity (p < 0.005) compared to the control group. Conclusions: Our findings showed that ERT can improve muscle and brain function in middle-aged and older adults during a four-week intervention program whereas significant improvements were not observed with RT. Therefore might be one of the feasible alternative intervention to RT for the prevention of muscle loss whilst improving brain function for middle-aged and older population.
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Affiliation(s)
- Ngeemasara Thapa
- Department of Health Sciences, Graduate School, Dong-A University, Busan 49315, Republic of Korea
- Laboratory of Smart Healthcare, Dong-A University, Busan 49315, Republic of Korea
| | - Ja-Gyeong Yang
- Department of Health Sciences, Graduate School, Dong-A University, Busan 49315, Republic of Korea
- Laboratory of Smart Healthcare, Dong-A University, Busan 49315, Republic of Korea
| | - Seongryu Bae
- Department of Health Sciences, Graduate School, Dong-A University, Busan 49315, Republic of Korea
- Laboratory of Smart Healthcare, Dong-A University, Busan 49315, Republic of Korea
| | - Gwon-Min Kim
- Medical Research Institute, Pusan National University, Busan 49241, Republic of Korea
| | - Hye-Jin Park
- Department of Health Sciences, Graduate School, Dong-A University, Busan 49315, Republic of Korea
- Laboratory of Smart Healthcare, Dong-A University, Busan 49315, Republic of Korea
| | - Hyuntae Park
- Department of Health Sciences, Graduate School, Dong-A University, Busan 49315, Republic of Korea
- Laboratory of Smart Healthcare, Dong-A University, Busan 49315, Republic of Korea
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24
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Wang C, Xu T, Yu W, Li T, Han H, Zhang M, Tao M. Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography: From the perspective of event related potentials and deep learning. Int J Psychophysiol 2022; 182:182-189. [DOI: 10.1016/j.ijpsycho.2022.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/21/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022]
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25
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Hyperconnectivity matters in early-onset Alzheimer's disease: a resting-state EEG connectivity study. Neurophysiol Clin 2022; 52:459-471. [DOI: 10.1016/j.neucli.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 11/11/2022] Open
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26
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Patchitt J, Porffy LA, Whomersley G, Szentgyorgyi T, Brett J, Mouchlianitis E, Mehta MA, Nottage JF, Shergill SS. Alpha3/alpha2 power ratios relate to performance on a virtual reality shopping task in ageing adults. Front Aging Neurosci 2022; 14:876832. [PMID: 36212034 PMCID: PMC9540381 DOI: 10.3389/fnagi.2022.876832] [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: 02/15/2022] [Accepted: 07/18/2022] [Indexed: 11/18/2022] Open
Abstract
Background Aspects of cognitive function decline with age. This phenomenon is referred to as age-related cognitive decline (ARCD). Improving the understanding of these changes that occur as part of the ageing process can serve to enhance the detection of the more incapacitating neurodegenerative disorders such as Alzheimer’s disease (AD). In this study, we employ novel methods to assess ARCD by exploring the utility of the alpha3/alpha2 electroencephalogram (EEG) power ratio – a marker of AD, and a novel virtual reality (VR) functional cognition task – VStore, in discriminating between young and ageing healthy adults. Materials and methods Twenty young individuals aged 20–30, and 20 older adults aged 60–70 took part in the study. Participants underwent resting-state EEG and completed VStore and the Cogstate Computerised Cognitive Battery. The difference in alpha3/alpha2 power ratios between the age groups was tested using t-test. In addition, the discriminatory accuracy of VStore and Cogstate were compared using logistic regression and overlying receiver operating characteristic (ROC) curves. Youden’s J statistic was used to establish the optimal threshold for sensitivity and specificity and model performance was evaluated with the DeLong’s test. Finally, alpha3/alpha2 power ratios were correlated with VStote and Cogstate performance. Results The difference in alpha3/alpha2 power ratios between age cohorts was not statistically significant. On the other hand, VStore discriminated between age groups with high sensitivity (94%) and specificity (95%) The Cogstate Pre-clinical Alzheimer’s Battery achieved a sensitivity of 89% and specificity of 60%, and Cogstate Composite Score achieved a sensitivity of 83% and specificity of 85%. The differences between the discriminatory accuracy of VStore and Cogstate models were statistically significant. Finally, high alpha3/alpha2 power ratios correlated strongly with VStore (r = 0.73), the Cogstate Pre-clinical Alzheimer’s Battery (r = -0.67), and Cogstate Composite Score (r = -0.76). Conclusion While we did not find evidence that the alpha3/alpha2 power ratio is elevated in healthy ageing individuals compared to young individuals, we demonstrated that VStore can classify age cohorts with high accuracy, supporting its utility in the assessment of ARCD. In addition, we found preliminary evidence that elevated alpha3/alpha2 power ratio may be linked to lower cognitive performance.
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Affiliation(s)
- Joel Patchitt
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Trafford Centre for Medical Research, University of Sussex, Brighton, United Kingdom
| | - Lilla A. Porffy
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- *Correspondence: Lilla A. Porffy,
| | - Gabriella Whomersley
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Timea Szentgyorgyi
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Jack Brett
- Faculty of Media and Communications, Bournemouth University, Poole, United Kingdom
| | - Elias Mouchlianitis
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- School of Psychology, University of East London, London, United Kingdom
| | - Mitul A. Mehta
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Judith F. Nottage
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Department of Psychological Sciences, Birkbeck, University of London, London, United Kingdom
| | - Sukhi S. Shergill
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Kent and Medway Medical School, Canterbury, United Kingdom
- Kent and Medway National Health Service and Social Care Partnership Trust, Kent, United Kingdom
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Buján A, Sampaio A, Pinal D. Resting-state electroencephalographic correlates of cognitive reserve: Moderating the age-related worsening in cognitive function. Front Aging Neurosci 2022; 14:854928. [PMID: 36185469 PMCID: PMC9521492 DOI: 10.3389/fnagi.2022.854928] [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: 01/14/2022] [Accepted: 08/08/2022] [Indexed: 11/23/2022] Open
Abstract
This exploratory study aimed to investigate the resting-state electroencephalographic (rsEEG) correlates of the cognitive reserve from a life span perspective. Current source density (CSD) and lagged-linear connectivity (LLC) measures were assessed to this aim. We firstly explored the relationship between rsEEG measures for the different frequency bands and a socio-behavioral proxy of cognitive reserve, the Cognitive Reserve Index (CRI). Secondly, we applied moderation analyses to assess whether any of the correlated rsEEG measures showed a moderating role in the relationship between age and cognitive function. Moderate negative correlations were found between the CRI and occipital CSD of delta and beta 2. Moreover, inter- and intrahemispheric LLC measures were correlated with the CRI, showing a negative association with delta and positive associations with alpha 1, beta 1, and beta 2. Among those correlated measures, just two rsEEG variables were significant moderators of the relationship between age and cognition: occipital delta CSD and right hemispheric beta 2 LLC between occipital and limbic regions. The effect of age on cognitive performance was stronger for higher values of both measures. Therefore, lower values of occipital delta CSD and lower beta 2 LLC between right occipital and limbic regions might protect or compensate for the effects of age on cognition. Results of this exploratory study might be helpful to allocate more preventive efforts to curb the progression of cognitive decline in adults with less CR, possibly characterized by these rsEEG parameters at a neural level. However, given the exploratory nature of this study, more conclusive work on these rsEEG measures is needed to firmly establish their role in the cognition–age relationship, for example, verifying if these measures moderate the relationship between brain structure and cognition.
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Spinelli G, Bakardjian H, Schwartz D, Potier MC, Habert MO, Levy M, Dubois B, George N. Theta Band-Power Shapes Amyloid-Driven Longitudinal EEG Changes in Elderly Subjective Memory Complainers At-Risk for Alzheimer's Disease. J Alzheimers Dis 2022; 90:69-84. [PMID: 36057818 DOI: 10.3233/jad-220204] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) includes progressive symptoms spread along a continuum of preclinical and clinical stages. Although numerous studies uncovered the neuro-cognitive changes of AD, very little is known on the natural history of brain lesions and modifications of brain networks in elderly cognitively-healthy memory complainers at risk of AD for carrying pathophysiological biomarkers (amyloidopathy and tauopathy). OBJECTIVE We analyzed resting-state electroencephalography (EEG) of 318 cognitively-healthy subjective memory complainers from the INSIGHT-preAD cohort at the time of their first visit (M0) and two-years later (M24). METHODS Using 18F-florbetapir PET-scanner, subjects were stratified between amyloid negative (A-; n = 230) and positive (A+; n = 88) groups. Differences between A+ and A-were estimated at source-level in each band-power of the EEG spectrum. RESULTS At M0, we found an increase of theta power in the mid-frontal cortex in A+ compared to A-. No significant association was found between mid-frontal theta and the individuals' cognitive performance. At M24, theta power increased in A+ relative to A-individuals in the posterior cingulate cortex and the pre-cuneus. Alpha band revealed a peculiar decremental trend in posterior brain regions in the A+ relative to the A-group only at M24. Theta power increase over the mid-frontal and mid-posterior cortices suggests an hypoactivation of the default-mode network in the A+ individuals and a non-linear longitudinal progression at M24. CONCLUSION We provide the first source-level longitudinal evidence on the impact of brain amyloidosis on the EEG dynamics of a large-scale, monocentric cohort of elderly individuals at-risk for AD.
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Affiliation(s)
- Giuseppe Spinelli
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France.,AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | - Hovagim Bakardjian
- AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | | | - Marie-Claude Potier
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France
| | - Marie-Odile Habert
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France.,AP-HP, Hôpital de la Pitié-Salpêtrière, Médecine Nucléaire, Paris, France.,Centre d'Acquisition et Traitement des Images (CATI), http://www.cati-neuroimaging.com
| | - Marcel Levy
- AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | - Bruno Dubois
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France.,AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | - Nathalie George
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France
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Martin T, Giordani B, Kavcic V. EEG asymmetry and cognitive testing in MCI identification. Int J Psychophysiol 2022; 177:213-219. [PMID: 35618112 PMCID: PMC10756646 DOI: 10.1016/j.ijpsycho.2022.05.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 04/05/2022] [Accepted: 05/18/2022] [Indexed: 01/18/2023]
Abstract
BACKGROUND Finding the baseline resting-state EEG markers for early identification of cognitive decline can contribute to the identification of individuals at risk of further change. Potential applications include identifying participants for clinical trials, early treatment, and evaluation of treatment, accessible even from a community setting. METHODS Analyses were completed on a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling African Americans (58 cognitively typical/HC, and 41 mildly cognitively impaired/MCI), who were recruited from the Michigan Alzheimer's Disease Research Center (MADRC) and the Wayne State University Institute of Gerontology. In addition to neuropsychological testing with CogState and Toolbox computerized batteries, resting-state EEGs (rsEEG, eyes closed) were acquired before and after participants were engaged in a visual motion direction discrimination task. rsEEG frontal alpha asymmetry (FAA) and frontal beta asymmetry (FBA) were calculated. RESULTS FAA showed no difference across groups for the pre-task resting state. FBA was significantly different between groups, with more asymmetric frontal beta in MCI. Both physiological indices, however, along with computerized neuropsychological tests were significant predictors in logistic regression classification of MCI vs. control participants. CONCLUSION rsEEG asymmetries can contribute significantly to successful discrimination of older persons with MCI from those without, over and above cognitive testing, alone.
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Affiliation(s)
- Tim Martin
- Department of Psychological Sciences, Kennesaw State University, GA, USA
| | - Bruno Giordani
- Departments of Psychiatry, Neurology, and Psychology and School of Nursing, University of Michigan, Ann Arbor, MI, USA
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, USA; International Institute of Applied Gerontology, Ljubljana, Slovenia.
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Biophysical mechanism underlying compensatory preservation of neural synchrony over the adult lifespan. Commun Biol 2022; 5:567. [PMID: 35681107 PMCID: PMC9184644 DOI: 10.1038/s42003-022-03489-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 05/12/2022] [Indexed: 11/17/2022] Open
Abstract
We propose that the preservation of functional integration, estimated from measures of neural synchrony, is a key objective of neurocompensatory mechanisms associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at the peak alpha frequency in Magnetoencephalography recordings remains invariant over the lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delays associated with age-related degeneration of white matter tracts, albeit at slower network frequencies. By deriving analytical solutions for simplified connection topologies, we further establish the theoretical principles underlying compensatory network re-organization. Our findings suggest that frequency slowing with age- frequently observed in the alpha band in diverse populations- may be viewed as an epiphenomenon of the underlying compensatory mechanism. Analysis of MEG data from healthy participants and whole-brain network modeling suggests that the brain compensates for age-related disruptions in connectivity by slowing down the frequency of neural synchronization.
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Wang J, Sun T, Zhang Y, Yu X, Wang H. Distinct Effects of the Apolipoprotein E ε4 Genotype on Associations Between Delayed Recall Performance and Resting-State Electroencephalography Theta Power in Elderly People Without Dementia. Front Aging Neurosci 2022; 14:830149. [PMID: 35693343 PMCID: PMC9178171 DOI: 10.3389/fnagi.2022.830149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 05/06/2022] [Indexed: 11/21/2022] Open
Abstract
Background Abnormal electroencephalography (EEG) activity has been demonstrated in mild cognitive impairment (MCI), and theta rhythm might be inversely related to memory. The apolipoprotein E (ApoE) epsilon 4 (ε4) allele, as a genetic vulnerability factor for pathologic and normal age-related cognitive decline, may influence different patterns of cognitive dysfunction. Therefore, the present study primarily aimed to verify the role of resting theta rhythm in delayed recall deficits, and further explore the effects of the ApoE genotype on the associations between the resting theta power and delayed recall performance in the elderly individuals without dementia. Methods A total of 47 individuals without dementia, including 23 MCI and 24 healthy subjects (HCs), participated in the study. All subjects were administered the Hopkins Verbal Learning Test–Revised (HVLT-R) to measure delayed recall performance. Power spectra based on resting-state EEG data were used to examine brain oscillations. Linear regression was used to examine the relationships between EEG power and delayed recall performance in each subgroup. Results The increased theta power in the bilateral central and temporal areas (Ps = 0.02–0.044, uncorrected) was found in the patients with MCI, and were negatively correlated with delayed recall performance (rs = −0.358 to −0.306, Ps = 0.014–0.036, FDR corrected) in the elderly individuals without dementia. The worse delayed recall performance was associated with higher theta power in the left central and temporal areas, especially in ApoE ε4 non-carriers and not in carriers (rs = −0.404 to −0.369, Ps = 0.02–0.035, uncorrected). Conclusion Our study suggests that theta disturbances might contribute to delayed recall memory decline. The ApoE genotype may have distinct effects on EEG-based neural correlates of episodic memory performance.
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Affiliation(s)
- Jing Wang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Tingting Sun
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
- Department of Psychiatry, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Zhang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Xin Yu
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Huali Wang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
- *Correspondence: Huali Wang,
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Torres-Simón L, Doval S, Nebreda A, Llinas SJ, Marsh EB, Maestú F. Understanding brain function in vascular cognitive impairment and dementia with EEG and MEG: A systematic review. Neuroimage Clin 2022; 35:103040. [PMID: 35653914 PMCID: PMC9163840 DOI: 10.1016/j.nicl.2022.103040] [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: 01/25/2022] [Revised: 04/09/2022] [Accepted: 05/06/2022] [Indexed: 11/22/2022]
Abstract
Vascular Cognitive Impairment (VCI) is the second most prevalent dementia worldwide. Cerebrovascular disease is a major comorbid contributor to neurodegenerative diseases. VCI patients show specific spectral, connectivity and evoked responses patterns. Literature suggests that EEG-MEG might provide promising biomarkers for early VCI. Further neurophysiological research is needed for VCI subtypes differentiation.
Vascular Cognitive Impairment (VCI) is the second most prevalent dementia after Alzheimer’s Disease (AD), and cerebrovascular disease (CBVD) is a major comorbid contributor to the progression of most neurodegenerative diseases. Early differentiation of cognitive impairment is critical given both the high prevalence of CBVD, and that its risk factors are modifiable. The ability for electroencephalogram (EEG) and magnetoencephalogram (MEG) to detect changes in brain functioning for other dementias suggests that they may also be promising biomarkers for early VCI. The present systematic review aims to summarize the literature regarding electrophysiological patterns of mild and major VCI. Despite considerable heterogeneity in clinical definition and electrophysiological methodology, common patterns exist when comparing patients with VCI to healthy controls (HC) and patients with AD, though there is a low specificity when comparing between VCI subgroups. Similar to other dementias, slowed frequency patterns and disrupted inter- and intra-hemispheric connectivity are repeatedly reported for VCI patients, as well as longer latencies and smaller amplitudes in evoked responses. Further study is needed to fully establish MEG and EEG as clinically useful biomarkers, including a clear definition of VCI and standardized methodology, allowing for comparison across groups and consolidation of multicenter efforts.
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Affiliation(s)
- Lucía Torres-Simón
- Center of Cognitive and Computational Neuroscience; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.
| | - Sandra Doval
- Center of Cognitive and Computational Neuroscience; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Alberto Nebreda
- Center of Cognitive and Computational Neuroscience; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Sophia J Llinas
- Department of Neurology, the Johns Hopkins School of Medicine, Baltimore, MD USA
| | - Elisabeth B Marsh
- Department of Neurology, the Johns Hopkins School of Medicine, Baltimore, MD USA
| | - Fernando Maestú
- Center of Cognitive and Computational Neuroscience; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
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Öksüz Ö, Günver MG, Arıkan MK. Quantitative Electroencephalography Findings in Patients With Diabetes Mellitus. Clin EEG Neurosci 2022; 53:248-255. [PMID: 33729035 DOI: 10.1177/1550059421997657] [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] [Indexed: 11/15/2022]
Abstract
Objective. Diabetes mellitus (DM) causes structural central nervous system (CNS) impairment, and this situation can be detected by quantitative electroencephalography (QEEG) findings before cognitive impairment is clinically observed. The main aim of this study is to uncover the effect of DM on brain function. Since QEEG reflects the CNS functioning, particularly in cognitive aspects, we expected electrophysiological clues to be found for prevention and follow-up in DM-related cognitive decline. Since a majority of the psychiatric population have cognitive dysfunction, we have given particular attention to those people. It was stated that a decrease was observed in the posterior cortical alpha power due to the hippocampal atrophy by several previous studies and we hypothesize that decreased alpha power will be observed also in DM. Methods. This study included 2094 psychiatric patients, 207 of whom were diagnosed with DM and 1887 of whom were not diagnosed with DM, and QEEG recordings were performed. Eyes-closed electroencephalography data were segmented into consecutive 2 s epochs. Fourier analysis was performed by averaging across 2 s epochs without artifacts. The absolute alpha power in the occipital regions (O1 and O2) of patients with and without DM was compared. Results. In the DM group, a decrease in the absolute alpha, alpha 1, and alpha 2 power in O1 and O2 was observed in comparison with the control group. It was determined that the type of psychiatric diagnosis did not affect QEEG findings. Conclusion. The decrease in absolute alpha power observed in patients diagnosed with DM may be related to the CNS impairment in DM. QEEG findings in DM can be useful while monitoring the CNS impairment, diagnosing DM-related dementia, in the follow-up of the cognitive process, constructing the protocols for electrophysiological interventions like neurofeedback and transcranial magnetic stimulation and monitoring the response to treatment.
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Affiliation(s)
- Özden Öksüz
- Department of Neuroscience, 52998Yeditepe University, İstanbul, Turkey
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Lazarou I, Georgiadis K, Nikolopoulos S, Oikonomou VP, Stavropoulos TG, Tsolaki A, Kompatsiaris I, Tsolaki M. Exploring Network Properties Across Preclinical Stages of Alzheimer’s Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study. J Alzheimers Dis 2022; 87:643-664. [DOI: 10.3233/jad-215421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Visual short-term memory (VSTMT) and visual attention (VAT) exhibit decline in the Alzheimer’s disease (AD) continuum; however, network disruption in preclinical stages is scarcely explored. Objective: To advance our knowledge about brain networks in AD and discover connectivity alterations during VSTMT and VAT. Methods: Twelve participants with AD, 23 with mild cognitive impairment (MCI), 17 with subjective cognitive decline (SCD), and 21 healthy controls (HC) were examined using a neuropsychological battery at baseline and follow-up (three years). At baseline, the subjects were examined using high density electroencephalography while performing a VSTMT and VAT. For exploring network organization, we constructed weighted undirected networks and examined clustering coefficient, strength, and betweenness centrality from occipito-parietal regions. Results: One-way ANOVA and pair-wise t-test comparisons showed statistically significant differences in HC compared to SCD (t (36) = 2.43, p = 0.026), MCI (t (42) = 2.34, p = 0.024), and AD group (t (31) = 3.58, p = 0.001) in Clustering Coefficient. Also with regards to Strength, higher values for HC compared to SCD (t (36) = 2.45, p = 0.019), MCI (t (42) = 2.41, p = 0.020), and AD group (t (31) = 3.58, p = 0.001) were found. Follow-up neuropsychological assessment revealed converge of 65% of the SCD group to MCI. Moreover, SCD who were converted to MCI showed significant lower values in all network metrics compared to the SCD that remained stable. Conclusion: The present findings reveal that SCD exhibits network disorganization during visual encoding and retrieval with intermediate values between MCI and HC.
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Affiliation(s)
- Ioulietta Lazarou
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- 1 Department of Neurology, G.H. “AHEPA”, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Greece
| | - Kostas Georgiadis
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- Informatics Department, Aristotle University of Thessaloniki, Makedonia, Greece
| | - Spiros Nikolopoulos
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Vangelis P. Oikonomou
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Thanos G. Stavropoulos
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Anthoula Tsolaki
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders, Thessaloniki, Makedonia, Greece
| | - Ioannis Kompatsiaris
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Magda Tsolaki
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- 1 Department of Neurology, G.H. “AHEPA”, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders, Thessaloniki, Makedonia, Greece
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Karimi H, Marefat H, Khanbagi M, Kalafatis C, Modarres MH, Vahabi Z, Khaligh-Razavi SM. Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment. PLoS One 2022; 17:e0264058. [PMID: 35196356 PMCID: PMC8865635 DOI: 10.1371/journal.pone.0264058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 02/02/2022] [Indexed: 11/18/2022] Open
Abstract
Electroencephalography (EEG) has been commonly used to measure brain alterations in Alzheimer’s Disease (AD). However, reported changes are limited to those obtained from using univariate measures, including activation level and frequency bands. To look beyond the activation level, we used multivariate pattern analysis (MVPA) to extract patterns of information from EEG responses to images in an animacy categorization task. Comparing healthy controls (HC) with patients with mild cognitive impairment (MCI), we found that the neural speed of animacy information processing is decreased in MCI patients. Moreover, we found critical time-points during which the representational pattern of animacy for MCI patients was significantly discriminable from that of HC, while the activation level remained unchanged. Together, these results suggest that the speed and pattern of animacy information processing provide clinically useful information as a potential biomarker for detecting early changes in MCI and AD patients.
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Affiliation(s)
- Hamed Karimi
- Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
- Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
- * E-mail: (HK); (SMKR)
| | - Haniyeh Marefat
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mahdiyeh Khanbagi
- Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
| | - Chris Kalafatis
- South London & Maudsley NHS Foundation Trust, London, United Kingdom
- Department of Old Age Psychiatry, King’s College London, London, United Kingdom
- Cognetivity Ltd, London, United Kingdom
| | | | - Zahra Vahabi
- Department of Geriatric Medicine, Ziaeian Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Memory and Behavioral Neurology Division, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed-Mahdi Khaligh-Razavi
- Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
- Cognetivity Ltd, London, United Kingdom
- * E-mail: (HK); (SMKR)
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Yao S, Zhu J, Li S, Zhang R, Zhao J, Yang X, Wang Y. Bibliometric Analysis of Quantitative Electroencephalogram Research in Neuropsychiatric Disorders From 2000 to 2021. Front Psychiatry 2022; 13:830819. [PMID: 35677873 PMCID: PMC9167960 DOI: 10.3389/fpsyt.2022.830819] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 04/05/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND With the development of quantitative electroencephalography (QEEG), an increasing number of studies have been published on the clinical use of QEEG in the past two decades, particularly in the diagnosis, treatment, and prognosis of neuropsychiatric disorders. However, to date, the current status and developing trends of this research field have not been systematically analyzed from a macroscopic perspective. The present study aimed to identify the hot spots, knowledge base, and frontiers of QEEG research in neuropsychiatric disorders from 2000 to 2021 through bibliometric analysis. METHODS QEEG-related publications in the neuropsychiatric field from 2000 to 2021 were retrieved from the Web of Science Core Collection (WOSCC). CiteSpace and VOSviewer software programs, and the online literature analysis platform (bibliometric.com) were employed to perform bibliographic and visualized analysis. RESULTS A total of 1,904 publications between 2000 and 2021 were retrieved. The number of QEEG-related publications in neuropsychiatric disorders increased steadily from 2000 to 2021, and research in psychiatric disorders requires more attention in comparison to research in neurological disorders. During the last two decades, QEEG has been mainly applied in neurodegenerative diseases, cerebrovascular diseases, and mental disorders to reveal the pathological mechanisms, assist clinical diagnosis, and promote the selection of effective treatments. The recent hot topics focused on QEEG utilization in neurodegenerative disorders like Alzheimer's and Parkinson's disease, traumatic brain injury and related cerebrovascular diseases, epilepsy and seizure, attention-deficit hyperactivity disorder, and other mental disorders like major depressive disorder and schizophrenia. In addition, studies to cross-validate QEEG biomarkers, develop new biomarkers (e.g., functional connectivity and complexity), and extract compound biomarkers by machine learning were the emerging trends. CONCLUSION The present study integrated bibliometric information on the current status, the knowledge base, and future directions of QEEG studies in neuropsychiatric disorders from a macroscopic perspective. It may provide valuable insights for researchers focusing on the utilization of QEEG in this field.
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Affiliation(s)
- Shun Yao
- Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China.,Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Jieying Zhu
- Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Shuiyan Li
- Department of Rehabilitation Medicine, School of Rehabilitation Medicine, Southern Medical University, Guangzhou, China
| | - Ruibin Zhang
- Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jiubo Zhao
- Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China.,Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Xueling Yang
- Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China.,Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - You Wang
- Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China.,Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China
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Griffa A, Legdeur N, Badissi M, van den Heuvel MP, Stam CJ, Visser PJ, Hillebrand A. Magnetoencephalography Brain Signatures Relate to Cognition and Cognitive Reserve in the Oldest-Old: The EMIF-AD 90 + Study. Front Aging Neurosci 2021; 13:746373. [PMID: 34899269 PMCID: PMC8656941 DOI: 10.3389/fnagi.2021.746373] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/01/2021] [Indexed: 11/25/2022] Open
Abstract
The oldest-old subjects represent the fastest growing segment of society and are at high risk for dementia with a prevalence of up to 40%. Lifestyle factors, such as lifelong participation in cognitive and leisure activities, may contribute to individual cognitive reserve and reduce the risk for cognitive impairments. However, the neural bases underlying cognitive functioning and cognitive reserve in this age range are still poorly understood. Here, we investigate spectral and functional connectivity features obtained from resting-state MEG recordings in a cohort of 35 cognitively normal (92.2 ± 1.8 years old, 19 women) and 11 cognitively impaired (90.9 ± 1.9 years old, 1 woman) oldest-old participants, in relation to cognitive traits and cognitive reserve. The latter was approximated with a self-reported scale on lifelong engagement in cognitively demanding activities. Cognitively impaired oldest-old participants had slower cortical rhythms in frontal, parietal and default mode network regions compared to the cognitively normal subjects. These alterations mainly concerned the theta and beta band and partially explained inter-subject variability of episodic memory scores. Moreover, a distinct spectral pattern characterized by higher relative power in the alpha band was specifically associated with higher cognitive reserve while taking into account the effect of age and education level. Finally, stronger functional connectivity in the alpha and beta band were weakly associated with better cognitive performances in the whole group of subjects, although functional connectivity effects were less prominent than the spectral ones. Our results shed new light on the neural underpinnings of cognitive functioning in the oldest-old population and indicate that cognitive performance and cognitive reserve may have distinct spectral electrophysiological substrates.
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Affiliation(s)
- Alessandra Griffa
- Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Center of Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.,Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Nienke Legdeur
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Maryam Badissi
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Martijn P van den Heuvel
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neuroscience and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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Rios-Arismendy S, Ochoa-Gómez JF, Serna-Rojas C. Revisión de electroencefalografía portable y su aplicabilidad en neurociencias. REVISTA POLITÉCNICA 2021. [DOI: 10.33571/rpolitec.v17n34a9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
La electroencefalografía (EEG) es una técnica que permite registrar la actividad eléctrica del cerebro y ha sido estudiada durante los últimos cien años en diferentes ámbitos de la neurociencia. En los últimos años se ha investigado y desarrollado equipos de medición que sean portables y que permitan una buena calidad de la señal, por lo cual se realizó una revisión bibliográfica de las compañías fabricantes de algunos dispositivos de electroencefalografía portable disponibles en el mercado, se exponen sus características principales, algunos trabajos encontrados que fueron realizados con los dispositivos, comparaciones entre los mismos y una discusión acerca de las ventajas y desventajas de sus características. Finalmente se concluye que a la hora de comprar un dispositivo para electroencefalografía portable es necesario tener en cuenta el uso que se le va a dar y el costo-beneficio que tiene el equipo de acuerdo con sus características.
Encephalography is a technique that allows the recording of electrical activity of the brain and has been studied during the last hundred years in different areas of neuroscience. For several years, measuring equipment that are portable and that allow a good signal quality to have been researched and developed, so a literature review of the manufacturing companies of some of portable electroencephalography devices available on the market was carried out: Its main features are exposed, as well as some of the work found that were made with those, comparisons between them and a discussion about the advantages and disadvantages of their features. It is concluded that, when a portable encephalography device is bought, it’s necessary to take into consideration the use that it will be having and the cost-benefit that the device has according to its features.
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Chan D, Suk HJ, Jackson B, Milman NP, Stark D, Beach SD, Tsai LH. Induction of specific brain oscillations may restore neural circuits and be used for the treatment of Alzheimer's disease. J Intern Med 2021; 290:993-1009. [PMID: 34156133 DOI: 10.1111/joim.13329] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 03/24/2021] [Accepted: 05/17/2021] [Indexed: 01/08/2023]
Abstract
Brain oscillations underlie the function of our brains, dictating how we both think and react to the world around us. The synchronous activity of neurons generates these rhythms, which allow different parts of the brain to communicate and orchestrate responses to internal and external stimuli. Perturbations of cognitive rhythms and the underlying oscillator neurons that synchronize different parts of the brain contribute to the pathophysiology of diseases including Alzheimer's disease, (AD), Parkinson's disease (PD), epilepsy and other diseases of rhythm that have been studied extensively by Gyorgy Buzsaki. In this review, we discuss how neurologists manipulate brain oscillations with neuromodulation to treat diseases and how this can be leveraged to improve cognition and pathology underlying AD. While multiple modalities of neuromodulation are currently clinically indicated for some disorders, nothing is yet approved for improving memory in AD. Recent investigations into novel methods of neuromodulation show potential for improving cognition in memory disorders. Here, we demonstrate that neuronal stimulation using audiovisual sensory stimulation that generated 40-HZ gamma waves reduced AD-specific pathology and improved performance in behavioural tests in mouse models of AD, making this new mode of neuromodulation a promising new avenue for developing a new therapeutic intervention for the treatment of dementia.
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Affiliation(s)
- D Chan
- From the, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - H-J Suk
- From the, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - B Jackson
- From the, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.,Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - N P Milman
- From the, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Behavioral Neuroscience, Northeastern University, Boston, MA, USA
| | - D Stark
- From the, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - S D Beach
- From the, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.,Division of Medical Sciences, Harvard Medical School, Boston, MA, USA
| | - L-H Tsai
- From the, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA
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40
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Babaeeghazvini P, Rueda-Delgado LM, Gooijers J, Swinnen SP, Daffertshofer A. Brain Structural and Functional Connectivity: A Review of Combined Works of Diffusion Magnetic Resonance Imaging and Electro-Encephalography. Front Hum Neurosci 2021; 15:721206. [PMID: 34690718 PMCID: PMC8529047 DOI: 10.3389/fnhum.2021.721206] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 09/10/2021] [Indexed: 11/13/2022] Open
Abstract
Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.
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Affiliation(s)
- Parinaz Babaeeghazvini
- Department of Human Movements Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Science Institute (AMS), Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Institute for Brain and Behaviour Amsterdam (iBBA), Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Laura M. Rueda-Delgado
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium
- Trinity Centre for Biomedical Engineering, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | - Jolien Gooijers
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Stephan P. Swinnen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Andreas Daffertshofer
- Department of Human Movements Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Science Institute (AMS), Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Institute for Brain and Behaviour Amsterdam (iBBA), Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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41
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Fröhlich S, Kutz DF, Müller K, Voelcker-Rehage C. Characteristics of Resting State EEG Power in 80+-Year-Olds of Different Cognitive Status. Front Aging Neurosci 2021; 13:675689. [PMID: 34456708 PMCID: PMC8387136 DOI: 10.3389/fnagi.2021.675689] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 07/07/2021] [Indexed: 11/28/2022] Open
Abstract
Compared with healthy older adults, patients with Alzheimer's disease show decreased alpha and beta power as well as increased delta and theta power during resting state electroencephalography (rsEEG). Findings for mild cognitive impairment (MCI), a stage of increased risk of conversion to dementia, are less conclusive. Cognitive status of 213 non-demented high-agers (mean age, 82.5 years) was classified according to a neuropsychological screening and a cognitive test battery. RsEEG was measured with eyes closed and open, and absolute power in delta, theta, alpha, and beta bands were calculated for nine regions. Results indicate no rsEEG power differences between healthy individuals and those with MCI. There were also no differences present between groups in EEG reactivity, the change in power from eyes closed to eyes open, or the topographical pattern of each frequency band. Overall, EEG reactivity was preserved in 80+-year-olds without dementia, and topographical patterns were described for each frequency band. The application of rsEEG power as a marker for the early detection of dementia might be less conclusive for high-agers.
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Affiliation(s)
- Stephanie Fröhlich
- Department of Neuromotor Behavior and Exercise, Institute of Sport and Exercise Sciences, Faculty of Psychology and Sport Sciences, University of Münster, Münster, Germany.,Department of Sports Psychology (With Focus on Prevention and Rehabilitation), Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany
| | - Dieter F Kutz
- Department of Neuromotor Behavior and Exercise, Institute of Sport and Exercise Sciences, Faculty of Psychology and Sport Sciences, University of Münster, Münster, Germany.,Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany
| | - Katrin Müller
- Department of Sports Psychology (With Focus on Prevention and Rehabilitation), Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany.,Department of Social Science of Physical Activity and Health, Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany
| | - Claudia Voelcker-Rehage
- Department of Neuromotor Behavior and Exercise, Institute of Sport and Exercise Sciences, Faculty of Psychology and Sport Sciences, University of Münster, Münster, Germany.,Department of Sports Psychology (With Focus on Prevention and Rehabilitation), Institute of Human Movement Science and Health, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany
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42
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Özbek Y, Fide E, Yener GG. Resting-state EEG alpha/theta power ratio discriminates early-onset Alzheimer's disease from healthy controls. Clin Neurophysiol 2021; 132:2019-2031. [PMID: 34284236 DOI: 10.1016/j.clinph.2021.05.012] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 03/12/2021] [Accepted: 05/17/2021] [Indexed: 11/17/2022]
Abstract
OBJECTIVES The present study aims to compare early-onset Alzheimer's disease (EOAD) patients with healthy controls (HC), and late-onset Alzheimer's disease (LOAD) patients using resting-state delta, theta, alpha, and beta oscillations and provide a cut-off score of alpha/theta ratio to discriminate individuals with EOAD and young HC. METHODS Forty-seven individuals with EOAD, 51 individuals with LOAD, and demographically-matched 49 young and 51 older controls were included in the study. Spectral-power analysis using Fast-Fourier Transformation (FFT) is performed on resting-state electroencephalography (EEG) data. Delta, theta, alpha, and beta oscillations compared between groups and Receiver Operating Characteristic (ROC) curve analysis was conducted. RESULTS Compared to healthy controls individuals with EOAD showed an increase in slow frequency bands and a decrease in fast frequency bands. Frontal alpha/theta power ratio is the best discriminating value between EOAD and young HC with the sensitivity and specificity greater than 80% with area under the curve (AUC) 0.881. CONCLUSIONS EOAD display more widespread and severe electrophysiological abnormalities than LOAD and HC which may reflect more pronounced pathological burden and cholinergic deficits in EOAD. Additionally, the alpha/theta ratio can discriminate EOAD and young HC successfully. SIGNIFICANCE This study is the first to report that resting-state EEG power can be a promising marker for diagnostic accuracy between EOAD and healthy controls.
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Affiliation(s)
- Yağmur Özbek
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Ezgi Fide
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Görsev G Yener
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey; Izmir University of Economics, Faculty of Medicine, Izmir, Turkey.
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43
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Riganello F, Vatrano M, Carozzo S, Russo M, Lucca LF, Ursino M, Ruggiero V, Cerasa A, Porcaro C. The Timecourse of Electrophysiological Brain-Heart Interaction in DoC Patients. Brain Sci 2021; 11:750. [PMID: 34198911 PMCID: PMC8228557 DOI: 10.3390/brainsci11060750] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 05/31/2021] [Accepted: 06/03/2021] [Indexed: 01/09/2023] Open
Abstract
Disorders of Consciousness (DOC) are a spectrum of pathologies affecting one's ability to interact with the external world. Two possible conditions of patients with DOC are Unresponsive Wakefulness Syndrome/Vegetative State (UWS/VS) and Minimally Conscious State (MCS). Analysis of spontaneous EEG activity and the Heart Rate Variability (HRV) are effective techniques in exploring and evaluating patients with DOC. This study aims to observe fluctuations in EEG and HRV parameters in the morning/afternoon resting-state recording. The study enrolled 13 voluntary Healthy Control (HC) subjects and 12 DOC patients (7 MCS, 5 UWS/VS). EEG and EKG were recorded. PSDalpha, PSDtheta powerband, alpha-blocking, alpha/theta of the EEG, Complexity Index (CI) and SDNN of EKG were analyzed. Higher values of PSDalpha, alpha-blocking, alpha/theta and CI values and lower values of PSD theta characterized HC individuals in the morning with respect to DOC patients. In the afternoon, we detected a significant difference between groups in the CI, PSDalpha, PSDtheta, alpha/theta and SDNN, with lower PSDtheta value for HC. CRS-R scores showed a strong correlation with recorded parameters mainly during evaluations in the morning. Our finding put in evidence the importance of the assessment, as the stimulation of DOC patients in research for behavioural response, in the morning.
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Affiliation(s)
- Francesco Riganello
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
| | - Martina Vatrano
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
| | - Simone Carozzo
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
| | - Miriam Russo
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
| | - Lucia Francesca Lucca
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
| | - Maria Ursino
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
| | - Valentina Ruggiero
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
| | - Antonio Cerasa
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
- Institute for Biomedical Research and Innovation (IRIB)—National Research Council of Italy (CNR), 87050 Mangone, Italy
| | - Camillo Porcaro
- S.Anna Institute—Research in Advanced Neurorehabilitation, 88900 Crotone, Italy; (M.V.); (S.C.); (M.R.); (L.F.L.); (M.U.); (V.R.); (A.C.); (C.P.)
- Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
- Institute of Cognitive Sciences and Technologies (ISTC) - National Research Council (CNR), 00185 Rome, Italy
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44
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D'Atri A, Scarpelli S, Gorgoni M, Truglia I, Lauri G, Cordone S, Ferrara M, Marra C, Rossini PM, De Gennaro L. EEG alterations during wake and sleep in mild cognitive impairment and Alzheimer's disease. iScience 2021; 24:102386. [PMID: 33981973 PMCID: PMC8086022 DOI: 10.1016/j.isci.2021.102386] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 03/03/2021] [Accepted: 03/30/2021] [Indexed: 02/08/2023] Open
Abstract
Patients with Alzheimer's disease (AD) undergo a slowing of waking electroencephalographic (EEG) rhythms since prodromal stages, which could be ascribed to poor sleep quality. We examined the relationship between wake and sleep alterations by assessing EEG activity during sleep and (pre-sleep/post-sleep) wakefulness in AD, mild cognitive impairment (MCI) and healthy controls. AD and MCI show high sleep latency and less slow-wave sleep. Reduced sigma activity characterizes non-rapid eye movement (NREM) sleep, reflecting sleep spindles loss. The EEG slowing characterizes REM sleep and wakefulness of AD and MCI, with strong correlations among the two phenomena suggesting common neuropathological mechanisms. Evening-to-morning variations in waking EEG revealed the gradual disappearance in MCI and AD of overnight changes in delta activity, indicating a progressive decay of sleep restorative functions on diurnal activity that correlates with the impairment of sleep high-frequency activity in AD. Our findings support a linkage between wake and sleep alterations, and the importance of sleep-related processes in Alzheimer's disease progression.
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Affiliation(s)
- Aurora D'Atri
- Department of Psychology, University of Rome “Sapienza”, Via dei Marsi, 78, Rome 00185, Italy
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Coppito (L'Aquila) 67100, Italy
| | | | - Maurizio Gorgoni
- Department of Psychology, University of Rome “Sapienza”, Via dei Marsi, 78, Rome 00185, Italy
| | - Ilaria Truglia
- Department of Psychology, University of Rome “Sapienza”, Via dei Marsi, 78, Rome 00185, Italy
| | - Giulia Lauri
- Department of Psychology, University of Rome “Sapienza”, Via dei Marsi, 78, Rome 00185, Italy
| | - Susanna Cordone
- Department of Psychology, University of Rome “Sapienza”, Via dei Marsi, 78, Rome 00185, Italy
| | - Michele Ferrara
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Coppito (L'Aquila) 67100, Italy
| | - Camillo Marra
- Foundation Policlinico Universitario Agostino Gemelli IRCCS – Department of aging, neuroscience, orthopaedic and head-neck, Rome 00168, Italy
| | - Paolo Maria Rossini
- Department of Neuroscience & Neurorehabil., IRCCS San Raffaele-Pisana, Rome, 00163, Italy
| | - Luigi De Gennaro
- Department of Psychology, University of Rome “Sapienza”, Via dei Marsi, 78, Rome 00185, Italy
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45
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Babiloni C, Arakaki X, Azami H, Bennys K, Blinowska K, Bonanni L, Bujan A, Carrillo MC, Cichocki A, de Frutos-Lucas J, Del Percio C, Dubois B, Edelmayer R, Egan G, Epelbaum S, Escudero J, Evans A, Farina F, Fargo K, Fernández A, Ferri R, Frisoni G, Hampel H, Harrington MG, Jelic V, Jeong J, Jiang Y, Kaminski M, Kavcic V, Kilborn K, Kumar S, Lam A, Lim L, Lizio R, Lopez D, Lopez S, Lucey B, Maestú F, McGeown WJ, McKeith I, Moretti DV, Nobili F, Noce G, Olichney J, Onofrj M, Osorio R, Parra-Rodriguez M, Rajji T, Ritter P, Soricelli A, Stocchi F, Tarnanas I, Taylor JP, Teipel S, Tucci F, Valdes-Sosa M, Valdes-Sosa P, Weiergräber M, Yener G, Guntekin B. Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel. Alzheimers Dement 2021; 17:1528-1553. [PMID: 33860614 DOI: 10.1002/alz.12311] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 12/28/2020] [Accepted: 01/01/2021] [Indexed: 12/25/2022]
Abstract
The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino (FR), Italy
| | | | - Hamed Azami
- Department of Neurology and Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Karim Bennys
- Centre Mémoire de Ressources et de Recherche (CMRR), Centre Hospitalier, Universitaire de Montpellier, Montpellier, France
| | - Katarzyna Blinowska
- Institute of Biocybernetics, Warsaw, Poland.,Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ana Bujan
- Psychological Neuroscience Lab, School of Psychology, University of Minho, Minho, Portugal
| | - Maria C Carrillo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Andrzej Cichocki
- Skolkowo Institute of Science and Technology (SKOLTECH), Moscow, Russia.,Systems Research Institute PAS, Warsaw, Poland.,Nicolaus Copernicus University (UMK), Torun, Poland
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Bruno Dubois
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Rebecca Edelmayer
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Gary Egan
- Foundation Director of the Monash Biomedical Imaging (MBI) Research Facilities, Monash University, Clayton, Australia
| | - Stephane Epelbaum
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh, UK
| | - Alan Evans
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Francesca Farina
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Keith Fargo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Giovanni Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Harald Hampel
- GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Sorbonne University, Paris, France
| | | | - Vesna Jelic
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Jaeseung Jeong
- Department of Bio and Brain Engineering/Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Yang Jiang
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, Kentucky, USA
| | - Maciej Kaminski
- Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | - Kerry Kilborn
- School of Psychology, University of Glasgow, Glasgow, UK
| | - Sanjeev Kumar
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Alice Lam
- MGH Epilepsy Service, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lew Lim
- Vielight Inc., Toronto, Ontario, Canada
| | | | - David Lopez
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Brendan Lucey
- Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - William J McGeown
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
| | - Ian McKeith
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | | | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy.,Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - John Olichney
- UC Davis Department of Neurology and Center for Mind and Brain, Davis, California, USA
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ricardo Osorio
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, New York, USA
| | | | - Tarek Rajji
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Petra Ritter
- Brain Simulation Section, Department of Neurology, Charité Universitätsmedizin and Berlin Institute of Health, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Ioannis Tarnanas
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA.,Global Brain Health Institute, Trinity College Dublin, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - John Paul Taylor
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | - Stefan Teipel
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.,German Center for Neurodegenerative Diseases (DZNE) - Rostock/Greifswald, Rostock, Germany
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Pedro Valdes-Sosa
- Cuban Neuroscience Center, Havana, Cuba.,Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Marco Weiergräber
- Experimental Neuropsychopharmacology, BfArM), Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, Bonn, Germany
| | - Gorsev Yener
- Departments of Neurosciences and Department of Neurology, Dokuz Eylül University Medical School, Izmir, Turkey
| | - Bahar Guntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
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46
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Clements GM, Bowie DC, Gyurkovics M, Low KA, Fabiani M, Gratton G. Spontaneous Alpha and Theta Oscillations Are Related to Complementary Aspects of Cognitive Control in Younger and Older Adults. Front Hum Neurosci 2021; 15:621620. [PMID: 33841114 PMCID: PMC8025241 DOI: 10.3389/fnhum.2021.621620] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 02/15/2021] [Indexed: 12/18/2022] Open
Abstract
The resting-state human electroencephalogram (EEG) power spectrum is dominated by alpha (8-12 Hz) and theta (4-8 Hz) oscillations, and also includes non-oscillatory broadband activity inversely related to frequency (1/f activity). Gratton proposed that alpha and theta oscillations are both related to cognitive control function, though in a complementary manner. Alpha activity is hypothesized to facilitate the maintenance of representations, such as task sets in preparation for expected task conditions. In contrast, theta activity would facilitate changes in representations, such as the updating of task sets in response to unpredicted task demands. Therefore, theta should be related to reactive control (which may prompt changes in task representations), while alpha may be more relevant to proactive control (which implies the maintenance of current task representations). Less is known about the possible relationship between 1/f activity and cognitive control, which was analyzed here in an exploratory fashion. To investigate these hypothesized relationships, we recorded eyes-open and eyes-closed resting-state EEG from younger and older adults and subsequently tested their performance on a cued flanker task, expected to elicit both proactive and reactive control processes. Results showed that alpha power and 1/f offset were smaller in older than younger adults, whereas theta power did not show age-related reductions. Resting alpha power and 1/f offset were associated with proactive control processes, whereas theta power was related to reactive control as measured by the cued flanker task. All associations were present over and above the effect of age, suggesting that these resting-state EEG correlates could be indicative of trait-like individual differences in cognitive control performance, which may be already evident in younger adults, and are still similarly present in healthy older adults.
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Affiliation(s)
- Grace M Clements
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Daniel C Bowie
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Mate Gyurkovics
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Kathy A Low
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Monica Fabiani
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Gabriele Gratton
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
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47
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Babiloni C, Ferri R, Noce G, Lizio R, Lopez S, Lorenzo I, Panzavolta A, Soricelli A, Nobili F, Arnaldi D, Famà F, Orzi F, Buttinelli C, Giubilei F, Cipollini V, Marizzoni M, Güntekin B, Aktürk T, Hanoğlu L, Yener G, Özbek Y, Stocchi F, Vacca L, Frisoni GB, Del Percio C. Abnormalities of Cortical Sources of Resting State Alpha Electroencephalographic Rhythms are Related to Education Attainment in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment. Cereb Cortex 2021; 31:2220-2237. [PMID: 33251540 DOI: 10.1093/cercor/bhaa356] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 10/23/2020] [Accepted: 10/26/2020] [Indexed: 12/21/2022] Open
Abstract
In normal old (Nold) and Alzheimer's disease (AD) persons, a high cognitive reserve (CR) makes them more resistant and resilient to brain neuropathology and neurodegeneration. Here, we tested whether these effects may affect neurophysiological oscillatory mechanisms generating dominant resting state electroencephalographic (rsEEG) alpha rhythms in Nold and patients with mild cognitive impairment (MCI) due to AD (ADMCI). Data in 60 Nold and 70 ADMCI participants, stratified in higher (Edu+) and lower (Edu-) educational attainment subgroups, were available in an Italian-Turkish archive. The subgroups were matched for age, gender, and education. RsEEG cortical sources were estimated by eLORETA freeware. As compared to the Nold-Edu- subgroup, the Nold-Edu+ subgroup showed greater alpha source activations topographically widespread. On the contrary, in relation to the ADMCI-Edu- subgroup, the ADMCI-Edu+ subgroup displayed lower alpha source activations topographically widespread. Furthermore, the 2 ADMCI subgroups had matched cerebrospinal AD diagnostic biomarkers, brain gray-white matter measures, and neuropsychological scores. The current findings suggest that a high CR may be related to changes in rsEEG alpha rhythms in Nold and ADMCI persons. These changes may underlie neuroprotective effects in Nold seniors and subtend functional compensatory mechanisms unrelated to brain structure alterations in ADMCI patients.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino, Italy
| | | | | | | | - Susanna Lopez
- Nephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, Aldo Moro University of Bari, Bari, Italy
| | | | - Andrea Panzavolta
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Flavio Nobili
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Dario Arnaldi
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Francesco Famà
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Virginia Cipollini
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab., Istanbul Medipol University, Istanbul, Turkey
| | - Tuba Aktürk
- REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab., Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey.,Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Yağmur Özbek
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
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48
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Borhani S, Zhao X, Kelly MR, Gottschalk KE, Yuan F, Jicha GA, Jiang Y. Gauging Working Memory Capacity From Differential Resting Brain Oscillations in Older Individuals With A Wearable Device. Front Aging Neurosci 2021; 13:625006. [PMID: 33716711 PMCID: PMC7944100 DOI: 10.3389/fnagi.2021.625006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/20/2021] [Indexed: 11/29/2022] Open
Abstract
Working memory is a core cognitive function and its deficits is one of the most common cognitive impairments. Reduced working memory capacity manifests as reduced accuracy in memory recall and prolonged speed of memory retrieval in older adults. Currently, the relationship between healthy older individuals’ age-related changes in resting brain oscillations and their working memory capacity is not clear. Eyes-closed resting electroencephalogram (rEEG) is gaining momentum as a potential neuromarker of mild cognitive impairments. Wearable and wireless EEG headset measuring key electrophysiological brain signals during rest and a working memory task was utilized. This research’s central hypothesis is that rEEG (e.g., eyes closed for 90 s) frequency and network features are surrogate markers for working memory capacity in healthy older adults. Forty-three older adults’ memory performance (accuracy and reaction times), brain oscillations during rest, and inter-channel magnitude-squared coherence during rest were analyzed. We report that individuals with a lower memory retrieval accuracy showed significantly increased alpha and beta oscillations over the right parietal site. Yet, faster working memory retrieval was significantly correlated with increased delta and theta band powers over the left parietal sites. In addition, significantly increased coherence between the left parietal site and the right frontal area is correlated with the faster speed in memory retrieval. The frontal and parietal dynamics of resting EEG is associated with the “accuracy and speed trade-off” during working memory in healthy older adults. Our results suggest that rEEG brain oscillations at local and distant neural circuits are surrogates of working memory retrieval’s accuracy and processing speed. Our current findings further indicate that rEEG frequency and coherence features recorded by wearable headsets and a brief resting and task protocol are potential biomarkers for working memory capacity. Additionally, wearable headsets are useful for fast screening of cognitive impairment risk.
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Affiliation(s)
- Soheil Borhani
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States
| | - Xiaopeng Zhao
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States
| | - Margaret R Kelly
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Karah E Gottschalk
- Center on Gerontology, School of Public Health, University of Kentucky, Lexington, KY, United States.,Department of Audiology, Nova Southeastern University, Florida, FL, United States
| | - Fengpei Yuan
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States
| | - Gregory A Jicha
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States.,Department of Neurology, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Yang Jiang
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States.,Department of Behavioral Sciences, College of Medicine, University of Kentucky, Lexington, KY, United States
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49
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Miraglia F, Vecchio F, Alù F, Orticoni A, Judica E, Cotelli M, Rossini PM. Brain sources' activity in resting state before a visuo-motor task. J Neural Eng 2021; 18. [PMID: 33601343 DOI: 10.1088/1741-2552/abe7ba] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 02/18/2021] [Indexed: 11/12/2022]
Abstract
Objective In modern neuroscience, the underlying mechanisms of the elaboration and reaction to different kinds of stimuli of the brain hemispheres remain still very challenging to understand, together with the possibility to anticipate certain behaviors to improve the performance. Approach The purpose of the present study was to investigate the brain rhythms characteristics of EEG recordings and in particular, their interhemispheric differences in resting state condition before a visuo-motor task in a population of healthy adults. During the task, subjects were asked to react to a sequence of visual cues as quick as possible. The reaction times (RTs) to the task were measured, collected and correlated with the EEG signals recorded in a resting state condition immediately preceding the task. The EEG data were analyzed in the space of cortical sources of EEG rhythms by the computation of the Global Spectra Power Density (GSPD) in the left and in the right hemisphere, and of an index of brain Laterality L. Main results The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open and eyes closed conditions. A close to significant and negative correlation was found in the parietal areas. Furthermore, RTs negatively correlated with L in the central areas in eyes closed condition. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open and eyes closed conditions. Significance The correlations between the brain activity before a task and the RTs to the task can represent an interesting tool for exploring the brain state characterization for the upcoming tasks performance.
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Affiliation(s)
- Francesca Miraglia
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Via di Val Cannuta, 247, Roma, 00166, ITALY
| | - Fabrizio Vecchio
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Via di Val Cannuta, 247, Roma, Lazio, 00166, ITALY
| | - Francesca Alù
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Via di Val Cannuta, 247, Roma, Lazio, 00166, ITALY
| | - Alessandro Orticoni
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Via di Val Cannuta, 247, Roma, Lazio, 00166, ITALY
| | - Elda Judica
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico SpA, Via Giuseppe Dezza, 48, Milano, Lombardia, 20144, ITALY
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Via Pilastroni, 4, Brescia, Lombardia, 25125, ITALY
| | - Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Via di Val Cannuta, 247, Roma, Lazio, 00166, ITALY
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50
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Iliadou P, Paliokas I, Zygouris S, Lazarou E, Votis K, Tzovaras D, Tsolaki M. A Comparison of Traditional and Serious Game-Based Digital Markers of Cognition in Older Adults with Mild Cognitive Impairment and Healthy Controls. J Alzheimers Dis 2021; 79:1747-1759. [PMID: 33459650 PMCID: PMC7990420 DOI: 10.3233/jad-201300] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Background: Electroencephalography (EEG) has been used to assess brain activity while users are playing an immersive serious game. Objective: To assess differences in brain activation as measured with a non-intrusive wearable EEG device, differences in game performance and correlations between EEG power, game performance and global cognition, between cognitively impaired and non-impaired older adults, during the administration of a novel self-administered serious game-based test, the Virtual Supermarket Test (VST). Methods: 43 older adults with subjective cognitive decline (SCD) and 33 older adults with mild cognitive impairment (MCI) were recruited from day centers for cognitive disorders. Global cognition was assessed with the Montreal Cognitive Assessment (MoCA). Brain activity was measured with a non-intrusive wearable EEG device in a resting state condition and while they were administered the VST. Results: During resting state condition, the MCI group showed increased alpha, beta, delta, and theta band power compared to the SCD group. During the administration of the VST, the MCI group showed increased beta and theta band power compared to the SCD group. Regarding game performance, alpha, beta, delta, and theta rhythms were positively correlated with average duration, while delta rhythm was positively correlated with mean errors. MoCA correlated with alpha, beta, delta, and theta rhythms and with average game duration and mean game errors indicating that elevated EEG rhythms in MCI may be associated with an overall cognitive decline. Conclusion: VST performance can be used as a digital biomarker. Cheap commercially available wearable EEG devices can be used for obtaining brain activity biomarkers.
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Affiliation(s)
| | - Ioannis Paliokas
- Centre for Research and Technology Hellas/ Information Technologies Institute, Thessaloniki, Greece
| | - Stelios Zygouris
- School of Medicine, Aristotle University of Thessaloniki, Greece.,Network Aging Research, Heidelberg University, Germany
| | - Eftychia Lazarou
- Greek Association of Alzheimer's Disease and Related Disorders, Thessaloniki, Greece
| | - Konstantinos Votis
- Centre for Research and Technology Hellas/ Information Technologies Institute, Thessaloniki, Greece
| | - Dimitrios Tzovaras
- Centre for Research and Technology Hellas/ Information Technologies Institute, Thessaloniki, Greece
| | - Magdalini Tsolaki
- School of Medicine, Aristotle University of Thessaloniki, Greece.,Greek Association of Alzheimer's Disease and Related Disorders, Thessaloniki, Greece
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