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Cecchetti G, Agosta F, Canu E, Basaia S, Rugarli G, Curti DG, Coraglia F, Cursi M, Spinelli EG, Santangelo R, Caso F, Fanelli GF, Magnani G, Filippi M. Analysis of individual alpha frequency in a large cohort from a tertiary memory center. Eur J Neurol 2024:e16424. [PMID: 39087560 DOI: 10.1111/ene.16424] [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: 02/07/2024] [Revised: 06/19/2024] [Accepted: 07/17/2024] [Indexed: 08/02/2024]
Abstract
BACKGROUND AND PURPOSE Precise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost-effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. METHODS This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting-state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. RESULTS IAF was higher in amyloid-negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A-T-N- from the A+T+N+ and A+T-N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). CONCLUSIONS IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease-modifying treatments.
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Affiliation(s)
- Giordano Cecchetti
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giulia Rugarli
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Davide G Curti
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | | | - Marco Cursi
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Edoardo G Spinelli
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Roberto Santangelo
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesca Caso
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Giuseppe Magnani
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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Esmaelpoor J, Peng T, Jelfs B, Mao D, Shader MJ, McKay CM. Resting-State Functional Connectivity Predicts Cochlear-Implant Speech Outcomes. Ear Hear 2024:00003446-990000000-00313. [PMID: 39012793 DOI: 10.1097/aud.0000000000001564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2024]
Abstract
OBJECTIVES Cochlear implants (CIs) have revolutionized hearing restoration for individuals with severe or profound hearing loss. However, a substantial and unexplained variability persists in CI outcomes, even when considering subject-specific factors such as age and the duration of deafness. In a pioneering study, we use resting-state functional near-infrared spectroscopy to predict speech-understanding outcomes before and after CI implantation. Our hypothesis centers on resting-state functional connectivity (FC) reflecting brain plasticity post-hearing loss and implantation, specifically targeting the average clustering coefficient in resting FC networks to capture variation among CI users. DESIGN Twenty-three CI candidates participated in this study. Resting-state functional near-infrared spectroscopy data were collected preimplantation and at 1 month, 3 months, and 1 year postimplantation. Speech understanding performance was assessed using consonant-nucleus-consonant words in quiet and Bamford-Kowal-Bench sentences in noise 1-year postimplantation. Resting-state FC networks were constructed using regularized partial correlation, and the average clustering coefficient was measured in the signed weighted networks as a predictive measure for implantation outcomes. RESULTS Our findings demonstrate a significant correlation between the average clustering coefficient in resting-state functional networks and speech understanding outcomes, both pre- and postimplantation. CONCLUSIONS This approach uses an easily deployable resting-state functional brain imaging metric to predict speech-understanding outcomes in implant recipients. The results indicate that the average clustering coefficient, both pre- and postimplantation, correlates with speech understanding outcomes.
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Affiliation(s)
- Jamal Esmaelpoor
- Department of Medical Bionics, University of Melbourne, Melbourne, Australia
- The Bionics Institute of Australia, Melbourne, Australia
| | - Tommy Peng
- Department of Medical Bionics, University of Melbourne, Melbourne, Australia
- The Bionics Institute of Australia, Melbourne, Australia
| | - Beth Jelfs
- Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham, United Kingdom
| | - Darren Mao
- Department of Medical Bionics, University of Melbourne, Melbourne, Australia
- The Bionics Institute of Australia, Melbourne, Australia
| | - Maureen J Shader
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Colette M McKay
- Department of Medical Bionics, University of Melbourne, Melbourne, Australia
- The Bionics Institute of Australia, Melbourne, Australia
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Penalver-Andres JA, Buetler KA, Koenig T, Müri RM, Marchal-Crespo L. Resting-State Functional Networks Correlate with Motor Performance in a Complex Visuomotor Task: An EEG Microstate Pilot Study on Healthy Individuals. Brain Topogr 2024; 37:590-607. [PMID: 36566448 PMCID: PMC11199229 DOI: 10.1007/s10548-022-00934-9] [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: 07/10/2022] [Accepted: 12/05/2022] [Indexed: 12/26/2022]
Abstract
Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners' functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks-the Attention Network (AN) and the Default Mode Network (DMN)-affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN-linked to internally diverted attention and mind-wandering-would be detrimental for posterior motor performance. We extracted seven widely accepted microstates-representing participants mind states at rest-out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN-imaged using EEG microstates-as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.
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Affiliation(s)
- Joaquin A Penalver-Andres
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
- Psychosomatic Medicine, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
| | - Karin A Buetler
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - René M Müri
- Perception and Eye Movement Laboratory, Department of Biomedical Research (DBMR) and Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Gerontechnology and Rehabilitation Group, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Laura Marchal-Crespo
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
- Department of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands
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Li J, Li X, Chen F, Li W, Chen J, Zhang B. Studying the Alzheimer's disease continuum using EEG and fMRI in single-modality and multi-modality settings. Rev Neurosci 2024; 35:373-386. [PMID: 38157429 DOI: 10.1515/revneuro-2023-0098] [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: 08/28/2023] [Accepted: 12/01/2023] [Indexed: 01/03/2024]
Abstract
Alzheimer's disease (AD) is a biological, clinical continuum that covers the preclinical, prodromal, and clinical phases of the disease. Early diagnosis and identification of the stages of Alzheimer's disease (AD) are crucial in clinical practice. Ideally, biomarkers should reflect the underlying process (pathological or otherwise), be reproducible and non-invasive, and allow repeated measurements over time. However, the currently known biomarkers for AD are not suitable for differentiating the stages and predicting the trajectory of disease progression. Some objective parameters extracted using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are widely applied to diagnose the stages of the AD continuum. While electroencephalography (EEG) has a high temporal resolution, fMRI has a high spatial resolution. Combined EEG and fMRI (EEG-fMRI) can overcome single-modality drawbacks and obtain multi-dimensional information simultaneously, and it can help explore the hemodynamic changes associated with the neural oscillations that occur during information processing. This technique has been used in the cognitive field in recent years. This review focuses on the different techniques available for studying the AD continuum, including EEG and fMRI in single-modality and multi-modality settings, and the possible future directions of AD diagnosis using EEG-fMRI.
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Affiliation(s)
- Jing Li
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, 210008, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, 210008, China
- Medical Imaging Center, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210008, China
| | - Xin Li
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, 210008, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, 210008, China
- Medical Imaging Center, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210008, China
| | - Futao Chen
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, 210008, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, 210008, China
- Medical Imaging Center, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210008, China
| | - Weiping Li
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, 210008, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, 210008, China
- Medical Imaging Center, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210008, China
| | - Jiu Chen
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, 210008, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, 210008, China
- Medical Imaging Center, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210008, China
| | - Bing Zhang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, 210008, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, 210008, China
- Medical Imaging Center, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210008, China
- Jiangsu Key Laboratory of Molecular Medicine, Nanjing, Jiangsu, 210008, China
- Institute of Brain Science, Nanjing University, Nanjing, Jiangsu, 210008, China
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Vecchio F, Miraglia F, Pappalettera C, Nucci L, Cacciotti A, Rossini PM. Small World derived index to distinguish Alzheimer's type dementia and healthy subjects. Age Ageing 2024; 53:afae121. [PMID: 38935531 PMCID: PMC11210397 DOI: 10.1093/ageing/afae121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 04/26/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND This article introduces a novel index aimed at uncovering specific brain connectivity patterns associated with Alzheimer's disease (AD), defined according to neuropsychological patterns. METHODS Electroencephalographic (EEG) recordings of 370 people, including 170 healthy subjects and 200 mild-AD patients, were acquired in different clinical centres using different acquisition equipment by harmonising acquisition settings. The study employed a new derived Small World (SW) index, SWcomb, that serves as a comprehensive metric designed to integrate the seven SW parameters, computed across the typical EEG frequency bands. The objective is to create a unified index that effectively distinguishes individuals with a neuropsychological pattern compatible with AD from healthy ones. RESULTS Results showed that the healthy group exhibited the lowest SWcomb values, while the AD group displayed the highest SWcomb ones. CONCLUSIONS These findings suggest that SWcomb index represents an easy-to-perform, low-cost, widely available and non-invasive biomarker for distinguishing between healthy individuals and AD patients.
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Affiliation(s)
- Fabrizio Vecchio
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy
| | - Francesca Miraglia
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy
| | - Chiara Pappalettera
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy
| | - Lorenzo Nucci
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, 00166 Rome, Italy
| | - Alessia Cacciotti
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy
| | - Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, 00166 Rome, Italy
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Babiloni C, Jakhar D, Tucci F, Del Percio C, Lopez S, Soricelli A, Salvatore M, Ferri R, Catania V, Massa F, Arnaldi D, Famà F, Güntekin B, Yener G, Stocchi F, Vacca L, Marizzoni M, Giubilei F, Yıldırım E, Hanoğlu L, Hünerli D, Frisoni GB, Noce G. Resting state electroencephalographic alpha rhythms are sensitive to Alzheimer's disease mild cognitive impairment progression at a 6-month follow-up. Neurobiol Aging 2024; 137:19-37. [PMID: 38402780 DOI: 10.1016/j.neurobiolaging.2024.01.013] [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: 10/07/2022] [Revised: 10/31/2023] [Accepted: 01/26/2024] [Indexed: 02/27/2024]
Abstract
Are posterior resting-state electroencephalographic (rsEEG) alpha rhythms sensitive to the Alzheimer's disease mild cognitive impairment (ADMCI) progression at a 6-month follow-up? Clinical, cerebrospinal, neuroimaging, and rsEEG datasets in 52 ADMCI and 60 Healthy old seniors (equivalent groups for demographic features) were available from an international archive (www.pdwaves.eu). The ADMCI patients were arbitrarily divided into two groups: REACTIVE and UNREACTIVE, based on the reduction (reactivity) in the posterior rsEEG alpha eLORETA source activities from the eyes-closed to eyes-open condition at ≥ -10% and -10%, respectively. 75% of the ADMCI patients were REACTIVE. Compared to the UNREACTIVE group, the REACTIVE group showed (1) less abnormal posterior rsEEG source activity during the eyes-closed condition and (2) a decrease in that activity at the 6-month follow-up. These effects could not be explained by neuroimaging and neuropsychological biomarkers of AD. Such a biomarker might reflect abnormalities in cortical arousal in quiet wakefulness to be used for clinical studies in ADMCI patients using 6-month follow-ups.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino, Cassino (FR), Italy.
| | - Dharmendra Jakhar
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy; Department of Medical, Movement and Wellbeing Sciences, University of Naples Parthenope, Naples, Italy
| | | | | | | | - Federico Massa
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy; Clinica neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Dario Arnaldi
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy; Neurofisiopatologia, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Francesco Famà
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy; Neurofisiopatologia, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey; Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Izmir University of Economics, Faculty of Medicine, Izmir, Turkey
| | | | | | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Ebru Yıldırım
- Program of Electroneurophysiology, Vocational School, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Duygu Hünerli
- Health Sciences Institute, Department of Neurosciences, Dokuz Eylül University, 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 University of Geneva, Geneva, Switzerland
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7
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Lopez S, Hampel H, Chiesa PA, Del Percio C, Noce G, Lizio R, Teipel SJ, Dyrba M, González-Escamilla G, Bakardjian H, Cavedo E, Lista S, Vergallo A, Lemercier P, Spinelli G, Grothe MJ, Potier MC, Stocchi F, Ferri R, Habert MO, Dubois B, Babiloni C. The association between posterior resting-state EEG alpha rhythms and functional MRI connectivity in older adults with subjective memory complaint. Neurobiol Aging 2024; 137:62-77. [PMID: 38431999 DOI: 10.1016/j.neurobiolaging.2024.02.008] [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: 05/25/2020] [Revised: 02/09/2024] [Accepted: 02/19/2024] [Indexed: 03/05/2024]
Abstract
Resting-state eyes-closed electroencephalographic (rsEEG) alpha rhythms are dominant in posterior cortical areas in healthy adults and are abnormal in subjective memory complaint (SMC) persons with Alzheimer's disease amyloidosis. This exploratory study in 161 SMC participants tested the relationships between those rhythms and seed-based resting-state functional magnetic resonance imaging (rs-fMRI) connectivity between thalamus and visual cortical networks as a function of brain amyloid burden, revealed by positron emission tomography and cognitive reserve, measured by educational attainment. The SMC participants were divided into 4 groups according to 2 factors: Education (Edu+ and Edu-) and Amyloid burden (Amy+ and Amy-). There was a statistical interaction (p < 0.05) between the two factors, and the subgroup analysis using estimated marginal means showed a positive association between the mentioned rs-fMRI connectivity and the posterior rsEEG alpha rhythms in the SMC participants with low brain amyloidosis and high CR (Amy-/Edu+). These results suggest that in SMC persons, early Alzheimer's disease amyloidosis may contrast the beneficial effects of cognitive reserve on neurophysiological oscillatory mechanisms at alpha frequencies and connectivity between the thalamus and visual cortical networks.
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Affiliation(s)
- Susanna Lopez
- Department of Physiology and Pharmacology "Erspamer", Sapienza University of Rome, Rome, Italy
| | - Harald Hampel
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris F-75013, France
| | - Patrizia Andrea Chiesa
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris F-75013, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris F-75013, France; Institut du Cerveau et de la Moelle épinière, ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Paris F- 75013, France
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Erspamer", Sapienza University of Rome, Rome, Italy
| | - Stefan J Teipel
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany; German Center for Neurodegenerative Diseases (DZNE), Greifswald, Rostock, Germany
| | - Martin Dyrba
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany
| | - Gabriel González-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Hovagim Bakardjian
- Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris F-75013, France; Centre pour l'Acquisition et le Traitement des Images, (CATI platform), France; Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne University, LIB, Paris F-75006, France
| | - Enrica Cavedo
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris F-75013, France
| | - Simone Lista
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris F-75013, France
| | - Andrea Vergallo
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris F-75013, France
| | - Pablo Lemercier
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris F-75013, France; Centre pour l'Acquisition et le Traitement des Images, (CATI platform), France; Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne University, LIB, Paris F-75006, France
| | - Giuseppe Spinelli
- Centre pour l'Acquisition et le Traitement des Images, (CATI platform), France; Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne University, LIB, Paris F-75006, France
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE), Greifswald, Rostock, Germany
| | - Marie-Claude Potier
- Institut du Cerveau et de la Moelle épinière, ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Paris F- 75013, France
| | - Fabrizio Stocchi
- IRCCS San Raffaele, Rome, Italy; Telematic University, San Raffaele, Rome, Italy
| | | | - Marie-Odile Habert
- Centre pour l'Acquisition et le Traitement des Images, (CATI platform), France; Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne University, LIB, Paris F-75006, France; AP-HP, Pitié-Salpêtrière Hospital, Department of Nuclear Medicine, Paris F-75013, France
| | - Bruno Dubois
- Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris F-75013, France; Institut du Cerveau et de la Moelle épinière, ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Paris F- 75013, France
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "Erspamer", Sapienza University of Rome, Rome, Italy; San Raffaele Cassino, Cassino, FR, Italy.
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Fernández A, Cuesta P, Marcos A, Montenegro-Peña M, Yus M, Rodríguez-Rojo IC, Bruña R, Maestú F, López ME. Sex differences in the progression to Alzheimer's disease: a combination of functional and structural markers. GeroScience 2024; 46:2619-2640. [PMID: 38105400 PMCID: PMC10828170 DOI: 10.1007/s11357-023-01020-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 11/14/2023] [Indexed: 12/19/2023] Open
Abstract
Mild cognitive impairment (MCI) has been frequently interpreted as a transitional phase between healthy cognitive aging and dementia, particularly of the Alzheimer's disease (AD) type. Of note, few studies explored that transition from a multifactorial perspective, taking into consideration the effect of basic factors such as biological sex. In the present study 96 subjects with MCI (37 males and 59 females) were followed-up and divided into two subgroups according to their clinical outcome: "progressive" MCI (pMCI = 41), if they fulfilled the diagnostic criteria for AD at the end of follow-up; and "stable" MCI (sMCI = 55), if they remained with the initial diagnosis. Different markers were combined to characterize sex differences between groups, including magnetoencephalography recordings, cognitive performance, and brain volumes derived from magnetic resonance imaging. Results indicated that the pMCI group exhibited higher low-frequency activity, lower scores in neuropsychological tests and reduced brain volumes than the sMCI group, being these measures significantly correlated. When sex was considered, results revealed that this pattern was mainly due to the influence of the females' sample. Overall, females exhibited lower cognitive scores and reduced brain volumes. More interestingly, females in the pMCI group showed an increased theta activity that correlated with a more abrupt reduction of cognitive and volumetric scores as compared with females in the sMCI group and with males in the pMCI group. These findings suggest that females' brains might be more vulnerable to the effects of AD pathology, since regardless of age, they showed signs of more pronounced deterioration than males.
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Affiliation(s)
- Alberto Fernández
- Department of Legal Medicine, Psychiatry and Pathology, Universidad Complutense de Madrid, Madrid, Spain
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
| | - Pablo Cuesta
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Radiology, Rehabilitation and Physiotherapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Alberto Marcos
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Neurology Department, Hospital Clínico San Carlos, Madrid, Spain
| | - Mercedes Montenegro-Peña
- Centre for the Prevention of Cognitive Impairment, Madrid Salud, Madrid City Council, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Miguel Yus
- Radiology Department, Hospital Clínico San Carlos, Madrid, Spain
| | - Inmaculada Concepción Rodríguez-Rojo
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Nursing and Psysiotherapy, Universidad de Alcalá, Madrid, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Radiology, Rehabilitation and Physiotherapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - María Eugenia López
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain.
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain.
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.
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9
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Dzianok P, Kublik E. PEARL-Neuro Database: EEG, fMRI, health and lifestyle data of middle-aged people at risk of dementia. Sci Data 2024; 11:276. [PMID: 38453963 PMCID: PMC10920678 DOI: 10.1038/s41597-024-03106-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 02/29/2024] [Indexed: 03/09/2024] Open
Abstract
Interdisciplinary approaches are needed to understand the relationship between genetic factors and brain structure and function. Here we describe a database that includes genetic data on apolipoprotein E (APOE) and phosphatidylinositol binding clathrin assembly protein (PICALM) genes, both of which are known to increase the risk of late-onset Alzheimer's disease, paired with psychometric (memory, intelligence, mood, personality, stress coping strategies), basic demographic and health data on a cohort of 192 healthy middle-aged (50-63) individuals. Part of the database (~79 participants) also includes blood tests (blood counts, lipid profile, HSV virus) and functional neuroimaging data (EEG/fMRI) recorded with a resting-state protocol (eyes open and eyes closed) and two cognitive tasks (multi-source interference task, MSIT; and Sternberg's memory task). The data were validated and showed overall good quality. This open-science dataset is well suited not only for research relating to susceptibility to Alzheimer's disease but also for more general questions on brain aging or can be used as part of meta-analytical multi-disciplinary projects.
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Affiliation(s)
- Patrycja Dzianok
- Laboratory of Emotions Neurobiology, Nencki Institute of Experimental Biology PAS, Warsaw, Poland
| | - Ewa Kublik
- Laboratory of Emotions Neurobiology, Nencki Institute of Experimental Biology PAS, Warsaw, Poland.
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Manippa V, Palmisano A, Nitsche MA, Filardi M, Vilella D, Logroscino G, Rivolta D. Cognitive and Neuropathophysiological Outcomes of Gamma-tACS in Dementia: A Systematic Review. Neuropsychol Rev 2024; 34:338-361. [PMID: 36877327 PMCID: PMC10920470 DOI: 10.1007/s11065-023-09589-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 01/23/2023] [Indexed: 03/07/2023]
Abstract
Despite the numerous pharmacological interventions targeting dementia, no disease-modifying therapy is available, and the prognosis remains unfavorable. A promising perspective involves tackling high-frequency gamma-band (> 30 Hz) oscillations involved in hippocampal-mediated memory processes, which are impaired from the early stages of typical Alzheimer's Disease (AD). Particularly, the positive effects of gamma-band entrainment on mouse models of AD have prompted researchers to translate such findings into humans using transcranial alternating current stimulation (tACS), a methodology that allows the entrainment of endogenous cortical oscillations in a frequency-specific manner. This systematic review examines the state-of-the-art on the use of gamma-tACS in Mild Cognitive Impairment (MCI) and dementia patients to shed light on its feasibility, therapeutic impact, and clinical effectiveness. A systematic search from two databases yielded 499 records resulting in 10 included studies and a total of 273 patients. The results were arranged in single-session and multi-session protocols. Most of the studies demonstrated cognitive improvement following gamma-tACS, and some studies showed promising effects of gamma-tACS on neuropathological markers, suggesting the feasibility of gamma-tACS in these patients anyhow far from the strong evidence available for mouse models. Nonetheless, the small number of studies and their wide variability in terms of aims, parameters, and measures, make it difficult to draw firm conclusions. We discuss results and methodological limitations of the studies, proposing possible solutions and future avenues to improve research on the effects of gamma-tACS on dementia.
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Affiliation(s)
- Valerio Manippa
- Department of Education, Psychology and Communication, University of Bari "Aldo Moro", Bari, Italy.
| | - Annalisa Palmisano
- Department of Education, Psychology and Communication, University of Bari "Aldo Moro", Bari, Italy
| | - Michael A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
- Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Marco Filardi
- Center for Neurodegenerative Diseases and the Aging Brain, University of Bari "Aldo Moro" at Pia Fondazione "Cardinale G. Panico", Tricase, Lecce, Italy
- Department of Basic Medicine, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Davide Vilella
- Center for Neurodegenerative Diseases and the Aging Brain, University of Bari "Aldo Moro" at Pia Fondazione "Cardinale G. Panico", Tricase, Lecce, Italy
| | - Giancarlo Logroscino
- Center for Neurodegenerative Diseases and the Aging Brain, University of Bari "Aldo Moro" at Pia Fondazione "Cardinale G. Panico", Tricase, Lecce, Italy
- Department of Basic Medicine, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Davide Rivolta
- Department of Education, Psychology and Communication, University of Bari "Aldo Moro", Bari, Italy
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Cecchetti G, Basaia S, Canu E, Cividini C, Cursi M, Caso F, Santangelo R, Fanelli GF, Magnani G, Agosta F, Filippi M. EEG Correlates in the 3 Variants of Primary Progressive Aphasia. Neurology 2024; 102:e207993. [PMID: 38165298 DOI: 10.1212/wnl.0000000000207993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES The 3 clinical presentations of primary progressive aphasia (PPA) reflect heterogenous neuropathology, which is difficult to be recognized in vivo. Resting-state (RS) EEG is promising for the investigation of brain electrical substrates in neurodegenerative conditions. In this study, we aim to explore EEG cortical sources in the characterization of the 3 variants of PPA. METHODS This is a cross-sectional, single-center, memory center-based cohort study. Patients with PPA and healthy controls were consecutively recruited at the Neurology Unit, IRCCS San Raffaele Scientific Institute (Milan, Italy). Each participant underwent an RS 19-channel EEG. Using standardized low-resolution brain electromagnetic tomography, EEG current source densities were estimated at voxel level and compared among study groups. Using an RS functional MRI-driven model of source reconstruction, linear lagged connectivity (LLC) values within language and extra-language brain networks were obtained and analyzed among groups. RESULTS Eighteen patients with logopenic PPA variant (lvPPA; mean age = 72.7 ± 6.6; % female = 52.4), 21 patients with nonfluent/agrammatic PPA variant (nfvPPA; mean age = 71.7 ± 8.1; % female = 66.6), and 9 patients with semantic PPA variant (svPPA; mean age = 65.0 ± 6.9; % female = 44.4) were enrolled in the study, together with 21 matched healthy controls (mean age = 69.2 ± 6.5; % female = 57.1). Patients with lvPPA showed a higher delta density than healthy controls (p < 0.01) and patients with nfvPPA (p < 0.05) and svPPA (p < 0.05). Patients with lvPPA also displayed a greater theta density over the left posterior hemisphere (p < 0.01) and lower alpha2 values (p < 0.05) over the left frontotemporal regions than controls. Patients with nfvPPA showed a diffuse greater theta density than controls (p < 0.05). LLC was altered in all patients relative to controls (p < 0.05); the alteration was greater at slow frequency bands and within language networks than extra-language networks. Patients with lvPPA also showed greater LLC values at theta band than patients with nfvPPA (p < 0.05). DISCUSSION EEG findings in patients with PPA suggest that lvPPA-related pathology is associated with a characteristic disruption of the cortical electrical activity, which might help in the differential diagnosis from svPPA and nfvPPA. EEG connectivity was disrupted in all PPA variants, with distinct findings in disease-specific PPA groups. CLASSIFICATION OF EVIDENCE This study provides Class IV evidence that EEG analysis can distinguish PPA due to probable Alzheimer disease from PPA due to probable FTD from normal aging.
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Affiliation(s)
- Giordano Cecchetti
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Canu
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Camilla Cividini
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Cursi
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesca Caso
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberto Santangelo
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giovanna F Fanelli
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giuseppe Magnani
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- From the Neurology Unit (G.C., F.C., R.S., G.M., F.A., M.F.), Neurophysiology Service (G.C., M.C., R.S., G.F.F., M.F.), and Neuroimaging Research Unit (G.C., S.B., E.C., C.C., F.A., M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (G.C., F.A., M.F.); and Neurorehabilitation Unit (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
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Deng J, Sun B, Kavcic V, Liu M, Giordani B, Li T. Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG. Alzheimers Dement 2024; 20:145-158. [PMID: 37496373 PMCID: PMC10811294 DOI: 10.1002/alz.13411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/28/2023]
Abstract
BACKGROUND Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency. METHODS Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score. RESULTS The leave-one-out cross-validation accuracy is 91.97% and 3-fold accuracy is 91.17%. The 9 to 18 months' progression trend prediction accuracy over an availability-limited subset sample is 84.61%. CONCLUSION The EEG-based soft discrimination model demonstrates high sensitivity and reliability for MCI detection and shows promising capability in proactive prediction of people at risk of MCI before clinical symptoms may occur.
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Affiliation(s)
- Jinxian Deng
- Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingMichiganUSA
| | - Boxin Sun
- Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingMichiganUSA
| | - Voyko Kavcic
- Institute of GerontologyWayne State UniversityDetroitMichiganUSA
- International Institute of Applied GerontologyLjubljanaSlovenia
| | - Mingyan Liu
- Department of Electrical Engineering and Computer ScienceUniversity of MichiganAnn ArborMichiganUSA
| | - Bruno Giordani
- Departments of PsychiatryNeurologyPsychology and School of NursingUniversity of MichiganAnn ArborMichiganUSA
- Michigan Alzheimer's Disease Research CenterAnn ArborMichiganUSA
| | - Tongtong Li
- Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingMichiganUSA
- Michigan Alzheimer's Disease Research CenterAnn ArborMichiganUSA
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Buzi G, Fornari C, Perinelli A, Mazza V. Functional connectivity changes in mild cognitive impairment: A meta-analysis of M/EEG studies. Clin Neurophysiol 2023; 156:183-195. [PMID: 37967512 DOI: 10.1016/j.clinph.2023.10.011] [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: 04/19/2023] [Revised: 08/31/2023] [Accepted: 10/22/2023] [Indexed: 11/17/2023]
Abstract
OBJECTIVE Early synchrony alterations have been observed through electrophysiological techniques in Mild Cognitive Impairment (MCI), which is considered the intermediate phase between healthy aging (HC) and Alzheimer's disease (AD). However, the documented direction (hyper/hypo-synchronization), regions and frequency bands affected are inconsistent. This meta-analysis intended to elucidate existing evidence linked to potential neurophysiological biomarkers of AD. METHODS We conducted a random-effects meta-analysis that entailed the unbiased inclusion of Non-statistically Significant Unreported Effect Sizes ("MetaNSUE") of electroencephalogram (EEG) and magnetoencephalogram (MEG) studies investigating functional connectivity changes at rest along the healthy-pathological aging continuum, searched through PubMed, Scopus, Web of Science and PsycINFO databases until June 2023. RESULTS Of the 3852 articles extracted, we analyzed 12 papers, and we found an alpha synchrony decrease in MCI compared to HC, specifically between temporal-parietal (d = -0.26) and frontal-parietal areas (d = -0.25). CONCLUSIONS Alterations of alpha synchrony are present even at MCI stage. SIGNIFICANCE Synchrony measures may be promising for the detection of the first hallmarks of connectivity alterations, even at the prodromal stages of the AD, before clinical symptoms occur.
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Affiliation(s)
- Giulia Buzi
- U1077 INSERM-EPHE-UNICAEN, Caen 14000, France
| | - Chiara Fornari
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy.
| | - Alessio Perinelli
- Department of Physics, University of Trento, Trento, Italy; INFN-TIFPA, Trento, Italy
| | - Veronica Mazza
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy.
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14
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Setogawa S, Kanda R, Tada S, Hikima T, Saitoh Y, Ishikawa M, Nakada S, Seki F, Hikishima K, Matsumoto H, Mizuseki K, Fukayama O, Osanai M, Sekiguchi H, Ohkawa N. A novel micro-ECoG recording method for recording multisensory neural activity from the parietal to temporal cortices in mice. Mol Brain 2023; 16:38. [PMID: 37138338 PMCID: PMC10157930 DOI: 10.1186/s13041-023-01019-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 03/09/2023] [Indexed: 05/05/2023] Open
Abstract
Characterization of inter-regional interactions in brain is essential for understanding the mechanism relevant to normal brain function and neurological disease. The recently developed flexible micro (μ)-electrocorticography (μECoG) device is one prominent method used to examine large-scale cortical activity across multiple regions. The sheet-shaped μECoG electrodes arrays can be placed on a relatively wide area of cortical surface beneath the skull by inserting the device into the space between skull and brain. Although rats and mice are useful tools for neuroscience, current μECoG recording methods in these animals are limited to the parietal region of cerebral cortex. Recording cortical activity from the temporal region of cortex in mice has proven difficult because of surgical barriers created by the skull and surrounding temporalis muscle anatomy. Here, we developed a sheet-shaped 64-channel μECoG device that allows access to the mouse temporal cortex, and we determined the factor determining the appropriate bending stiffness for the μECoG electrode array. We also established a surgical technique to implant the electrode arrays into the epidural space over a wide area of cerebral cortex covering from the barrel field to olfactory (piriform) cortex, which is the deepest region of the cerebral cortex. Using histology and computed tomography (CT) images, we confirmed that the tip of the μECoG device reached to the most ventral part of cerebral cortex without causing noticeable damage to the brain surface. Moreover, the device simultaneously recorded somatosensory and odor stimulus-evoked neural activity from dorsal and ventral parts of cerebral cortex in awake and anesthetized mice. These data indicate that our μECoG device and surgical techniques enable the recording of large-scale cortical activity from the parietal to temporal cortex in mice, including somatosensory and olfactory cortices. This system will provide more opportunities for the investigation of physiological functions from wider areas of the mouse cerebral cortex than those currently available with existing ECoG techniques.
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Affiliation(s)
- Susumu Setogawa
- Division for Memory and Cognitive Function, Research Center for Advanced Medical Science, Comprehensive Research Facilities for Advanced Medical Science, Dokkyo Medical University, Tochigi, 321-0293, Japan
- Department of Physiology, Osaka Metropolitan University Graduate School of Medicine, Osaka, 545-8585, Japan
| | - Ryota Kanda
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi, 441-8580, Japan
| | - Shuto Tada
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi, 441-8580, Japan
| | - Takuya Hikima
- Division for Memory and Cognitive Function, Research Center for Advanced Medical Science, Comprehensive Research Facilities for Advanced Medical Science, Dokkyo Medical University, Tochigi, 321-0293, Japan
| | - Yoshito Saitoh
- Division for Memory and Cognitive Function, Research Center for Advanced Medical Science, Comprehensive Research Facilities for Advanced Medical Science, Dokkyo Medical University, Tochigi, 321-0293, Japan
| | - Mikiko Ishikawa
- Division for Memory and Cognitive Function, Research Center for Advanced Medical Science, Comprehensive Research Facilities for Advanced Medical Science, Dokkyo Medical University, Tochigi, 321-0293, Japan
| | - Satoshi Nakada
- Japanese Center for Research on Women in Sport, Graduate School of Health and Sports Science, Juntendo University, Chiba, 270-1695, Japan
| | - Fumiko Seki
- Live Animal Imaging Center, Central Institutes for Experimental Animals (CIEA), Kanagawa, 210-0821, Japan
| | - Keigo Hikishima
- Medical Devices Research Group, Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, 305-8564, Japan
| | - Hideyuki Matsumoto
- Department of Physiology, Osaka Metropolitan University Graduate School of Medicine, Osaka, 545-8585, Japan
| | - Kenji Mizuseki
- Department of Physiology, Osaka Metropolitan University Graduate School of Medicine, Osaka, 545-8585, Japan
| | - Osamu Fukayama
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, 565-0871, Japan
| | - Makoto Osanai
- Laboratory for Physiological Functional Imaging, Department of Medical Physics and Engineering, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, 565-0871, Japan
| | - Hiroto Sekiguchi
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi, 441-8580, Japan.
- Japan Science and Technology, Precursory Research for Embryonic Science and Technology (PRESTO), Kawaguchi, Saitama, 332-0012, Japan.
| | - Noriaki Ohkawa
- Division for Memory and Cognitive Function, Research Center for Advanced Medical Science, Comprehensive Research Facilities for Advanced Medical Science, Dokkyo Medical University, Tochigi, 321-0293, Japan.
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Chino-Vilca B, Concepción Rodríguez-Rojo I, Torres-Simón L, Cuesta P, Carnes Vendrell A, Piñol-Ripoll G, Huerto R, Tahan N, Maestú F. Sex specific EEG signatures associated with cerebrospinal fluid biomarkers in mild cognitive impairment. Clin Neurophysiol 2022; 142:190-198. [DOI: 10.1016/j.clinph.2022.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 06/07/2022] [Accepted: 08/06/2022] [Indexed: 11/25/2022]
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Jiang Y, Jessee W, Hoyng S, Borhani S, Liu Z, Zhao X, Price LK, High W, Suhl J, Cerel-Suhl S. Sharpening Working Memory With Real-Time Electrophysiological Brain Signals: Which Neurofeedback Paradigms Work? Front Aging Neurosci 2022; 14:780817. [PMID: 35418848 PMCID: PMC8995767 DOI: 10.3389/fnagi.2022.780817] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 02/08/2022] [Indexed: 09/19/2023] Open
Abstract
Growing evidence supports the idea that the ultimate biofeedback is to reward sensory pleasure (e.g., enhanced visual clarity) in real-time to neural circuits that are associated with a desired performance, such as excellent memory retrieval. Neurofeedback is biofeedback that uses real-time sensory reward to brain activity associated with a certain performance (e.g., accurate and fast recall). Working memory is a key component of human intelligence. The challenges are in our current limited understanding of neurocognitive dysfunctions as well as in technical difficulties for closed-loop feedback in true real-time. Here we review recent advancements of real time neurofeedback to improve memory training in healthy young and older adults. With new advancements in neuromarkers of specific neurophysiological functions, neurofeedback training should be better targeted beyond a single frequency approach to include frequency interactions and event-related potentials. Our review confirms the positive trend that neurofeedback training mostly works to improve memory and cognition to some extent in most studies. Yet, the training typically takes multiple weeks with 2-3 sessions per week. We review various neurofeedback reward strategies and outcome measures. A well-known issue in such training is that some people simply do not respond to neurofeedback. Thus, we also review the literature of individual differences in psychological factors e.g., placebo effects and so-called "BCI illiteracy" (Brain Computer Interface illiteracy). We recommend the use of Neural modulation sensitivity or BCI insensitivity in the neurofeedback literature. Future directions include much needed research in mild cognitive impairment, in non-Alzheimer's dementia populations, and neurofeedback using EEG features during resting and sleep for memory enhancement and as sensitive outcome measures.
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Affiliation(s)
- Yang Jiang
- Lexington Veteran Affairs Medical Center, Lexington, KY, United States
- College of Medicine, University of Kentucky, Lexington, KY, United States
| | - William Jessee
- College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Stevie Hoyng
- College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Soheil Borhani
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States
| | - Ziming Liu
- 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
| | - Lacey K. Price
- Lexington Veteran Affairs Medical Center, Lexington, KY, United States
| | - Walter High
- New Mexico Veteran Affairs Medical Center, Albuquerque, NM, United States
| | - Jeremiah Suhl
- Lexington Veteran Affairs Medical Center, Lexington, KY, United States
| | - Sylvia Cerel-Suhl
- Lexington Veteran Affairs Medical Center, Lexington, KY, United States
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Brain Connectivity and Graph Theory Analysis in Alzheimer’s and Parkinson’s Disease: The Contribution of Electrophysiological Techniques. Brain Sci 2022; 12:brainsci12030402. [PMID: 35326358 PMCID: PMC8946843 DOI: 10.3390/brainsci12030402] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/08/2022] [Accepted: 03/16/2022] [Indexed: 12/31/2022] Open
Abstract
In recent years, applications of the network science to electrophysiological data have increased as electrophysiological techniques are not only relatively low cost, largely available on the territory and non-invasive, but also potential tools for large population screening. One of the emergent methods for the study of functional connectivity in electrophysiological recordings is graph theory: it allows to describe the brain through a mathematic model, the graph, and provides a simple representation of a complex system. As Alzheimer’s and Parkinson’s disease are associated with synaptic disruptions and changes in the strength of functional connectivity, they can be well described by functional connectivity analysis computed via graph theory. The aim of the present review is to provide an overview of the most recent applications of the graph theory to electrophysiological data in the two by far most frequent neurodegenerative disorders, Alzheimer’s and Parkinson’s diseases.
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Torabinikjeh M, Asayesh V, Dehghani M, Kouchakzadeh A, Marhamati H, Gharibzadeh S. Correlations of frontal resting-state EEG markers with MMSE scores in patients with Alzheimer’s disease. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2022. [DOI: 10.1186/s41983-022-00465-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
A previous study suggests that resting-state EEG biomarkers measured at prefrontal region (Fp1, and Fp2) are moderately correlated with Mini-Mental State Examination (MMSE) scores of elderly people with Alzheimer’s disease. In this study, our objective was to investigate whether resting-state EEG biomarkers recorded from frontal region are correlated with each MMSE sub-scores. 20 elderly patients diagnosed as Alzheimer’s disease entered to the study. After completion of MMSE, subjects underwent EEG for 5 min with closed eyes condition. We measured median frequency, theta/alpha power ratio, and relative powers. To examine the relationship between these features and MMSE sub-scores first, Pearson correlation coefficients were computed for each feature and MMSE sub-scores. Then, p values were computed for each correlation. Finally, a Bonferroni correction was done.
Results
Nine correlations have been found for markers recorded from F3, F7, and Fz. Alpha and beta relative powers were the markers which shows correlations. We found that MMSE overall, attention, and calculation scores are significantly correlated with beta relative powers recorded from F3, and Fz, and alpha relative power from F7. Orientation to time scores were correlated with F3, and Fz beta relative powers. The only correlation found for orientation to place was beta relative power of F3.
Conclusions
Our results indicate that there are correlations between frontal EEG markers and MMSE sub-scores of patients with Alzheimer’s disease. The results show that alpha and beta relative powers are markers correlated with MMSE scores. It seems that if we want to develop predicting models for Alzheimer’s disease, using data recorded from other frontal electrodes, especially what we have introduced should be considered.
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Cognitive, EEG, and MRI features of COVID-19 survivors: a 10-month study. J Neurol 2022; 269:3400-3412. [PMID: 35249144 PMCID: PMC8898558 DOI: 10.1007/s00415-022-11047-5] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 01/21/2023]
Abstract
Background and objectives To explore cognitive, EEG, and MRI features in COVID-19 survivors up to 10 months after hospital discharge. Methods Adult patients with a recent diagnosis of COVID-19 and reporting subsequent cognitive complaints underwent neuropsychological assessment and 19-channel-EEG within 2 months (baseline, N = 49) and 10 months (follow-up, N = 33) after hospital discharge. A brain MRI was obtained for 36 patients at baseline. Matched healthy controls were included. Using eLORETA, EEG regional current densities and linear lagged connectivity values were estimated. Total brain and white matter hyperintensities (WMH) volumes were measured. Clinical and instrumental data were evaluated between patients and controls at baseline, and within patient whole group and with/without dysgeusia/hyposmia subgroups over time. Correlations among findings at each timepoint were computed. Results At baseline, 53% and 28% of patients showed cognitive and psychopathological disturbances, respectively, with executive dysfunctions correlating with acute-phase respiratory distress. Compared to healthy controls, patients also showed higher regional current density and connectivity at delta band, correlating with executive performances, and greater WMH load, correlating with verbal memory deficits. A reduction of cognitive impairment and delta band EEG connectivity were observed over time, while psychopathological symptoms persisted. Patients with acute dysgeusia/hyposmia showed lower improvement at memory tests than those without. Lower EEG delta band at baseline predicted worse cognitive functioning at follow-up. Discussion COVID-19 patients showed interrelated cognitive, EEG, and MRI abnormalities 2 months after hospital discharge. Cognitive and EEG findings improved at 10 months. Dysgeusia and hyposmia during acute COVID-19 were related with increased vulnerability in memory functions over time. Supplementary Information The online version contains supplementary material available at 10.1007/s00415-022-11047-5.
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Kenny A, Wright D, Stanfield AC. EEG as a translational biomarker and outcome measure in fragile X syndrome. Transl Psychiatry 2022; 12:34. [PMID: 35075104 PMCID: PMC8786970 DOI: 10.1038/s41398-022-01796-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 12/01/2021] [Accepted: 01/12/2022] [Indexed: 01/08/2023] Open
Abstract
Targeted treatments for fragile X syndrome (FXS) have frequently failed to show efficacy in clinical testing, despite success at the preclinical stages. This has highlighted the need for more effective translational outcome measures. EEG differences observed in FXS, including exaggerated N1 ERP amplitudes, increased resting gamma power and reduced gamma phase-locking in the sensory cortices, have been suggested as potential biomarkers of the syndrome. These abnormalities are thought to reflect cortical hyper excitability resulting from an excitatory (glutamate) and inhibitory (GABAergic) imbalance in FXS, which has been the target of several pharmaceutical remediation studies. EEG differences observed in humans also show similarities to those seen in laboratory models of FXS, which may allow for greater translational equivalence and better predict clinical success of putative therapeutics. There is some evidence from clinical trials showing that treatment related changes in EEG may be associated with clinical improvements, but these require replication and extension to other medications. Although the use of EEG characteristics as biomarkers is still in the early phases, and further research is needed to establish its utility in clinical trials, the current research is promising and signals the emergence of an effective translational biomarker.
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Affiliation(s)
- Aisling Kenny
- Patrick Wild Centre, Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, EH10 5HF, Edinburgh, UK.
| | - Damien Wright
- grid.4305.20000 0004 1936 7988Patrick Wild Centre, Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, EH10 5HF Edinburgh, UK
| | - Andrew C. Stanfield
- grid.4305.20000 0004 1936 7988Patrick Wild Centre, Division of Psychiatry, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, EH10 5HF Edinburgh, UK
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