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Ji Y, Yang C, Pang X, Yan Y, Wu Y, Geng Z, Hu W, Hu P, Wu X, Wang K. Repetitive transcranial magnetic stimulation in Alzheimer's disease: effects on neural and synaptic rehabilitation. Neural Regen Res 2025; 20:326-342. [PMID: 38819037 PMCID: PMC11317939 DOI: 10.4103/nrr.nrr-d-23-01201] [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: 07/19/2023] [Revised: 10/23/2023] [Accepted: 12/13/2023] [Indexed: 06/01/2024] Open
Abstract
Alzheimer's disease is a neurodegenerative disease resulting from deficits in synaptic transmission and homeostasis. The Alzheimer's disease brain tends to be hyperexcitable and hypersynchronized, thereby causing neurodegeneration and ultimately disrupting the operational abilities in daily life, leaving patients incapacitated. Repetitive transcranial magnetic stimulation is a cost-effective, neuro-modulatory technique used for multiple neurological conditions. Over the past two decades, it has been widely used to predict cognitive decline; identify pathophysiological markers; promote neuroplasticity; and assess brain excitability, plasticity, and connectivity. It has also been applied to patients with dementia, because it can yield facilitatory effects on cognition and promote brain recovery after a neurological insult. However, its therapeutic effectiveness at the molecular and synaptic levels has not been elucidated because of a limited number of studies. This study aimed to characterize the neurobiological changes following repetitive transcranial magnetic stimulation treatment, evaluate its effects on synaptic plasticity, and identify the associated mechanisms. This review essentially focuses on changes in the pathology, amyloidogenesis, and clearance pathways, given that amyloid deposition is a major hypothesis in the pathogenesis of Alzheimer's disease. Apoptotic mechanisms associated with repetitive transcranial magnetic stimulation procedures and different pathways mediating gene transcription, which are closely related to the neural regeneration process, are also highlighted. Finally, we discuss the outcomes of animal studies in which neuroplasticity is modulated and assessed at the structural and functional levels by using repetitive transcranial magnetic stimulation, with the aim to highlight future directions for better clinical translations.
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Affiliation(s)
- Yi Ji
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
| | - Chaoyi Yang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
| | - Xuerui Pang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
| | - Yibing Yan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
| | - Yue Wu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Zhi Geng
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
| | - Wenjie Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, China
| | - Xingqi Wu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, Anhui Province, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, Anhui Province, China
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
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Hall JD, Green JM, Chen YCA, Liu Y, Zhang H, Sundman MH, Chou YH. Exploring the potential of combining transcranial magnetic stimulation and electroencephalography to investigate mild cognitive impairment and Alzheimer's disease: a systematic review. GeroScience 2024; 46:3659-3693. [PMID: 38356029 PMCID: PMC11226590 DOI: 10.1007/s11357-024-01075-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 01/02/2024] [Indexed: 02/16/2024] Open
Abstract
Transcranial magnetic stimulation (TMS) and electroencephalography (EEG) are non-invasive techniques used for neuromodulation and recording brain electrical activity, respectively. The integration of TMS-EEG has emerged as a valuable tool for investigating the complex mechanisms involved in age-related disorders, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). By systematically synthesizing TMS-EEG studies, this review aims to shed light on the neurophysiological mechanisms underlying MCI and AD, while also exploring the practical applications of TMS-EEG in clinical settings. PubMed, ScienceDirect, and PsychInfo were selected as the databases for this review. The 22 eligible studies included a total of 592 individuals with MCI or AD as well as 301 cognitively normal adults. TMS-EEG assessments unveiled specific patterns of corticospinal excitability, plasticity, and brain connectivity that distinguished individuals on the AD spectrum from cognitively normal older adults. Moreover, the TMS-induced EEG features were observed to be correlated with cognitive performance and the presence of AD pathological biomarkers. The comprehensive examination of the existing studies demonstrates that the combination of TMS and EEG has yielded valuable insights into the neurophysiology of MCI and AD. This integration shows great potential for early detection, monitoring disease progression, and anticipating response to treatment. Future research is of paramount importance to delve into the potential utilization of TMS-EEG for treatment optimization in individuals with MCI and AD.
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Affiliation(s)
- J D Hall
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, 1230 N Cherry Ave., Tucson, AZ, USA
| | - Jacob M Green
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, 1230 N Cherry Ave., Tucson, AZ, USA
| | - Yu-Chin A Chen
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, 1230 N Cherry Ave., Tucson, AZ, USA
| | - Yilin Liu
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, 1230 N Cherry Ave., Tucson, AZ, USA
| | - Hangbin Zhang
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, 1230 N Cherry Ave., Tucson, AZ, USA
| | - Mark H Sundman
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, 1230 N Cherry Ave., Tucson, AZ, USA
| | - Ying-Hui Chou
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, 1230 N Cherry Ave., Tucson, AZ, USA.
- Evelyn F McKnight Brain Institute, Arizona Center On Aging, and BIO5 Institute, University of Arizona, Tucson, AZ, USA.
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Pascarella A, Manzo L, Ferlazzo E. Modern neurophysiological techniques indexing normal or abnormal brain aging. Seizure 2024:S1059-1311(24)00194-8. [PMID: 38972778 DOI: 10.1016/j.seizure.2024.07.001] [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: 04/09/2024] [Accepted: 07/01/2024] [Indexed: 07/09/2024] Open
Abstract
Brain aging is associated with a decline in cognitive performance, motor function and sensory perception, even in the absence of neurodegeneration. The underlying pathophysiological mechanisms remain incompletely understood, though alterations in neurogenesis, neuronal senescence and synaptic plasticity are implicated. Recent years have seen advancements in neurophysiological techniques such as electroencephalography (EEG), magnetoencephalography (MEG), event-related potentials (ERP) and transcranial magnetic stimulation (TMS), offering insights into physiological and pathological brain aging. These methods provide real-time information on brain activity, connectivity and network dynamics. Integration of Artificial Intelligence (AI) techniques promise as a tool enhancing the diagnosis and prognosis of age-related cognitive decline. Our review highlights recent advances in these electrophysiological techniques (focusing on EEG, ERP, TMS and TMS-EEG methodologies) and their application in physiological and pathological brain aging. Physiological aging is characterized by changes in EEG spectral power and connectivity, ERP and TMS parameters, indicating alterations in neural activity and network function. Pathological aging, such as in Alzheimer's disease, is associated with further disruptions in EEG rhythms, ERP components and TMS measures, reflecting underlying neurodegenerative processes. Machine learning approaches show promise in classifying cognitive impairment and predicting disease progression. Standardization of neurophysiological methods and integration with other modalities are crucial for a comprehensive understanding of brain aging and neurodegenerative disorders. Advanced network analysis techniques and AI methods hold potential for enhancing diagnostic accuracy and deepening insights into age-related brain changes.
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Affiliation(s)
- Angelo Pascarella
- Department of Medical and Surgical Sciences, Magna Græcia University of Catanzaro, Italy; Regional Epilepsy Centre, Great Metropolitan "Bianchi-Melacrino-Morelli Hospital", Reggio Calabria, Italy.
| | - Lucia Manzo
- Regional Epilepsy Centre, Great Metropolitan "Bianchi-Melacrino-Morelli Hospital", Reggio Calabria, Italy
| | - Edoardo Ferlazzo
- Department of Medical and Surgical Sciences, Magna Græcia University of Catanzaro, Italy; Regional Epilepsy Centre, Great Metropolitan "Bianchi-Melacrino-Morelli Hospital", Reggio Calabria, Italy
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Mimura Y, Tobari Y, Nakajima S, Takano M, Wada M, Honda S, Bun S, Tabuchi H, Ito D, Matsui M, Uchida H, Mimura M, Noda Y. Decreased short-latency afferent inhibition in individuals with mild cognitive impairment: A TMS-EEG study. Prog Neuropsychopharmacol Biol Psychiatry 2024; 132:110967. [PMID: 38354899 DOI: 10.1016/j.pnpbp.2024.110967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 12/03/2023] [Accepted: 02/11/2024] [Indexed: 02/16/2024]
Abstract
TMS combined with EEG (TMS-EEG) is a tool to characterize the neurophysiological dynamics of the cortex. Among the TMS paradigms, short-latency afferent inhibition (SAI) allows the investigation of inhibitory effects mediated by the cholinergic system. The aim of this study was to compare cholinergic function in the DLPFC between individuals with mild cognitive impairment (MCI) and healthy controls (HC) using TMS-EEG with the SAI paradigm. In this study, 30 MCI and 30 HC subjects were included. The SAI paradigm consisted of 80 single pulse TMS and 80 SAI stimulations applied to the left DLPFC. N100 components, global mean field power (GMFP) and total power were calculated. As a result, individuals with MCI showed reduced inhibitory effects on N100 components and GMFP at approximately 100 ms post-stimulation and on β-band activity at 200 ms post-stimulation compared to HC. Individuals with MCI showed reduced SAI, suggesting impaired cholinergic function in the DLPFC compared to the HC group. We conclude that these findings underscore the clinical applicability of the TMS-EEG method as a powerful tool for assessing cholinergic function in individuals with MCI.
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Affiliation(s)
- Yu Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yui Tobari
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan.
| | - Mayuko Takano
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; TEIJIN PHARMA LIMITED, Tokyo 100-8585, Japan
| | - Masataka Wada
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shiori Honda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shogyoku Bun
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Hajime Tabuchi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Daisuke Ito
- Department of Physiology/Memory Center, Keio University School of Medicine, Tokyo, Japan
| | - Mie Matsui
- Laboratory of Clinical Cognitive Neuroscience, Graduate School of Medical Science, Kanazawa University, Ishikawa 920-0934, Japan
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan.
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Ding Z, Wang Y, Niu Z, Ouyang G, Li X. The effect of EEG microstate on the characteristics of TMS-EEG. Comput Biol Med 2024; 173:108332. [PMID: 38555703 DOI: 10.1016/j.compbiomed.2024.108332] [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: 01/28/2024] [Revised: 02/26/2024] [Accepted: 03/17/2024] [Indexed: 04/02/2024]
Abstract
OBJECTIVE Differences in neural states at the time of transcranial magnetic stimulation (TMS) can lead to variations in the effectiveness of TMS stimulation. Strategies that aim to lock neural activity states and improve the precision of stimulation timing in TMS optimization should gradually receive attention. One feasible approach is to utilize microstate locking for TMS stimulation, and understanding the impact of microstates at the time of stimulation on TMS response forms the foundation of this approach. APPROACH TMS-EEG data were extracted from 21 healthy subjects through experiments. Based on the different microstates at the time of stimulation, the trials were classified into four datasets. TMS-evoked potential (TEP), topographical distribution, and natural frequency, were computed for each dataset to explore the differences in TMS-EEG characteristics across different microstates. MAIN RESULTS The N100 component of microstate C group (-2.376 μV) was significantly higher (p = 0.003) than of microstate D group (-1.739 μV), and the P180 component of microstate D group (2.482 μV) was significantly higher (p = 0.024) than of microstate B group (1.766 μV) and slightly higher (p = 0.058) than of microstate C group (1.863 μV) by calculating the ROI. The topographical distribution of TEP components during microstate C and microstate D still retained the template characteristics of the microstate at the time of stimulation, and the natural frequencies did not differ among the four classical microstates. SIGNIFICANCE This study showed the potential for future closed-loop TMS based on microstates and would guiding the development of microstate-based closed-loop TMS techniques.
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Affiliation(s)
- Zhaohuan Ding
- Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, 510640, China
| | - Yong Wang
- Zhuhai UM Science & Technology Research Institute, Zhuhai, 519031, China
| | - Zikang Niu
- Aviation Psychology Research Office, Air Force Medical Center, Beijing, 100142, China
| | - Gaoxiang Ouyang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
| | - Xiaoli Li
- Guangdong Artificial Intelligence and Digital Economy Laboratory (Guangzhou), Guangzhou, 510335, China; School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China.
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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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Monteverdi A, Palesi F, Schirner M, Argentino F, Merante M, Redolfi A, Conca F, Mazzocchi L, Cappa SF, Cotta Ramusino M, Costa A, Pichiecchio A, Farina LM, Jirsa V, Ritter P, Gandini Wheeler-Kingshott CAM, D’Angelo E. Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias. Front Aging Neurosci 2023; 15:1204134. [PMID: 37577354 PMCID: PMC10419271 DOI: 10.3389/fnagi.2023.1204134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023] Open
Abstract
Introduction Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission. Methods We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer's disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks. Results The pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles. Discussion These TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.
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Affiliation(s)
- Anita Monteverdi
- Unit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Michael Schirner
- Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
| | - Francesca Argentino
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Mariateresa Merante
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Alberto Redolfi
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Laura Mazzocchi
- Advanced Imaging and Artificial Intelligence Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Stefano F. Cappa
- IRCCS Mondino Foundation, Pavia, Italy
- University Institute of Advanced Studies (IUSS), Pavia, Italy
| | | | - Alfredo Costa
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Anna Pichiecchio
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Advanced Imaging and Artificial Intelligence Center, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, INSERM, INS, Aix Marseille University, Marseille, France
| | - Petra Ritter
- Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
| | - Claudia A. M. Gandini Wheeler-Kingshott
- Unit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Egidio D’Angelo
- Unit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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Buss SS, Fried PJ, Macone J, Zeng V, Zingg E, Santarnecchi E, Pascual-Leone A, Bartrés-Faz D. Greater cognitive reserve is related to lower cortical excitability in healthy cognitive aging, but not in early clinical Alzheimer's disease. Front Hum Neurosci 2023; 17:1193407. [PMID: 37576473 PMCID: PMC10413110 DOI: 10.3389/fnhum.2023.1193407] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 07/05/2023] [Indexed: 08/15/2023] Open
Abstract
Objective To investigate the relationship between cortico-motor excitability and cognitive reserve (CR) in cognitively unimpaired older adults (CU) and in older adults with mild cognitive impairment or mild dementia due to Alzheimer's disease (AD). Methods Data were collected and analyzed from 15 CU and 24 amyloid-positive AD participants aged 50-90 years. A cognitive reserve questionnaire score (CRQ) assessed education, occupation, leisure activities, physical activities, and social engagement. Cortical excitability was quantified as the average amplitude of motor evoked potentials (MEP amplitude) elicited with single-pulse transcranial magnetic stimulation delivered to primary motor cortex. A linear model compared MEP amplitudes between groups. A linear model tested for an effect of CRQ on MEP amplitude across all participants. Finally, separate linear models tested for an effect of CRQ on MEP amplitude within each group. Exploratory analyses tested for effect modification of demographics, cognitive scores, atrophy measures, and CSF measures within each group using nested regression analysis. Results There was no between-group difference in MEP amplitude after accounting for covariates. The primary model showed a significant interaction term of group*CRQ (R2adj = 0.18, p = 0.013), but no main effect of CRQ. Within the CU group, higher CRQ was significantly associated with lower MEP amplitude (R2adj = 0.45, p = 0.004). There was no association in the AD group. Conclusion Lower cortico-motor excitability is related to greater CRQ in CU, but not in AD. Lower MEP amplitudes may reflect greater neural efficiency in cognitively unimpaired older adults. The lack of association seen in AD participants may reflect disruption of the protective effects of CR. Future work is needed to better understand the neurophysiologic mechanisms leading to the protective effects of CR in older adults with and without neurodegenerative disorders.
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Affiliation(s)
- Stephanie S. Buss
- Division of Cognitive Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Department of Neurology, Harvard Medical School, Boston, MA, United States
| | - Peter J. Fried
- Division of Cognitive Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Department of Neurology, Harvard Medical School, Boston, MA, United States
| | - Joanna Macone
- Division of Cognitive Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Department of Neurology, Harvard Medical School, Boston, MA, United States
| | - Victor Zeng
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Emma Zingg
- Division of Cognitive Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Program of All-inclusive Care for the Elderly (PACE), Cambridge Health Alliance, Cambridge, MA, United States
| | - Emiliano Santarnecchi
- Division of Cognitive Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Department of Neurology, Harvard Medical School, Boston, MA, United States
- Precision Neuromodulation Program, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, MA, United States
- Deanna and Sidney Wolk Center for Memory Health, Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, United States
| | - David Bartrés-Faz
- Division of Cognitive Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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9
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Tăuƫan AM, Casula EP, Pellicciari MC, Borghi I, Maiella M, Bonni S, Minei M, Assogna M, Palmisano A, Smeralda C, Romanella SM, Ionescu B, Koch G, Santarnecchi E. TMS-EEG perturbation biomarkers for Alzheimer's disease patients classification. Sci Rep 2023; 13:7667. [PMID: 37169900 PMCID: PMC10175269 DOI: 10.1038/s41598-022-22978-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 10/21/2022] [Indexed: 05/13/2023] Open
Abstract
The combination of TMS and EEG has the potential to capture relevant features of Alzheimer's disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45-80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients' classification as well as longitudinal disease tracking.
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Affiliation(s)
- Alexandra-Maria Tăuƫan
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- AI Multimedia Lab, Research Center CAMPUS, University Politehnica of Bucharest, 061344, Bucharest, Romania
| | - Elias P Casula
- Santa Lucia Foundation, 00179, Rome, Italy
- Department of Psychology, La Sapienza University, Via dei Marsi 78, 00185, Rome, Italy
| | | | | | | | | | | | | | - Annalisa Palmisano
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Education, Psychology and Communication, University of Bari Aldo Moro, Bari, Italy
| | - Carmelo Smeralda
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery, Neurology and Clinical Neurophysiology Section, University of Siena, Siena, Italy
| | - Sara M Romanella
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery, Neurology and Clinical Neurophysiology Section, University of Siena, Siena, Italy
| | - Bogdan Ionescu
- AI Multimedia Lab, Research Center CAMPUS, University Politehnica of Bucharest, 061344, Bucharest, Romania
| | - Giacomo Koch
- Department of Neuroscience and Rehabilitation, Section of Human Physiology, University of Ferrara, 44121, Ferrara, Italy
- Santa Lucia Foundation, 00179, Rome, Italy
| | - Emiliano Santarnecchi
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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10
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Invitto S, Boscolo-Rizzo P, Fantin F, Bonifati DM, de Filippis C, Emanuelli E, Frezza D, Giopato F, Caggiula M, Schito A, Ciccarese V, Spinato G. Exploratory Study on Chemosensory Event-Related Potentials in Long COVID-19 and Mild Cognitive Impairment: A Common Pathway? Bioengineering (Basel) 2023; 10:bioengineering10030376. [PMID: 36978767 PMCID: PMC10045951 DOI: 10.3390/bioengineering10030376] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/13/2023] [Accepted: 03/17/2023] [Indexed: 03/30/2023] Open
Abstract
People affected by the Long COVID-19 (LC) syndrome often show clinical manifestations that are similar to those observed in patients with mild cognitive impairments (MCI), such as olfactory dysfunction (OD), brain fog, and cognitive and attentional diseases. This study aimed to investigate the chemosensory-evoked related potentials (CSERP) in LC and MCI to understand if there is a common pathway for the similarity of symptoms associated with these disorders. Eighteen LC patients (mean age 53; s.d. = 7), 12 patients diagnosed with MCI (mean age 67; s.d. = 6), and 10 healthy control subjects (mean age 66; s.d. = 5, 7) were recruited for this exploratory study. All of them performed a chemosensory event-related potentials (CSERP) task with the administration of trigeminal stimulations (e.g., the odorants cinnamaldehyde and eucalyptus). Study results highlighted that MCI and LC showed reduced N1 amplitude, particularly in the left frontoparietal network, involved in working memory and attentional deficits, and a reduction of P3 latency in LC. This study lays the foundations for evaluating aspects of LC as a process that could trigger long-term functional alterations, and CSERPs could be considered valid biomarkers for assessing the progress of OD and an indicator of other impairments (e.g., attentional and cognitive impairments), as they occur in MCI.
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Affiliation(s)
- Sara Invitto
- INSPIRE Lab, Laboratory on Cognitive and Psychophysiological Olfactory Processing, DiSTeBA, University of Salento, 73100 Lecce, Italy
| | - Paolo Boscolo-Rizzo
- Department of Medical, Surgical and Health Sciences, Section of Otolaryngology, University of Trieste, 34123 Trieste, Italy
| | - Francesco Fantin
- Department of Neuroscience DNS, Audiology Unit at Treviso Hospital, University of Padova, 31100 Treviso, Italy
| | - Domenico Marco Bonifati
- Unit of Neurology, Department of Neuro-Cardio-Vascular, Ca' Foncello Hospital, 31100 Treviso, Italy
| | - Cosimo de Filippis
- Department of Neuroscience DNS, University of Padova, Audiology and Phoniatrics Unit, Ca' Foncello Hospital, 31100 Treviso, Italy
| | - Enzo Emanuelli
- Otolaringology Unit, Ca' Foncello Hospital, Local Health Unit N.2 "Marca Trevigiana", 31100 Treviso, Italy
| | - Daniele Frezza
- Otolaringology Unit, Ca' Foncello Hospital, Local Health Unit N.2 "Marca Trevigiana", 31100 Treviso, Italy
| | - Federico Giopato
- Unit of Neurology, Department of Neuro-Cardio-Vascular, Ca' Foncello Hospital, 31100 Treviso, Italy
| | | | - Andrea Schito
- INSPIRE Lab, Laboratory on Cognitive and Psychophysiological Olfactory Processing, DiSTeBA, University of Salento, 73100 Lecce, Italy
- Istituto Santa Chiara, 73100 Lecce, Italy
| | | | - Giacomo Spinato
- Department of Neuroscience DNS, Section of Otorhinolaryngology, University of Padova, 35121 Padova, Italy
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11
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Koppelmans V, Ruitenberg MF, Schaefer SY, King JB, Hoffman JM, Mejia AF, Tasdizen T, Duff K. Delayed and More Variable Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers and Applications for Classification. J Alzheimers Dis 2023; 95:1233-1252. [PMID: 37694362 PMCID: PMC10578230 DOI: 10.3233/jad-221297] [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] [Accepted: 07/24/2023] [Indexed: 09/12/2023]
Abstract
BACKGROUND Despite reports of gross motor problems in mild cognitive impairment (MCI) and Alzheimer's disease (AD), fine motor function has been relatively understudied. OBJECTIVE We examined if finger tapping is affected in AD, related to AD biomarkers, and able to classify MCI or AD. METHODS Forty-seven cognitively normal, 27 amnestic MCI, and 26 AD subjects completed unimanual and bimanual computerized tapping tests. We tested 1) group differences in tapping with permutation models; 2) associations between tapping and biomarkers (PET amyloid-β, hippocampal volume, and APOEɛ4 alleles) with linear regression; and 3) the predictive value of tapping for group classification using machine learning. RESULTS AD subjects had slower reaction time and larger speed variability than controls during all tapping conditions, except for dual tapping. MCI subjects performed worse than controls on reaction time and speed variability for dual and non-dominant hand tapping. Tapping speed and variability were related to hippocampal volume, but not to amyloid-β deposition or APOEɛ4 alleles. Random forest classification (overall accuracy = 70%) discriminated control and AD subjects, but poorly discriminated MCI from controls or AD. CONCLUSIONS MCI and AD are linked to more variable finger tapping with slower reaction time. Associations between finger tapping and hippocampal volume, but not amyloidosis, suggest that tapping deficits are related to neuropathology that presents later during the disease. Considering that tapping performance is able to differentiate between control and AD subjects, it can offer a cost-efficient tool for augmenting existing AD biomarkers.
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Affiliation(s)
- Vincent Koppelmans
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Huntsman Mental Health Institute, University of Utah, Salt Lake City, UT, USA
| | - Marit F.L. Ruitenberg
- Department of Health, Medical and Neuropsychology, Leiden University, Leiden, the Netherlands
- Leiden Institute for Brain and Cognition, Leiden, the Netherlands
| | - Sydney Y. Schaefer
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Jace B. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - John M. Hoffman
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Amanda F. Mejia
- Department of Statistics, University of Indiana, Bloomington, IN, USA
| | - Tolga Tasdizen
- School of Computing, University of Utah, Salt Lake City, UT, USA
| | - Kevin Duff
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
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12
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Ferreri F, Francesca M, Fabrizio V, Manzo N, Maria C, Elda J, Rossini PM. EEG, ERPs, and EROs in patients with neurodegenerative dementing disorders: A window into the cortical neurophysiology of cognition and behavior. Int J Psychophysiol 2022; 181:85-94. [PMID: 36055410 DOI: 10.1016/j.ijpsycho.2022.08.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/20/2022] [Accepted: 08/18/2022] [Indexed: 10/31/2022]
Abstract
In the human brain, physiological aging is characterized by progressive neuronal loss, leading to disruption of synapses and to a degree of failure in neurotransmission and information flow. However, there is increasing evidence to support the notion that the aged brain has a remarkable level of resilience (i.s. ability to reorganize itself), with the aim of preserving its physiological activity. It is therefore of paramount interest to develop objective markers able to characterize the biological processes underlying brain aging in the intact human, and to distinguish them from brain degeneration associated to age-related neurological progressive diseases like Alzheimer's disease. EEG, alone and combined with transcranial magnetic stimulation (TMS-EEG), is particularly suited to this aim, due to the functional nature of the information provided, and thanks to the ease with which it can be integrated in ecological scenarios including behavioral tasks. In this review, we aimed to provide the reader with updated information about the role of modern methods of EEG and TMS-EEG analysis in the investigation of physiological brain aging and Alzheimer's disease. In particular, we focused on data about cortical connectivity obtained by using readouts such graph theory network brain organization and architecture, and transcranial evoked potentials (TEPs) during TMS-EEG. Overall, findings in the literature support an important potential contribution of such neurophysiological techniques to the understanding of the mechanisms underlying normal brain aging and the early (prodromal/pre-symptomatic) stages of dementia.
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Affiliation(s)
- Florinda Ferreri
- Unit of Neurology, Unit of Clinical Neurophysiology and Study Center of Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy; Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Miraglia Francesca
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy; Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy.
| | - Vecchio Fabrizio
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy; Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy
| | - Nicoletta Manzo
- IRCCS San Camillo Hospital, Via Alberoni 70, 30126 Lido di Venezia, Venice, Italy
| | - Cotelli Maria
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di DioFatebenefratelli, Brescia, Italy
| | - Judica Elda
- Department of Neurorehabilitation Sciences, Casa Cura Policlinico, Milano, Italy
| | - Paolo Maria Rossini
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy
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13
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Chou YH, Sundman M, Ton That V, Green J, Trapani C. Cortical excitability and plasticity in Alzheimer's disease and mild cognitive impairment: A systematic review and meta-analysis of transcranial magnetic stimulation studies. Ageing Res Rev 2022; 79:101660. [PMID: 35680080 DOI: 10.1016/j.arr.2022.101660] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 05/13/2022] [Accepted: 05/30/2022] [Indexed: 11/01/2022]
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique. When stimulation is applied over the primary motor cortex and coupled with electromyography measures, TMS can probe functions of cortical excitability and plasticity in vivo. The purpose of this meta-analysis is to evaluate the utility of TMS-derived measures for differentiating patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) from cognitively normal older adults (CN). METHODS Databases searched included PubMed, Embase, APA PsycInfo, Medline, and CINAHL Plus from inception to July 2021. RESULTS Sixty-one studies with a total of 2728 participants (1454 patients with AD, 163 patients with MCI, and 1111 CN) were included. Patients with AD showed significantly higher cortical excitability, lower cortical inhibition, and impaired cortical plasticity compared to the CN cohorts. Patients with MCI exhibited increased cortical excitability and reduced plasticity compared to the CN cohort. Additionally, lower cognitive performance was significantly associated with higher cortical excitability and lower inhibition. No seizure events due to TMS were reported, and the mild adverse response rate is approximately 3/1000 (i.e., 9/2728). CONCLUSIONS Findings of our meta-analysis demonstrate the potential of using TMS-derived cortical excitability and plasticity measures as diagnostic biomarkers and therapeutic targets for AD and MCI.
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Affiliation(s)
- Ying-Hui Chou
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, USA; Evelyn F McKnight Brain Institute, Arizona Center on Aging, and BIO5 Institute, University of Arizona, Tucson, USA.
| | - Mark Sundman
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, USA
| | - Viet Ton That
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, USA
| | - Jacob Green
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, USA
| | - Chrisopher Trapani
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, USA
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14
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Bridging the gap: TMS-EEG from Lab to Clinic. J Neurosci Methods 2022; 369:109482. [PMID: 35041855 DOI: 10.1016/j.jneumeth.2022.109482] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/09/2022] [Accepted: 01/13/2022] [Indexed: 01/06/2023]
Abstract
The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has reached technological maturity and has been an object of significant scientific interest for over two decades. Ιn parallel, accumulating evidence highlights the potential of TMS-EEG as a useful tool in the field of clinical neurosciences. Nevertheless, its clinical utility has not yet been established, partly because technical and methodological limitations have created a gap between an evolving scientific tool and standard clinical practice. Here we review some of the identified gaps that still prevent TMS-EEG moving from science laboratories to clinical practice. The principal and partly overlapping gaps include: 1) complex and laborious application, 2) difficulty in obtaining high-quality signals, 3) suboptimal accuracy and reliability, and 4) insufficient understanding of the neurobiological substrate of the responses. All these four aspects need to be satisfactorily addressed for the method to become clinically applicable and enter the diagnostic and therapeutic arena. In the current review, we identify steps that might be taken to address these issues and discuss promising recent studies providing tools to aid bridging the gaps.
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15
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TMS-EEG responses across the lifespan: Measurement, methods for characterisation and identified responses. J Neurosci Methods 2022; 366:109430. [PMID: 34856320 DOI: 10.1016/j.jneumeth.2021.109430] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/02/2021] [Accepted: 11/25/2021] [Indexed: 01/29/2023]
Abstract
The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows probing of the neurophysiology of any neocortical brain area in vivo with millisecond accuracy. TMS-EEG is particularly unique compared with other available neurophysiological methods, as it can measure the state and dynamics of excitatory and inhibitory systems separately. Because of these capabilities, TMS-EEG responses are sensitive to the brain state, and the responses are influenced by brain maturation and ageing, making TMS-EEG a suitable method to study age-specific pathophysiology. In this review, we outline the TMS-EEG measurement procedure, the existing methods used for characterising TMS-EEG responses and the challenges associated with identifying the responses. We also summarise the findings thus far on how TMS-EEG responses change across the lifespan and the TMS-EEG features that separate typical and atypical brain maturation and ageing. Finally, we give an overview of the gaps in current knowledge to provide directions for future studies.
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16
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Su IJ, Hsu CY, Shen S, Chao PK, Hsu JTA, Hsueh JT, Liang JJ, Hsu YT, Shie FS. The Beneficial Effects of Combining Anti-Aβ Antibody NP106 and Curcumin Analog TML-6 on the Treatment of Alzheimer's Disease in APP/PS1 Mice. Int J Mol Sci 2022; 23:ijms23010556. [PMID: 35008983 PMCID: PMC8745390 DOI: 10.3390/ijms23010556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 12/30/2021] [Accepted: 12/31/2021] [Indexed: 11/22/2022] Open
Abstract
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with a multifactorial etiology. A multitarget treatment that modulates multifaceted biological functions might be more effective than a single-target approach. Here, the therapeutic efficacy of combination treatment using anti-Aβ antibody NP106 and curcumin analog TML-6 versus monotherapy was investigated in an APP/PS1 mouse model of AD. Our data demonstrate that both combination treatment and monotherapy attenuated brain Aβ and improved the nesting behavioral deficit to varying degrees. Importantly, the combination treatment group had the lowest Aβ levels, and insoluble forms of Aβ were reduced most effectively. The nesting performance of APP/PS1 mice receiving combination treatment was better than that of other APP/PS1 groups. Further findings indicate that enhanced microglial Aβ phagocytosis and lower levels of proinflammatory cytokines were concurrent with the aforementioned effects of NP106 in combination with TML-6. Intriguingly, combination treatment also normalized the gut microbiota of APP/PS1 mice to levels resembling the wild-type control. Taken together, combination treatment outperformed NP106 or TML-6 monotherapy in ameliorating Aβ pathology and the nesting behavioral deficit in APP/PS1 mice. The superior effect might result from a more potent modulation of microglial function, cerebral inflammation, and the gut microbiota. This innovative treatment paradigm confers a new avenue to develop more efficacious AD treatments.
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Affiliation(s)
- Ih-Jen Su
- Merry Life Biomedical Company, Ltd., 1F., No. 186, Daqiao 2nd St., Yongkang Dist., Tainan City 71048, Taiwan; (I.-J.S.); (C.-Y.H.); (J.-T.H.)
| | - Chia-Yu Hsu
- Merry Life Biomedical Company, Ltd., 1F., No. 186, Daqiao 2nd St., Yongkang Dist., Tainan City 71048, Taiwan; (I.-J.S.); (C.-Y.H.); (J.-T.H.)
| | - Santai Shen
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County 35053, Taiwan; (S.S.); (P.-K.C.); (J.-J.L.); (Y.-T.H.)
| | - Po-Kuan Chao
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County 35053, Taiwan; (S.S.); (P.-K.C.); (J.-J.L.); (Y.-T.H.)
| | - John Tsu-An Hsu
- Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Miaoli County 35053, Taiwan;
| | - Jung-Tsung Hsueh
- Merry Life Biomedical Company, Ltd., 1F., No. 186, Daqiao 2nd St., Yongkang Dist., Tainan City 71048, Taiwan; (I.-J.S.); (C.-Y.H.); (J.-T.H.)
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County 35053, Taiwan; (S.S.); (P.-K.C.); (J.-J.L.); (Y.-T.H.)
| | - Jia-Jun Liang
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County 35053, Taiwan; (S.S.); (P.-K.C.); (J.-J.L.); (Y.-T.H.)
| | - Ying-Ting Hsu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County 35053, Taiwan; (S.S.); (P.-K.C.); (J.-J.L.); (Y.-T.H.)
| | - Feng-Shiun Shie
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County 35053, Taiwan; (S.S.); (P.-K.C.); (J.-J.L.); (Y.-T.H.)
- Correspondence: ; Tel.: +886-37-246166-36709
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