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Sahu M, Ambasta RK, Das SR, Mishra MK, Shanker A, Kumar P. Harnessing Brainwave Entrainment: A Non-invasive Strategy To Alleviate Neurological Disorder Symptoms. Ageing Res Rev 2024; 101:102547. [PMID: 39419401 DOI: 10.1016/j.arr.2024.102547] [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: 09/19/2024] [Revised: 10/07/2024] [Accepted: 10/10/2024] [Indexed: 10/19/2024]
Abstract
From 1990-2019, the burden of neurological disorders varied considerably across countries and regions. Psychiatric disorders, often emerging in early to mid-adulthood, are linked to late-life neurodegenerative diseases like Alzheimer's disease and Parkinson's disease. Individuals with conditions such as Major Depressive Disorder, Anxiety Disorder, Schizophrenia, and Bipolar Disorder face up to four times higher risk of developing neurodegenerative disorders. Contrarily, 65 % of those with neurodegenerative conditions experience severe psychiatric symptoms during their illness. Further, the limitation of medical resources continues to make this burden a significant global and local challenge. Therefore, brainwave entrainment provides therapeutic avenues for improving the symptoms of diseases. Brainwaves are rhythmic oscillations produced either spontaneously or in response to stimuli. Key brainwave patterns include gamma, beta, alpha, theta, and delta waves, yet the underlying physiological mechanisms and the brain's ability to shift between these dynamic states remain areas for further exploration. In neurological disorders, brainwaves are often disrupted, a phenomenon termed "oscillopathy". However, distinguishing these impaired oscillations from the natural variability in brainwave activity across different regions and functional states poses significant challenges. Brainwave-mediated therapeutics represents a promising research field aimed at correcting dysfunctional oscillations. Herein, we discuss a range of non-invasive techniques such as non-invasive brain stimulation (NIBS), neurologic music therapy (NMT), gamma stimulation, and somatosensory interventions using light, sound, and visual stimuli. These approaches, with their minimal side effects and cost-effectiveness, offer potential therapeutic benefits. When integrated, they may not only help in delaying disease progression but also contribute to the development of innovative medical devices for neurological care.
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Affiliation(s)
- Mehar Sahu
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University (Formerly Delhi College of Engineering), Shahbad Daulatpur, Bawana Road, Delhi 110042, India
| | - Rashmi K Ambasta
- Department of Medicine, Vanderbilt University Medical Center (VUMC), Nashville, TN, USA
| | - Suman R Das
- Department of Medicine, Vanderbilt University Medical Center (VUMC), Nashville, TN, USA
| | - Manoj K Mishra
- Cancer Biology Research and Training, Department of Biological Sciences, Alabama State University, Montgomery, AL 36104, USA
| | - Anil Shanker
- Department of Biochemistry, Cancer Biology, Neuroscience & Pharmacology, School of Medicine, Meharry Medical College, and The Office for Research and Innovation, Meharry Medical College, Nashville, TN 37208, USA
| | - Pravir Kumar
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University (Formerly Delhi College of Engineering), Shahbad Daulatpur, Bawana Road, Delhi 110042, India.
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Song Y, Gordon PC, Roy O, Metsomaa J, Belardinelli P, Rostami M, Ziemann U. Involvement of muscarinic acetylcholine receptor-mediated cholinergic neurotransmission in TMS-EEG responses. Prog Neuropsychopharmacol Biol Psychiatry 2024; 136:111167. [PMID: 39383933 DOI: 10.1016/j.pnpbp.2024.111167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 10/01/2024] [Accepted: 10/03/2024] [Indexed: 10/11/2024]
Abstract
The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a valuable tool for investigating brain functions in health and disease. However, the detailed neural mechanisms underlying TMS-EEG responses, including TMS-evoked EEG potentials (TEPs) and TMS-induced EEG oscillations (TIOs), remain largely unknown. Combining TMS-EEG with pharmacological interventions provides a unique opportunity to elucidate the roles of specific receptor-mediated neurotransmissions in these responses. Here, we investigated the involvement of muscarinic acetylcholine receptor (mAChR)-mediated cholinergic neurotransmission in TMS-EEG responses by evaluating the effects of mAChR antagonists on TEPs and TIOs in twenty-four healthy participants using a randomized, placebo-controlled crossover design. TEPs and TIOs were measured before and after administering a single oral dose of scopolamine (a non-selective mAChR antagonist), biperiden (an M1 mAChR antagonist), or placebo, with TMS targeting the left medial prefrontal cortex (mPFC), angular gyrus (AG), and supplementary motor area (SMA). The results indicated that mAChR-mediated cholinergic neurotransmission played a role in TEPs, but not TIOs, in a target-specific manner. Specifically, scopolamine significantly increased the amplitude of a local TEP component between approximately 40 and 63 ms post-stimulus when TMS was applied to the SMA, but not the mPFC or AG. Biperiden produced a similar but less pronounced effect. Importantly, the effects of these mAChR antagonists on TEPs were independent of those on sensory-evoked EEG potentials caused by TMS-associated sensory stimulation. These findings expand our understanding of TMS-EEG physiology, providing insights for its application in physiological and clinical research.
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Affiliation(s)
- Yufei Song
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Pedro C Gordon
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Olivier Roy
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; CERVO Brain Research Centre, Quebec, Canada; Department of Psychiatry and Neurosciences, Université Laval, Quebec, Canada
| | - Johanna Metsomaa
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Finland
| | - Paolo Belardinelli
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; CIMeC, Center for Mind/Brain Sciences, University of Trento, Italy
| | - Maryam Rostami
- Faculty of Electrical and Computer Engineering, University of Tehran, Iran
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany.
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Sun J, Xing F, Feng J, Chen X, Lv L, Yao X, Wang M, Zhao Z, Zhou Q, Liu T, Zhan Y, Gong-Jun J, Wang K, Hu P. Differential symptom cluster responses and predictors to repetitive transcranial magnetic stimulation treatment in Parkinson's disease: A retrospective study. Heliyon 2024; 10:e32799. [PMID: 38975093 PMCID: PMC11226850 DOI: 10.1016/j.heliyon.2024.e32799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 06/08/2024] [Accepted: 06/10/2024] [Indexed: 07/09/2024] Open
Abstract
Background Repetitive transcranial magnetic stimulation (rTMS) is an effective noninvasive neuromodulation technique for Parkinson's disease (PD). However, the efficacy of rTMS varies widely between individuals. This study aimed to investigate the factors related to the response to rTMS in PD patients. Methods We retrospectively analyzed the response of 70 idiopathic PD patients who underwent rTMS for 14 consecutive days targeting the supplementary motor area (SMA) in either an open-label trail (n = 31) or a randomized, double-blind, placebo-controlled trial (RCT) (n = 39). The motor symptoms of PD patients were assessed by the United Parkinson's Disease Rating Scale Part III (UPDRSIII). Based on previous studies, the UPDRSIII were divided into six symptom clusters: axial dysfunction, resting tremor, rigidity, bradykinesia affecting right and left extremities, and postural tremor. Subsequently, the efficacy of rTMS to different motor symptom clusters and clinical predictors were analyzed in these two trails. Results After 14 days of treatment, only the total UPDRSIII scores and rigidity scores improved in both the open-label trial and the RCT. The results of multiple linear regression analysis indicated that baseline rigidity scores (β = 0.37, p = 0.047) and RMT (β = 0.30, P = 0.02) positively predicted the improvement of UPDRSIII. The baseline rigidity score (β = 0.55, P < 0.0001) was identified as an independent factor to predict the improvement of rigidity. Conclusion This study demonstrated significant improvements in total UPDRSIII scores and rigidity after 14-day treatment, with baseline rigidity scores and RMT identified as predictors of treatment response, underscoring the need for individualized therapy.
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Affiliation(s)
- Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Fengbo Xing
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Jingjing Feng
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Xin Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Lingling Lv
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Xiaoqing Yao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Mengqi Wang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Ziye Zhao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Qian Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Tingting Liu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - Yuqian Zhan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
| | - J.I. Gong-Jun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- Anhui Institute of Translational Medicine, Hefei, 230000, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- Anhui Institute of Translational Medicine, Hefei, 230000, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, 230000, China
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, 230000, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230032, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, 230000, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230088, China
- Anhui Institute of Translational Medicine, Hefei, 230000, China
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Romano A, Liparoti M, Minino R, Polverino A, Cipriano L, Carotenuto A, Tafuri D, Sorrentino G, Sorrentino P, Troisi Lopez E. The effect of dopaminergic treatment on whole body kinematics explored through network theory. Sci Rep 2024; 14:1913. [PMID: 38253728 PMCID: PMC10803322 DOI: 10.1038/s41598-023-50546-x] [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: 07/28/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024] Open
Abstract
Three-dimensional motion analysis represents a quantitative approach to assess spatio-temporal and kinematic changes in health and disease. However, these parameters provide only segmental information, discarding minor changes of complex whole body kinematics characterizing physiological and/or pathological conditions. We aimed to assess how levodopa intake affects the whole body, analyzing the kinematic interactions during gait in Parkinson's disease (PD) through network theory which assess the relationships between elements of a system. To this end, we analysed gait data of 23 people with PD applying network theory to the acceleration kinematic data of 21 markers placed on participants' body landmarks. We obtained a matrix of kinematic interactions (i.e., the kinectome) for each participant, before and after the levodopa intake, we performed a topological analysis to evaluate the large-scale interactions among body elements, and a multilinear regression analysis to verify whether the kinectome's topology could predict the clinical variations induced by levodopa. We found that, following levodopa intake, patients with PD showed less trunk and head synchronization (p-head = 0.048; p-7th cervical vertebrae = 0.032; p-10th thoracic vertebrae = 0.006) and an improved upper-lower limbs synchronization (elbows right, p = 0.002; left, p = 0.005), (wrists right, p = 0.003; left, p = 0.002; knees right, p = 0.003; left, p = 0.039) proportional to the UPDRS-III scores. These results may be attributable to the reduction of rigidity, following pharmacological treatment.
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Affiliation(s)
- Antonella Romano
- Department of Medical, Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Marianna Liparoti
- Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Chieti-Pescara G. D'Annunzio, Chieti, Italy
| | - Roberta Minino
- Department of Medical, Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Arianna Polverino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, Naples, Italy
| | - Lorenzo Cipriano
- Department of Medical, Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | | | - Domenico Tafuri
- Department of Medical, Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Giuseppe Sorrentino
- Department of Medical, Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
- Institute of Diagnosis and Treatment Hermitage Capodimonte, Naples, Italy
- Institute of Applied Sciences and Intelligent Systems of National Research Council, Pozzuoli, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences Des Systèmes, Inserm, INS, Aix-Marseille University, Marseille, France.
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems of National Research Council, Pozzuoli, Italy
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Gronlier E, Volle J, Coizet V, Paccard A, Habermacher C, Roche Y, Roucard C, Duveau V, David O. Evoked responses to single pulse electrical stimulation reveal impaired striatal excitability in a rat model of Parkinson's disease. Neurobiol Dis 2023; 185:106266. [PMID: 37604316 PMCID: PMC10480488 DOI: 10.1016/j.nbd.2023.106266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/02/2023] [Accepted: 08/18/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND Sensorimotor beta oscillations are increased in Parkinson's disease (PD) due to the alteration of dopaminergic transmission. This electrophysiological read-out is reported both in patients and in animal models such as the 6-OHDA rat model obtained with unilateral nigral injection of 6-hydroxydopamine (6-OHDA). Current treatments, based on dopaminergic replacement, transiently normalize this pathological beta activity and improve patients' quality of life. OBJECTIVES We wanted to assess in vivo whether the abnormal beta oscillations can be correlated with impaired striatal or cortical excitability of the sensorimotor system and modulated by the pharmacological manipulation of the dopaminergic system. METHODS In the unilateral 6-OHDA rat model and control animals, we used intra-striatal and intra-cortical single-pulse electrical stimulation (SPES) and concurrent local field potentials (LFP) recordings. In the two groups, we quantified basal cortico-striatal excitability from time-resolved spectral analyses of LFP evoked responses induced remotely by intracerebral stimulations. The temporal dependance of cortico-striatal excitability to dopaminergic transmission was further tested using electrophysiological recordings combined with levodopa injection. RESULTS LFP evoked responses after striatal stimulation showed a transient reduction of power in a large time-frequency domain in the 6-OHDA group compared to the sham group. This result was specific to the striatum, as no significant difference was observed in cortical LFP evoked responses between the two groups. This impaired striatal excitability in the 6-OHDA group was observed in the striatum at least during the first 3 months after the initial lesion. In addition, the striatum responses to SPES during a levodopa challenge showed a transient potentiation of the decrease of responsiveness in frequencies below 40 Hz. CONCLUSION The spectral properties of striatal responses to SPES show high sensitivity to dopaminergic transmission in the unilateral 6-OHDA rat model. We thus propose that this approach could be used in preclinical models as a time-resolved biomarker of impaired dopaminergic transmission capable of monitoring progressive neurodegeneration and/or challenges to drug intake.
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Affiliation(s)
- Eloïse Gronlier
- SynapCell SAS, Saint-Ismier, France; Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France.
| | | | - Véronique Coizet
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Antoine Paccard
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | | | | | | | | | - Olivier David
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
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Bhat P, Kumaran SS, Goyal V, Srivastava AK, Behari M. Effect of rTMS at SMA on task-based connectivity in PD. Behav Brain Res 2023; 452:114602. [PMID: 37516209 DOI: 10.1016/j.bbr.2023.114602] [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: 05/09/2023] [Revised: 07/14/2023] [Accepted: 07/26/2023] [Indexed: 07/31/2023]
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) can aid in alleviating clinical symptoms in Parkinson's disease (PD). To better understand the neural mechanism of the intervention, neuroimaging modalities have been used to assess the effects of rTMS. OBJECTIVE To study the changes in cortical connectivity and motor performance with rTMS at supplementary motor area (SMA) in PD using clinical assessment tools and task-based functional MRI. METHODOLOGY 3000 pulses at 5 Hz TMS were delivered at the left SMA once a week for a total of 8 consecutive weeks in 4 sham sessions (week 1-4) and 4 real sessions (week 5 to week 8) in 16 subjects with PD. The outcomes were assessed with UPDRS, PDQ 39 and task-based fMRI at baseline, after sham sessions at week 4, and after real sessions at week 8. Visuo-spatial functional MRI task along with T1 weighted scans (at 3 Tesla) were used to evaluate the effects of rTMS intervention. Multivariate pattern analysis (MVPA) was used to analyse task-based fMRI using Conn toolbox. RESULTS Improvements (p < 0.05) were observed in UPDRS II, III, Mobility and ADL of PDQ39 after real sessions of rTMS. MVPA of task-based connectivity revealed clusters of activation in right hemispheric precentral area, superior frontal gyrus, middle frontal gyrus, thalamus and cerebellum (cluster threshold pFDR=0.001). CONCLUSIONS Weekly rTMS sessions at SMA incurred clinical motor benefits as revealed by an improvement in clinical scales and dexterity performance. These benefits could be attributed to changes in connectivity remote brain regions in the motor network.
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Affiliation(s)
- Priyanka Bhat
- Department of Neurology, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - S Senthil Kumaran
- Department of NMR, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India.
| | - Vinay Goyal
- Department of Neurology, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - Achal K Srivastava
- Department of Neurology, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - Madhuri Behari
- Department of Neurology, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
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Vucic S, Stanley Chen KH, Kiernan MC, Hallett M, Benninger DH, Di Lazzaro V, Rossini PM, Benussi A, Berardelli A, Currà A, Krieg SM, Lefaucheur JP, Long Lo Y, Macdonell RA, Massimini M, Rosanova M, Picht T, Stinear CM, Paulus W, Ugawa Y, Ziemann U, Chen R. Clinical diagnostic utility of transcranial magnetic stimulation in neurological disorders. Updated report of an IFCN committee. Clin Neurophysiol 2023; 150:131-175. [PMID: 37068329 PMCID: PMC10192339 DOI: 10.1016/j.clinph.2023.03.010] [Citation(s) in RCA: 67] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/28/2023] [Accepted: 03/09/2023] [Indexed: 03/31/2023]
Abstract
The review provides a comprehensive update (previous report: Chen R, Cros D, Curra A, Di Lazzaro V, Lefaucheur JP, Magistris MR, et al. The clinical diagnostic utility of transcranial magnetic stimulation: report of an IFCN committee. Clin Neurophysiol 2008;119(3):504-32) on clinical diagnostic utility of transcranial magnetic stimulation (TMS) in neurological diseases. Most TMS measures rely on stimulation of motor cortex and recording of motor evoked potentials. Paired-pulse TMS techniques, incorporating conventional amplitude-based and threshold tracking, have established clinical utility in neurodegenerative, movement, episodic (epilepsy, migraines), chronic pain and functional diseases. Cortical hyperexcitability has emerged as a diagnostic aid in amyotrophic lateral sclerosis. Single-pulse TMS measures are of utility in stroke, and myelopathy even in the absence of radiological changes. Short-latency afferent inhibition, related to central cholinergic transmission, is reduced in Alzheimer's disease. The triple stimulation technique (TST) may enhance diagnostic utility of conventional TMS measures to detect upper motor neuron involvement. The recording of motor evoked potentials can be used to perform functional mapping of the motor cortex or in preoperative assessment of eloquent brain regions before surgical resection of brain tumors. TMS exhibits utility in assessing lumbosacral/cervical nerve root function, especially in demyelinating neuropathies, and may be of utility in localizing the site of facial nerve palsies. TMS measures also have high sensitivity in detecting subclinical corticospinal lesions in multiple sclerosis. Abnormalities in central motor conduction time or TST correlate with motor impairment and disability in MS. Cerebellar stimulation may detect lesions in the cerebellum or cerebello-dentato-thalamo-motor cortical pathways. Combining TMS with electroencephalography, provides a novel method to measure parameters altered in neurological disorders, including cortical excitability, effective connectivity, and response complexity.
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Affiliation(s)
- Steve Vucic
- Brain, Nerve Research Center, The University of Sydney, Sydney, Australia.
| | - Kai-Hsiang Stanley Chen
- Department of Neurology, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
| | - Matthew C Kiernan
- Brain and Mind Centre, The University of Sydney; and Department of Neurology, Royal Prince Alfred Hospital, Australia
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, Maryland, United States
| | - David H Benninger
- Department of Neurology, University Hospital of Lausanne (CHUV), Switzerland
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - Paolo M Rossini
- Department of Neurosci & Neurorehab IRCCS San Raffaele-Rome, Italy
| | - Alberto Benussi
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alfredo Berardelli
- IRCCS Neuromed, Pozzilli; Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Antonio Currà
- Department of Medico-Surgical Sciences and Biotechnologies, Alfredo Fiorini Hospital, Sapienza University of Rome, Terracina, LT, Italy
| | - Sandro M Krieg
- Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany
| | - Jean-Pascal Lefaucheur
- Univ Paris Est Creteil, EA4391, ENT, Créteil, France; Clinical Neurophysiology Unit, Henri Mondor Hospital, AP-HP, Créteil, France
| | - Yew Long Lo
- Department of Neurology, National Neuroscience Institute, Singapore General Hospital, Singapore, and Duke-NUS Medical School, Singapore
| | | | - Marcello Massimini
- Dipartimento di Scienze Biomediche e Cliniche, Università degli Studi di Milano, Milan, Italy; Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences University of Milan, Milan, Italy
| | - Thomas Picht
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Cluster of Excellence: "Matters of Activity. Image Space Material," Humboldt University, Berlin Simulation and Training Center (BeST), Charité-Universitätsmedizin Berlin, Germany
| | - Cathy M Stinear
- Department of Medicine Waipapa Taumata Rau, University of Auckland, Auckland, Aotearoa, New Zealand
| | - Walter Paulus
- Department of Neurology, Ludwig-Maximilians-Universität München, München, Germany
| | - Yoshikazu Ugawa
- Department of Human Neurophysiology, School of Medicine, Fukushima Medical University, Japan
| | - Ulf Ziemann
- Department of Neurology and Stroke, Eberhard Karls University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany; Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Otfried-Müller-Straße 27, 72076 Tübingen, Germany
| | - Robert Chen
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital-UHN, Division of Neurology-University of Toronto, Toronto Canada
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Wang T, Chen X, Zhang J, Feng Q, Huang M. Deep multimodality-disentangled association analysis network for imaging genetics in neurodegenerative diseases. Med Image Anal 2023; 88:102842. [PMID: 37247468 DOI: 10.1016/j.media.2023.102842] [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: 11/02/2022] [Revised: 03/01/2023] [Accepted: 05/15/2023] [Indexed: 05/31/2023]
Abstract
Imaging genetics is a crucial tool that is applied to explore potentially disease-related biomarkers, particularly for neurodegenerative diseases (NDs). With the development of imaging technology, the association analysis between multimodal imaging data and genetic data is gradually being concerned by a wide range of imaging genetics studies. However, multimodal data are fused first and then correlated with genetic data in traditional methods, which leads to an incomplete exploration of their common and complementary information. In addition, the inaccurate formulation in the complex relationships between imaging and genetic data and information loss caused by missing multimodal data are still open problems in imaging genetics studies. Therefore, in this study, a deep multimodality-disentangled association analysis network (DMAAN) is proposed to solve the aforementioned issues and detect the disease-related biomarkers of NDs simultaneously. First, the imaging data are nonlinearly projected into a latent space and imaging representations can be achieved. The imaging representations are further disentangled into common and specific parts by using a multimodal-disentangled module. Second, the genetic data are encoded to achieve genetic representations, and then, the achieved genetic representations are nonlinearly mapped to the common and specific imaging representations to build nonlinear associations between imaging and genetic data through an association analysis module. Moreover, modality mask vectors are synchronously synthesized to integrate the genetic and imaging data, which helps the following disease diagnosis. Finally, the proposed method achieves reasonable diagnosis performance via a disease diagnosis module and utilizes the label information to detect the disease-related modality-shared and modality-specific biomarkers. Furthermore, the genetic representation can be used to impute the missing multimodal data with our learning strategy. Two publicly available datasets with different NDs are used to demonstrate the effectiveness of the proposed DMAAN. The experimental results show that the proposed DMAAN can identify the disease-related biomarkers, which suggests the proposed DMAAN may provide new insights into the pathological mechanism and early diagnosis of NDs. The codes are publicly available at https://github.com/Meiyan88/DMAAN.
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Affiliation(s)
- Tao Wang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Xiumei Chen
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Jiawei Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Qianjin Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China; Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.
| | - Meiyan Huang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China; Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.
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Vitório R, Lirani-Silva E, Orcioli-Silva D, Beretta VS, Oliveira AS, Gobbi LTB. Electrocortical Dynamics of Usual Walking and the Planning to Step over Obstacles in Parkinson's Disease. SENSORS (BASEL, SWITZERLAND) 2023; 23:4866. [PMID: 37430780 DOI: 10.3390/s23104866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/09/2023] [Accepted: 05/17/2023] [Indexed: 07/12/2023]
Abstract
The neural correlates of locomotion impairments observed in people with Parkinson's disease (PD) are not fully understood. We investigated whether people with PD present distinct brain electrocortical activity during usual walking and the approach phase of obstacle avoidance when compared to healthy individuals. Fifteen people with PD and fourteen older adults walked overground in two conditions: usual walking and obstacle crossing. Scalp electroencephalography (EEG) was recorded using a mobile 64-channel EEG system. Independent components were clustered using a k-means clustering algorithm. Outcome measures included absolute power in several frequency bands and alpha/beta ratio. During the usual walk, people with PD presented a greater alpha/beta ratio in the left sensorimotor cortex than healthy individuals. While approaching obstacles, both groups reduced alpha and beta power in the premotor and right sensorimotor cortices (balance demand) and increased gamma power in the primary visual cortex (visual demand). Only people with PD reduced alpha power and alpha/beta ratio in the left sensorimotor cortex when approaching obstacles. These findings suggest that PD affects the cortical control of usual walking, leading to a greater proportion of low-frequency (alpha) neuronal firing in the sensorimotor cortex. Moreover, the planning for obstacle avoidance changes the electrocortical dynamics associated with increased balance and visual demands. People with PD rely on increased sensorimotor integration to modulate locomotion.
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Affiliation(s)
- Rodrigo Vitório
- Institute of Biosciences, Sao Paulo State University (UNESP), Rio Claro 13506-900, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro 13506-900, Brazil
- Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
| | - Ellen Lirani-Silva
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Diego Orcioli-Silva
- Institute of Biosciences, Sao Paulo State University (UNESP), Rio Claro 13506-900, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro 13506-900, Brazil
| | - Victor Spiandor Beretta
- Institute of Biosciences, Sao Paulo State University (UNESP), Rio Claro 13506-900, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro 13506-900, Brazil
- School of Technology and Sciences, Sao Paulo State University (UNESP), Presidente Prudente 19060-900, Brazil
| | | | - Lilian Teresa Bucken Gobbi
- Institute of Biosciences, Sao Paulo State University (UNESP), Rio Claro 13506-900, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro 13506-900, Brazil
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10
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Formaggio E, Tonellato M, Antonini A, Castiglia L, Gallo L, Manganotti P, Masiero S, Del Felice A. Oscillatory EEG-TMS Reactivity in Parkinson Disease. J Clin Neurophysiol 2023; 40:263-268. [PMID: 34280941 DOI: 10.1097/wnp.0000000000000881] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE A dysfunction of beta oscillatory activity is the neurophysiological hallmark of Parkinson disease (PD). How cortical activity reacts to external perturbations may provide insight into pathophysiological mechanisms. This study aims at identifying modifications in EEG rhythms after transcranial magnetic stimulation (TMS) in PD. We hypothesize that single-pulse TMS can modulate brain intrinsic oscillatory properties (e.g., beta excess). METHODS EEG data were coregistered during single-pulse TMS (100 stimuli over the primary motor cortex [M1, hotspot for Abductor Pollicis Brevis], random intertrial interval from 8 to 13 seconds). We used a time-frequency analysis based on wavelet method to characterize modification of oscillatory rhythms (delta [1-4 Hz], theta [4-7 Hz], alpha [8-12 Hz], and beta [13-30 Hz] in 15 participants with PD compared with 10 healthy controls. RESULTS An increase in beta power over the sensorimotor areas was recorded at rest in the PD group ( P < 0.05). Brain oscillations in PD transiently reset after TMS: beta power over M1 becomes comparable to that recorded in aged-matched healthy subjects in the 2 seconds following TMS. CONCLUSIONS Transcranial magnetic stimulation over the dominant motor cortex transiently normalizes cortical oscillations. More user-friendly noninvasive brain stimulation needs to be trialed, based on this proof of concept, to provide practical, portable techniques to treat motor symptoms in PD.
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Affiliation(s)
- Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Michele Tonellato
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Leonora Castiglia
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Laura Gallo
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Paolo Manganotti
- Neurology Section, Cattinara University Hospital, University of Trieste, Trieste, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
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11
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Liu FT, Lu JY, Sun YM, Li L, Yang YJ, Zhao J, Ge JJ, Wu P, Jiang JH, Wu JJ, Zuo CT, Wang J. Dopaminergic Dysfunction and Glucose Metabolism Characteristics in Parkin-Induced Early-Onset Parkinson's Disease Compared to Genetically Undetermined Early-Onset Parkinson's Disease. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:22-33. [PMID: 36939793 PMCID: PMC9883374 DOI: 10.1007/s43657-022-00077-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 09/06/2022] [Accepted: 09/09/2022] [Indexed: 01/28/2023]
Abstract
While early-onset Parkinson's disease (EOPD) caused by mutations in the parkin gene (PRKN) tends to have a relatively benign course compared to genetically undetermined (GU)-EOPD, the exact underlying mechanisms remain elusive. We aimed to search for the differences between PRKN-EOPD and GU-EOPD by dopamine transporter (DAT) and glucose metabolism positron-emission-tomography (PET) imaging. Twelve patients with PRKN-EOPD and 16 with GU-EOPD who accepted both 11C-2b-carbomethoxy-3b-(4-trimethylstannylphenyl) tropane (11C-CFT) and 18F-fluorodeoxyglucose PET were enrolled. The 11C-CFT uptake was analyzed on both regional and voxel levels, whereas glucose metabolism was assessed in a voxel-wise fashion. Correlations between DAT and glucose metabolism imaging, DAT imaging and clinical severity, as well as glucose metabolism imaging and clinical severity were explored. Both clinical symptoms and DAT-binding patterns in the posterior putamen were highly symmetrical in patients with PRKN-EOPD, and dopaminergic dysfunction in the ipsilateral putamen was severer in patients with PRKN-EOPD than GU-EOPD. Meanwhile, the DAT binding was associated with the severity of motor dysfunction in patients with GU-EOPD only. Patients with PRKN-EOPD showed increased glucose metabolism in the contralateral medial frontal gyrus (supplementary motor area (SMA)), contralateral substantia nigra, contralateral thalamus, and contralateral cerebellum. Notably, glucose metabolic activity in the contralateral medial frontal gyrus was inversely associated with regional DAT binding in the bilateral putamen. Patients with PRKN-EOPD showed enhanced metabolic connectivity within the bilateral putamen, ipsilateral paracentral and precentral lobules, and the ipsilateral SMA. Collectively, compared to GU-EOPD, PRKN-EOPD is characterized by symmetrical, more severe dopaminergic dysfunction and relative increased glucose metabolism. Meanwhile, SMA with elevated glucose metabolism and enhanced connectivity may act as compensatory mechanisms in PRKN-EOPD. Supplementary Information The online version contains supplementary material available at 10.1007/s43657-022-00077-8.
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Affiliation(s)
- Feng-Tao Liu
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040 China
| | - Jia-Ying Lu
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235 China
| | - Yi-Min Sun
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040 China
| | - Ling Li
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235 China
| | - Yu-Jie Yang
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040 China
| | - Jue Zhao
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040 China
| | - Jing-Jie Ge
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235 China
| | - Ping Wu
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235 China
| | - Jie-Hui Jiang
- Institute of Biomedical Engineering, School of Life Sciences, Shanghai University, Shanghai, 200444 China
| | - Jian-Jun Wu
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040 China
| | - Chuan-Tao Zuo
- Department of Nuclear Medicine & PET Center, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 518 East Wuzhong Road, Shanghai, 200235 China
- Human Phenome Institute, Fudan University, Shanghai, 200433 China
| | - Jian Wang
- Department of Neurology, National Clinical Research Center for Aging and Medicine & National Center for Neurological Disorders, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040 China
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12
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Sure M, Mertiens S, Vesper J, Schnitzler A, Florin E. Alterations of resting-state networks of Parkinson's disease patients after subthalamic DBS surgery. Neuroimage Clin 2023; 37:103317. [PMID: 36610312 PMCID: PMC9850202 DOI: 10.1016/j.nicl.2023.103317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 12/27/2022] [Accepted: 01/02/2023] [Indexed: 01/05/2023]
Abstract
The implantation of deep brain stimulation (DBS) electrodes in Parkinson's disease (PD) patients can lead to a temporary improvement in motor symptoms, known as the stun effect. However, the network alterations induced by the stun effect are not well characterized. As therapeutic DBS is known to alter resting-state networks (RSN) and subsequent motor symptoms in patients with PD, we aimed to investigate whether the DBS-related stun effect also modulated RSNs. Therefore, we analyzed RSNs of 27 PD patients (8 females, 59.0 +- 8.7 years) using magnetoencephalography and compared them to RSNs of 24 age-matched healthy controls (8 females, 62.8 +- 5.1 years). We recorded 30 min of resting-state activity two days before and one day after implantation of the electrodes with and without dopaminergic medication. RSNs were determined by use of phase-amplitude coupling between a low frequency phase and a high gamma amplitude and examined for differences between conditions (i.e., pre vs post surgery). We identified four RSNs across all conditions: sensory-motor, visual, fronto-occipital, and frontal. Each RSN was altered due to electrode implantation. Importantly, these changes were not restricted to spatially close areas to the electrode trajectory. Interestingly, pre-operative RSNs corresponded better with healthy control RSNs regarding the spatial overlap, although the stun effect is associated with motor improvement. Our findings reveal that the stun effect induced by implantation of electrodes exerts brain wide changes in different functional RSNs.
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Affiliation(s)
- Matthias Sure
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
| | - Sean Mertiens
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
| | - Jan Vesper
- Department of Functional Neurosurgery and Stereotaxy, Medical Faculty, University Hospital, Düsseldorf, Germany.
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany; Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, University Hospital, Düsseldorf, Germany.
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
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13
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Pei G, Liu X, Huang Q, Shi Z, Wang L, Suo D, Funahashi S, Wu J, Zhang J, Fang B. Characterizing cortical responses to short-term multidisciplinary intensive rehabilitation treatment in patients with Parkinson’s disease: A transcranial magnetic stimulation and electroencephalography study. Front Aging Neurosci 2022; 14:1045073. [PMID: 36408100 PMCID: PMC9669794 DOI: 10.3389/fnagi.2022.1045073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is a powerful non-invasive tool for qualifying the neurophysiological effects of interventions by recording TMS-induced cortical activation with high temporal resolution and generates reproducible and reliable waves of activity without participant cooperation. Cortical dysfunction contributes to the pathogenesis of the clinical symptoms of Parkinson’s disease (PD). Here, we examined changes in cortical activity in patients with PD following multidisciplinary intensive rehabilitation treatment (MIRT). Forty-eight patients with PD received 2 weeks of MIRT. The cortical response was examined following single-pulse TMS over the primary motor cortex by 64-channel EEG, and clinical symptoms were assessed before and after MIRT. TMS-evoked potentials were quantified by the global mean field power, as well as oscillatory power in theta, alpha, beta, and gamma bands, and their clinical correlations were calculated. After MIRT, motor and non-motor symptoms improved in 22 responders, and only non-motor function was enhanced in 26 non-responders. Primary motor cortex stimulation reduced global mean field power amplitudes in responders but not significantly in non-responders. Oscillations exhibited attenuated power in the theta, beta, and gamma bands in responders but only reduced gamma power in non-responders. Associations were observed between beta oscillations and motor function and between gamma oscillations and non-motor symptoms. Our results suggest that motor function enhancement by MIRT may be due to beta oscillatory power modulation and that alterations in cortical plasticity in the primary motor cortex contribute to PD recovery.
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Affiliation(s)
- Guangying Pei
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Xinting Liu
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Qiwei Huang
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Zhongyan Shi
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Li Wang
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Dingjie Suo
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Shintaro Funahashi
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing, China
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Jian Zhang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
- Jian Zhang,
| | - Boyan Fang
- Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
- *Correspondence: Boyan Fang,
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14
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Lioumis P, Rosanova M. The role of neuronavigation in TMS-EEG studies: current applications and future perspectives. J Neurosci Methods 2022; 380:109677. [PMID: 35872153 DOI: 10.1016/j.jneumeth.2022.109677] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 07/12/2022] [Accepted: 07/19/2022] [Indexed: 11/28/2022]
Abstract
Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) allows measuring non-invasively the electrical response of the human cerebral cortex to a direct perturbation. Complementing TMS-EEG with a structural neuronavigation tool (nTMS-EEG) is key for accurately selecting cortical areas, targeting them, and adjusting the stimulation parameters based on some relevant anatomical priors. This step, together with the employment of visualization tools designed to perform a quality check of TMS-evoked potentials (TEPs) in real-time during acquisition, is key for maximizing the impact of the TMS pulse on the cortex and in ensuring highly reproducible measurements within sessions and across subjects. Moreover, storing stimulation parameters in the neuronavigation system can help in reproducing the stimulation parameters within and across experimental sessions and sharing them across research centers. Finally, the systematic employment of neuronavigation in TMS-EEG studies is also key to standardize measurements in clinical populations in search for reliable diagnostic and prognostic TMS-EEG-based biomarkers for neurological and psychiatric disorders.
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Affiliation(s)
- Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy
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15
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Yang X, Li Z, Bai L, Shen X, Wang F, Han X, Zhang R, Li Z, Zhang J, Dong M, Wang Y, Cao T, Zhao S, Chu C, Liu C, Zhu X. Association of Plasma and Electroencephalography Markers With Motor Subtypes of Parkinson’s Disease. Front Aging Neurosci 2022; 14:911221. [PMID: 35903537 PMCID: PMC9314775 DOI: 10.3389/fnagi.2022.911221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 06/16/2022] [Indexed: 11/30/2022] Open
Abstract
Objective The aim of this study was to investigate the correlations of plasma neurodegenerative proteins and electroencephalography (EEG) dynamic functional network (DFN) parameters with disease progression in early Parkinson’s disease (PD) with different motor subtypes, including tremor-dominant (TD) and postural instability and gait disorder (PIGD). Methods In our study, 33 patients with PD (21 TD and 12 PIGD) and 33 healthy controls (HCs) were enrolled. Plasma neurofilament light chain (NfL), α-synuclein (α-syn), total-tau (t-tau), β-amyloid 42 (Aβ42), and β-amyloid 40 (Aβ40) levels were measured using an ultrasensitive single-molecule array (Simoa) immunoassay. All the patients with PD underwent EEG quantified by DFN analysis. The motor and non-motor performances were evaluated by a series of clinical assessments. Subsequently, a correlation analysis of plasma biomarkers and EEG measures with clinical scales was conducted. Results In the TD group, plasma NfL exhibited a significant association with MDS-UPDRS III and Montreal Cognitive Assessment (MoCA). A higher Aβ42/40 level was significantly related to a decrease in Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA) in the PIGD group. In terms of the correlation between EEG characteristic parameters and clinical outcomes, trapping time (TT) delta was positively correlated with MDS-UPDRS III and MoCA scores in the TD group, especially in the prefrontal and frontal regions. For other non-motor symptoms, there were significant direct associations of kPLI theta with HAMD and HAMA, especially in the prefrontal region, and kPLI gamma was particularly correlated with Rapid Eye Movement Sleep Behavior Disorder Screening Questionnaire (RBDSQ) scores in the prefrontal, frontal, and parietal regions in the TD group. Furthermore, there was a significant positive correlation between plasma t-tau and kPLI, and pairwise correlations were found among plasma NfL, theta TT, and MoCA scores in the TD group. Conclusion These results provide evidence that plasma neurodegenerative proteins and EEG measures have great potential in predicting the disease progression of PD subtypes, especially for the TD subtype. A combination of these two kinds of markers may have a superposition effect on monitoring and estimating the prognosis of PD subtypes and deserves further research in larger, follow-up PD cohorts.
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Affiliation(s)
- Xiaoxia Yang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhen Li
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Lipeng Bai
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiao Shen
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Fei Wang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaoxuan Han
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Rui Zhang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhuo Li
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Jinghui Zhang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Mengmeng Dong
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Yanlin Wang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Tingyu Cao
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Shujun Zhao
- National Health Commission Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute Endocrinology, Tianjin Medical University, Tianjin, China
| | - Chunguang Chu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
- *Correspondence: Chunguang Chu,
| | - Chen Liu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
- Chen Liu,
| | - Xiaodong Zhu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
- Xiaodong Zhu,
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16
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Granö I, Mutanen TP, Tervo A, Nieminen JO, Souza VH, Fecchio M, Rosanova M, Lioumis P, Ilmoniemi RJ. Local brain-state dependency of effective connectivity: a pilot TMS-EEG study. OPEN RESEARCH EUROPE 2022; 2:45. [PMID: 36035767 PMCID: PMC7613446 DOI: 10.12688/openreseurope.14634.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/07/2022] [Indexed: 11/20/2022]
Abstract
Background: Spontaneous cortical oscillations have been shown to modulate cortical responses to transcranial magnetic stimulation (TMS). However, whether these oscillations influence cortical effective connectivity is largely unknown. We conducted a pilot study to set the basis for addressing how spontaneous oscillations affect cortical effective connectivity measured through TMS-evoked potentials (TEPs). Methods: We applied TMS to the left primary motor cortex and right pre-supplementary motor area of three subjects while recording EEG. We classified trials off-line into positive- and negative-phase classes according to the mu and beta rhythms. We calculated differences in the global mean-field amplitude (GMFA) and compared the cortical spreading of the TMS-evoked activity between the two classes. Results: Phase affected the GMFA in four out of 12 datasets (3 subjects × 2 stimulation sites × 2 frequency bands). Two of the observed significant intervals were before 50 ms, two between 50 and 100 ms, and one after 100 ms post-stimulus. Source estimates showed complex spatial differences between the classes in the cortical spreading of the TMS-evoked activity. Conclusions: TMS-evoked effective connectivity seems to depend on the phase of local cortical oscillations at the stimulated site. This work paves the way to design future closed-loop stimulation paradigms.
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Affiliation(s)
- Ida Granö
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Tuomas P. Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Aino Tervo
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jaakko O. Nieminen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Victor H. Souza
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- School of Physiotherapy, Federal University of Juiz de Fora, Juiz de Fora, MG, Brazil
| | - Matteo Fecchio
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Risto J. Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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17
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Zhang J, Villringer A, Nikulin VV. Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson's Disease: An EEG Study. Front Aging Neurosci 2022; 14:846017. [PMID: 35572144 PMCID: PMC9106139 DOI: 10.3389/fnagi.2022.846017] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Dopaminergic medication for Parkinson's disease (PD) modulates neuronal oscillations and functional connectivity (FC) across the basal ganglia-thalamic-cortical circuit. However, the non-oscillatory component of the neuronal activity, potentially indicating a state of excitation/inhibition balance, has not yet been investigated and previous studies have shown inconsistent changes of cortico-cortical connectivity as a response to dopaminergic medication. To further elucidate changes of regional non-oscillatory component of the neuronal power spectra, FC, and to determine which aspects of network organization obtained with graph theory respond to dopaminergic medication, we analyzed a resting-state electroencephalography (EEG) dataset including 15 PD patients during OFF and ON medication conditions. We found that the spectral slope, typically used to quantify the broadband non-oscillatory component of power spectra, steepened particularly in the left central region in the ON compared to OFF condition. In addition, using lagged coherence as a FC measure, we found that the FC in the beta frequency range between centro-parietal and frontal regions was enhanced in the ON compared to the OFF condition. After applying graph theory analysis, we observed that at the lower level of topology the node degree was increased, particularly in the centro-parietal area. Yet, results showed no significant difference in global topological organization between the two conditions: either in global efficiency or clustering coefficient for measuring global and local integration, respectively. Interestingly, we found a close association between local/global spectral slope and functional network global efficiency in the OFF condition, suggesting a crucial role of local non-oscillatory dynamics in forming the functional global integration which characterizes PD. These results provide further evidence and a more complete picture for the engagement of multiple cortical regions at various levels in response to dopaminergic medication in PD.
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Affiliation(s)
- Juanli Zhang
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Vadim V. Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Neurophysics Group, Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
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18
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Pozzi NG, Isaias IU. Adaptive deep brain stimulation: Retuning Parkinson's disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:273-284. [PMID: 35034741 DOI: 10.1016/b978-0-12-819410-2.00015-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A brain-machine interface represents a promising therapeutic avenue for the treatment of many neurologic conditions. Deep brain stimulation (DBS) is an invasive, neuro-modulatory tool that can improve different neurologic disorders by delivering electric stimulation to selected brain areas. DBS is particularly successful in advanced Parkinson's disease (PD), where it allows sustained improvement of motor symptoms. However, this approach is still poorly standardized, with variable clinical outcomes. To achieve an optimal therapeutic effect, novel adaptive DBS (aDBS) systems are being developed. These devices operate by adapting stimulation parameters in response to an input signal that can represent symptoms, motor activity, or other behavioral features. Emerging evidence suggests greater efficacy with fewer adverse effects during aDBS compared with conventional DBS. We address this topic by discussing the basics principles of aDBS, reviewing current evidence, and tackling the many challenges posed by aDBS for PD.
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Affiliation(s)
- Nicoló G Pozzi
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany
| | - Ioannis U Isaias
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany.
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19
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Leodori G, De Bartolo MI, Guerra A, Fabbrini A, Rocchi L, Latorre A, Paparella G, Belvisi D, Conte A, Bhatia KP, Rothwell JC, Berardelli A. Motor Cortical Network Excitability in Parkinson's Disease. Mov Disord 2022; 37:734-744. [PMID: 35001420 DOI: 10.1002/mds.28914] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 12/13/2021] [Accepted: 12/15/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Motor impairment in Parkinson's disease (PD) reflects changes in the basal ganglia-thalamocortical circuit converging on the primary motor cortex (M1) and supplementary motor area (SMA). Previous studies assessed M1 excitability in PD using transcranial magnetic stimulation (TMS)-evoked electromyographic activity. TMS-evoked electroencephalographic activity may unveil broader motor cortical network changes in PD. OBJECTIVE The aim was to assess motor cortical network excitability in PD. METHODS We compared TMS-evoked cortical potentials (TEPs) from M1 and the pre-SMA between 20 PD patients tested off and on medication and 19 healthy controls (HCs) and investigated possible correlations with bradykinesia. RESULTS Off PD patients compared to HCs had smaller P30 responses from the M1s contralateral (M1+) and ipsilateral (M1-) to the most bradykinetic side and increased pre-SMA N40. Dopaminergic therapy normalized the amplitude of M1+ and M1- P30 as well as pre-SMA N40. We found a positive correlation between M1+ P30 amplitude and bradykinesia in off PD patients. CONCLUSIONS Changes in M1 P30 and pre-SMA N40 in PD suggest that M1 excitability is reduced on both sides, whereas pre-SMA excitability is increased. The effect of dopaminergic therapy and the clinical correlation suggest that these cortical changes may reflect abnormal basal ganglia-thalamocortical activity. TMS electroencephalography provides novel insight into motor cortical network changes related to the pathophysiology of PD. © 2022 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Giorgio Leodori
- IRCCS Neuromed, Pozzilli, Italy.,Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | | | | | - Andrea Fabbrini
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Lorenzo Rocchi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Anna Latorre
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | | | - Daniele Belvisi
- IRCCS Neuromed, Pozzilli, Italy.,Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Antonella Conte
- IRCCS Neuromed, Pozzilli, Italy.,Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Kailash P Bhatia
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - John C Rothwell
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Alfredo Berardelli
- IRCCS Neuromed, Pozzilli, Italy.,Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
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20
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The rt-TEP tool: real-time visualization of TMS-Evoked Potential to maximize cortical activation and minimize artifacts. J Neurosci Methods 2022; 370:109486. [DOI: 10.1016/j.jneumeth.2022.109486] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/14/2022] [Accepted: 01/19/2022] [Indexed: 12/11/2022]
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21
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Altered Regional Homogeneity and Functional Connectivity during Microlesion Period after Deep Brain Stimulation in Parkinson's Disease. PARKINSON'S DISEASE 2021; 2021:2711365. [PMID: 34512944 PMCID: PMC8429001 DOI: 10.1155/2021/2711365] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 08/10/2021] [Accepted: 08/23/2021] [Indexed: 11/28/2022]
Abstract
Background Patients with Parkinson's disease (PD) undergoing deep brain electrode implantation experience a temporary improvement in motor symptoms before the electrical stimulation begins. We usually call this the microlesion effect (MLE), but the mechanism behind it is not clear. Purpose This study aimed to assess the alterations in brain functions at the regional and whole-brain levels, using regional homogeneity (ReHo) and functional connectivity (FC), during the postoperative microlesion period after deep brain stimulation (DBS) in PD patients. Method Resting-state functional MRI data were collected from 27 PD patients before and after the first day of DBS and 12 healthy controls (HCs) in this study. The ReHo in combination with FC analysis was used to investigate the alterations of regional brain activity in all the subjects. Results There were increased ReHo in the basal ganglia-thalamocortical circuit (left supplementary motor area and bilateral paracentral lobule), whereas decreased ReHo in the default mode network (DMN) (left angular gyrus, bilateral precuneus), prefrontal cortex (bilateral middle frontal gyrus), and the cerebello-thalamocortical (CTC) circuit (Cerebellum_crus2/1_L) after DBS. In addition, we also found abnormal FC in the lingual gyrus, cerebellum, and DMN. Conclusion Microlesion of the thalamus caused by electrode implantation can alter the activity of the basal ganglia-thalamocortical circuit, prefrontal cortex, DMN, and CTC circuit and induce abnormal FC in the lingual gyrus, cerebellum, prefrontal cortex, and DMN among PD patients. The findings of this study contribute to the understanding of the mechanism of MLE.
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22
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Shukla S, Thirugnanasambandam N. Tapping the Potential of Multimodal Non-invasive Brain Stimulation to Elucidate the Pathophysiology of Movement Disorders. Front Hum Neurosci 2021; 15:661396. [PMID: 34054449 PMCID: PMC8149895 DOI: 10.3389/fnhum.2021.661396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 03/30/2021] [Indexed: 11/18/2022] Open
Abstract
This mini-review provides a detailed outline of studies that have used multimodal approaches in non-invasive brain stimulation to investigate the pathophysiology of the three common movement disorders, namely, essential tremor, Parkinson’s disease, and dystonia. Using specific search terms and filters in the PubMed® database, we finally shortlisted 27 studies in total that were relevant to this review. While two-thirds (Brittain et al., 2013) of these studies were performed on Parkinson’s disease patients, we could find only three studies that were conducted in patients with essential tremor. We clearly show that although multimodal non-invasive brain stimulation holds immense potential in unraveling the physiological mechanisms that are disrupted in movement disorders, the technical challenges and pitfalls of combining these methods may hinder their widespread application by movement disorder specialists. A multidisciplinary team with clinical and technical expertise may be crucial in reaping the fullest benefits from such novel multimodal approaches.
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Affiliation(s)
- Sakshi Shukla
- National Brain Research Centre (NBRC), Manesar, India
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23
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Ferrarelli F, Phillips M. Examining and Modulating Neural Circuits in Psychiatric Disorders With Transcranial Magnetic Stimulation and Electroencephalography: Present Practices and Future Developments. Am J Psychiatry 2021; 178:400-413. [PMID: 33653120 PMCID: PMC8119323 DOI: 10.1176/appi.ajp.2020.20071050] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique uniquely equipped to both examine and modulate neural systems and related cognitive and behavioral functions in humans. As an examination tool, TMS can be used in combination with EEG (TMS-EEG) to elucidate directly, objectively, and noninvasively the intrinsic properties of a specific cortical region, including excitation, inhibition, reactivity, and oscillatory activity, irrespective of the individual's conscious effort. Additionally, when applied in repetitive patterns, TMS has been shown to modulate brain networks in healthy individuals, as well as ameliorate symptoms in individuals with psychiatric disorders. The key role of TMS in assessing and modulating neural dysfunctions and associated clinical and cognitive deficits in psychiatric populations is therefore becoming increasingly evident. In this article, the authors review TMS-EEG studies in schizophrenia and mood disorders, as most TMS-EEG studies to date have focused on individuals with these disorders. The authors present the evidence on the efficacy of repetitive TMS (rTMS) and theta burst stimulation (TBS), when targeting specific cortical areas, in modulating neural circuits and ameliorating symptoms and abnormal behaviors in individuals with psychiatric disorders, especially when informed by resting-state and task-related neuroimaging measures. Examples of how the combination of TMS-EEG assessments and rTMS and TBS paradigms can be utilized to both characterize and modulate neural circuit alterations in individuals with psychiatric disorders are also provided. This approach, along with the evaluation of the behavioral effects of TMS-related neuromodulation, has the potential to lead to the development of more effective and personalized interventions for individuals with psychiatric disorders.
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Affiliation(s)
- Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh School of Medicine
| | - Mary Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine
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24
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Rawji V, Latorre A, Sharma N, Rothwell JC, Rocchi L. On the Use of TMS to Investigate the Pathophysiology of Neurodegenerative Diseases. Front Neurol 2020; 11:584664. [PMID: 33224098 PMCID: PMC7669623 DOI: 10.3389/fneur.2020.584664] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 10/05/2020] [Indexed: 12/22/2022] Open
Abstract
Neurodegenerative diseases are a collection of disorders that result in the progressive degeneration and death of neurons. They are clinically heterogenous and can present as deficits in movement, cognition, executive function, memory, visuospatial awareness and language. Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation tool that allows for the assessment of cortical function in vivo. We review how TMS has been used for the investigation of three neurodegenerative diseases that differ in their neuroanatomical axes: (1) Motor cortex-corticospinal tract (motor neuron diseases), (2) Non-motor cortical areas (dementias), and (3) Subcortical structures (parkinsonisms). We also make four recommendations that we hope will benefit the use of TMS in neurodegenerative diseases. Firstly, TMS has traditionally been limited by the lack of an objective output and so has been confined to stimulation of the motor cortex; this limitation can be overcome by the use of concurrent neuroimaging methods such as EEG. Given that neurodegenerative diseases progress over time, TMS measures should aim to track longitudinal changes, especially when the aim of the study is to look at disease progression and symptomatology. The lack of gold-standard diagnostic confirmation undermines the validity of findings in clinical populations. Consequently, diagnostic certainty should be maximized through a variety of methods including multiple, independent clinical assessments, imaging and fluids biomarkers, and post-mortem pathological confirmation where possible. There is great interest in understanding the mechanisms by which symptoms arise in neurodegenerative disorders. However, TMS assessments in patients are usually carried out during resting conditions, when the brain network engaged during these symptoms is not expressed. Rather, a context-appropriate form of TMS would be more suitable in probing the physiology driving clinical symptoms. In all, we hope that the recommendations made here will help to further understand the pathophysiology of neurodegenerative diseases.
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Affiliation(s)
| | | | | | | | - Lorenzo Rocchi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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25
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Vissani M, Isaias IU, Mazzoni A. Deep brain stimulation: a review of the open neural engineering challenges. J Neural Eng 2020; 17:051002. [PMID: 33052884 DOI: 10.1088/1741-2552/abb581] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) is an established and valid therapy for a variety of pathological conditions ranging from motor to cognitive disorders. Still, much of the DBS-related mechanism of action is far from being understood, and there are several side effects of DBS whose origin is unclear. In the last years DBS limitations have been tackled by a variety of approaches, including adaptive deep brain stimulation (aDBS), a technique that relies on using chronically implanted electrodes on 'sensing mode' to detect the neural markers of specific motor symptoms and to deliver on-demand or modulate the stimulation parameters accordingly. Here we will review the state of the art of the several approaches to improve DBS and summarize the main challenges toward the development of an effective aDBS therapy. APPROACH We discuss models of basal ganglia disorders pathogenesis, hardware and software improvements for conventional DBS, and candidate neural and non-neural features and related control strategies for aDBS. MAIN RESULTS We identify then the main operative challenges toward optimal DBS such as (i) accurate target localization, (ii) increased spatial resolution of stimulation, (iii) development of in silico tests for DBS, (iv) identification of specific motor symptoms biomarkers, in particular (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) clarify how stimulation affects the cortico-basal-ganglia-thalamic network to (vii) design optimal stimulation patterns. SIGNIFICANCE This roadmap will lead neural engineers novel to the field toward the most relevant open issues of DBS, while the in-depth readers might find a careful comparison of advantages and drawbacks of the most recent attempts to improve DBS-related neuromodulatory strategies.
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Affiliation(s)
- Matteo Vissani
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56025 Pisa, Italy. Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56025 Pisa, Italy
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26
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Madrid J, Benninger DH. Non-invasive brain stimulation for Parkinson's disease: Clinical evidence, latest concepts and future goals: A systematic review. J Neurosci Methods 2020; 347:108957. [PMID: 33017643 DOI: 10.1016/j.jneumeth.2020.108957] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 08/27/2020] [Accepted: 09/18/2020] [Indexed: 12/16/2022]
Abstract
Parkinson's disease (PD) is becoming a major public-health issue in an aging population. Available approaches to treat advanced PD still have limitations; new therapies are needed. The non-invasive brain stimulation (NIBS) may offer a complementary approach to treat advanced PD by personalized stimulation. Although NIBS is not as effective as the gold-standard levodopa, recent randomized controlled trials show promising outcomes in the treatment of PD symptoms. Nevertheless, only a few NIBS-stimulation paradigms have shown to improve PD's symptoms. Current clinical recommendations based on the level of evidence are reported in Table 1 through Table 3. Furthermore, novel technological advances hold promise and may soon enable the non-invasive stimulation of deeper brain structures for longer periods.
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Affiliation(s)
- Julian Madrid
- Service of Neurology, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.
| | - David H Benninger
- Service of Neurology, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.
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27
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Busan P. Developmental stuttering and the role of the supplementary motor cortex. JOURNAL OF FLUENCY DISORDERS 2020; 64:105763. [PMID: 32361030 DOI: 10.1016/j.jfludis.2020.105763] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 04/05/2020] [Accepted: 04/08/2020] [Indexed: 06/11/2023]
Abstract
Developmental stuttering is a frequent neurodevelopmental disorder with a complex neurobiological basis. Robust neural markers of stuttering include imbalanced activity of speech and motor related brain regions, and their impaired structural connectivity. The dynamic interaction of cortical regions is regulated by the cortico-basal ganglia-thalamo-cortical system with the supplementary motor area constituting a crucial cortical site. The SMA integrates information from different neural circuits, and manages information about motor programs such as self-initiated movements, motor sequences, and motor learning. Abnormal functioning of SMA is increasingly reported in stuttering, and has been recently indicated as an additional "neural marker" of DS: anatomical and functional data have documented abnormal structure and activity of the SMA, especially in motor and speech networks. Its connectivity is often impaired, especially when considering networks of the left hemisphere. Compatibly, recent data suggest that, in DS, SMA is part of a poorly synchronized neural network, thus resulting in a likely substrate for the appearance of DS symptoms. However, as evident when considering neural models of stuttering, the role of SMA has not been fully clarified. Herein, the available evidence is reviewed, which highlights the role of the SMA in DS as a neural "hub", receiving and conveying altered information, thus "gating" the release of correct or abnormal motor plans.
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28
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Schneider L, Seeger V, Timmermann L, Florin E. Electrophysiological resting state networks of predominantly akinetic-rigid Parkinson patients: Effects of dopamine therapy. NEUROIMAGE-CLINICAL 2020; 25:102147. [PMID: 31954989 PMCID: PMC6965744 DOI: 10.1016/j.nicl.2019.102147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 11/21/2019] [Accepted: 12/21/2019] [Indexed: 11/25/2022]
Abstract
Analysis of whole-brain frequency-specific resting state networks with EEG. Comparison of dopamine medication ON and OFF state in Parkinson patients. Parkinson patients show distinct frequency-specific network alterations. Motor network at beta frequencies is re-instated after dopamine medication.
Parkinson's disease (PD) causes both motor and non-motor symptoms, which can partially be reversed by dopamine therapy. These symptoms as well as the effect of dopamine may be explained by distinct alterations in whole-brain architecture. We used functional connectivity (FC) and in particular resting state network (RSN) analysis to identify such whole-brain alterations in a frequency-specific manner. In addition, we hypothesized that standard dopaminergic medication would have a normalizing effect on these whole brain alterations. We recorded resting-state EEGs of 19 PD patients in the medical OFF and ON states, and of 12 healthy age-matched controls. The PD patients were either of akinetic-rigid or mixed subtype. We extracted RSNs with independent component analysis in the source space for five frequency bands. Within the sensorimotor network (SMN) the supplementary motor area (SMA) showed decreased FC in the OFF state compared to healthy controls. This finding was reversed after dopamine administration. Furthermore, in the OFF state no stable SMN beta component could be identified. The default mode network showed alterations due to PD independent of the medication state. The visual network was altered in the OFF state, and reinstated to a pattern similar to healthy controls by medication. In conclusion, PD causes distinct RSN alterations, which are partly reversed after levodopa administration. The changes within the SMN are of particular interest, because they broaden the pathophysiological understanding of PD. Our results identify the SMA as a central network hub affected in PD and a crucial effector of dopamine therapy.
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Affiliation(s)
- Lukas Schneider
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany
| | - Valentin Seeger
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany; Department of Neurology, University Hospital Marburg, Baldingerstrasse, 35043 Marburg, Germany
| | - Esther Florin
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Germany.
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29
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Rossini P, Di Iorio R, Bentivoglio M, Bertini G, Ferreri F, Gerloff C, Ilmoniemi R, Miraglia F, Nitsche M, Pestilli F, Rosanova M, Shirota Y, Tesoriero C, Ugawa Y, Vecchio F, Ziemann U, Hallett M. Methods for analysis of brain connectivity: An IFCN-sponsored review. Clin Neurophysiol 2019; 130:1833-1858. [DOI: 10.1016/j.clinph.2019.06.006] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 05/08/2019] [Accepted: 06/18/2019] [Indexed: 01/05/2023]
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