1
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Choi IS, Kim J, Choi JH, Kim EM, Choi JW, Rah JC. Modulation of premotor cortex excitability mitigates the behavioral and electrophysiological abnormalities in a Parkinson's disease mouse model. Prog Neurobiol 2025; 249:102761. [PMID: 40258455 DOI: 10.1016/j.pneurobio.2025.102761] [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: 05/22/2024] [Revised: 03/27/2025] [Accepted: 04/14/2025] [Indexed: 04/23/2025]
Abstract
The subthalamic nucleus (STN) plays a crucial role in suppressing prepotent response tendency. The prefrontal regions innervating the STN exhibit increased activity during the stop-signal responses, and the optogenetic activation of these neurons suppresses ongoing behavior. High-frequency electrical stimulation of the STN effectively treats the motor symptoms of Parkinson's disease (PD), yet its underlying circuit mechanisms remain unclear. Here, we investigated the involvement of STN-projecting premotor (M2) neurons in PD mouse models and the impact of deep brain stimulation targeting the STN (DBS-STN). We found that the M2 neurons exhibited enhanced burst firing and synchronous oscillations in the PD mouse model. Remarkably, high-frequency stimulation of STN-projecting M2 neurons, simulating antidromic activation during DBS-STN relieved motor symptoms and hyperexcitability. These changes were attributed to reduced firing frequency vs. current relationship through normalized hyperpolarization-activated inward current (Ih). The M2 neurons in the PD model mouse displayed increased Ih, which was reversed by high-frequency stimulation. Additionally, the infusion of ZD7288, an HCN channel blocker, into the M2 replicated the effects of high-frequency stimulation. In conclusion, our study reveals excessive excitability and suppressive motor control through M2-STN synapses in a PD mouse model. Antidromic excitation of M2 neurons during DBS-STN alleviates this suppression, thereby improving motor impairment. These findings provide insights into the circuit-level dynamics underlying deep brain stimulation's therapeutic effects in PD, suggesting that M2-STN synapses could serve as potential targets for future therapeutic strategies.
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Affiliation(s)
- In Sun Choi
- Laboratory of Neurophysiology, Sensory and Motor Neuroscience Group, Korea Brain Research Institute, Daegu 41602, Republic of Korea; Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
| | - Jinmo Kim
- Department of Electrical Engineering and Computer Science, DGIST, Daegu 42988, Republic of Korea
| | - Joon Ho Choi
- Laboratory of Neurophysiology, Sensory and Motor Neuroscience Group, Korea Brain Research Institute, Daegu 41602, Republic of Korea
| | - Eun-Mee Kim
- Department of Paramedicine, Korea Nazarene University, Cheonan 31172, Republic of Korea
| | - Ji-Woong Choi
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea; Department of Electrical Engineering and Computer Science, DGIST, Daegu 42988, Republic of Korea.
| | - Jong-Cheol Rah
- Laboratory of Neurophysiology, Sensory and Motor Neuroscience Group, Korea Brain Research Institute, Daegu 41602, Republic of Korea; Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea; Department of Brain Sciences, DGIST, Daegu 42988, Republic of Korea.
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2
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Du D, Fu W, Su S, Mao X, Yang L, Xu M, Yuan Y, Gao Y, Geng Z, Chen Y, Zhao M, Fu Y, Yin F, Han H. Remote Regulation of Molecular Diffusion in Extracellular Space of Parkinson's Disease Rat Model by Subthalamic Nucleus Deep Brain Stimulation. CYBORG AND BIONIC SYSTEMS 2025; 6:0218. [PMID: 40190716 PMCID: PMC11969791 DOI: 10.34133/cbsystems.0218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2024] [Revised: 11/30/2024] [Accepted: 12/29/2024] [Indexed: 04/09/2025] Open
Abstract
Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective therapy for Parkinson's disease (PD). However, the therapeutic mechanisms remain incompletely understood, particularly regarding the extracellular space (ECS), a critical microenvironment where molecular diffusion and interstitial fluid (ISF) dynamics are essential for neural function. This study aims to explore the regulatory mechanisms of the ECS in the substantia nigra (SN) of PD rats following STN-DBS. To evaluate whether STN-DBS can modulate ECS diffusion and drainage, we conducted quantitative measurements using a tracer-based magnetic resonance imaging. Our findings indicated that, compared to the PD group, STN-DBS treatment resulted in a decreased diffusion coefficient (D*), shorted half-life (T 1/2), and increased clearance coefficient (k') in the SN. To investigate the mechanisms underlying these changes in molecular diffusion, we employed enzyme-linked immunosorbent assay (ELISA), Western blotting (WB), and microdialysis techniques. The results revealed that STN-DBS led to an increase in hyaluronic acid content, elevated expression of excitatory amino acid transporter 2 (EAAT2), and a reduction in extracellular glutamate concentration. Additionally, to further elucidate the mechanisms influencing ISF drainage, we employed immunofluorescence and immunohistochemical techniques for staining aquaporin-4 (AQP-4) and α-synuclein. The results demonstrated that STN-DBS restored the expression of AQP-4 while decreasing the expression of α-synuclein. In conclusion, our findings suggest that STN-DBS improves PD symptoms by modifying the ECS and enhancing ISF drainage in the SN regions. These results offer new insights into the mechanisms and long-term outcomes of DBS in ECS, paving the way for precision therapies.
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Affiliation(s)
- Dan Du
- Department of Radiology,
Peking University Third Hospital, Beijing 100191, China
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao 066000, China
| | - Wanyi Fu
- Department of Electronic Engineering,
Tsinghua University, Beijing 100084, China
- Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology,
Peking University Third Hospital, Beijing 100191, China
| | - Shaoyi Su
- Institute of Medical Technology,
Peking University Health Science Center, Beijing 100191, China
| | - Xin Mao
- Department of Radiology,
Peking University Third Hospital, Beijing 100191, China
- Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology,
Peking University Third Hospital, Beijing 100191, China
| | - Liu Yang
- Department of Radiology,
Peking University Third Hospital, Beijing 100191, China
| | - Meng Xu
- Institute of Medical Technology,
Peking University Health Science Center, Beijing 100191, China
| | - Yi Yuan
- School of Electrical Engineering,
Yanshan University, Qinhuangdao 066004, China
| | - Yajuan Gao
- Department of Radiology,
Peking University Third Hospital, Beijing 100191, China
- Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology,
Peking University Third Hospital, Beijing 100191, China
- Institute of Medical Technology,
Peking University Health Science Center, Beijing 100191, China
- National Medical Products Administration Key Laboratory for Evaluation of Medical Imaging Equipment and Technique, Beijing 100191, China
| | - Ziyao Geng
- Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology,
Peking University Third Hospital, Beijing 100191, China
| | - Yanjing Chen
- Department of Radiology,
Peking University Third Hospital, Beijing 100191, China
| | - Mingming Zhao
- Department of Neurosurgery, Aerospace Center Hospital, Beijing 100049, China
| | - Yu Fu
- Department of Neurology,
Peking University Third Hospital, Beijing 100191, China
| | - Feng Yin
- Department of Neurosurgery, Aerospace Center Hospital, Beijing 100049, China
| | - Hongbin Han
- Department of Radiology,
Peking University Third Hospital, Beijing 100191, China
- Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology,
Peking University Third Hospital, Beijing 100191, China
- Institute of Medical Technology,
Peking University Health Science Center, Beijing 100191, China
- National Medical Products Administration Key Laboratory for Evaluation of Medical Imaging Equipment and Technique, Beijing 100191, China
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3
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Lee CH, Juan CH, Chen HH, Hong JP, Liao TW, French I, Lo YS, Wang YR, Cheng ML, Wu HC, Chen CM, Chang KH. Long-Range Temporal Correlations in Electroencephalography for Parkinson's Disease Progression. Mov Disord 2025; 40:266-275. [PMID: 39663783 DOI: 10.1002/mds.30074] [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: 07/25/2024] [Revised: 10/15/2024] [Accepted: 11/12/2024] [Indexed: 12/13/2024] Open
Abstract
BACKGROUND Patients with Parkinson's disease (PD) present progressive deterioration in both motor and non-motor manifestations. However, the absence of clinical biomarkers for disease progression hinders clinicians from tailoring treatment strategies effectively. OBJECTIVES To identify electroencephalography (EEG) biomarker that can track disease progression in PD. METHODS A total of 116 patients with PD were initially enrolled, whereas 63 completed 2-year follow-up evaluation. Fifty-eight age- and sex-matched healthy individuals were recruited as the control group. All participants underwent EEG and clinical assessments. Long-range temporal correlations (LRTC) of EEG data were analyzed using the detrended fluctuation analysis. RESULTS Patients with PD exhibited higher LRTC in left parietal θ oscillations (P = 0.0175) and lower LRTC in centro-parietal γ oscillations (P = 0.0258) compared to controls. LRTC in parietal γ oscillations inversely correlated with changes in Unified Parkinson's Disease Rating Scale (UPDRS) part III scores over 2 years (Spearman ρ = -0.34, P = 0.0082). Increased LRTC in left parietal θ oscillations were associated with rapid motor progression (P = 0.0107), defined as an annual increase in UPDRS part III score ≥3. In cognitive assessments, LRTC in parieto-occipital α oscillations exhibited a positive correlation with changes in Mini-Mental State Examination and Montreal Cognitive Assessment scores over 2 years (Spearman ρ = 0.27-0.38, P = 0.0037-0.0452). CONCLUSIONS LRTC patterns in EEG potentially predict rapid progression of both motor and non-motor manifestations in PD patients, enhancing clinical assessment and understanding of the disease. © 2024 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Chih-Hong Lee
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
| | - Hsiang-Han Chen
- Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei, Taiwan
| | - Jia-Pei Hong
- Department of Physical Medicine and Rehabilitation, Shuang Ho Hospital, Taipei Medical University, Taipei, Taiwan
| | - Ting-Wei Liao
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Isobel French
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
| | - Yen-Shi Lo
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Yi-Ru Wang
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Mei-Ling Cheng
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan
- Clinical Phenome Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Hsiu-Chuan Wu
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Chiung-Mei Chen
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Kuo-Hsuan Chang
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University College of Medicine, Taoyuan, Taiwan
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4
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Asadi A, Wiesman AI, Wiest C, Baillet S, Tan H, Muthuraman M. Electrophysiological approaches to informing therapeutic interventions with deep brain stimulation. NPJ Parkinsons Dis 2025; 11:20. [PMID: 39833210 PMCID: PMC11747345 DOI: 10.1038/s41531-024-00847-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 12/03/2024] [Indexed: 01/22/2025] Open
Abstract
Neuromodulation therapy comprises a range of non-destructive and adjustable methods for modulating neural activity using electrical stimulations, chemical agents, or mechanical interventions. Here, we discuss how electrophysiological brain recording and imaging at multiple scales, from cells to large-scale brain networks, contribute to defining the target location and stimulation parameters of neuromodulation, with an emphasis on deep brain stimulation (DBS).
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Affiliation(s)
- Atefeh Asadi
- Neural Engineering with Signal Analytics and Artificial Intelligence, Department of Neurology, University Clinic Würzburg, Würzburg, Germany.
| | - Alex I Wiesman
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada
| | - Christoph Wiest
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Muthuraman Muthuraman
- Neural Engineering with Signal Analytics and Artificial Intelligence, Department of Neurology, University Clinic Würzburg, Würzburg, Germany
- Informatics for Medical Technology, Institute of Computer Science, University Augsburg, Augsburg, Germany
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5
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Gimenez-Aparisi G, Guijarro-Estelles E, Chornet-Lurbe A, Cerveró-Albert D, Hao D, Li G, Ye-Lin Y. Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson's disease by resting-state electroencephalography: Systematic analysis of the influence of eye condition. Heliyon 2025; 11:e41500. [PMID: 39850414 PMCID: PMC11755055 DOI: 10.1016/j.heliyon.2024.e41500] [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: 03/06/2024] [Revised: 12/24/2024] [Accepted: 12/24/2024] [Indexed: 01/25/2025] Open
Abstract
Resting state electroencephalography (EEG) has proved useful in studying electrophysiological changes in neurodegenerative diseases. In many neuropathologies, microstate analysis of the eyes-closed (EC) scalp EEG is a robust and highly reproducible technique for assessing topological changes with high temporal resolution. However, scalp EEG microstate maps tend to underestimate the non-occipital or non-alpha-band networks, which can also be used to detect neuropathological changes. Recent evidence has shown that the source-space microstates can characterize distinct functional connectivity patterns but its clinical ability to detect neuropathological changes has not been demonstrated so far. It should also be remembered that the eye condition may play an important role in neural activity dynamics. The aim of this study was to systematically characterize the dynamic neuropathological features of sensor-space and source-space EEG microstates in PD patients with no cognitive impairment in both EC and EO conditions with the aim of identifying potential biomarkers that could be used as a complementary clinical screening method for early PD detection. We found that the dynamic features of the source-space microstates were more sensitive in detecting PD than the sensor-space microstates, while EO was able to detect neuropathological changes in PD patients better than EC. In EO, PD disease exhibited significantly higher occurrence and coverage in visual-network related source-space microstates and abnormally high duration in sensorimotor network-related microstates. Our results suggest that the source-space microstate analysis of resting-state EEG could provide robust biomarkers to detect early-stage PD, which would allow the development of patient-oriented strategies to prevent the disease and improve the patients' quality of life.
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Affiliation(s)
- G. Gimenez-Aparisi
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
| | - E. Guijarro-Estelles
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, China
| | - A. Chornet-Lurbe
- Servicio de Neurofisiología Clínica. Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, Xàtiva, 46800, València, Spain
| | - D. Cerveró-Albert
- Servicio de Neurofisiología Clínica. Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, Xàtiva, 46800, València, Spain
| | - Dongmei Hao
- College of Chemistry and Life Science, Beijing University of Technology, 100124, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, 100124, Beijing, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, China
| | - Guangfei Li
- College of Chemistry and Life Science, Beijing University of Technology, 100124, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, 100124, Beijing, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, China
| | - Y. Ye-Lin
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, China
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6
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Seo S, Kim S, Kim SP, Kim J, Kang SY, Chung D. Low-frequency EEG power and coherence differ between drug-induced parkinsonism and Parkinson's disease. Clin Neurophysiol 2024; 168:131-138. [PMID: 39509953 DOI: 10.1016/j.clinph.2024.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 10/03/2024] [Accepted: 10/24/2024] [Indexed: 11/15/2024]
Abstract
OBJECTIVE Drug-induced parkinsonism (DIP) ranks second to Parkinson's disease (PD) in causing parkinsonism. Despite sharing similar symptoms, DIP results from exposure to specific medications or substances, underscoring the need for accurate diagnosis. Here, we used resting-state electroencephalography (rsEEG) to investigate neural markers characterizing DIP and PD. METHODS We conducted a retrospective analysis of rsEEG recordings from 18 DIP patients, 43 de novo PD patients, and 12 healthy controls (HC). After exclusions, data from 15 DIP, 41 PD, and 12 HC participants were analyzed. EEG spectral power and inter-channel coherence were compared across the groups. RESULTS Our results demonstrated significant differences in rsEEG patterns among DIP, PD, and HC groups. DIP patients exhibited increased theta band power compared with PD patients and HC. Moreover, DIP patients showed higher delta band coherence compared with PD patients. CONCLUSION The current study highlights the differences in EEG spectral power and inter-channel coherence between DIP and PD patients. SIGNIFICANCE Our results suggest that rsEEG holds promise as a valuable tool for capturing differential characteristics between DIP and PD patients.
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Affiliation(s)
- Seungbeom Seo
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea; Department of Electrical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Sunmin Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Jaeho Kim
- Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Gyeonggi-do, South Korea.
| | - Suk Yun Kang
- Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Gyeonggi-do, South Korea.
| | - Dongil Chung
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea.
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7
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Zhao S, Dai G, Li J, Zhu X, Huang X, Li Y, Tan M, Wang L, Fang P, Chen X, Yan N, Liu H. An interpretable model based on graph learning for diagnosis of Parkinson's disease with voice-related EEG. NPJ Digit Med 2024; 7:3. [PMID: 38182737 PMCID: PMC10770376 DOI: 10.1038/s41746-023-00983-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/29/2023] [Indexed: 01/07/2024] Open
Abstract
Parkinson's disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained by the interpretable features and the stochastic nature of resting-state EEG. The present study proposes a novel and interpretable deep learning model, graph signal processing-graph convolutional networks (GSP-GCNs), using event-related EEG data obtained from a specific task involving vocal pitch regulation for PD diagnosis. By incorporating both local and global information from single-hop and multi-hop networks, our proposed GSP-GCNs models achieved an averaged classification accuracy of 90.2%, exhibiting a significant improvement of 9.5% over other deep learning models. Moreover, the interpretability analysis revealed discriminative distributions of large-scale EEG networks and topographic map of microstate MS5 learned by our models, primarily located in the left ventral premotor cortex, superior temporal gyrus, and Broca's area that are implicated in PD-related speech disorders, reflecting our GSP-GCN models' ability to provide interpretable insights identifying distinctive EEG biomarkers from large-scale networks. These findings demonstrate the potential of interpretable deep learning models coupled with voice-related EEG signals for distinguishing PD patients from healthy controls with accuracy and elucidating the underlying neurobiological mechanisms.
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Affiliation(s)
- Shuzhi Zhao
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Guangyan Dai
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jingting Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoxia Zhu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiyan Huang
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yongxue Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Mingdan Tan
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Lan Wang
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Peng Fang
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xi Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
| | - Nan Yan
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
| | - Hanjun Liu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
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8
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Molcho L, Maimon NB, Hezi N, Zeimer T, Intrator N, Gurevich T. Evaluation of Parkinson's disease early diagnosis using single-channel EEG features and auditory cognitive assessment. Front Neurol 2023; 14:1273458. [PMID: 38174098 PMCID: PMC10762798 DOI: 10.3389/fneur.2023.1273458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 11/29/2023] [Indexed: 01/05/2024] Open
Abstract
Background Parkinson's disease (PD) often presents with subtle early signs, making diagnosis difficult. F-DOPA PET imaging provides a reliable measure of dopaminergic function and is a primary tool for early PD diagnosis. This study aims to evaluate the ability of machine-learning (ML) extracted EEG features to predict F-DOPA results and distinguish between PD and non-PD patients. These features, extracted using a single-channel EEG during an auditory cognitive assessment, include EEG feature A0 associated with cognitive load in healthy subjects, and EEG feature L1 associated with cognitive task differentiation. Methods Participants in this study are comprised of cognitively healthy patients who had undergone an F-DOPA PET scan as a part of their standard care (n = 32), and cognitively healthy controls (n = 20). EEG data collected using the Neurosteer system during an auditory cognitive task, was decomposed using wavelet-packet analysis and machine learning methods for feature extraction. These features were used in a connectivity analysis that was applied in a similar manner to fMRI connectivity. A preliminary model that relies on the features and their connectivity was used to predict initially unrevealed F-DOPA test results. Then, generalized linear mixed models (LMM) were used to discern between PD and non-PD subjects based on EEG variables. Results The prediction model correctly classified patients with unrevealed scores as positive F-DOPA. EEG feature A0 and the Delta band revealed distinct activity patterns separating between study groups, with controls displaying higher activity than PD patients. In controls, EEG feature L1 showed variations between resting state and high-cognitive load, an effect lacking in PD patients. Conclusion Our findings exhibit the potential of single-channel EEG technology in combination with an auditory cognitive assessment to distinguish positive from negative F-DOPA PET scores. This approach shows promise for early PD diagnosis. Additional studies are needed to further verify the utility of this tool as a potential biomarker for PD.
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Affiliation(s)
- Lior Molcho
- Neurosteer Inc., New York, NY, United States
| | - Neta B. Maimon
- Neurosteer Inc., New York, NY, United States
- Department of Musicology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Neomi Hezi
- Movement Disorders Unit, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | | | - Nathan Intrator
- Neurosteer Inc., New York, NY, United States
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Tanya Gurevich
- Movement Disorders Unit, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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9
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Gimenez-Aparisi G, Guijarro-Estelles E, Chornet-Lurbe A, Ballesta-Martinez S, Pardo-Hernandez M, Ye-Lin Y. Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography. Heliyon 2023; 9:e20625. [PMID: 37829809 PMCID: PMC10565694 DOI: 10.1016/j.heliyon.2023.e20625] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 07/24/2023] [Accepted: 10/02/2023] [Indexed: 10/14/2023] Open
Abstract
While resting state electroencephalography (EEG) provides relevant information on pathological changes in Parkinson's disease, most studies focus on the eyes-closed EEG biomarkers. Recent evidence has shown that both eyes-open EEG and reactivity to eyes-opening can also differentiate Parkinson's disease from healthy aging, but no consensus has been reached on a discriminatory capability benchmark. The aim of this study was to determine the resting-state EEG biomarkers suitable for real-time application that can differentiate Parkinson's patients from healthy subjects under both eyes closed and open. For this, we analysed and compared the quantitative EEG analyses of 13 early-stage cognitively normal Parkinson's patients with an age and sex-matched healthy group. We found that Parkinson's disease exhibited abnormal excessive theta activity in eyes-closed, which was reflected by a significantly higher relative theta power, a higher time percentage with a frequency peak in the theta band and a reduced alpha/theta ratio, while Parkinson's patients showed a significantly steeper non-oscillatory spectral slope activity than that of healthy subjects. We also found considerably less alpha and beta reactivity to eyes-opening in Parkinson's disease plus a significant moderate correlation between these EEG-biomarkers and the MDS-UPDRS score, used to assesses the clinical symptoms of Parkinson's Disease. Both EEG recordings with the eyes open and reactivity to eyes-opening provided additional information to the eyes-closed condition. We thus strongly recommend that both eyes open and closed be used in clinical practice recording protocols to promote EEG as a complementary non-invasive screening method for the early detection of Parkinson's disease, which would allow clinicians to design patient-oriented treatment and improve the patient's quality of life.
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Affiliation(s)
- G. Gimenez-Aparisi
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
| | - E. Guijarro-Estelles
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
| | - A. Chornet-Lurbe
- Servicio de Neurofisiología Clínica, Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, 46800, Xàtiva, València, Spain
| | - S. Ballesta-Martinez
- Servicio de Neurofisiología Clínica, Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, 46800, Xàtiva, València, Spain
| | - M. Pardo-Hernandez
- Servicio de Neurofisiología Clínica, Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, 46800, Xàtiva, València, Spain
| | - Y. Ye-Lin
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
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10
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Jacob D, Guerrini L, Pescaglia F, Pierucci S, Gelormini C, Minutolo V, Fratini A, Di Lorenzo G, Petersen H, Gargiulo P. Adaptation strategies and neurophysiological response in early-stage Parkinson's disease: BioVRSea approach. Front Hum Neurosci 2023; 17:1197142. [PMID: 37529404 PMCID: PMC10389765 DOI: 10.3389/fnhum.2023.1197142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 06/28/2023] [Indexed: 08/03/2023] Open
Abstract
Introduction There is accumulating evidence that many pathological conditions affecting human balance are consequence of postural control (PC) failure or overstimulation such as in motion sickness. Our research shows the potential of using the response to a complex postural control task to assess patients with early-stage Parkinson's Disease (PD). Methods We developed a unique measurement model, where the PC task is triggered by a moving platform in a virtual reality environment while simultaneously recording EEG, EMG and CoP signals. This novel paradigm of assessment is called BioVRSea. We studied the interplay between biosignals and their differences in healthy subjects and with early-stage PD. Results Despite the limited number of subjects (29 healthy and nine PD) the results of our work show significant differences in several biosignals features, demonstrating that the combined output of posturography, muscle activation and cortical response is capable of distinguishing healthy from pathological. Discussion The differences measured following the end of the platform movement are remarkable, as the induced sway is different between the two groups and triggers statistically relevant cortical activities in α and θ bands. This is a first important step to develop a multi-metric signature able to quantify PC and distinguish healthy from pathological response.
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Affiliation(s)
- Deborah Jacob
- Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland
| | - Lorena Guerrini
- Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland
- Department of Engineering, University of Campania L. Vanvitelli, Aversa, Italy
| | - Federica Pescaglia
- Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland
- Department of Electrical, Electronic and Information Engineering, University of Bologna, Cesena, Italy
| | - Simona Pierucci
- Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Carmine Gelormini
- Department of Civil Engineering and Computer Science Engineering, Tor Vergata University of Rome, Rome, Italy
| | - Vincenzo Minutolo
- Department of Engineering, University of Campania L. Vanvitelli, Aversa, Italy
| | - Antonio Fratini
- Engineering for Health Research Centre, Aston University, Birmingham, United Kingdom
| | - Giorgio Di Lorenzo
- Laboratory of Psychophysiology and Cognitive Neuroscience, Department of Systems Medicine, Tor Vergata University of Rome, Rome, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Hannes Petersen
- Department of Anatomy, University of Iceland, Reykjavik, Iceland
| | - Paolo Gargiulo
- Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland
- Department of Science, Landspitali University Hospital, Reykjavik, Iceland
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11
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Angelopoulou K, Vlachakis D, Darviri C, Chrousos GP, Kanaka-Gantenbein C, Bacopoulou F. Brain Activity of Professional Dancers During Audiovisual Stimuli Exposure: A Systematic Review. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1425:457-467. [PMID: 37581819 DOI: 10.1007/978-3-031-31986-0_44] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
Many studies have shown the effect of dance to the brain. It seems that long-term practice modulates brain plasticity and visuomotor skills, as it activates the Action Observation Network (AON). The aim of this systematic review was to evaluate potential differences in the brain activity (visuomotor skills) between professional dancers and non-dancer adults, measured by electroencephalography (EEG), during the observation of an individual who is dancing (video dance stimuli). This literature search was conducted from February to June 2022, according to the PRISMA guidelines, in the PubMed database using advanced search, mesh terms, and extensive manual search. The included articles were published in English. Specifically, case-control studies were selected, which used healthy adults, professional dancers, and non-dancers as participants, who were exposed to video dance clips and measured by EEG. The articles were excluded if they were based on different type of study, unhealthy population, control group with athletic background, different type of stimuli (rhythmic), or different type of task and procedure. The ratings of quality of evidence were conducted using the Joanna Briggs Institute's (JBI) critical appraisal tool. Five case-control studies were included with 193 participants in total, 87% females. The participating groups of professional dancers (n = 12-25) had mean age 25.14 years, with at least 9-19 years of professional training, whereas control groups had the same sample size, mean age of 24.14 years, and no experience in dancing. Most of the studies presented high methodological quality. All studies showed significant differences in dancers' brain activity, especially regarding the visuomotor skills. The results showed faster activation of AON demonstrated by higher P300 at the frontocentral regions and increased sensitivity of the occipital temporal cortex. Dancers could cope easier with familiar-unfamiliar and effortful-effortless movements. They also demonstrated faster alpha band peak frequency, stronger synchrony over the bands theta, beta, gamma during the audiovisual stimuli, and the ability to encode faster the visual information. The results demonstrate that dancers had better visuomotor skills suggesting dance-enhanced neuroplasticity, as professional dancers processed their actions easier. Dance, which includes visuomotor tasks, could help in prevention, therapy, and rehabilitation of neurodegenerative diseases or movement disorders.
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Affiliation(s)
- Kyriaki Angelopoulou
- School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Dimitrios Vlachakis
- Laboratory of Genetics, Department of Biotechnology, School of Applied Biology and Biotechnology, Agricultural University of Athens, Athens, Greece
| | - Christina Darviri
- School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - George P Chrousos
- University Research Institute of Maternal and Child Health & Precision Medicine, and UNESCO Chair in Adolescent Health Care, Aghia Sophia Children's Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Christina Kanaka-Gantenbein
- First Department of Pediatrics, School of Medicine, Aghia Sophia Children's Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Flora Bacopoulou
- Center for Adolescent Medicine and UNESCO Chair in Adolescent Health Care, First Department of Pediatrics, School of Medicine, Aghia Sophia Children's Hospital, National and Kapodistrian University of Athens, Athens, Greece.
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12
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Brak IV, Filimonova E, Zakhariya O, Khasanov R, Stepanyan I. Transcranial Current Stimulation as a Tool of Neuromodulation of Cognitive Functions in Parkinson’s Disease. Front Neurosci 2022; 16:781488. [PMID: 35903808 PMCID: PMC9314857 DOI: 10.3389/fnins.2022.781488] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 04/28/2022] [Indexed: 11/13/2022] Open
Abstract
Decrease in cognitive function is one of the most common causes of poor life quality and early disability in patients with Parkinson’s disease (PD). Existing methods of treatment are aimed at both correction of motor and non-motor symptoms. Methods of adjuvant therapy (or complementary therapy) for maintaining cognitive functions in patients with PD are of interest. A promising subject of research in this regard is the method of transcranial electric current stimulation (tES). Here we reviewed the current understanding of the pathogenesis of cognitive impairment in PD and of the effects of transcranial direct current stimulation and transcranial alternating current stimulation on the cognitive function of patients with PD-MCI (Parkinson’s Disease–Mild Cognitive Impairment).
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Affiliation(s)
- Ivan V. Brak
- Laboratory of Comprehensive Problems of Risk Assessment to Population and Workers’ Health, Federal State Budgetary Scientific Institution “Izmerov Research Institute of Occupational Health”, Moscow, Russia
- “Engiwiki” Scientific and Engineering Projects Laboratory, Department of Information Technologies, Novosibirsk State University, Novosibirsk, Russia
- *Correspondence: Ivan V. Brak,
| | | | - Oleg Zakhariya
- Faculty of Philosophy, Lomonosov Moscow State University, Moscow, Russia
| | - Rustam Khasanov
- Faculty of Philosophy, Lomonosov Moscow State University, Moscow, Russia
- Independent Researcher, Novosibirsk, Russia
| | - Ivan Stepanyan
- Peoples’ Friendship University of Russia (RUDN University), Moscow, Russia
- Mechanical Engineering Research Institute of the Russian Academy of Sciences, Moscow, Russia
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13
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Chang KH, French IT, Liang WK, Lo YS, Wang YR, Cheng ML, Huang NE, Wu HC, Lim SN, Chen CM, Juan CH. Evaluating the Different Stages of Parkinson's Disease Using Electroencephalography With Holo-Hilbert Spectral Analysis. Front Aging Neurosci 2022; 14:832637. [PMID: 35619940 PMCID: PMC9127298 DOI: 10.3389/fnagi.2022.832637] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 03/08/2022] [Indexed: 01/04/2023] Open
Abstract
Electroencephalography (EEG) can reveal the abnormalities of dopaminergic subcortico-cortical circuits in patients with Parkinson's disease (PD). However, conventional time-frequency analysis of EEG signals cannot fully reveal the non-linear processes of neural activities and interactions. A novel Holo-Hilbert Spectral Analysis (HHSA) was applied to reveal non-linear features of resting state EEG in 99 PD patients and 59 healthy controls (HCs). PD patients demonstrated a reduction of β bands in frontal and central regions, and reduction of γ bands in central, parietal, and temporal regions. Compared with early-stage PD patients, late-stage PD patients demonstrated reduction of β bands in the posterior central region, and increased θ and δ2 bands in the left parietal region. θ and β bands in all brain regions were positively correlated with Hamilton depression rating scale scores. Machine learning algorithms using three prioritized HHSA features demonstrated "Bag" with the best accuracy of 0.90, followed by "LogitBoost" with an accuracy of 0.89. Our findings strengthen the application of HHSA to reveal high-dimensional frequency features in EEG signals of PD patients. The EEG characteristics extracted by HHSA are important markers for the identification of depression severity and diagnosis of PD.
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Affiliation(s)
- Kuo-Hsuan Chang
- Department of Neurology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Isobel Timothea French
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Taiwan International Graduate Program in Interdisciplinary Neuroscience, National Central University and Academia Sinica, Taipei, Taiwan
| | - Wei-Kuang Liang
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
| | - Yen-Shi Lo
- Department of Neurology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Yi-Ru Wang
- Department of Neurology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Mei-Ling Cheng
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan
- Clinical Phenome Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Norden E. Huang
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
- Data Analysis and Application Laboratory, The First Institute of Oceanography, Qingdao, China
| | - Hsiu-Chuan Wu
- Department of Neurology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Siew-Na Lim
- Department of Neurology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Chiung-Mei Chen
- Department of Neurology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
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14
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Yang CY, Huang YZ. Parkinson’s Disease Classification Using Machine Learning Approaches and Resting-State EEG. J Med Biol Eng 2022. [DOI: 10.1007/s40846-022-00695-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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15
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Wagner JR, Schaper M, Hamel W, Westphal M, Gerloff C, Engel AK, Moll CKE, Gulberti A, Pötter-Nerger M. Combined Subthalamic and Nigral Stimulation Modulates Temporal Gait Coordination and Cortical Gait-Network Activity in Parkinson's Disease. Front Hum Neurosci 2022; 16:812954. [PMID: 35295883 PMCID: PMC8919031 DOI: 10.3389/fnhum.2022.812954] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 01/27/2022] [Indexed: 01/10/2023] Open
Abstract
Background Freezing of gait (FoG) is a disabling burden for Parkinson's disease (PD) patients with poor response to conventional therapies. Combined deep brain stimulation of the subthalamic nucleus and substantia nigra (STN+SN DBS) moved into focus as a potential therapeutic option to treat the parkinsonian gait disorder and refractory FoG. The mechanisms of action of DBS within the cortical-subcortical-basal ganglia network on gait, particularly at the cortical level, remain unclear. Methods Twelve patients with idiopathic PD and chronically-implanted DBS electrodes were assessed on their regular dopaminergic medication in a standardized stepping in place paradigm. Patients executed the task with DBS switched off (STIM OFF), conventional STN DBS and combined STN+SN DBS and were compared to healthy matched controls. Simultaneous high-density EEG and kinematic measurements were recorded during resting-state, effective stepping, and freezing episodes. Results Clinically, STN+SN DBS was superior to conventional STN DBS in improving temporal stepping variability of the more affected leg. During resting-state and effective stepping, the cortical activity of PD patients in STIM OFF was characterized by excessive over-synchronization in the theta (4-8 Hz), alpha (9-13 Hz), and high-beta (21-30 Hz) band compared to healthy controls. Both active DBS settings similarly decreased resting-state alpha power and reduced pathologically enhanced high-beta activity during resting-state and effective stepping compared to STIM OFF. Freezing episodes during STN DBS and STN+SN DBS showed spectrally and spatially distinct cortical activity patterns when compared to effective stepping. During STN DBS, FoG was associated with an increase in cortical alpha and low-beta activity over central cortical areas, while with STN+SN DBS, an increase in high-beta was prominent over more frontal areas. Conclusions STN+SN DBS improved temporal aspects of parkinsonian gait impairment compared to conventional STN DBS and differentially affected cortical oscillatory patterns during regular locomotion and freezing suggesting a potential modulatory effect on dysfunctional cortical-subcortical communication in PD.
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Affiliation(s)
- Jonas R. Wagner
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Miriam Schaper
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Wolfgang Hamel
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Manfred Westphal
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andreas K. Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian K. E. Moll
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alessandro Gulberti
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Monika Pötter-Nerger
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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16
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Peng-Li D, Alves Da Mota P, Correa CMC, Chan RCK, Byrne DV, Wang QJ. “Sound” Decisions: The Combined Role of Ambient Noise and Cognitive Regulation on the Neurophysiology of Food Cravings. Front Neurosci 2022; 16:827021. [PMID: 35250463 PMCID: PMC8888436 DOI: 10.3389/fnins.2022.827021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/17/2022] [Indexed: 12/24/2022] Open
Abstract
Our ability to evaluate long-term goals over immediate rewards is manifested in the brain’s decision circuit. Simplistically, it can be divided into a fast, impulsive, reward “system 1” and a slow, deliberate, control “system 2.” In a noisy eating environment, our cognitive resources may get depleted, potentially leading to cognitive overload, emotional arousal, and consequently more rash decisions, such as unhealthy food choices. Here, we investigated the combined impact of cognitive regulation and ambient noise on food cravings through neurophysiological activity. Thirty-seven participants were recruited for an adapted version of the Regulation of Craving (ROC) task. All participants underwent two sessions of the ROC task; once with soft ambient restaurant noise (∼50 dB) and once with loud ambient restaurant noise (∼70 dB), while data from electroencephalography (EEG), electrodermal activity (EDA), and self-reported craving were collected for all palatable food images presented in the task. The results indicated that thinking about future (“later”) consequences vs. immediate (“now”) sensations associated with the food decreased cravings, which were mediated by frontal EEG alpha power. Likewise, “later” trials also increased frontal alpha asymmetry (FAA) —an index for emotional motivation. Furthermore, loud (vs. soft) noise increased alpha, beta, and theta activity, but for theta activity, this was solely occurring during “later” trials. Similarly, EDA signal peak probability was also higher during loud noise. Collectively, our findings suggest that the presence of loud ambient noise in conjunction with prospective thinking can lead to the highest emotional arousal and cognitive load as measured by EDA and EEG, respectively, both of which are important in regulating cravings and decisions. Thus, exploring the combined effects of interoceptive regulation and exteroceptive cues on food-related decision-making could be methodologically advantageous in consumer neuroscience and entail theoretical, commercial, and managerial implications.
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Affiliation(s)
- Danni Peng-Li
- Food Quality Perception and Society Team, iSENSE Lab, Department of Food Science, Aarhus University, Aarhus, Denmark
- Sino-Danish College (SDC), University of Chinese Academy of Sciences, Beijing, China
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- *Correspondence: Danni Peng-Li,
| | - Patricia Alves Da Mota
- Food Quality Perception and Society Team, iSENSE Lab, Department of Food Science, Aarhus University, Aarhus, Denmark
- Department of Clinical Medicine, Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Camile Maria Costa Correa
- Food Quality Perception and Society Team, iSENSE Lab, Department of Food Science, Aarhus University, Aarhus, Denmark
| | - Raymond C. K. Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Derek Victor Byrne
- Food Quality Perception and Society Team, iSENSE Lab, Department of Food Science, Aarhus University, Aarhus, Denmark
- Sino-Danish College (SDC), University of Chinese Academy of Sciences, Beijing, China
| | - Qian Janice Wang
- Food Quality Perception and Society Team, iSENSE Lab, Department of Food Science, Aarhus University, Aarhus, Denmark
- Sino-Danish College (SDC), University of Chinese Academy of Sciences, Beijing, China
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17
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Covantes-Osuna C, López JB, Paredes O, Vélez-Pérez H, Romo-Vázquez R. Multilayer Network Approach in EEG Motor Imagery with an Adaptive Threshold. SENSORS 2021; 21:s21248305. [PMID: 34960399 PMCID: PMC8704651 DOI: 10.3390/s21248305] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/05/2021] [Accepted: 12/06/2021] [Indexed: 12/15/2022]
Abstract
The brain has been understood as an interconnected neural network generally modeled as a graph to outline the functional topology and dynamics of brain processes. Classic graph modeling is based on single-layer models that constrain the traits conveyed to trace brain topologies. Multilayer modeling, in contrast, makes it possible to build whole-brain models by integrating features of various kinds. The aim of this work was to analyze EEG dynamics studies while gathering motor imagery data through single-layer and multilayer network modeling. The motor imagery database used consists of 18 EEG recordings of four motor imagery tasks: left hand, right hand, feet, and tongue. Brain connectivity was estimated by calculating the coherence adjacency matrices from each electrophysiological band (δ, θ, α and β) from brain areas and then embedding them by considering each band as a single-layer graph and a layer of the multilayer brain models. Constructing a reliable multilayer network topology requires a threshold that distinguishes effective connections from spurious ones. For this reason, two thresholds were implemented, the classic fixed (average) one and Otsu’s version. The latter is a new proposal for an adaptive threshold that offers reliable insight into brain topology and dynamics. Findings from the brain network models suggest that frontal and parietal brain regions are involved in motor imagery tasks.
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18
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Morawska MM, Moreira CG, Ginde VR, Valko PO, Weiss T, Büchele F, Imbach LL, Masneuf S, Kollarik S, Prymaczok N, Gerez JA, Riek R, Baumann CR, Noain D. Slow-wave sleep affects synucleinopathy and regulates proteostatic processes in mouse models of Parkinson's disease. Sci Transl Med 2021; 13:eabe7099. [PMID: 34878820 DOI: 10.1126/scitranslmed.abe7099] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Marta M Morawska
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland.,University of Zurich (UZH), Neuroscience Center Zurich (ZNZ), Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Carlos G Moreira
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland.,ETH Zurich, Neuroscience Center Zurich (ZNZ), Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Varun R Ginde
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland
| | - Philipp O Valko
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland
| | - Tobias Weiss
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland
| | - Fabian Büchele
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland
| | - Lukas L Imbach
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland
| | - Sophie Masneuf
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland
| | - Sedef Kollarik
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland.,University of Zurich (UZH), Neuroscience Center Zurich (ZNZ), Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Natalia Prymaczok
- ETH Zurich, Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 2, Zurich 8093, Switzerland
| | - Juan A Gerez
- ETH Zurich, Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 2, Zurich 8093, Switzerland
| | - Roland Riek
- ETH Zurich, Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 2, Zurich 8093, Switzerland
| | - Christian R Baumann
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland.,University of Zurich (UZH), Neuroscience Center Zurich (ZNZ), Winterthurerstrasse 190, Zurich 8057, Switzerland.,Center of Competence Sleep and Health Zurich, University of Zurich, Frauenklinikstrasse 26, Zurich 8091, Switzerland
| | - Daniela Noain
- Department of Neurology, University Hospital Zurich (USZ), Frauenklinikstrasse 26, Zurich 8091, Switzerland.,University of Zurich (UZH), Neuroscience Center Zurich (ZNZ), Winterthurerstrasse 190, Zurich 8057, Switzerland.,Center of Competence Sleep and Health Zurich, University of Zurich, Frauenklinikstrasse 26, Zurich 8091, Switzerland
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19
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Maggioni E, Arienti F, Minella S, Mameli F, Borellini L, Nigro M, Cogiamanian F, Bianchi AM, Cerutti S, Barbieri S, Brambilla P, Ardolino G. Effective Connectivity During Rest and Music Listening: An EEG Study on Parkinson's Disease. Front Aging Neurosci 2021; 13:657221. [PMID: 33994997 PMCID: PMC8113619 DOI: 10.3389/fnagi.2021.657221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 03/31/2021] [Indexed: 11/30/2022] Open
Abstract
Music-based interventions seem to enhance motor, sensory and cognitive functions in Parkinson’s disease (PD), but the underlying action mechanisms are still largely unknown. This electroencephalography (EEG) study aimed to investigate the effective connectivity patterns characterizing PD in the resting state and during music listening. EEG recordings were obtained from fourteen non-demented PD patients and 12 healthy controls, at rest and while listening to three music tracks. Theta- and alpha-band power spectral density and multivariate partial directed coherence were computed. Power and connectivity measures were compared between patients and controls in the four conditions and in music vs. rest. Compared to controls, patients showed enhanced theta-band power and slightly enhanced alpha-band power, but markedly reduced theta- and alpha-band interactions among EEG channels, especially concerning the information received by the right central channel. EEG power differences were partially reduced by music listening, which induced power increases in controls but not in patients. Connectivity differences were slightly compensated by music, whose effects largely depended on the track. In PD, music enhanced the frontotemporal inter-hemispheric communication. Our findings suggest that PD is characterized by enhanced activity but reduced information flow within the EEG network, being only partially normalized by music. Nevertheless, music capability to facilitate inter-hemispheric communication might underlie its beneficial effects on PD pathophysiology and should be further investigated.
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Affiliation(s)
- Eleonora Maggioni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Federica Arienti
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Stella Minella
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Francesca Mameli
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Linda Borellini
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Martina Nigro
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Filippo Cogiamanian
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Anna Maria Bianchi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Sergio Cerutti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Sergio Barbieri
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.,Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Gianluca Ardolino
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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20
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Kim JA, Davis KD. Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences. J Neurophysiol 2021; 125:938-956. [PMID: 33567968 DOI: 10.1152/jn.00530.2020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.
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Affiliation(s)
- Junseok A Kim
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Karen D Davis
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Surgery, University of Toronto, Toronto, Ontario, Canada
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21
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Parkinsonism Alters Beta Burst Dynamics across the Basal Ganglia-Motor Cortical Network. J Neurosci 2021; 41:2274-2286. [PMID: 33483430 DOI: 10.1523/jneurosci.1591-20.2021] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 01/13/2021] [Accepted: 01/15/2021] [Indexed: 01/30/2023] Open
Abstract
Elevated synchronized oscillatory activity in the beta band has been hypothesized to be a pathophysiological marker of Parkinson's disease (PD). Recent studies have suggested that parkinsonism is closely associated with increased amplitude and duration of beta burst activity in the subthalamic nucleus (STN). How beta burst dynamics are altered from the normal to parkinsonian state across the basal ganglia-thalamocortical (BGTC) motor network, however, remains unclear. In this study, we simultaneously recorded local field potential activity from the STN, internal segment of the globus pallidus (GPi), and primary motor cortex (M1) in three female rhesus macaques, and characterized how beta burst activity changed as the animals transitioned from normal to progressively more severe parkinsonian states. Parkinsonism was associated with an increased incidence of beta bursts with longer duration and higher amplitude in the low beta band (8-20 Hz) in both the STN and GPi, but not in M1. We observed greater concurrence of beta burst activity, however, across all recording sites (M1, STN, and GPi) in PD. The simultaneous presence of low beta burst activity across multiple nodes of the BGTC network that increased with severity of PD motor signs provides compelling evidence in support of the hypothesis that low beta synchronized oscillations play a significant role in the underlying pathophysiology of PD. Given its immersion throughout the motor circuit, we hypothesize that this elevated beta-band activity interferes with spatial-temporal processing of information flow in the BGTC network that contributes to the impairment of motor function in PD.SIGNIFICANCE STATEMENT This study fills a knowledge gap regarding the change in temporal dynamics and coupling of beta burst activity across the basal ganglia-thalamocortical (BGTC) network during the evolution from normal to progressively more severe parkinsonian states. We observed that changes in beta oscillatory activity occur throughout BGTC and that increasing severity of parkinsonism was associated with a higher incidence of longer duration, higher amplitude low beta bursts in the basal ganglia, and increased concurrence of beta bursts across the subthalamic nucleus, globus pallidus, and motor cortex. These data provide new insights into the potential role of changes in the temporal dynamics of low beta activity within the BGTC network in the pathogenesis of Parkinson's disease.
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22
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Wang Y, Dong G, Shi L, Yang T, Chen R, Wang H, Han G. Depression of auditory cortex excitability by transcranial alternating current stimulation. Neurosci Lett 2020; 742:135559. [PMID: 33359048 DOI: 10.1016/j.neulet.2020.135559] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 12/02/2020] [Accepted: 12/07/2020] [Indexed: 11/27/2022]
Abstract
Transcranial alternating current stimulation (tACS) is a type of noninvasive brain stimulation technique that has been shown to modulate motor, cognitive and memory function. Direct electrophysiological evidence of an interaction between tACS and the auditory cortex excitability has rarely been reported. Different stimulation parameters and areas of tACS may have different influence on the regulatory results. In this study, 11-Hz tACS was applied to the auditory cortex of 12 subjects with normal hearing in order to explore its effects on the auditory steady-state response (ASSR). The results indicate that tACS has an inhibitory effect on 40-Hz ASSR. In addition, EEG source analysis shows that 11-Hz tACS may enhance the activity of the middle temporal gyrus under both sham and real conditions, while the estimated source activity of the posterior cingulate gyrus may be reduced under real condition. The results reveal that tACS applied to the temporal lobe of humans will make the 40-Hz ASSR a tendency to decrease, and help improve the understanding of modulation of tACS-induced auditory cortex excitability changes in humans.
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Affiliation(s)
- Yao Wang
- School of Electronics & Information Engineering, Tiangong University, Tianjin, 300387, China; Department of Biomedical Engineering, School of Life Sciences, Tiangong University, Tianjin, 300387, China; School of Precision Instruments and Optoelectronics Engineering Tianjin University, Tianjin University, Tianjin, 300072, China
| | - Gaoyuan Dong
- School of Electronics & Information Engineering, Tiangong University, Tianjin, 300387, China
| | - Limeng Shi
- Department of Biomedical Engineering, School of Life Sciences, Tiangong University, Tianjin, 300387, China
| | - Tianshun Yang
- School of Electronics & Information Engineering, Tiangong University, Tianjin, 300387, China
| | - Ruijuan Chen
- School of Electronics & Information Engineering, Tiangong University, Tianjin, 300387, China; Department of Biomedical Engineering, School of Life Sciences, Tiangong University, Tianjin, 300387, China
| | - Huiquan Wang
- School of Electronics & Information Engineering, Tiangong University, Tianjin, 300387, China; Department of Biomedical Engineering, School of Life Sciences, Tiangong University, Tianjin, 300387, China; School of Precision Instruments and Optoelectronics Engineering Tianjin University, Tianjin University, Tianjin, 300072, China
| | - Guang Han
- School of Electronics & Information Engineering, Tiangong University, Tianjin, 300387, China; Department of Biomedical Engineering, School of Life Sciences, Tiangong University, Tianjin, 300387, China; School of Precision Instruments and Optoelectronics Engineering Tianjin University, Tianjin University, Tianjin, 300072, China.
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23
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Pal A, Pegwal N, Behari M, Sharma R. High delta and gamma EEG power in resting state characterise dementia in Parkinson’s patients. Biomark Neuropsychiatry 2020. [DOI: 10.1016/j.bionps.2020.100027] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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24
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Lejko N, Larabi DI, Herrmann CS, Aleman A, Ćurčić-Blake B. Alpha Power and Functional Connectivity in Cognitive Decline: A Systematic Review and Meta-Analysis. J Alzheimers Dis 2020; 78:1047-1088. [PMID: 33185607 PMCID: PMC7739973 DOI: 10.3233/jad-200962] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background: Mild cognitive impairment (MCI) is a stage between expected age-related cognitive decline and dementia. Dementias have been associated with changes in neural oscillations across the frequency spectrum, including the alpha range. Alpha is the most prominent rhythm in human EEG and is best detected during awake resting state (RS). Though several studies measured alpha power and synchronization in MCI, findings have not yet been integrated. Objective: To consolidate findings on power and synchronization of alpha oscillations across stages of cognitive decline. Methods: We included studies published until January 2020 that compared power or functional connectivity between 1) people with MCI and cognitively healthy older adults (OA) or people with a neurodegenerative dementia, and 2) people with progressive and stable MCI. Random-effects meta-analyses were performed when enough data was available. Results: Sixty-eight studies were included in the review. Global RS alpha power was lower in AD than in MCI (ES = –0.30; 95% CI = –0.51, –0.10; k = 6), and in MCI than in OA (ES = –1.49; 95% CI = –2.69, –0.29; k = 5). However, the latter meta-analysis should be interpreted cautiously due to high heterogeneity. The review showed lower RS alpha power in progressive than in stable MCI, and lower task-related alpha reactivity in MCI than in OA. People with MCI had both lower and higher functional connectivity than OA. Publications lacked consistency in MCI diagnosis and EEG measures. Conclusion: Research indicates that RS alpha power decreases with increasing impairment, and could—combined with measures from other frequency bands—become a biomarker of early cognitive decline.
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Affiliation(s)
- Nena Lejko
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands
| | - Daouia I Larabi
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - André Aleman
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands
| | - Branislava Ćurčić-Blake
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands
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25
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A brain connectivity characterization of children with different levels of mathematical achievement based on graph metrics. PLoS One 2020; 15:e0227613. [PMID: 31951604 PMCID: PMC6968862 DOI: 10.1371/journal.pone.0227613] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 12/21/2019] [Indexed: 11/30/2022] Open
Abstract
Recent studies aiming to facilitate mathematical skill development in primary school children have explored the electrophysiological characteristics associated with different levels of arithmetic achievement. The present work introduces an alternative EEG signal characterization using graph metrics and, based on such features, a classification analysis using a decision tree model. This proposal aims to identify group differences in brain connectivity networks with respect to mathematical skills in elementary school children. The methods of analysis utilized were signal-processing (EEG artifact removal, Laplacian filtering, and magnitude square coherence measurement) and the characterization (Graph metrics) and classification (Decision Tree) of EEG signals recorded during performance of a numerical comparison task. Our results suggest that the analysis of quantitative EEG frequency-band parameters can be used successfully to discriminate several levels of arithmetic achievement. Specifically, the most significant results showed an accuracy of 80.00% (α band), 78.33% (δ band), and 76.67% (θ band) in differentiating high-skilled participants from low-skilled ones, averaged-skilled subjects from all others, and averaged-skilled participants from low-skilled ones, respectively. The use of a decision tree tool during the classification stage allows the identification of several brain areas that seem to be more specialized in numerical processing.
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26
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Gallay MN, Moser D, Rossi F, Magara AE, Strasser M, Bühler R, Kowalski M, Pourtehrani P, Dragalina C, Federau C, Jeanmonod D. MRgFUS Pallidothalamic Tractotomy for Chronic Therapy-Resistant Parkinson's Disease in 51 Consecutive Patients: Single Center Experience. Front Surg 2020; 6:76. [PMID: 31993437 PMCID: PMC6971056 DOI: 10.3389/fsurg.2019.00076] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 12/19/2019] [Indexed: 11/13/2022] Open
Abstract
Background: There is a long history, beginning in the 1940s, of ablative neurosurgery on the pallidal efferent fibers to treat patients suffering from Parkinson's disease (PD). Since the early 1990s, we undertook a re-actualization of the approach to the subthalamic region, and proposed, on a histological basis, to target specifically the pallidothalamic tract at the level of Forel's field H1. This intervention, the pallidothalamic tractotomy (PTT), has been performed since 2011 using the MR-guided focused ultrasound (MRgFUS) technique. A reappraisal of the histology of the pallidothalamic tract was combined recently with an optimization of our lesioning strategy using thermal dose control. Objective: This study was aimed at demonstrating the efficacy and risk profile of MRgFUS PTT against chronic therapy-resistant PD. Methods: This consecutive case series reflects our current treatment routine and was collected between 2017 and 2018. Fifty-two interventions in 47 patients were included. Fifteen patients received bilateral PTT. The median follow-up was 12 months. Results: The Unified Parkinson's Disease Rating Scale (UPDRS) off-medication postoperative score was compared to the baseline on-medication score and revealed percentage reductions of the mean of 84% for tremor, 70% for rigidity, and 73% for distal hypobradykinesia, all values given for the treated side. Axial items (for voice, trunk and gait) were not significantly improved. PTT achieved 100% suppression of on-medication dyskinesias as well as reduction in pain (p < 0.001), dystonia (p < 0.001) and REM sleep disorders (p < 0.01). Reduction of the mean L-Dopa intake was 55%. Patients reported an 88% mean tremor relief and 82% mean global symptom relief on the operated side and 69% mean global symptom improvement for the whole body. There was no significant change of cognitive functions. The small group of bilateral PTTs at 1 year follow-up shows similar results as compared to unilateral PTTs but does not allow to draw firm conclusions at this point. Conclusion: MRgFUS PTT was shown to be a safe and effective intervention for PD patients, addressing all symptoms, with varying effectiveness. We discuss the need to integrate the preoperative state of the thalamocortical network as well as the psycho-emotional dimension.
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Affiliation(s)
- Marc N Gallay
- SoniModul, Center for Ultrasound Functional Neurosurgery, Solothurn, Switzerland
| | - David Moser
- SoniModul, Center for Ultrasound Functional Neurosurgery, Solothurn, Switzerland
| | - Franziska Rossi
- SoniModul, Center for Ultrasound Functional Neurosurgery, Solothurn, Switzerland
| | | | - Maja Strasser
- Neurologische Praxis Solothurn, Solothurn, Switzerland
| | - Robert Bühler
- Neurological Division, Bürgerspital Solothurn, Solothurn, Switzerland
| | | | | | | | - Christian Federau
- Department of Radiology, University Hospital Basel, Basel, Switzerland.,Institute for Biomedical Engineering, ETH Zürich, University Zürich, Zurich, Switzerland
| | - Daniel Jeanmonod
- SoniModul, Center for Ultrasound Functional Neurosurgery, Solothurn, Switzerland
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27
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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: 15] [Impact Index Per Article: 3.0] [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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28
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Wang Z, Yan J, Wang X, Yuan Y, Li X. Transcranial Ultrasound Stimulation Directly Influences the Cortical Excitability of the Motor Cortex in Parkinsonian Mice. Mov Disord 2019; 35:693-698. [PMID: 31829467 DOI: 10.1002/mds.27952] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 10/28/2019] [Accepted: 11/25/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Low-intensity transcranial ultrasound stimulation is a new noninvasive brain modulation method with high spatial resolution and high penetration depth. However, until now, it was unclear whether transcranial ultrasound stimulation has a significant effect on PD. OBJECTIVES In order to evaluate the effect of transcranial ultrasound stimulation on PD. METHODS We used transcranial ultrasound stimulation to modulate parkinsonian-related activity in mice administered MPTP and recorded local field potentials in the motor cortex before and after ultrasound stimulation. We analyzed neuronal oscillatory activity known to be relevant to the pathophysiology of PD. RESULTS After ultrasound stimulation, mean power intensity in the beta band (13-30 Hz) significantly decreased, and the phase-amplitude coupling strength between the beta and high gamma (55-100 Hz) bands and between the beta and ripple (100-200 Hz) bands also became significantly weaker. CONCLUSIONS This study demonstrates that ultrasonic neuromodulation can significantly decrease parkinsonian-related activity in mice administered MPTP. © 2019 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Zhijie Wang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Xingrang Wang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Yi Yuan
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China.,Institute of Brain and Cognitive Science, Yanshan University, Qinhuangdao, China
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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29
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Dykstra RM, Hanson NJ, Miller MG. Brain activity during self-paced vs. fixed protocols in graded exercise testing. Exp Brain Res 2019; 237:3273-3279. [PMID: 31650214 DOI: 10.1007/s00221-019-05669-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 10/05/2019] [Indexed: 10/25/2022]
Abstract
Electroencephalography research surrounding maximal exercise testing has been limited to male subjects. Additionally, studies have used open-looped protocols, meaning individuals do not know the exercise endpoint. Closed-loop protocols are often shown to result in optimal performance as self-pacing is permitted. The purpose of this study was to compare brain activity during open- and closed-loop maximal exercise protocols, and to determine if any sex differences are present. Twenty-seven subjects (12 males, ages 22.0 ± 2.5 years) participated in this study. A pre-assembled EEG sensor strip was used to collect brain activity from specific electrodes (F3/F4: dorsolateral prefrontal cortex, or dlPFC; and C3/Cz/C4: motor cortex, or MC). Alpha (8-12 Hz) and beta (12-30 Hz) frequency bands were analyzed. Subjects completed two maximal exercise tests on a cycle ergometer, separated by at least 48 h: a traditional, open-loop graded exercise test (GXT) and a closed-loop self-paced VO2max (SPV) test. Mixed model ANOVAs were performed to compare power spectral density (PSD) between test protocols and sexes. A significant interaction of time and sex was shown in the dlPFC for males, during the GXT only (p = 001), where a peak was reached and then a decrease was shown. A continuous increase was shown in the SPV. Sex differences in brain activity during exercise could be associated with inhibitory control, which is a function of the dlPFC. Knowledge of an exercise endpoint could be influential towards cessation of exercise and changes in cortical brain activity.
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Affiliation(s)
- Rachel M Dykstra
- Department of Human Performance and Health Education, Western Michigan University, 1903 W. Michigan Ave, Kalamazoo, MI, 49008, USA.
| | - Nicholas J Hanson
- Department of Human Performance and Health Education, Western Michigan University, 1903 W. Michigan Ave, Kalamazoo, MI, 49008, USA
| | - Michael G Miller
- Department of Human Performance and Health Education, Western Michigan University, 1903 W. Michigan Ave, Kalamazoo, MI, 49008, USA
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30
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Adenzato M, Imperatori C, Ardito RB, Valenti EM, Marca GD, D’Ari S, Palmiero L, Penso JS, Farina B. Activating attachment memories affects default mode network in a non-clinical sample with perceived dysfunctional parenting: An EEG functional connectivity study. Behav Brain Res 2019; 372:112059. [DOI: 10.1016/j.bbr.2019.112059] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 06/18/2019] [Accepted: 06/24/2019] [Indexed: 01/17/2023]
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31
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Di Nota PM, Huhta JM. Complex Motor Learning and Police Training: Applied, Cognitive, and Clinical Perspectives. Front Psychol 2019; 10:1797. [PMID: 31440184 PMCID: PMC6692711 DOI: 10.3389/fpsyg.2019.01797] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Accepted: 07/19/2019] [Indexed: 01/13/2023] Open
Abstract
The practices surrounding police training of complex motor skills, including the use of force, varies greatly around the world, and even over the course of an officer’s career. As the nature of policing changes with society and the advancement of science and technology, so should the training practices that officers undertake at both central (i.e., police academy basic recruit training) and local (i.e., individual agency or precinct) levels. The following review is intended to bridge the gap between scientific knowledge and applied practice to inform best practices for training complex motor skills that are unique and critical to law enforcement, including the use of lethal force. We begin by providing a basic understanding of the fundamental cognitive processes underlying motor learning, from novel skill acquisition to complex behaviors including situational awareness, and decision-making that precede and inform action. Motor learning, memory, and perception are then discussed within the context of occupationally relevant stress, with a review of evidence-based training practices that promote officer performance and physiological responses to stress during high-stakes encounters. A lack of applied research identifying the neurophysiological mechanisms underlying motor learning in police is inferred from a review of evidence from various clinical populations suffering from disorders of cognitive and motor systems, including Alzheimer’s and Parkinson’s disease and stroke. We conclude this review by identifying practical, organizational, and systemic challenges to implementing evidence-based practices in policing and provide recommendations for best practices that will promote training effectiveness and occupational safety of end-users (i.e., police trainers and officers).
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Affiliation(s)
- Paula M Di Nota
- Department of Psychology, University of Toronto, Mississauga, ON, Canada.,Office of Applied Research & Graduate Studies, Justice Institute of British Columbia, New Westminster, BC, Canada
| | - Juha-Matti Huhta
- Police University College, Tampere, Finland.,Faculty of Education, University of Tampere, Tampere, Finland
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Zhu M, HajiHosseini A, Baumeister TR, Garg S, Appel-Cresswell S, McKeown MJ. Altered EEG alpha and theta oscillations characterize apathy in Parkinson's disease during incentivized movement. NEUROIMAGE-CLINICAL 2019; 23:101922. [PMID: 31284232 PMCID: PMC6614604 DOI: 10.1016/j.nicl.2019.101922] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 06/01/2019] [Accepted: 06/30/2019] [Indexed: 12/03/2022]
Abstract
Apathy is a common non-motor symptom of Parkinson's disease (PD) that is difficult to quantify and poorly understood. Some studies have used incentivized motor tasks to assess apathy, as the condition is often associated with a reduction in motivated behavior. Normally event-related desynchronization, a reduction of power in specific frequency bands, is observed in the motor cortex during the peri-movement period. Also, alpha (8–12 Hz) and theta (4–7 Hz) oscillations are sensitive to rewards that are closely related to motivational states however these oscillations have not been widely investigated in relation to apathy in PD. Using EEG recordings, we investigated the neural oscillatory characteristics of apathy in PD during an incentivized motor task with interleaved rest periods. Apathetic and non-apathetic PD subjects on dopaminergic medication and healthy control subjects were instructed to squeeze a hand grip device for a monetary reward proportional to the subject's grip force and the monetary value attributed to that trial. Apathetic PD subjects exhibited higher alpha and theta powers in the pre-trial baseline rest period compared to non-apathetic PD subjects and healthy subjects. Further, we found that both resting power and relative power in alpha and theta bands during incentivized movement predicted PD subjects' apathy scores. Our results suggest that apathetic PD patients may need to overcome greater baseline alpha and theta oscillatory activity in order to facilitate incentivized movement. Clinically, resting alpha and theta power as well as alpha and theta event-related desynchronization during movement may serve as potential neural markers for apathy severity in PD. Apathetic patients with Parkinson's disease on dopaminergic medication have distinct neural oscillatory characteristics. Apathetic patients exhibit a higher resting EEG theta and alpha power compared to non-apathetic patients. Both resting power and relative event-related theta and alpha desynchronization during squeezing are able to predict patient apathy scores.
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Affiliation(s)
- Maria Zhu
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC, Canada
| | | | - Tobias R Baumeister
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC, Canada; School of Biomedical Engineering, Faculty of Applied Science, University of British Columbia, Vancouver, BC, Canada
| | - Saurabh Garg
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Silke Appel-Cresswell
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Martin J McKeown
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC, Canada.
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Sushkova OS, Morozov AA, Gabova AV, Karabanov AV. [Application of brain electrical activity burst analysis method for detection of EEG characteristics in the early stage of Parkinson's disease]. Zh Nevrol Psikhiatr Im S S Korsakova 2019; 118:45-48. [PMID: 30132456 DOI: 10.17116/jnevro20181187145] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
AIM To develop a mathematical method of analysis and visualization of EEG based on the ROC analysis of burst electrical activity in the cerebral cortex. MATERIAL AND METHODS Using a new method of analysis of EEG burst activity, the frequency parameters of brain electrical activity have been investigated in patients in the first stage of Parkinson's disease (PD) defined by the Hoehn and Yahr scale. Patients were right-handed, with disease onset in either the right or the left side. The burst term is used in neurophysiology for the description of wave activity in EEG signals. Bursts are reflected in the local peaks of wavelet spectrograms, some of the parameters of which have been analyzed. Electrical activity of the left and right central cortex areas was investigated. The results were compared with those obtained from healthy volunteers. RESULTS In PD patients, burst activity was changed in alpha- and beta bands. Compared to healthy volunteers, it was higher in alpha band 8-9 Hz and lower in upper alpha band 11-13 Hz and beta band 18-24 Hz. With regard to asymmetry of the brain in PD patients, there was the change in burst activity in both brain hemispheres. Diagrams of burst activity showed the difference between the patients with tremor onset in the left hand and tremor onset in the right hand. CONCLUSION This suggests differences in brain electrical activity changes in patients with left-sided and right-sided disease onset. The initial results of the study demonstrate that the method of analysis and visualization based on the evaluation of certain parameters of EEG bursts is promising for the analysis of EEG features in PD patients.
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Affiliation(s)
- O S Sushkova
- Kotel'nikov Institute of Radio Engineering and Electronics of RAS, Moscow, Russia
| | - A A Morozov
- Kotel'nikov Institute of Radio Engineering and Electronics of RAS, Moscow, Russia
| | - A V Gabova
- Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russia
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Yener GG, Fide E, Özbek Y, Emek-Savaş DD, Aktürk T, Çakmur R, Güntekin B. The difference of mild cognitive impairment in Parkinson's disease from amnestic mild cognitive impairment: Deeper power decrement and no phase-locking in visual event-related responses. Int J Psychophysiol 2019; 139:48-58. [DOI: 10.1016/j.ijpsycho.2019.03.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 03/04/2019] [Accepted: 03/05/2019] [Indexed: 11/28/2022]
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Carmona Arroyave JA, Tobón Quintero CA, Suárez Revelo JJ, Ochoa Gómez JF, García YB, Gómez LM, Pineda Salazar DA. Resting functional connectivity and mild cognitive impairment in Parkinson’s disease. An electroencephalogram study. FUTURE NEUROLOGY 2019. [DOI: 10.2217/fnl-2018-0048] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Objective: Parkinson’s disease (PD) is characterized by cognitive deficits. There is not clarity about electroencephalogram (EEG) connectivity related to the cognitive profile of patients. Our objective was to evaluate connectivity over resting EEG in nondemented PD. Methods: PD subjects with and without mild cognitive impairment (MCI) were assessed using coherence from resting EEG for local, intra and interhemispheric connectivity. Results: PD subjects without MCI (PD-nMCI) had lower intra and interhemispheric coherence in alpha2 compared with controls. PD with MCI (PD-MCI) showed higher intra and posterior interhemispheric coherence in alpha2 and beta1, respectively, in comparison to PD-nMCI. PD-MCI presented lower frontal coherence in beta frequencies compared with PD-nMCI. Conclusion: EEG coherence measures indicate distinct cortical activity in PD with and without MCI.
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Affiliation(s)
- Jairo Alexander Carmona Arroyave
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Carlos Andrés Tobón Quintero
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Jasmín Jimena Suárez Revelo
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Bioinstrumentation & Clinical Engineering Research Group (GIBIC), Bioengineering Program, University of Antioquia, Calle 70 No. 52–21, Medellín, Colombia
| | - John Fredy Ochoa Gómez
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Bioinstrumentation & Clinical Engineering Research Group (GIBIC), Bioengineering Program, University of Antioquia, Calle 70 No. 52–21, Medellín, Colombia
| | - Yamile Bocanegra García
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Leonardo Moreno Gómez
- Neurology Unit, Pablo Tobón Uribe Hospital, Calle 78B No. 69–240, Medellín, Colombia
| | - David Antonio Pineda Salazar
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Psychology Department, University of San Buenaventura, Carrera 56 C No. 51–110, Medellín, Colombia
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Lee S, Liu A, Wang ZJ, McKeown MJ. Abnormal Phase Coupling in Parkinson's Disease and Normalization Effects of Subthreshold Vestibular Stimulation. Front Hum Neurosci 2019; 13:118. [PMID: 31001099 PMCID: PMC6456700 DOI: 10.3389/fnhum.2019.00118] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 03/19/2019] [Indexed: 12/14/2022] Open
Abstract
The human brain is a highly dynamic structure requiring dynamic coordination between different neural systems to perform numerous cognitive and behavioral tasks. Emerging perspectives on basal ganglia (BG) and thalamic functions have highlighted their role in facilitating and mediating information transmission among cortical regions. Thus, changes in BG and thalamic structures can induce aberrant modulation of cortico-cortical interactions. Recent work in deep brain stimulation (DBS) has demonstrated that externally applied electrical current to BG structures can have multiple downstream effects in large-scale brain networks. In this work, we identified EEG-based altered resting-state cortical functional connectivity in Parkinson's disease (PD) and examined effects of dopaminergic medication and electrical vestibular stimulation (EVS), a non-invasive brain stimulation (NIBS) technique capable of stimulating the BG and thalamus through vestibular pathways. Resting EEG was collected from 16 PD subjects and 18 age-matched, healthy controls (HC) in four conditions: sham (no stimulation), EVS1 (4-8 Hz multisine), EVS2 (50-100 Hz multisine) and EVS3 (100-150 Hz multisine). The mean, variability, and entropy were extracted from time-varying phase locking value (PLV), a non-linear measure of pairwise functional connectivity, to probe abnormal cortical couplings in the PD subjects. We found the mean PLV of Cz and C3 electrodes were important for discrimination between PD and HC subjects. In addition, the PD subjects exhibited lower variability and entropy of PLV (mostly in theta and alpha bands) compared to the controls, which were correlated with their clinical characteristics. While levodopa medication was effective in normalizing the mean PLV only, all EVS stimuli normalized the mean, variability and entropy of PLV in the PD subject, with the exact extent and duration of improvement a function of stimulus type. These findings provide evidence demonstrating both low- and high-frequency EVS exert widespread influences on cortico-cortical connectivity, likely via subcortical activation. The improvement observed in PD in a stimulus-dependent manner suggests that EVS with optimized parameters may provide a new non-invasive means for neuromodulation of functional brain networks.
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Affiliation(s)
- Soojin Lee
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.,Pacific Parkinson's Research Centre, Vancouver, BC, Canada
| | - Aiping Liu
- Pacific Parkinson's Research Centre, Vancouver, BC, Canada.,Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, China
| | - Z Jane Wang
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.,Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Martin J McKeown
- Pacific Parkinson's Research Centre, Vancouver, BC, Canada.,Department of Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
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Tzounopoulos T, Balaban C, Zitelli L, Palmer C. Towards a Mechanistic-Driven Precision Medicine Approach for Tinnitus. J Assoc Res Otolaryngol 2019; 20:115-131. [PMID: 30825037 PMCID: PMC6453992 DOI: 10.1007/s10162-018-00709-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Accepted: 12/18/2018] [Indexed: 12/17/2022] Open
Abstract
In this position review, we propose to establish a path for replacing the empirical classification of tinnitus with a taxonomy from precision medicine. The goal of a classification system is to understand the inherent heterogeneity of individuals experiencing and suffering from tinnitus and to identify what differentiates potential subgroups. Identification of different patient subgroups with distinct audiological, psychophysical, and neurophysiological characteristics will facilitate the management of patients with tinnitus as well as the design and execution of drug development and clinical trials, which, for the most part, have not yielded conclusive results. An alternative outcome of a precision medicine approach in tinnitus would be that additional mechanistic phenotyping might not lead to the identification of distinct drivers in each individual, but instead, it might reveal that each individual may display a quantitative blend of causal factors. Therefore, a precision medicine approach towards identifying these causal factors might not lead to subtyping these patients but may instead highlight causal pathways that can be manipulated for therapeutic gain. These two outcomes are not mutually exclusive, and no matter what the final outcome is, a mechanistic-driven precision medicine approach is a win-win approach for advancing tinnitus research and treatment. Although there are several controversies and inconsistencies in the tinnitus field, which will not be discussed here, we will give a few examples, as to how the field can move forward by exploring the major neurophysiological tinnitus models, mostly by taking advantage of the common features supported by all of the models. Our position stems from the central concept that, as a field, we can and must do more to bring studies of mechanisms into the realm of neuroscience.
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Affiliation(s)
- Thanos Tzounopoulos
- Pittsburgh Hearing Research Center and Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA.
| | - Carey Balaban
- Pittsburgh Hearing Research Center and Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Lori Zitelli
- Pittsburgh Hearing Research Center and Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Catherine Palmer
- Pittsburgh Hearing Research Center and Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, 15213, USA
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Default mode network alterations in individuals with high-trait-anxiety: An EEG functional connectivity study. J Affect Disord 2019; 246:611-618. [PMID: 30605880 DOI: 10.1016/j.jad.2018.12.071] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 11/10/2018] [Accepted: 12/23/2018] [Indexed: 02/01/2023]
Abstract
BACKGROUND Although several researches investigated Default Mode Network (DMN) alterations in individuals with anxiety disorders, up to now no studies have investigated DMN functional connectivity in non-clinical individuals with high-trait-anxiety using quantitative electroencephalography (EEG). Here, the main aim was to extend previous findings investigating the association between trait anxiety and DMN EEG functional connectivity. METHODS Twenty-three individuals with high-trait-anxiety and twenty-four controls were enrolled. EEG was recorded during 5 min of resting state (RS). EEG analyses were conducted by means of the exact Low-Resolution Electromagnetic Tomography software (eLORETA). RESULTS Compared to controls, individuals with high-trait-anxiety showed a decrease of theta connectivity between right medial prefrontal cortex (mPFC) and right posterior cingulate/retrosplenial cortex. A decrease of beta connectivity was also observed between right mPFC and right anterior cingulate cortex. Furthermore, DMN functional connectivity strength was negatively related with STAI-T total score (i.e., lower connectivity was associated with higher trait anxiety), even when controlling for potential confounding variables (i.e., sex, age, and general psychopathology). LIMITATIONS Small sample size makes it difficult to draw definitive conclusions. Furthermore, we did not assess state variation of anxiety, which make our interpretation specific to trait anxiety. CONCLUSIONS Taken together, our results suggest that high-trait-anxiety individuals fail to synchronize DMN during RS, reflecting a possible top-down cognitive control deficit. These results may help in the understanding of the individual differences in functional brain networks associated with trait anxiety, a crucial aim in the prevention and in the early etiology understanding of clinical anxiety and related sequelae.
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Affan RO, Huang S, Cruz SM, Holcomb LA, Nguyen E, Marinkovic K. High-intensity binge drinking is associated with alterations in spontaneous neural oscillations in young adults. Alcohol 2018; 70:51-60. [PMID: 29778070 DOI: 10.1016/j.alcohol.2018.01.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Revised: 01/04/2018] [Accepted: 01/04/2018] [Indexed: 01/07/2023]
Abstract
Heavy episodic alcohol consumption (also termed binge drinking) contributes to a wide range of health and cognitive deficits, but the associated brain-based indices are poorly understood. The current study used electroencephalography (EEG) to examine spontaneous neural oscillations in young adults as a function of quantity, frequency, and the pattern of their alcohol consumption. Sixty-one young adults (23.4 ± 3.4 years of age) were assigned to binge drinking (BD) and light drinking (LD) groups that were equated on gender, race/ethnic identity, age, educational background, and family history of alcoholism. EEG activity was recorded during eyes-open and eyes-closed resting conditions. Each participant's alpha peak frequency (APF) was used to calculate absolute power in individualized theta and alpha frequency bands, with a canonical frequency range used for beta. APF was slower by 0.7 Hz in BD, especially in individuals engaging in high-intensity drinking, but there were no changes in alpha power. BD also exhibited higher frontal theta and beta power than LD. Alpha slowing and increased theta power in BD remained after accounting for depression, anxiety, and personality characteristics, while elevated beta power covaried with sensation seeking. Furthermore, APF slowing and theta power correlated with various measures of alcohol consumption, including binge episodes and blackouts, but not with measures of working and episodic memory, cognitive flexibility, processing speed, or personality variables, suggesting that these physiological changes may be modulated by high-intensity alcohol intake. These results are consistent with studies of alcohol-use disorder (AUD) and support the hypothesis that binge drinking is a transitional stage toward alcohol dependence. The observed thalamocortical dysrhythmia may be indicative of an excitatory-inhibitory imbalance in BD and may potentially serve as an index of the progressive development of AUD, with a goal of informing possible interventions to minimize alcohol's deleterious effects on the brain.
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González-Garrido AA, Gómez-Velázquez FR, Salido-Ruiz RA, Espinoza-Valdez A, Vélez-Pérez H, Romo-Vazquez R, Gallardo-Moreno GB, Ruiz-Stovel VD, Martínez-Ramos A, Berumen G. The analysis of EEG coherence reflects middle childhood differences in mathematical achievement. Brain Cogn 2018; 124:57-63. [PMID: 29747149 DOI: 10.1016/j.bandc.2018.04.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 03/15/2018] [Accepted: 04/30/2018] [Indexed: 10/17/2022]
Abstract
Symbolic numerical magnitude processing is crucial to arithmetic development, and it is thought to be supported by the functional activation of several brain-interconnected structures. In this context, EEG beta oscillations have been recently associated with attention and working memory processing that underlie math achievement. Due to that EEG coherence represents a useful measure of brain functional connectivity, we aimed to contrast the EEG coherence in forty 8-to-9-year-old children with different math skill levels (High: HA, and Low achievement: LA) according to their arithmetic scores in the Fourth Edition of the Wide Range Achievement Test (WRAT-4) while performing a symbolic magnitude comparison task (i.e. determining which of two numbers is numerically larger). The analysis showed significantly greater coherence over the right hemisphere in the two groups, but with a distinctive connectivity pattern. Whereas functional connectivity in the HA group was predominant in parietal areas, especially involving beta frequencies, the LA group showed more extensive frontoparietal relationships, with higher participation of delta, theta and alpha band frequencies, along with a distinct time-frequency domain expression. The results seem to reflect that lower math achievements in children mainly associate with cognitive processing steps beyond stimulus encoding, along with the need of further attentional resources and cognitive control than their peers, suggesting a lower degree of numerical processing automation.
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Affiliation(s)
- Andrés A González-Garrido
- Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo 180, Col. Arcos Vallarta, Guadalajara, Jalisco 44130, Mexico; O.P.D. Hospital Civil de Guadalajara, Calle Coronel Calderón #777, El Retiro, 44280 Guadalajara, Jalisco, Mexico.
| | - Fabiola R Gómez-Velázquez
- Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo 180, Col. Arcos Vallarta, Guadalajara, Jalisco 44130, Mexico
| | | | | | - Hugo Vélez-Pérez
- Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, Mexico
| | - Rebeca Romo-Vazquez
- Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, Mexico
| | - Geisa B Gallardo-Moreno
- Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo 180, Col. Arcos Vallarta, Guadalajara, Jalisco 44130, Mexico
| | - Vanessa D Ruiz-Stovel
- Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo 180, Col. Arcos Vallarta, Guadalajara, Jalisco 44130, Mexico
| | | | - Gustavo Berumen
- Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo 180, Col. Arcos Vallarta, Guadalajara, Jalisco 44130, Mexico
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Time estimation and beta segregation: An EEG study and graph theoretical approach. PLoS One 2018; 13:e0195380. [PMID: 29624619 PMCID: PMC5889177 DOI: 10.1371/journal.pone.0195380] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Accepted: 03/21/2018] [Indexed: 11/28/2022] Open
Abstract
Elucidation of the neural correlates of time perception constitutes an important research topic in cognitive neuroscience. The focus to date has been on durations in the millisecond to seconds range, but here we used electroencephalography (EEG) to examine brain functional connectivity during much longer durations (i.e., 15 min). For this purpose, we conducted an initial exploratory experiment followed by a confirmatory experiment. Our results showed that those participants who overestimated time exhibited lower activity of beta (18–30 Hz) at several electrode sites. Furthermore, graph theoretical analysis indicated significant differences in the beta range (15–30 Hz) between those that overestimated and underestimated time. Participants who underestimated time showed higher clustering coefficient compared to those that overestimated time. We discuss our results in terms of two aspects. FFT results, as a linear approach, are discussed within localized/dedicated models (i.e., scalar timing model). Second, non-localized properties of psychological interval timing (as emphasized by intrinsic models) are addressed and discussed based on results derived from graph theory. Results suggested that although beta amplitude in central regions (related to activity of BG-thalamocortical pathway as a dedicated module) is important in relation to timing mechanisms, the properties of functional activity of brain networks; such as the segregation of beta network, are also crucial for time perception. These results may suggest subjective time may be created by vector units instead of scalar ticks.
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Functional cortical source connectivity of resting state electroencephalographic alpha rhythms shows similar abnormalities in patients with mild cognitive impairment due to Alzheimer's and Parkinson's diseases. Clin Neurophysiol 2018; 129:766-782. [PMID: 29448151 DOI: 10.1016/j.clinph.2018.01.009] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 11/30/2017] [Accepted: 01/10/2018] [Indexed: 11/22/2022]
Abstract
OBJECTIVE This study tested the hypothesis that markers of functional cortical source connectivity of resting state eyes-closed electroencephalographic (rsEEG) rhythms may be abnormal in subjects with mild cognitive impairment due to Alzheimer's (ADMCI) and Parkinson's (PDMCI) diseases compared to healthy elderly subjects (Nold). METHODS rsEEG data had been collected in ADMCI, PDMCI, and Nold subjects (N = 75 for any group). eLORETA freeware estimated functional lagged linear connectivity (LLC) from rsEEG cortical sources. Area under receiver operating characteristic (AUROC) curve indexed the accuracy in the classification of Nold and MCI individuals. RESULTS Posterior interhemispheric and widespread intrahemispheric alpha LLC solutions were abnormally lower in both MCI groups compared to the Nold group. At the individual level, AUROC curves of LLC solutions in posterior alpha sources exhibited moderate accuracies (0.70-0.72) in the discrimination of Nold vs. ADMCI-PDMCI individuals. No differences in the LLC solutions were found between the two MCI groups. CONCLUSIONS These findings unveil similar abnormalities in functional cortical connectivity estimated in widespread alpha sources in ADMCI and PDMCI. This was true at both group and individual levels. SIGNIFICANCE The similar abnormality of alpha source connectivity in ADMCI and PDMCI subjects might reflect common cholinergic impairment.
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Babiloni C, Del Percio C, Lizio R, Noce G, Lopez S, Soricelli A, Ferri R, Nobili F, Arnaldi D, Famà F, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Garn H, Fraioli L, Pievani M, Frisoni GB, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, Taylor JP, Vacca L, De Pandis MF, Bonanni L. Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study. Neurobiol Aging 2017; 65:18-40. [PMID: 29407464 DOI: 10.1016/j.neurobiolaging.2017.12.023] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Revised: 12/21/2017] [Accepted: 12/21/2017] [Indexed: 11/30/2022]
Abstract
Previous evidence showed abnormal posterior sources of resting-state delta (<4 Hz) and alpha (8-12 Hz) rhythms in patients with Alzheimer's disease with dementia (ADD), Parkinson's disease with dementia (PDD), and Lewy body dementia (DLB), as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis of additional abnormalities in functional cortical connectivity computed in those sources, in ADD, considered as a "disconnection cortical syndrome", in comparison with PDD and DLB. Resting-state eyes-closed electroencephalographic (rsEEG) rhythms had been collected in 42 ADD, 42 PDD, 34 DLB, and 40 normal healthy older (Nold) participants. Exact low-resolution brain electromagnetic tomography (eLORETA) freeware estimated the functional lagged linear connectivity (LLC) from rsEEG cortical sources in delta, theta, alpha, beta, and gamma bands. The area under receiver operating characteristic (AUROC) curve indexed the classification accuracy between Nold and diseased individuals (only values >0.7 were considered). Interhemispheric and intrahemispheric LLCs in widespread delta sources were abnormally higher in the ADD group and, unexpectedly, normal in DLB and PDD groups. Intrahemispheric LLC was reduced in widespread alpha sources dramatically in ADD, markedly in DLB, and moderately in PDD group. Furthermore, the interhemispheric LLC in widespread alpha sources showed lower values in ADD and DLB than PDD groups. At the individual level, AUROC curves of LLC in alpha sources exhibited better classification accuracies for the discrimination of ADD versus Nold individuals (0.84) than for DLB versus Nold participants (0.78) and PDD versus Nold participants (0.75). Functional cortical connectivity markers in delta and alpha sources suggest a more compromised neurophysiological reserve in ADD than DLB, at both group and individual levels.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy.
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy; Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Flavio Nobili
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Görsev Yener
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy; Casa di Cura Privata del Policlinico (CCPP) Milano SpA, Milan, Italy
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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Daneshzand M, Faezipour M, Barkana BD. Computational Stimulation of the Basal Ganglia Neurons with Cost Effective Delayed Gaussian Waveforms. Front Comput Neurosci 2017; 11:73. [PMID: 28848417 PMCID: PMC5550730 DOI: 10.3389/fncom.2017.00073] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 07/25/2017] [Indexed: 11/16/2022] Open
Abstract
Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices.
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Affiliation(s)
- Mohammad Daneshzand
- D-BEST Lab, Departments of Computer Science and Engineering and Biomedical Engineering, University of BridgeportBridgeport, CT, United States
| | - Miad Faezipour
- D-BEST Lab, Departments of Computer Science and Engineering and Biomedical Engineering, University of BridgeportBridgeport, CT, United States
| | - Buket D Barkana
- Department of Electrical Engineering, University of BridgeportBridgeport, CT, United States
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Foldes ST, Weber DJ, Collinger JL. Altered modulation of sensorimotor rhythms with chronic paralysis. J Neurophysiol 2017; 118:2412-2420. [PMID: 28768745 DOI: 10.1152/jn.00878.2016] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Revised: 07/28/2017] [Accepted: 07/28/2017] [Indexed: 02/06/2023] Open
Abstract
After paralysis, the disconnection between the cortex and its peripheral targets leads to neuroplasticity throughout the nervous system. However, it is unclear how chronic paralysis specifically impacts cortical oscillations associated with attempted movement of impaired limbs. We hypothesized that μ- (8-13 Hz) and β- (15-30 Hz) event-related desynchronization (ERD) would be less modulated for individuals with hand paralysis due to cervical spinal cord injury (SCI). To test this, we compared the modulation of ERD from magnetoencephalography (MEG) during attempted and imagined grasping performed by participants with cervical SCI (n = 12) and able-bodied controls (n = 13). Seven participants with tetraplegia were able to generate some electromyography (EMG) activity during attempted grasping, whereas the other five were not. The peak and area of ERD were significantly decreased for individuals without volitional muscle activity when they attempted to grasp compared with able-bodied subjects and participants with SCI,with some residual EMG activity. However, no significant differences were found between subject groups during mentally simulated tasks (i.e., motor imagery) where no muscle activity or somatosensory consequences were expected. These findings suggest that individuals who are unable to produce muscle activity are capable of generating ERD when attempting to move, but the characteristics of this ERD are altered. However, for people who maintain volitional muscle activity after SCI, there are no significant differences in ERD characteristics compared with able-bodied controls. These results provide evidence that ERD is dependent on the level of intact muscle activity after SCI.NEW & NOTEWORTHY Source space MEG was used to investigate sensorimotor cortical oscillations in individuals with SCI. This study provides evidence that individuals with cervical SCI exhibit decreased ERD when they attempt to grasp if they are incapable of generating muscle activity. However, there were no significant differences in ERD between paralyzed and able-bodied participants during motor imagery. These results have important implications for the design and evaluation of new therapies, such as motor imagery and neurofeedback interventions.
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Affiliation(s)
- Stephen T Foldes
- Veterans Affairs Pittsburgh Healthcare System, Department of Veterans Affairs, Pittsburgh, Pennsylvania.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania.,Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, Arizona; and
| | - Douglas J Weber
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jennifer L Collinger
- Veterans Affairs Pittsburgh Healthcare System, Department of Veterans Affairs, Pittsburgh, Pennsylvania; .,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
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Li X, Ma R, Pang L, Lv W, Xie Y, Chen Y, Zhang P, Chen J, Wu Q, Cui G, Zhang P, Zhou Y, Zhang X. Delta coherence in resting-state EEG predicts the reduction in cigarette craving after hypnotic aversion suggestions. Sci Rep 2017; 7:2430. [PMID: 28546584 PMCID: PMC5445086 DOI: 10.1038/s41598-017-01373-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Accepted: 03/27/2017] [Indexed: 12/26/2022] Open
Abstract
Cigarette craving is a key contributor of nicotine addiction. Hypnotic aversion suggestions have been used to help smoking cessation and reduce smoking relapse rates but its neural basis is poorly understood. This study investigated the underlying neural basis of hypnosis treatment for nicotine addiction with resting state Electroencephalograph (EEG) coherence as the measure. The sample consisted of 42 male smokers. Cigarette craving was measured by the Tobacco Craving Questionnaire. The 8-minute resting state EEG was recorded in baseline state and after hypnotic induction in the hypnotic state. Then a smoking disgust suggestion was performed. A significant increase in EEG coherence in delta and theta frequency, and significant decrease in alpha and beta frequency, between the baseline and the hypnotic state was found, which may reflect alterations in consciousness after hypnotic induction. More importantly, the delta coherence between the right frontal region and the left posterior region predicted cigarette craving reduction after hypnotic aversion suggestions. This suggests that the functional connectivity between these regions plays an important role in reducing cigarette cravings via hypnotic aversion suggestions. Thus, these brain regions may serve as an important target to treat nicotine addiction, such as stimulating these brain regions via repetitive transcranial magnetic stimulation.
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Affiliation(s)
- Xiaoming Li
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
- Department of Medical Psychology, Anhui Medical University, Hefei, Anhui, China
| | - Ru Ma
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | | | - Wanwan Lv
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Yunlu Xie
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Ying Chen
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Pengyu Zhang
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Jiawen Chen
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Qichao Wu
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Guanbao Cui
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Peng Zhang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Hefei, Anhui, China
| | - Yifeng Zhou
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China
| | - Xiaochu Zhang
- CAS Key Laboratory of Brain Function & Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, China.
- School of Humanities & Social Science, University of Science & Technology of China, Beijing, China.
- Center for Biomedical Engineering, University of Science & Technology of China, Hefei, Anhui, China.
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47
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Experience-dependent modulation of alpha and beta during action observation and motor imagery. BMC Neurosci 2017; 18:28. [PMID: 28264664 PMCID: PMC5340035 DOI: 10.1186/s12868-017-0349-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Accepted: 03/01/2017] [Indexed: 01/18/2023] Open
Abstract
Background EEG studies investigating the neural networks that facilitate action observation (AO) and kinaesthetic motor imagery (KMI) have shown reduced, or desynchronized, power in the alpha (8–12 Hz) and beta (13–30 Hz) frequency bands relative to rest, reflecting efficient activation of task-relevant areas. Functional modulation of these networks through expertise in dance has been established using fMRI, with greater activation among experts during AO. While there is evidence for experience-dependent plasticity of alpha power during AO of dance, the influence of familiarity on beta power during AO, and alpha and beta activity during KMI, remain unclear. The purpose of the present study was to measure the impact of familiarity on confidence ratings and EEG activity during (1) AO of a brief ballet sequence, (2) KMI of this same sequence, and (3) KMI of non-dance movements among ballet dancers, dancers from other genres, and non-dancers. Results Ballet dancers highly familiar with the genre of the experimental stimulus demonstrated higher individual alpha peak frequency (iAPF), greater alpha desynchronization, and greater task-related beta power during AO, as well as faster iAPF during KMI of non-dance movements. While no between-group differences in alpha or beta power were observed during KMI of dance or non-dance movements, all participants showed significant desynchronization relative to baseline, and further desynchronization during dance KMI relative to non-dance KMI indicative of greater cognitive load. Conclusions These findings confirm and extend evidence for experience-dependent plasticity of alpha and beta activity during AO of dance and KMI. We also provide novel evidence for modulation of iAPF that is faster when tuned to the specific motor repertoire of the observer. By considering the multiple functional roles of these frequency bands during the same task (AO), we have disentangled the compounded contribution of familiarity and expertise to alpha desynchronization for mediating task engagement among familiar ballet dancers and reflecting task difficulty among unfamiliar non-dance subjects, respectively. That KMI of a complex dance sequence relative to everyday, non-dance movements recruits greater cognitive resources suggests it may be a more powerful tool in driving neural plasticity of action networks, especially among the elderly and those with movement disorders.
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Wang J, Johnson LA, Jensen AL, Baker KB, Molnar GF, Johnson MD, Vitek JL. Network-wide oscillations in the parkinsonian state: alterations in neuronal activities occur in the premotor cortex in parkinsonian nonhuman primates. J Neurophysiol 2017; 117:2242-2249. [PMID: 28228579 DOI: 10.1152/jn.00011.2017] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Revised: 02/21/2017] [Accepted: 02/21/2017] [Indexed: 11/22/2022] Open
Abstract
A number of studies suggest that Parkinson's disease (PD) is associated with alterations of neuronal activity patterns in the basal-ganglia-thalamocortical circuit. There are limited electrophysiological data, however, describing how the premotor cortex, which is involved in movement and decision-making, is likely impacted in PD. In this study, spontaneous local field potential (LFP) and single unit neuronal activity were recorded in the dorsal premotor area of nonhuman primates in both the naïve and parkinsonian state using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of parkinsonism. In both animals, we observed a shift of power in LFP power spectral densities (1-350 Hz) from higher to lower frequency bands; parkinsonism resulted in increased power in frequencies <8 Hz and decreased power at frequencies >30 Hz. A comparable but not identical trend was observed in the power spectral analysis of single unit spike trains: alpha power increased in both animals and gamma power decreased in one; power in other frequency bands remaining unchanged. Although not consistent across animals, we also observed changes in discharge rates and bursting activity. Overall, the LFP and single unit analysis suggest that abnormalities in premotor neural activity are a feature of parkinsonism, although specific details of those abnormalities may differ between subjects. This study further supports the concept that PD is a network disorder that induces abnormal spontaneous neural activities across the basal-ganglia-thalamocortical circuit including the premotor cortex and provides foundational knowledge for future studies regarding the relationship between changes in neuronal activity in this region and the development of motor deficits in PD.NEW & NOTEWORTHY This study begins to fill a gap in knowledge regarding how Parkinson's disease (PD) may cause abnormal functioning of the premotor cortex. It is novel as the premotor activity is examined in both the naïve and parkinsonian states, in the same subjects, at the single unit and LFP level. It provides foundational knowledge on which to build future studies to explore the relationships between premotor activities and specific parkinsonian motor and cognitive deficits.
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Affiliation(s)
- Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota; and
| | - Luke A Johnson
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota; and
| | - Alicia L Jensen
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota; and
| | - Kenneth B Baker
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota; and
| | - Gregory F Molnar
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota; and
| | - Matthew D Johnson
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Jerrold L Vitek
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota; and
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Obukhov YV, Malyuta IA, Obukhov KY. Metric classification of early Parkinsonism in the space of electroencephalographic features. PATTERN RECOGNITION AND IMAGE ANALYSIS 2016. [DOI: 10.1134/s105466181604012x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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50
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Basal ganglia impairments in autism spectrum disorder are related to abnormal signal gating to prefrontal cortex. Neuropsychologia 2016; 91:268-281. [PMID: 27542318 DOI: 10.1016/j.neuropsychologia.2016.08.007] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Revised: 07/19/2016] [Accepted: 08/09/2016] [Indexed: 12/13/2022]
Abstract
Research on the biological basis of autism spectrum disorder has yielded a list of brain abnormalities that are arguably as diverse as the set of behavioral symptoms that characterize the disorder. Among these are patterns of abnormal cortical connectivity and abnormal basal ganglia development. In attempts to integrate the existing literature, the current paper tests the hypothesis that impairments in the basal ganglia's function to flexibly select and route task-relevant neural signals to the prefrontal cortex underpins patterns of abnormal synchronization between the prefrontal cortex and other cortical processing centers observed in individuals with autism spectrum disorder (ASD). We tested this hypothesis using a Dynamic Causal Modeling analysis of neuroimaging data collected from 16 individuals with ASD (mean age=25.3 years; 6 female) and 17 age- and IQ-matched neurotypical controls (mean age=25.6, 6 female), who performed a Go/No-Go test of executive functioning. Consistent with the hypothesis tested, a random-effects Bayesian model selection procedure determined that a model of network connectivity in which basal ganglia activation modulated connectivity between the prefrontal cortex and other key cortical processing centers best fit the data of both neurotypicals and individuals with ASD. Follow-up analyses suggested that the largest group differences were observed for modulation of connectivity between prefrontal cortex and the sensory input region in the occipital lobe [t(31)=2.03, p=0.025]. Specifically, basal ganglia activation was associated with a small decrease in synchronization between the occipital region and prefrontal cortical regions in controls; however, in individuals with ASD, basal ganglia activation resulted in increased synchronization between the occipital region and the prefrontal cortex. We propose that this increased synchronization may reflect a failure in basal ganglia signal gating mechanisms, resulting in a non-selective copying of signals to prefrontal cortex. Such a failure to prioritize and filter signals to the prefrontal cortex could result in the pervasive impairments in cognitive flexibility and executive functioning that characterize autism spectrum disorder, and may offer a mechanistic explanation of some of the observed abnormalities in patterns of cortical synchronization in ASD.
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