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Vinding MC, Waldthaler J, Eriksson A, Manting CL, Ferreira D, Ingvar M, Svenningsson P, Lundqvist D. Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:51. [PMID: 38443402 PMCID: PMC10915140 DOI: 10.1038/s41531-024-00669-3] [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: 05/27/2022] [Accepted: 02/26/2024] [Indexed: 03/07/2024] Open
Abstract
Parkinson's disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients' disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.
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Affiliation(s)
- Mikkel C Vinding
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
| | - Josefine Waldthaler
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Section of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, University Hospital Marburg, Marburg, Germany
| | - Allison Eriksson
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Cassia Low Manting
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Cognitive Neuroimaging Centre, Lee Kong Chien School of Medicine, Nanyang Technological University, Singapore, Singapore
- McGovern Institute of Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer's Research, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran, Canaria, España
| | - Martin Ingvar
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Per Svenningsson
- Section of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Daniel Lundqvist
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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Özkurt TE. Abnormally low sensorimotor α band nonlinearity serves as an effective EEG biomarker of Parkinson's disease. J Neurophysiol 2024; 131:435-445. [PMID: 38230880 DOI: 10.1152/jn.00272.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/29/2023] [Accepted: 01/11/2024] [Indexed: 01/18/2024] Open
Abstract
Biomarkers obtained from the neurophysiological signals of patients with Parkinson's disease (PD) have objective value in assessing their motor condition for effective diagnosis, monitoring, and clinical intervention. Prominent cortical biomarkers of PD have typically been derived from various β band wave features. This study approached the topic from an alternative perspective and attempted to estimate a recently suggested measure representing α band nonlinear autocorrelative memory from a publicly available EEG dataset that involves 15 patients with earlier-stage PD (dopaminergic medication OFF and ON states) and 16 age-matched healthy controls. The cortical nonlinearity was elevated for the PD ON state compared with the OFF state for bilateral sensorimotor channels C3 and C4 (n = 26; P = 0.003). A similar statistical difference was also identified between PD OFF state and healthy subjects (n = 26; P = 0.049). Analysis over all channels revealed that the α band nonlinearity induced upon medication was constrained to sensorimotor regions. The α nonlinearity measure was compared with a well-accepted cortical biomarker of β-γ phase-amplitude coupling (PAC). They were in moderate negative correlation (r = -0.412; P = 0.036) for only healthy subjects, but not for the patients. The nonlinearity measure was found to be insusceptible to the nonstationary variations within the particular data. Our study provides further evidence that the α band nonlinearity measure can serve as a promising cortical biomarker of PD. The suggested measure can be estimated from a noninvasive low-resolution single scalp EEG channel of patients with relatively early-stage PD, who did not yet need to undergo deep brain stimulation operation.NEW & NOTEWORTHY This study suggests a nonlinearity measure that differentiates Parkinson's disease (PD) dopamine OFF-state scalp EEG data from those of dopamine ON-state patients and healthy subjects. Unlike typical PD cortical biomarkers based on β band activity, this metric shows elevation upon dopaminergic medication in the α band. We provide evidence supporting its potential as an early-stage promising PD biomarker that can be estimated from noninvasive EEG recordings with low resolution and SNR.
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Affiliation(s)
- Tolga Esat Özkurt
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University (METU), Ankara, Turkey
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Xia C, Li J, Yan R, Su W, Liu Y. Contribution of inter-trial phase coherence at theta, alpha, and beta frequencies in auditory change detection. Front Neurosci 2023; 17:1224479. [PMID: 38027496 PMCID: PMC10665517 DOI: 10.3389/fnins.2023.1224479] [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: 05/19/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction Auditory change detection is a pre-attentive cortical auditory processing ability. Many neurological and psychological disorders can lead to defects in this process. Some studies have shown that phase synchronization may be related to auditory discrimination. However, the specific contributions of phase synchronization at different frequencies remain unclear. Methods We analyzed the electroencephalogram (EEG) data of 29 healthy adults using an oddball paradigm consisting of a standard stimulus and five deviant stimuli with varying frequency modulation patterns, including midpoint frequency transitions and linear frequency modulation. We then compared the peak amplitude and latency of inter-trial phase coherence (ITC) at the theta(θ), alpha(α), and beta(β) frequencies, as well as the N1 component, and their relationships with stimulus changes. At the same time, the characteristics of inter-trial phase coherence in response to the pure tone stimulation and chirp sound with a fine time-frequency structure were also assessed. Result When the stimulus frequency did not change relative to the standard stimulus, the peak latency of phase coherence at β and α frequencies was consistent with that of the N1 component. The inter-trial phase coherence at β frequency (β-ITC)served as a faster indicator for detecting frequency transition when the stimulus frequency was changed relative to the standard stimulus. β-ITC demonstrates temporal stability when detecting pure sinusoidal tones and their frequency changes, and is less susceptible to interference from other neural activities. The phase coherence at θ frequency could integrate the frequency and temporal characteristics of deviant into a single representation, which can be compared with the memory trace formed by the standard stimulus, thus effectively identifying auditory changes. Pure sinusoidal tone stimulation could induce higher inter-trial phase coherence in a smaller time window, but chirp sounds with a fine time-frequency structure required longer latencies to achieve phase coherence. Conclusion Phase coherence at theta, alpha, and beta frequencies are all involved in auditory change detection, but play different roles in this automatic process. Complex time-frequency modulated stimuli require longer processing time for effective change detection.
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Affiliation(s)
- Caifeng Xia
- Department of Otolaryngology Head and Neck Surgery, Peking University First Hospital, Beijing, China
| | - Jinhong Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Rong Yan
- Department of Otolaryngology Head and Neck Surgery, Peking University First Hospital, Beijing, China
| | - Wenwen Su
- Department of Otolaryngology Head and Neck Surgery, Peking University First Hospital, Beijing, China
| | - Yuhe Liu
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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Paulo DL, Qian H, Subramanian D, Johnson GW, Zhao Z, Hett K, Kang H, Chris Kao C, Roy N, Summers JE, Claassen DO, Dhima K, Bick SK. Corticostriatal beta oscillation changes associated with cognitive function in Parkinson's disease. Brain 2023; 146:3662-3675. [PMID: 37327379 PMCID: PMC10681666 DOI: 10.1093/brain/awad206] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/08/2023] [Accepted: 05/16/2023] [Indexed: 06/18/2023] Open
Abstract
Cognitive impairment is the most frequent non-motor symptom in Parkinson's disease and is associated with deficits in a number of cognitive functions including working memory. However, the pathophysiology of Parkinson's disease cognitive impairment is poorly understood. Beta oscillations have previously been shown to play an important role in cognitive functions including working memory encoding. Decreased dopamine in motor cortico-striato-thalamo-cortical (CSTC) circuits increases the spectral power of beta oscillations and results in Parkinson's disease motor symptoms. Analogous changes in parallel cognitive CSTC circuits involving the caudate and dorsolateral prefrontal cortex (DLPFC) may contribute to Parkinson's disease cognitive impairment. The objective of our study is to evaluate whether changes in beta oscillations in the caudate and DLPFC contribute to cognitive impairment in Parkinson's disease patients. To investigate this, we used local field potential recordings during deep brain stimulation surgery in 15 patients with Parkinson's disease. Local field potentials were recorded from DLPFC and caudate at rest and during a working memory task. We examined changes in beta oscillatory power during the working memory task as well as the relationship of beta oscillatory activity to preoperative cognitive status, as determined from neuropsychological testing results. We additionally conducted exploratory analyses on the relationship between cognitive impairment and task-based changes in spectral power in additional frequency bands. Spectral power of beta oscillations decreased in both DLPFC and caudate during working memory encoding and increased in these structures during feedback. Subjects with cognitive impairment had smaller decreases in caudate and DLPFC beta oscillatory power during encoding. In our exploratory analysis, we found that similar differences occurred in alpha frequencies in caudate and theta and alpha in DLPFC. Our findings suggest that oscillatory power changes in cognitive CSTC circuits may contribute to cognitive symptoms in patients with Parkinson's disease. These findings may inform the future development of novel neuromodulatory treatments for cognitive impairment in Parkinson's disease.
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Affiliation(s)
- Danika L Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Helen Qian
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Neuroscience, Vanderbilt University, Nashville, TN 37212, USA
| | - Deeptha Subramanian
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Graham W Johnson
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- School of Medicine, Vanderbilt University, Nashville, TN 37212, USA
| | - Zixiang Zhao
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Kilian Hett
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - C Chris Kao
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Noah Roy
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Jessica E Summers
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Daniel O Claassen
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Kaltra Dhima
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37212 USA
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37212, USA
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Radcliffe EM, Baumgartner AJ, Kern DS, Al Borno M, Ojemann S, Kramer DR, Thompson JA. Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease. J Neurophysiol 2023; 129:1492-1504. [PMID: 37198135 DOI: 10.1152/jn.00055.2023] [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: 02/03/2023] [Revised: 04/23/2023] [Accepted: 05/17/2023] [Indexed: 05/19/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.
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Affiliation(s)
- Erin M Radcliffe
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Alexander J Baumgartner
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Drew S Kern
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Mazen Al Borno
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Computer Science and Engineering, University of Colorado Denver, Denver, Colorado, United States
| | - Steven Ojemann
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Daniel R Kramer
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - John A Thompson
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
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