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Rohr-Fukuma M, Stieglitz LH, Bujan B, Jedrysiak P, Oertel MF, Salzmann L, Baumann CR, Imbach LL, Gassert R, Bichsel O. Neurofeedback-enabled beta power control with a fully implanted DBS system in patients with Parkinson's disease. Clin Neurophysiol 2024; 165:1-15. [PMID: 38941959 DOI: 10.1016/j.clinph.2024.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 04/18/2024] [Accepted: 06/03/2024] [Indexed: 06/30/2024]
Abstract
OBJECTIVE Parkinsonian motor symptoms are linked to pathologically increased beta oscillations in the basal ganglia. Studies with externalised deep brain stimulation electrodes showed that Parkinson patients were able to rapidly gain control over these pathological basal ganglia signals through neurofeedback. Studies with fully implanted deep brain stimulation systems duplicating these promising results are required to grant transferability to daily application. METHODS In this study, seven patients with idiopathic Parkinson's disease and one with familial Parkinson's disease were included. In a postoperative setting, beta oscillations from the subthalamic nucleus were recorded with a fully implanted deep brain stimulation system and converted to a real-time visual feedback signal. Participants were instructed to perform bidirectional neurofeedback tasks with the aim to modulate these oscillations. RESULTS While receiving regular medication and deep brain stimulation, participants were able to significantly improve their neurofeedback ability and achieved a significant decrease of subthalamic beta power (median reduction of 31% in the final neurofeedback block). CONCLUSION We could demonstrate that a fully implanted deep brain stimulation system can provide visual neurofeedback enabling patients with Parkinson's disease to rapidly control pathological subthalamic beta oscillations. SIGNIFICANCE Fully-implanted DBS electrode-guided neurofeedback is feasible and can now be explored over extended timespans.
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Affiliation(s)
- Manabu Rohr-Fukuma
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | - Lennart H Stieglitz
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | | | | | - Markus F Oertel
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | - Lena Salzmann
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Christian R Baumann
- Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland; Department of Neurology, University Hospital Zurich, University of Zurich, Switzerland
| | | | - Roger Gassert
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Oliver Bichsel
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland; Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland.
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Ubeda Matzilevich E, Daniel PL, Little S. Towards therapeutic electrophysiological neurofeedback in Parkinson's disease. Parkinsonism Relat Disord 2024; 121:106010. [PMID: 38245382 DOI: 10.1016/j.parkreldis.2024.106010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 01/10/2024] [Accepted: 01/12/2024] [Indexed: 01/22/2024]
Abstract
Neurofeedback (NF) techniques support individuals to self-regulate specific features of brain activity, which has been shown to impact behavior and potentially ameliorate clinical symptoms. Electrophysiological NF (epNF) may be particularly impactful for patients with Parkinson's disease (PD), as evidence mounts to suggest a central role of pathological neural oscillations underlying symptoms in PD. Exaggerated beta oscillations (12-30 Hz) in the basal ganglia-cortical network are linked to motor symptoms (e.g., bradykinesia, rigidity), and beta is reduced by successful therapy with dopaminergic medication and Deep Brain Stimulation (DBS). PD patients also experience non-motor symptoms related to sleep, mood, motivation, and cognitive control. Although less is known about the mechanisms of non-motor symptoms in PD and how to successfully treat them, low frequency neural oscillations (1-12 Hz) in the basal ganglia-cortical network are particularly implicated in non-motor symptoms. Here, we review how cortical and subcortical epNF could be used to target motor and non-motor specific oscillations, and potentially serve as an adjunct therapy that enables PD patients to endogenously control their own pathological neural activities. Recent studies have demonstrated that epNF protocols can successfully support volitional control of cortical and subcortical beta rhythms. Importantly, this endogenous control of beta has been linked to changes in motor behavior. epNF for PD, as a casual intervention on neural signals, has the potential to increase understanding of the neurophysiology of movement, mood, and cognition and to identify new therapeutic approaches for motor and non-motor symptoms.
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Affiliation(s)
- Elena Ubeda Matzilevich
- Movement Disorders and Neuromodulation Division, Department of Neurology, University of California San Francisco, CA, USA
| | - Pria Lauren Daniel
- Movement Disorders and Neuromodulation Division, Department of Neurology, University of California San Francisco, CA, USA; Department of Psychology, University of California San Diego, CA, USA.
| | - Simon Little
- Movement Disorders and Neuromodulation Division, Department of Neurology, University of California San Francisco, CA, USA
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3
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Rouzitalab A, Boulay CB, Sachs AJ. Volitional control of beta activities in Parkinson's disease patients. Brain Res 2023; 1814:148394. [PMID: 37156320 DOI: 10.1016/j.brainres.2023.148394] [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: 02/27/2023] [Revised: 04/20/2023] [Accepted: 05/03/2023] [Indexed: 05/10/2023]
Abstract
Patients diagnosed with Parkinson's disease (PD) have difficulty initiating and executing movements due to an acquired imbalance of the basal ganglia thalamocortical circuit secondary to loss of dopaminergic input into the striatum. The unbalanced circuit is hyper-synchronized, presenting as larger and longer bursts of beta-band (13-30 Hz) oscillations in the subthalamic nucleus (STN). As a first step toward a novel PD therapy that aims to improve symptoms through beta desynchronization, we sought to determine if individuals with PD could acquire volitional control of STN beta power in a neurofeedback task. We found a significant difference in STN beta power between task conditions, and relevant brain signal features could be detected and decoded in real time. This demonstration of volitional control of STN beta motivates development of a neurofeedback therapy to modulate PD symptom severity.
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Affiliation(s)
- Alireza Rouzitalab
- School of Electrical Engineering and Computer Science, University of Ottawa, K1N 6N5 Ottawa, ON, Canada; The Ottawa Hospital Research Institute, Ottawa, ON, Canada.
| | | | - Adam J Sachs
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada; The University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada; Division of Neurosurgery, Department of Surgery, The Ottawa Hospital, Ottawa, ON, Canada
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Legarda SB, Michas-Martin PA, McDermott D. Managing Intractable Symptoms of Parkinson's Disease: A Nonsurgical Approach Employing Infralow Frequency Neuromodulation. Front Hum Neurosci 2022; 16:894781. [PMID: 35880105 PMCID: PMC9308006 DOI: 10.3389/fnhum.2022.894781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 06/24/2022] [Indexed: 11/13/2022] Open
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Gyoda T, Nojima I, Lin SC, Koganemaru S, Mima T, Tanabe S, Huang YZ. Strengthening the GABAergic system through neurofeedback training suppresses implicit motor learning. Neuroscience 2022; 488:112-121. [PMID: 35149145 DOI: 10.1016/j.neuroscience.2022.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 02/01/2022] [Accepted: 02/02/2022] [Indexed: 11/26/2022]
Abstract
Gamma-aminobutyric acid (GABA) activity within the primary motor cortex (M1) is essential for motor learning in cortical plasticity, and a recent study has suggested that real-time neurofeedback training (NFT) can self-regulate GABA activity. Therefore, this study aimed to investigate the effect of GABA activity strengthening via NFT on subsequent motor learning. Thirty-six healthy participants were randomly assigned to either an NFT group or control group, which received sham feedback. GABA activity was assessed for short intracortical inhibition (SICI) within the right M1 using paired-pulse transcranial magnetic stimulation. During the NFT intervention period, the participants tried to modulate the size of a circle, which was altered according to the degree of SICI in the NFT group. However, the size was altered independently of the degree of SICI in the control group. We measured the reaction time before, after (online learning), and 24 h after (offline learning) the finger-tapping task. Results showed the strengthening of GABA activity induced by the NFT intervention, and the suppression of the online but not the offline learning. These findings suggest that prior GABA activity modulation may affect online motor learning.
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Affiliation(s)
- Tomoya Gyoda
- Neuroscience Research Center and Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Ippei Nojima
- Division of Physical Therapy, Shinshu University School of Health Sciences, Matsumoto, Nagano, Japan.
| | - Su-Chuan Lin
- Neuroscience Research Center and Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Medical School, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Satoko Koganemaru
- Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Tatsuya Mima
- Graduate School of Core Ethics and Frontier Sciences, Ritsumeikan University, Kyoto, Japan
| | - Shigeo Tanabe
- Faculty of Rehabilitation, School of Health Sciences, Fujita Health University, Aichi, Japan
| | - Ying-Zu Huang
- Neuroscience Research Center and Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Medical School, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
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A Systematic Review of Neurofeedback for the Management of Motor Symptoms in Parkinson's Disease. Brain Sci 2021; 11:brainsci11101292. [PMID: 34679358 PMCID: PMC8534214 DOI: 10.3390/brainsci11101292] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 09/27/2021] [Indexed: 12/04/2022] Open
Abstract
Background: Neurofeedback has been proposed as a treatment for Parkinson’s disease (PD) motor symptoms by changing the neural network activity directly linked with movement. However, the effectiveness of neurofeedback as a treatment for PD motor symptoms is unclear. Aim: To systematically review the literature to identify the effects of neurofeedback in people with idiopathic PD; as defined by measurement of brain activity; motor function; and performance. Design: A systematic review. Included Sources and Articles: PubMed; MEDLINE; Cinhal; PsychoInfo; Prospero; Cochrane; ClinicalTrials.gov; EMBASE; Web of Science; PEDro; OpenGrey; Conference Paper Index; Google Scholar; and eThos; searched using the Population-Intervention-Comparison-Outcome (PICO) framework. Primary studies with the following designs were included: randomized controlled trials (RCTs), non-RCTs; quasi-experimental; pre/post studies; and case studies. Results: This review included 11 studies out of 6197 studies that were identified from the literature search. Neuroimaging methods used were fMRI; scalp EEG; surface brain EEG; and deep brain EEG; where 10–15 Hz and the supplementary motor area were the most commonly targeted signatures for EEG and fMRI, respectively. Success rates for changing one’s brain activity ranged from 47% to 100%; however, both sample sizes and success criteria differed considerably between studies. While six studies included a clinical outcome; a lack of consistent assessments prevented a reliable conclusion on neurofeedback’s effectiveness. Narratively, fMRI neurofeedback has the greatest potential to improve PD motor symptoms. Two main limitations were found in the studies that contributed to the lack of a confident conclusion: (1) insufficient clinical information and perspectives (e.g., no reporting of adverse events), and (2) limitations in numerical data reporting (e.g., lack of explicit statistics) that prevented a meta-analysis. Conclusions: While fMRI neurofeedback was narratively the most effective treatment; the omission of clinical outcome measures in studies using other neurofeedback approaches limits comparison. Therefore, no single neurofeedback type can currently be identified as an optimal treatment for PD motor symptoms. This systematic review highlights the need to improve the inclusion of clinical information and more robust reporting of numerical data in future work. Neurofeedback appears to hold great potential as a treatment for PD motor symptoms. However, this field is still in its infancy and needs high quality RCTs to establish its effectiveness. Review Registration: PROSPERO (ID: CRD42020191097)
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Deep brain electrical neurofeedback allows Parkinson patients to control pathological oscillations and quicken movements. Sci Rep 2021; 11:7973. [PMID: 33846456 PMCID: PMC8041890 DOI: 10.1038/s41598-021-87031-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Accepted: 03/23/2021] [Indexed: 11/12/2022] Open
Abstract
Parkinsonian motor symptoms are linked to pathologically increased beta-oscillations in the basal ganglia. While pharmacological treatment and deep brain stimulation (DBS) reduce these pathological oscillations concomitantly with improving motor performance, we set out to explore neurofeedback as an endogenous modulatory method. We implemented real-time processing of pathological subthalamic beta oscillations through implanted DBS electrodes to provide deep brain electrical neurofeedback. Patients volitionally controlled ongoing beta-oscillatory activity by visual neurofeedback within minutes of training. During a single one-hour training session, the reduction of beta-oscillatory activity became gradually stronger and we observed improved motor performance. Lastly, endogenous control over deep brain activity was possible even after removing visual neurofeedback, suggesting that neurofeedback-acquired strategies were retained in the short-term. Moreover, we observed motor improvement when the learnt mental strategies were applied 2 days later without neurofeedback. Further training of deep brain neurofeedback might provide therapeutic benefits for Parkinson patients by improving symptom control using strategies optimized through neurofeedback.
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Disruptions of cortico-kinematic interactions in Parkinson's disease. Behav Brain Res 2021; 404:113153. [PMID: 33571571 DOI: 10.1016/j.bbr.2021.113153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 01/08/2021] [Accepted: 01/27/2021] [Indexed: 11/21/2022]
Abstract
The cortical role of the motor symptoms reflected by kinematic characteristics in Parkinson's disease (PD) is poorly understood. In this study, we aim to explore how PD affects cortico-kinematic interactions. Electroencephalographic (EEG) and kinematic data were recorded from seven healthy participants and eight participants diagnosed with PD during a set of self-paced finger tapping tasks. Event-related desynchronization (ERD) was compared between groups in the α (8-14 Hz), low-ß (14-20 Hz), and high-ß (20-35 Hz) frequency bands to investigate between-group differences in the cortical activities associated with movement. Average kinematic peak amplitudes and latencies were extracted alongside Sample Entropy (SaEn), a measure of signal complexity, as variables for comparison between groups. These variables were further correlated with average EEG power in each frequency band to establish within-group interactions between cortical motor functions and kinematic motor output. High ß-band power correlated with mean kinematic peak latency and signal complexity in the healthy group, while no correlation was found in the PD group. Also, the healthy group demonstrated stronger ERD in the broad ß-band than the PD participants. Our results suggest that cortical ß-band power in healthy populations is graded to finger tapping latency and complexity of movement, but this relationship is impaired in PD. These insights could help further enhance our understanding of the role of cortical ß-band oscillations in healthy movement and the possible disruption of that relationship in PD. These outcomes can provide further directions for treatment and therapeutic applications and potentially establish cortical biomarkers of Parkinson's disease.
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He S, Mostofi A, Syed E, Torrecillos F, Tinkhauser G, Fischer P, Pogosyan A, Hasegawa H, Li Y, Ashkan K, Pereira E, Brown P, Tan H. Subthalamic beta-targeted neurofeedback speeds up movement initiation but increases tremor in Parkinsonian patients. eLife 2020; 9:e60979. [PMID: 33205752 PMCID: PMC7695453 DOI: 10.7554/elife.60979] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 11/16/2020] [Indexed: 12/17/2022] Open
Abstract
Previous studies have explored neurofeedback training for Parkinsonian patients to suppress beta oscillations in the subthalamic nucleus (STN). However, its impacts on movements and Parkinsonian tremor are unclear. We developed a neurofeedback paradigm targeting STN beta bursts and investigated whether neurofeedback training could improve motor initiation in Parkinson's disease compared to passive observation. Our task additionally allowed us to test which endogenous changes in oscillatory STN activities are associated with trial-to-trial motor performance. Neurofeedback training reduced beta synchrony and increased gamma activity within the STN, and reduced beta band coupling between the STN and motor cortex. These changes were accompanied by reduced reaction times in subsequently cued movements. However, in Parkinsonian patients with pre-existing symptoms of tremor, successful volitional beta suppression was associated with an amplification of tremor which correlated with theta band activity in STN local field potentials, suggesting an additional cross-frequency interaction between STN beta and theta activities.
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Affiliation(s)
- Shenghong He
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Abteen Mostofi
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of LondonLondonUnited Kingdom
| | - Emilie Syed
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
| | - Flavie Torrecillos
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Gerd Tinkhauser
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
- Department of Neurology, Bern University Hospital and University of BernBernSwitzerland
| | - Petra Fischer
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alek Pogosyan
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Harutomo Hasegawa
- Department of Neurosurgery, King's College Hospital NHS Foundation Trust, King's Health PartnersLondonUnited Kingdom
| | - Yuanqing Li
- School of Automation Science and Engineering, South China University of TechnologyGuangzhouChina
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College Hospital NHS Foundation Trust, King's Health PartnersLondonUnited Kingdom
| | - Erlick Pereira
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of LondonLondonUnited Kingdom
| | - Peter Brown
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Huiling Tan
- MRC Brain Network Dynamics Unit at the University of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
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Neurofeedback-Linked Suppression of Cortical β Bursts Speeds Up Movement Initiation in Healthy Motor Control: A Double-Blind Sham-Controlled Study. J Neurosci 2020; 40:4021-4032. [PMID: 32284339 PMCID: PMC7219286 DOI: 10.1523/jneurosci.0208-20.2020] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 03/10/2020] [Accepted: 03/30/2020] [Indexed: 11/30/2022] Open
Abstract
Abnormally increased β bursts in cortical-basal ganglia-thalamic circuits are associated with rigidity and bradykinesia in patients with Parkinson's disease. Increased β bursts detected in the motor cortex have also been associated with longer reaction times (RTs) in healthy participants. Here we further hypothesize that suppressing β bursts through neurofeedback training can improve motor performance in healthy subjects. Abnormally increased β bursts in cortical-basal ganglia-thalamic circuits are associated with rigidity and bradykinesia in patients with Parkinson's disease. Increased β bursts detected in the motor cortex have also been associated with longer reaction times (RTs) in healthy participants. Here we further hypothesize that suppressing β bursts through neurofeedback training can improve motor performance in healthy subjects. We conducted a double-blind sham-controlled study on 20 human volunteers (10 females) using a sequential neurofeedback-behavior task with the neurofeedback reflecting the occurrence of β bursts over sensorimotor cortex quantified in real time. The results show that neurofeedback training helps healthy participants learn to volitionally suppress β bursts in the sensorimotor cortex, with training being accompanied by reduced RT in subsequent cued movements. These changes were only significant in the real feedback group but not in the sham group, confirming the effect of neurofeedback training over simple motor imagery. In addition, RTs correlated with the rate and accumulated duration of β bursts in the contralateral motor cortex before the go-cue, but not with averaged β power. The reduced RTs induced by neurofeedback training positively correlated with reduced β bursts across all tested hemispheres. These results strengthen the link between the occurrence of β bursts in the sensorimotor cortex before the go-cue and slowed movement initiation in healthy motor control. The results also highlight the potential benefit of neurofeedback training in facilitating voluntary suppression of β bursts to speed up movement initiation. SIGNIFICANCE STATEMENT This double-blind sham-controlled study suggested that neurofeedback training can facilitate volitional suppression of β bursts in sensorimotor cortex in healthy motor control better than sham feedback. The training was accompanied by reduced reaction time (RT) in subsequent cued movements, and the reduced RT positively correlated with the level of reduction in cortical β bursts before the go-cue, but not with average β power. These results provide further evidence of a causal link between sensorimotor β bursts and movement initiation and suggest that neurofeedback training could potentially be used to train participants to speed up movement initiation.
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Neurofeedback Training Enables Voluntary Alteration of β-Band Power in the Subthalamic Nucleus of Individuals with Parkinson's Disease. eNeuro 2019; 6:eN-RHL-0144-19. [PMID: 31058212 PMCID: PMC6498418 DOI: 10.1523/eneuro.0144-19.2019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 04/15/2019] [Indexed: 11/21/2022] Open
Abstract
Highlighted Research Paper:Real-Time Neurofeedback to Modulate β-Band Power in the Subthalamic Nucleus in Parkinson’s Disease Patients, by Ryohei Fukuma, Takufumi Yanagisawa, Masataka Tanaka, Fumiaki Yoshida, Koichi Hosomi, Satoru Oshino, Naoki Tani and Haruhiko Kishima
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