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Swinnen BEKS, Fuentes A, Volz MM, Heath S, Starr PA, Little SJ, Ostrem JL. Clinically Implemented Sensing-Based Initial Programming of Deep Brain Stimulation for Parkinson's Disease: A Retrospective Study. Neuromodulation 2025; 28:501-510. [PMID: 39625426 DOI: 10.1016/j.neurom.2024.11.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 10/25/2024] [Accepted: 11/03/2024] [Indexed: 04/06/2025]
Abstract
OBJECTIVES Initial deep brain stimulation (DBS) programming using a monopolar review is time-consuming, subjective, and burdensome. Incorporating neurophysiology has the potential to expedite, objectify, and automatize initial DBS programming. We aimed to assess the feasibility and performance of clinically implemented sensing-based initial DBS programming for Parkinson's disease (PD). MATERIALS AND METHODS We conducted a single-center retrospective study in 15 patients with PD (25 hemispheres) implanted with a sensing-enabled neurostimulator in whom initial subthalamic nucleus/globus pallidus pars interna DBS programming was guided by beta power in real-time local field potential recordings, instead of a monopolar review. RESULTS The initial sensing-based programming visit lasted on average 42.2 minutes (SD 18) per hemisphere. During the DBS optimization phase, a conventional monopolar clinical review was not required in any patients. The initial stimulation contact level remained the same at the final follow-up visit in all hemispheres except three. The final amplitude was on average 0.8 mA (SD 0.9) higher than initially set after the original sensing-based programming visit. One year after surgery, off-medication International Parkinson and Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III total score, tremor subscore, MDS-UPDRS IV, and levodopa-equivalent dose improved by 47.0% (p < 0.001), 77.7% (p = 0.001), 51.1% (p = 0.006), and 44.8% (p = 0.011) compared with preoperatively using this approach. CONCLUSIONS This study shows that sensing-based initial DBS programming for PD is feasible and rapid, and selected clinically effective contacts in most patients, including those with tremor. Technologic innovations and practical developments could improve sensing-based programming.
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Affiliation(s)
- Bart E K S Swinnen
- University of California San Francisco Department of Neurology, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, USA
| | - Andrea Fuentes
- University of California San Francisco Department of Neurology, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, USA
| | - Monica M Volz
- University of California San Francisco Department of Neurology, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, USA
| | - Susan Heath
- University of California San Francisco Department of Neurology, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, USA
| | - Philip A Starr
- University of California San Francisco Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Department of Physiology, University of California San Francisco, San Francisco, CA, USA
| | - Simon J Little
- University of California San Francisco Department of Neurology, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, USA
| | - Jill L Ostrem
- University of California San Francisco Department of Neurology, University of California San Francisco, San Francisco, CA, USA; University of California San Francisco Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, USA.
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Swinnen BEKS, Buijink AWG, Stam MJ, Hubers D, de Neeling M, Keulen BJ, Morgante F, van Wijk BCM, de Bie RMA, Ricciardi L, Little SJ, Beudel M. Pitfalls and practical suggestions for using local field potential recordings in DBS clinical practice and research. J Neural Eng 2025; 22:014001. [PMID: 39870045 DOI: 10.1088/1741-2552/adaeee] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Accepted: 01/27/2025] [Indexed: 01/29/2025]
Abstract
Objective. Local field potential (LFP) recordings using chronically implanted sensing-enabled stimulators are a powerful tool for indexing symptom presence and severity in neurological and neuropsychiatric disorders, and for enhancing our neurophysiological understanding of brain processes. LFPs have gained interest as input signals for closed-loop deep brain stimulation (DBS) and can be used to inform DBS parameter selection. LFP recordings using chronically implanted sensing-enabled stimulators have various implementational challenges.Approach. Here we describe our collective experience using BrainSense (Medtronic®) for clinical and research work. We aim to provide insightful tips and practical advice to empower readers with the knowledge needed to navigate the intricacies of the device and make the most out of its features.Main results. The central issues that apply to several BrainSense features encompass restricted compatibility of stimulation configuration with sensing, differences in electrophysiological signal properties between 'stimulation OFF' and 'stimulation ON at 0.0 mA', and challenges associated with the internal clock of the neurostimulator. In addition, since recordings are obtained from bipolar and not monopolar channels, spatial certainty regarding the distribution of LFPs around the DBS electrode is limited. Several options exist to synchronize LFP time series with external data streams, but standardization and generalization are lacking. The use of at-home chronic LFP recording is limited by a low temporal and spectral resolution. Regarding at-home LFP snapshots, LFP time series are not stored, parts of the power spectrum are censored when stimulating at high or low frequencies, and the stimulation amplitude is not readily available.Significance. We discussed practical applications, implementation, system limitations, and pitfalls with the aim that sensing can be better applied for clinical practice and research.
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Affiliation(s)
- Bart E K S Swinnen
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
- UCSF Department of Neurology, University of California San Francisco, San Francisco, CA, United States of America
- UCSF Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, United States of America
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium
- Department of Neurosciences, Experimental Neurology, KU Leuven-University of Leuven, Leuven, Belgium
| | - Arthur W G Buijink
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Mariëlle J Stam
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Deborah Hubers
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Martijn de Neeling
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Bart J Keulen
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Francesca Morgante
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, United Kingdom
| | - Bernadette C M van Wijk
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Van der Boechorststraat 9, 1081 BT Amsterdam, The Netherlands
| | - Rob M A de Bie
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Lucia Ricciardi
- UCSF Department of Neurology, University of California San Francisco, San Francisco, CA, United States of America
- UCSF Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, United States of America
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, United Kingdom
| | - Simon J Little
- UCSF Department of Neurology, University of California San Francisco, San Francisco, CA, United States of America
- UCSF Weill Institute for Neurosciences, Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, CA, United States of America
| | - Martijn Beudel
- Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
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Trevarrow MP, Munoz MJ, Rivera YM, Arora R, Drane QH, Pal GD, Verhagen Metman L, Goelz LC, Corcos DM, David FJ. Medication improves velocity, reaction time, and movement time but not amplitude or error during memory-guided reaching in Parkinson's disease. Physiol Rep 2024; 12:e16150. [PMID: 39209762 PMCID: PMC11361790 DOI: 10.14814/phy2.16150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 07/04/2024] [Accepted: 07/04/2024] [Indexed: 09/04/2024] Open
Abstract
The motor impairments experienced by people with Parkinson's disease (PD) are exacerbated during memory-guided movements. Despite this, the effect of antiparkinson medication on memory-guided movements has not been elucidated. We evaluated the effect of antiparkinson medication on motor control during a memory-guided reaching task with short and long retention delays in participants with PD and compared performance to age-matched healthy control (HC) participants. Thirty-two participants with PD completed the motor section of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) and performed a memory-guided reaching task with two retention delays (0.5 s and 5 s) while on and off medication. Thirteen HC participants completed the MDS-UPDRS III and performed the memory-guided reaching task. In the task, medication increased movement velocity, decreased movement time, and decreased reaction time toward what was seen in the HC. However, movement amplitude and reaching error were unaffected by medication. Shorter retention delays increased movement velocity and amplitude, decreased movement time, and decreased error, but increased reaction times in the participants with PD and HC. Together, these results imply that antiparkinson medication is more effective at altering the neurophysiological mechanisms controlling movement velocity and reaction time compared with other aspects of movement control.
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Affiliation(s)
- Michael P. Trevarrow
- Department of Physical Therapy and Human Movement SciencesNorthwestern UniversityChicagoIllinoisUSA
| | - Miranda J. Munoz
- Department of Physical Therapy and Human Movement SciencesNorthwestern UniversityChicagoIllinoisUSA
| | - Yessenia M. Rivera
- Department of Physical Therapy and Human Movement SciencesNorthwestern UniversityChicagoIllinoisUSA
| | - Rishabh Arora
- Morsani College of MedicineUniversity of South FloridaTampaFloridaUSA
| | - Quentin H. Drane
- Department of Physical Therapy and Human Movement SciencesNorthwestern UniversityChicagoIllinoisUSA
| | - Gian D. Pal
- Division of Movement Disorders, Department of NeurologyRutgers – Robert Wood Johnson Medical SchoolNew BrunswickNew JerseyUSA
| | - Leonard Verhagen Metman
- Department of NeurologyNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Lisa C. Goelz
- Department of Kinesiology and NutritionUIC College of Applied Health SciencesChicagoIllinoisUSA
| | - Daniel M. Corcos
- Department of Physical Therapy and Human Movement SciencesNorthwestern UniversityChicagoIllinoisUSA
- McCormick School of EngineeringNorthwestern UniversityEvanstonIllinoisUSA
| | - Fabian J. David
- Department of Physical Therapy and Human Movement SciencesNorthwestern UniversityChicagoIllinoisUSA
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Alva L, Bernasconi E, Torrecillos F, Fischer P, Averna A, Bange M, Mostofi A, Pogosyan A, Ashkan K, Muthuraman M, Groppa S, Pereira EA, Tan H, Tinkhauser G. Clinical neurophysiological interrogation of motor slowing: A critical step towards tuning adaptive deep brain stimulation. Clin Neurophysiol 2023; 152:43-56. [PMID: 37285747 PMCID: PMC7615935 DOI: 10.1016/j.clinph.2023.04.013] [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: 08/23/2022] [Revised: 03/07/2023] [Accepted: 04/18/2023] [Indexed: 06/09/2023]
Abstract
OBJECTIVE Subthalamic nucleus (STN) beta activity (13-30 Hz) is the most accepted biomarker for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). We hypothesize that different frequencies within the beta range may exhibit distinct temporal dynamics and, as a consequence, different relationships to motor slowing and adaptive stimulation patterns. We aim to highlight the need for an objective method to determine the aDBS feedback signal. METHODS STN LFPs were recorded in 15 PD patients at rest and while performing a cued motor task. The impact of beta bursts on motor performance was assessed for different beta candidate frequencies: the individual frequency strongest associated with motor slowing, the individual beta peak frequency, the frequency most modulated by movement execution, as well as the entire-, low- and high beta band. How these candidate frequencies differed in their bursting dynamics and theoretical aDBS stimulation patterns was further investigated. RESULTS The individual motor slowing frequency often differs from the individual beta peak or beta-related movement-modulation frequency. Minimal deviations from a selected target frequency as feedback signal for aDBS leads to a substantial drop in the burst overlapping and in the alignment of the theoretical onset of stimulation triggers (to ∼ 75% for 1 Hz, to ∼ 40% for 3 Hz deviation). CONCLUSIONS Clinical-temporal dynamics within the beta frequency range are highly diverse and deviating from a reference biomarker frequency can result in altered adaptive stimulation patterns. SIGNIFICANCE A clinical-neurophysiological interrogation could be helpful to determine the patient-specific feedback signal for aDBS.
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Affiliation(s)
- Laura Alva
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Elena Bernasconi
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Flavie Torrecillos
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Petra Fischer
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, University Walk, BS8 1TD Bristol, United Kingdom
| | - Alberto Averna
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Manuel Bange
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Abteen Mostofi
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, London SW17 0RE, United Kingdom
| | - Alek Pogosyan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College Hospital, King's College London, SE59RS, United Kingdom
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Erlick A Pereira
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, London SW17 0RE, United Kingdom
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
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DBS-evoked cortical responses index optimal contact orientations and motor outcomes in Parkinson's disease. NPJ Parkinsons Dis 2023; 9:37. [PMID: 36906723 PMCID: PMC10008535 DOI: 10.1038/s41531-023-00474-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 02/13/2023] [Indexed: 03/13/2023] Open
Abstract
Although subthalamic deep brain stimulation (DBS) is a highly-effective treatment for alleviating motor dysfunction in patients with Parkinson's disease (PD), clinicians currently lack reliable neurophysiological correlates of clinical outcomes for optimizing DBS parameter settings, which may contribute to treatment inefficacies. One parameter that could aid DBS efficacy is the orientation of current administered, albeit the precise mechanisms underlying optimal contact orientations and associated clinical benefits are not well understood. Herein, 24 PD patients received monopolar stimulation of the left STN during magnetoencephalography and standardized movement protocols to interrogate the directional specificity of STN-DBS current administration on accelerometer metrics of fine hand movements. Our findings demonstrate that optimal contact orientations elicit larger DBS-evoked cortical responses in the ipsilateral sensorimotor cortex, and importantly, are differentially predictive of smoother movement profiles in a contact-dependent manner. Moreover, we summarize traditional evaluations of clinical efficacy (e.g., therapeutic windows, side effects) for a comprehensive review of optimal/non-optimal STN-DBS contact settings. Together, these data suggest that DBS-evoked cortical responses and quantitative movement outcomes may provide clinical insight for characterizing the optimal DBS parameters necessary for alleviating motor symptoms in patients with PD in the future.
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Morelli N, Summers RLS. Association of subthalamic beta frequency sub-bands to symptom severity in patients with Parkinson's disease: A systematic review. Parkinsonism Relat Disord 2023; 110:105364. [PMID: 36997437 DOI: 10.1016/j.parkreldis.2023.105364] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/08/2023] [Accepted: 03/10/2023] [Indexed: 03/29/2023]
Abstract
OBJECTIVE Local field potentials (LFP), specifically beta (13-30Hz) frequency measures, have been found to be associated with motor dysfunction in people with Parkinson's disease (PwPD). A consensus on beta subband (low- and high-beta) relationships to clinical state or therapy response has yet to be determined. The objective of this review is to synthesize literature reporting the association of low- and high-beta characteristics to clinical ratings of motor symptoms in PwPD. METHODS A systematic search of existing literature was completed using EMBASE. Articles which collected subthalamic nucleus (STN) LFPs using macroelectrodes in PwPD, analyzed low- (13-20 Hz) and high-beta (21-35 Hz) bands, collected UPDRS-III, and reported correlational strength or predictive capacity of LFPs to UPDRS-III scores. RESULTS The initial search yielded 234 articles, with 11 articles achieving inclusion. Beta measures included power spectral density, peak characteristics, and burst characteristics. High-beta was a significant predictor of UPDRS-III responses to therapy in 5 (100%) articles. Low-beta was significantly associated with UPDRS-III total score in 3 (60%) articles. Low- and high-beta associations to UPDRS-III subscores were mixed. CONCLUSION This systematic review reinforces previous reports that beta band oscillatory measures demonstrate a consistent relationship to Parkinsonian motor symptoms and ability to predict motor response to therapy. Specifically, high-beta, demonstrated a consistent ability to predict UPDRS-III responses to common PD therapies, while low-beta measures were associated with general Parkinsonian symptom severity. Continued research is needed to determine which beta subband demonstrates the greatest association to motor symptom subtypes and potentially offers clinical utility toward LFP-guided DBS programming and adaptive DBS.
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A systematic review of local field potential physiomarkers in Parkinson's disease: from clinical correlations to adaptive deep brain stimulation algorithms. J Neurol 2023; 270:1162-1177. [PMID: 36209243 PMCID: PMC9886603 DOI: 10.1007/s00415-022-11388-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/16/2022] [Indexed: 02/03/2023]
Abstract
Deep brain stimulation (DBS) treatment has proven effective in suppressing symptoms of rigidity, bradykinesia, and tremor in Parkinson's disease. Still, patients may suffer from disabling fluctuations in motor and non-motor symptom severity during the day. Conventional DBS treatment consists of continuous stimulation but can potentially be further optimised by adapting stimulation settings to the presence or absence of symptoms through closed-loop control. This critically relies on the use of 'physiomarkers' extracted from (neuro)physiological signals. Ideal physiomarkers for adaptive DBS (aDBS) are indicative of symptom severity, detectable in every patient, and technically suitable for implementation. In the last decades, much effort has been put into the detection of local field potential (LFP) physiomarkers and in their use in clinical practice. We conducted a research synthesis of the correlations that have been reported between LFP signal features and one or more specific PD motor symptoms. Features based on the spectral beta band (~ 13 to 30 Hz) explained ~ 17% of individual variability in bradykinesia and rigidity symptom severity. Limitations of beta band oscillations as physiomarker are discussed, and strategies for further improvement of aDBS are explored.
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Subthalamic beta bursts correlate with dopamine-dependent motor symptoms in 106 Parkinson's patients. NPJ Parkinsons Dis 2023; 9:2. [PMID: 36611027 PMCID: PMC9825387 DOI: 10.1038/s41531-022-00443-3] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 12/21/2022] [Indexed: 01/09/2023] Open
Abstract
Pathologically increased beta power has been described as a biomarker for Parkinson's disease (PD) and related to prolonged bursts of subthalamic beta synchronization. Here, we investigate the association between subthalamic beta dynamics and motor impairment in a cohort of 106 Parkinson's patients in the ON- and OFF-medication state, using two different methods of beta burst determination. We report a frequency-specific correlation of low beta power and burst duration with motor impairment OFF dopaminergic medication. Furthermore, reduction of power and burst duration correlated significantly with symptom alleviation through dopaminergic medication. Importantly, qualitatively similar results were yielded with two different methods of beta burst definition. Our findings validate the robustness of previous results on pathological changes in subcortical oscillations both in the frequency- as well as in the time-domain in the largest cohort of PD patients to date with important implications for next-generation adaptive deep brain stimulation control algorithms.
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Sure M, Mertiens S, Vesper J, Schnitzler A, Florin E. Alterations of resting-state networks of Parkinson's disease patients after subthalamic DBS surgery. Neuroimage Clin 2023; 37:103317. [PMID: 36610312 PMCID: PMC9850202 DOI: 10.1016/j.nicl.2023.103317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 12/27/2022] [Accepted: 01/02/2023] [Indexed: 01/05/2023]
Abstract
The implantation of deep brain stimulation (DBS) electrodes in Parkinson's disease (PD) patients can lead to a temporary improvement in motor symptoms, known as the stun effect. However, the network alterations induced by the stun effect are not well characterized. As therapeutic DBS is known to alter resting-state networks (RSN) and subsequent motor symptoms in patients with PD, we aimed to investigate whether the DBS-related stun effect also modulated RSNs. Therefore, we analyzed RSNs of 27 PD patients (8 females, 59.0 +- 8.7 years) using magnetoencephalography and compared them to RSNs of 24 age-matched healthy controls (8 females, 62.8 +- 5.1 years). We recorded 30 min of resting-state activity two days before and one day after implantation of the electrodes with and without dopaminergic medication. RSNs were determined by use of phase-amplitude coupling between a low frequency phase and a high gamma amplitude and examined for differences between conditions (i.e., pre vs post surgery). We identified four RSNs across all conditions: sensory-motor, visual, fronto-occipital, and frontal. Each RSN was altered due to electrode implantation. Importantly, these changes were not restricted to spatially close areas to the electrode trajectory. Interestingly, pre-operative RSNs corresponded better with healthy control RSNs regarding the spatial overlap, although the stun effect is associated with motor improvement. Our findings reveal that the stun effect induced by implantation of electrodes exerts brain wide changes in different functional RSNs.
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Affiliation(s)
- Matthias Sure
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
| | - Sean Mertiens
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
| | - Jan Vesper
- Department of Functional Neurosurgery and Stereotaxy, Medical Faculty, University Hospital, Düsseldorf, Germany.
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany; Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, University Hospital, Düsseldorf, Germany.
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
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Cortical network formation based on subthalamic beta bursts in Parkinson's disease. Neuroimage 2022; 263:119619. [PMID: 36087901 DOI: 10.1016/j.neuroimage.2022.119619] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 08/02/2022] [Accepted: 09/06/2022] [Indexed: 11/21/2022] Open
Abstract
Recent evidence suggests that beta bursts in subthalamic nucleus (STN) play an important role in Parkinsonian pathophysiology. We studied the spatio-temporal relationship between STN beta bursts and cortical activity in 26 Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery. Postoperatively, we simultaneously recorded STN local field potentials (LFP) from externalized DBS leads and cortical activity using whole-brain magnetoencephalography. Event-related magnetic fields (ERF) were averaged time-locked to STN beta bursts and subjected to source localization. Our results demonstrate that ERF exhibiting activity significantly different from baseline activity were localized within areas functionally related to associative, limbic, and motor systems as well as regions pertinent for visual and language processing. Our data suggest that STN beta bursts are involved in network formation between STN and cortex. This interaction is in line with the idea of parallel processing within the basal ganglia-cortex loop, specifically within the functional subsystems of the STN (i.e., associative, limbic, motor, and the related cortical areas). ERFs within visual and language-related cortical areas indicate involvement of beta bursts in STN-cortex networks beyond the associative, limbic, and motor loops. In sum, our results highlight the involvement of STN beta bursts in the formation of multiple STN - cortex loops in patients with PD.
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Cortical beta burst dynamics are altered in Parkinson's disease but normalized by deep brain stimulation. Neuroimage 2022; 257:119308. [PMID: 35569783 DOI: 10.1016/j.neuroimage.2022.119308] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 04/12/2022] [Accepted: 05/10/2022] [Indexed: 11/21/2022] Open
Abstract
Exaggerated subthalamic beta oscillatory activity and increased beta range cortico-subthalamic synchrony have crystallized as the electrophysiological hallmarks of Parkinson's disease. Beta oscillatory activity is not tonic but occurs in 'bursts' of transient amplitude increases. In Parkinson's disease, the characteristics of these bursts are altered especially in the basal ganglia. However, beta oscillatory dynamics at the cortical level and how they compare with healthy brain activity is less well studied. We used magnetoencephalography (MEG) to study sensorimotor cortical beta bursting and its modulation by subthalamic deep brain stimulation in Parkinson's disease patients and age-matched healthy controls. We show that the changes in beta bursting amplitude and duration typical of Parkinson's disease can also be observed in the sensorimotor cortex, and that they are modulated by chronic subthalamic deep brain stimulation, which, in turn, is reflected in improved motor function at the behavioural level. In addition to the changes in individual beta bursts, their timing relative to each other was altered in patients compared to controls: bursts were more clustered in untreated Parkinson's disease, occurring in 'bursts of bursts', and re-burst probability was higher for longer compared to shorter bursts. During active deep brain stimulation, the beta bursting in patients resembled healthy controls' data. In summary, both individual bursts' characteristics and burst patterning are affected in Parkinson's disease, and subthalamic deep brain stimulation normalizes some of these changes to resemble healthy controls' beta bursting activity, suggesting a non-invasive biomarker for patient and treatment follow-up.
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