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Ricci A, Rubino E, Serra GP, Wallén-Mackenzie Å. Concerning neuromodulation as treatment of neurological and neuropsychiatric disorder: Insights gained from selective targeting of the subthalamic nucleus, para-subthalamic nucleus and zona incerta in rodents. Neuropharmacology 2024; 256:110003. [PMID: 38789078 DOI: 10.1016/j.neuropharm.2024.110003] [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: 02/06/2024] [Revised: 04/26/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024]
Abstract
Neuromodulation such as deep brain stimulation (DBS) is advancing as a clinical intervention in several neurological and neuropsychiatric disorders, including Parkinson's disease, dystonia, tremor, and obsessive-compulsive disorder (OCD) for which DBS is already applied to alleviate severely afflicted individuals of symptoms. Tourette syndrome and drug addiction are two additional disorders for which DBS is in trial or proposed as treatment. However, some major remaining obstacles prevent this intervention from reaching its full therapeutic potential. Side-effects have been reported, and not all DBS-treated individuals are relieved of their symptoms. One major target area for DBS electrodes is the subthalamic nucleus (STN) which plays important roles in motor, affective and associative functions, with impact on for example movement, motivation, impulsivity, compulsivity, as well as both reward and aversion. The multifunctionality of the STN is complex. Decoding the anatomical-functional organization of the STN could enhance strategic targeting in human patients. The STN is located in close proximity to zona incerta (ZI) and the para-subthalamic nucleus (pSTN). Together, the STN, pSTN and ZI form a highly heterogeneous and clinically important brain area. Rodent-based experimental studies, including opto- and chemogenetics as well as viral-genetic tract tracings, provide unique insight into complex neuronal circuitries and their impact on behavior with high spatial and temporal precision. This research field has advanced tremendously over the past few years. Here, we provide an inclusive review of current literature in the pre-clinical research fields centered around STN, pSTN and ZI in laboratory mice and rats; the three highly heterogeneous and enigmatic structures brought together in the context of relevance for treatment strategies. Specific emphasis is placed on methods of manipulation and behavioral impact.
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Affiliation(s)
- Alessia Ricci
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Eleonora Rubino
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Gian Pietro Serra
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Åsa Wallén-Mackenzie
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA.
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Pavlovsky P, Sayfulina K, Gamaleya A, Tomskiy A, Belova E, Sedov A. Clinical asymmetry in Parkinson's disease is characterized by prevalence of subthalamic pause-burst neurons and alpha-beta oscillations. Clin Neurophysiol 2024; 165:36-43. [PMID: 38943791 DOI: 10.1016/j.clinph.2024.06.003] [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: 12/09/2023] [Revised: 04/22/2024] [Accepted: 06/03/2024] [Indexed: 07/01/2024]
Abstract
OBJECTIVE We aimed to establish specific biomarkers of Parkinson's disease (PD) by comparing activity of more affected (MA) and less affected (LA) subthalamic nucleus (STN) of patients with prominent clinical asymmetry. METHODS We recorded single unit activity and local field potentials (LFP) of the STN during deep brain stimulation surgeries. Neuronal firing patterns and discharge rate, as well as oscillatory features of both single cells and LFP, were analyzed. RESULTS We observed notable differences in proportions of irregular-burst and pause-burst, but not tonic neurons, between the hemispheres. Oscillations of pause-burst neurons correlated significantly with the bradykinesia and rigidity scores of the corresponding hemibody. LFP derived from MA STN featured greater power in 12-15 Hz. CONCLUSIONS Our results provide evidence that the increased proportion of units with prolonged pauses may be associated with PD. We also speculate that some of them may gain rhythmicity in the alpha-beta range in relation to hypokinetic symptoms, long-term disease, or both. SIGNIFICANCE Our findings highlight the relation between specific oscillatory features of the STN, predominance of subthalamic pause-burst units and PD pathophysiology.
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Affiliation(s)
- Philip Pavlovsky
- Laboratory of Human Cell Neurophysiology, N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences, 119991, Kosygina str.4, Moscow, Russian Federation; Lomonosov Moscow State University, Department of Biology, 119234, 1-12 Leninskie Gory, Moscow, Russian Federation.
| | - Ksenia Sayfulina
- Laboratory of Human Cell Neurophysiology, N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences, 119991, Kosygina str.4, Moscow, Russian Federation
| | - Anna Gamaleya
- N.N. Burdenko National Medical Research Center for Neurosurgery, 125047, 4th Tverskaya-Yamskaya str. 16, Moscow, Russian Federation
| | - Alexey Tomskiy
- N.N. Burdenko National Medical Research Center for Neurosurgery, 125047, 4th Tverskaya-Yamskaya str. 16, Moscow, Russian Federation
| | - Elena Belova
- Laboratory of Human Cell Neurophysiology, N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences, 119991, Kosygina str.4, Moscow, Russian Federation
| | - Alexey Sedov
- Laboratory of Human Cell Neurophysiology, N.N. Semenov Federal Research Center for Chemical Physics Russian Academy of Sciences, 119991, Kosygina str.4, Moscow, Russian Federation; Moscow Institute of Physics and Technology, 141701, 9 Institutskiy per., Dolgoprudny, Moscow Region, Russian Federation
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Baker SK, Radcliffe EM, Kramer DR, Ojemann S, Case M, Zarns C, Holt-Becker A, Raike RS, Baumgartner AJ, Kern DS, Thompson JA. Comparison of beta peak detection algorithms for data-driven deep brain stimulation programming strategies in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:150. [PMID: 39122725 PMCID: PMC11315991 DOI: 10.1038/s41531-024-00762-7] [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: 02/27/2024] [Accepted: 07/24/2024] [Indexed: 08/12/2024] Open
Abstract
Oscillatory activity within the beta frequency range (13-30 Hz) serves as a Parkinson's disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms against a benchmark established by expert consensus. The most accurate algorithms, all sharing similar underlying algebraic dynamic peak amplitude thresholding approaches, matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization.
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Affiliation(s)
- Sunderland K Baker
- Pennsylvania State University, Department of Biobehavioral Health, University Park, PA, 16802, USA
| | - Erin M Radcliffe
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Bioengineering, Aurora, CO, 80045, USA
| | - Daniel R Kramer
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
| | - Steven Ojemann
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA
| | - Michelle Case
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Caleb Zarns
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Abbey Holt-Becker
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Robert S Raike
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Alexander J Baumgartner
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA
| | - Drew S Kern
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA
| | - John A Thompson
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA.
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA.
- University of Colorado Anschutz Medical Campus, Department of Psychiatry, Aurora, CO, 80045, USA.
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Sheheitli H, Jirsa V. Incorporating slow NMDA-type receptors with nonlinear voltage-dependent magnesium block in a next generation neural mass model: derivation and dynamics. J Comput Neurosci 2024:10.1007/s10827-024-00874-2. [PMID: 38967732 DOI: 10.1007/s10827-024-00874-2] [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: 06/28/2023] [Revised: 03/11/2024] [Accepted: 06/26/2024] [Indexed: 07/06/2024]
Abstract
We derive a next generation neural mass model of a population of quadratic-integrate-and-fire neurons, with slow adaptation, and conductance-based AMPAR, GABAR and nonlinear NMDAR synapses. We show that the Lorentzian ansatz assumption can be satisfied by introducing a piece-wise polynomial approximation of the nonlinear voltage-dependent magnesium block of NMDAR current. We study the dynamics of the resulting system for two example cases of excitatory cortical neurons and inhibitory striatal neurons. Bifurcation diagrams are presented comparing the different dynamical regimes as compared to the case of linear NMDAR currents, along with sample comparison simulation time series demonstrating different possible oscillatory solutions. The omission of the nonlinearity of NMDAR currents results in a shift in the range (and possible disappearance) of the constant high firing rate regime, along with a modulation in the amplitude and frequency power spectrum of oscillations. Moreover, nonlinear NMDAR action is seen to be state-dependent and can have opposite effects depending on the type of neurons involved and the level of input firing rate received. The presented model can serve as a computationally efficient building block in whole brain network models for investigating the differential modulation of different types of synapses under neuromodulatory influence or receptor specific malfunction.
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Affiliation(s)
- Hiba Sheheitli
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France.
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States.
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States.
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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Vissani M, Bush A, Lipski WJ, Fischer P, Neudorfer C, Holt LL, Fiez JA, Turner RS, Richardson RM. Spike-phase coupling of subthalamic neurons to posterior opercular cortex predicts speech sound accuracy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.18.562969. [PMID: 37905141 PMCID: PMC10614892 DOI: 10.1101/2023.10.18.562969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Speech provides a rich context for understanding how cortical interactions with the basal ganglia contribute to unique human behaviors, but opportunities for direct intracranial recordings across cortical-basal ganglia networks are rare. We recorded electrocorticographic signals in the cortex synchronously with single units in the basal ganglia during awake neurosurgeries where subjects spoke syllable repetitions. We discovered that individual STN neurons have transient (200ms) spike-phase coupling (SPC) events with multiple cortical regions. The spike timing of STN neurons was coordinated with the phase of theta-alpha oscillations in the posterior supramarginal and superior temporal gyrus during speech planning and production. Speech sound errors occurred when this STN-cortical interaction was delayed. Our results suggest that the STN supports mechanisms of speech planning and auditory-sensorimotor integration during speech production that are required to achieve high fidelity of the phonological and articulatory representation of the target phoneme. These findings establish a framework for understanding cortical-basal ganglia interaction in other human behaviors, and additionally indicate that firing-rate based models are insufficient for explaining basal ganglia circuit behavior.
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Affiliation(s)
- Matteo Vissani
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Alan Bush
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Witold J. Lipski
- Department of Neurobiology, Systems Neuroscience Center and Center for Neuroscience, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - Petra Fischer
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, University Walk, BS8 1TD Bristol, United Kingdom
| | - Clemens Neudorfer
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Lori L. Holt
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712 USA
| | - Julie A. Fiez
- Department of Psychology, University of Pittsburgh, Pittsburgh 15260, PA, USA
| | - Robert S. Turner
- Department of Neurobiology, Systems Neuroscience Center and Center for Neuroscience, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - R. Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
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Molina Galindo LS, Gonzalez-Escamilla G, Fleischer V, Grotegerd D, Meinert S, Ciolac D, Person M, Stein F, Brosch K, Nenadić I, Alexander N, Kircher T, Hahn T, Winter Y, Othman AE, Bittner S, Zipp F, Dannlowski U, Groppa S. Concurrent inflammation-related brain reorganization in multiple sclerosis and depression. Brain Behav Immun 2024; 119:978-988. [PMID: 38761819 DOI: 10.1016/j.bbi.2024.05.015] [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: 12/20/2023] [Revised: 05/02/2024] [Accepted: 05/12/2024] [Indexed: 05/20/2024] Open
Abstract
BACKGROUND Neuroinflammation affects brain tissue integrity in multiple sclerosis (MS) and may have a role in major depressive disorder (MDD). Whether advanced magnetic resonance imaging characteristics of the gray-to-white matter border serve as proxy of neuroinflammatory activity in MDD and MS remain unknown. METHODS We included 684 participants (132 MDD patients with recurrent depressive episodes (RDE), 70 MDD patients with a single depressive episode (SDE), 222 MS patients without depressive symptoms (nMS), 58 MS patients with depressive symptoms (dMS), and 202 healthy controls (HC)). 3 T-T1w MRI-derived gray-to-white matter contrast (GWc) was used to reconstruct and characterize connectivity alterations of GWc-covariance networks by means of modularity, clustering coefficient, and degree. A cross-validated support vector machine was used to test the ability of GWc to stratify groups according to their depression symptoms, measured with BDI, at the single-subject level in MS and MDD independently. FINDINGS MS and MDD patients showed increased modularity (ANOVA partial-η2 = 0.3) and clustering (partial-η2 = 0.1) compared to HC. In the subgroups, a linear trend analysis attested a gradient of modularity increases in the form: HC, dMS, nMS, SDE, and RDE (ANOVA partial-η2 = 0.28, p < 0.001) while this trend was less evident for clustering coefficient. Reduced morphological integrity (GWc) was seen in patients with increased depressive symptoms (partial-η2 = 0.42, P < 0.001) and was associated with depression scores across patient groups (r = -0.2, P < 0.001). Depressive symptoms in MS were robustly classified (88 %). CONCLUSIONS Similar structural network alterations in MDD and MS exist, suggesting possible common inflammatory events like demyelination, neuroinflammation that are caught by GWc analyses. These alterations may vary depending on the severity of symptoms and in the case of MS may elucidate the occurrence of comorbid depression.
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Affiliation(s)
- Lara S Molina Galindo
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dumitru Ciolac
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Maren Person
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Frederike Stein
- Klinik für Psychiatrie und Psychotherapie, Philipps-Universität Marburg, Marburg, Germany
| | - Katharina Brosch
- Klinik für Psychiatrie und Psychotherapie, Philipps-Universität Marburg, Marburg, Germany
| | - Igor Nenadić
- Klinik für Psychiatrie und Psychotherapie, Philipps-Universität Marburg, Marburg, Germany
| | - Nina Alexander
- Klinik für Psychiatrie und Psychotherapie, Philipps-Universität Marburg, Marburg, Germany
| | - Tilo Kircher
- Klinik für Psychiatrie und Psychotherapie, Philipps-Universität Marburg, Marburg, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Yaroslav Winter
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Ahmed E Othman
- Department of Neuroradiology, Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany.
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Bange M, Gonzalez-Escamilla G, Herz DM, Tinkhauser G, Glaser M, Ciolac D, Pogosyan A, Kreis SL, Luhmann HJ, Tan H, Groppa S. Subthalamic stimulation modulates context-dependent effects of beta bursts during fine motor control. Nat Commun 2024; 15:3166. [PMID: 38605062 PMCID: PMC11009405 DOI: 10.1038/s41467-024-47555-3] [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: 07/19/2023] [Accepted: 04/02/2024] [Indexed: 04/13/2024] Open
Abstract
Increasing evidence suggests a considerable role of pre-movement beta bursts for motor control and its impairment in Parkinson's disease. However, whether beta bursts occur during precise and prolonged movements and if they affect fine motor control remains unclear. To investigate the role of within-movement beta bursts for fine motor control, we here combine invasive electrophysiological recordings and clinical deep brain stimulation in the subthalamic nucleus in 19 patients with Parkinson's disease performing a context-varying task that comprised template-guided and free spiral drawing. We determined beta bursts in narrow frequency bands around patient-specific peaks and assessed burst amplitude, duration, and their immediate impact on drawing speed. We reveal that beta bursts occur during the execution of drawing movements with reduced duration and amplitude in comparison to rest. Exclusively when drawing freely, they parallel reductions in acceleration. Deep brain stimulation increases the acceleration around beta bursts in addition to a general increase in drawing velocity and improvements of clinical function. These results provide evidence for a diverse and task-specific role of subthalamic beta bursts for fine motor control in Parkinson's disease; suggesting that pathological beta bursts act in a context dependent manner, which can be targeted by clinical deep brain stimulation.
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Affiliation(s)
- Manuel Bange
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Damian M Herz
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Dumitru Ciolac
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Alek Pogosyan
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Svenja L Kreis
- Institute of Physiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Heiko J Luhmann
- Institute of Physiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
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Abdulbaki A, Doll T, Helgers S, Heissler HE, Voges J, Krauss JK, Schwabe K, Alam M. Subthalamic Nucleus Deep Brain Stimulation Restores Motor and Sensorimotor Cortical Neuronal Oscillatory Activity in the Free-Moving 6-Hydroxydopamine Lesion Rat Parkinson Model. Neuromodulation 2024; 27:489-499. [PMID: 37002052 DOI: 10.1016/j.neurom.2023.01.014] [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: 08/10/2022] [Revised: 12/28/2022] [Accepted: 01/04/2023] [Indexed: 03/31/2023]
Abstract
OBJECTIVES Enhanced beta oscillations in cortical-basal ganglia (BG) thalamic circuitries have been linked to clinical symptoms of Parkinson's disease. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces beta band activity in BG regions, whereas little is known about activity in cortical regions. In this study, we investigated the effect of STN DBS on the spectral power of oscillatory activity in the motor cortex (MCtx) and sensorimotor cortex (SMCtx) by recording via an electrocorticogram (ECoG) array in free-moving 6-hydroxydopamine (6-OHDA) lesioned rats and sham-lesioned controls. MATERIALS AND METHODS Male Sprague-Dawley rats (250-350 g) were injected either with 6-OHDA or with saline in the right medial forebrain bundle, under general anesthesia. A stimulation electrode was then implanted in the ipsilateral STN, and an ECoG array was placed subdurally above the MCtx and SMCtx areas. Six days after the second surgery, the free-moving rats were individually recorded in three conditions: 1) basal activity, 2) during STN DBS, and 3) directly after STN DBS. RESULTS In 6-OHDA-lesioned rats (N = 8), the relative power of theta band activity was reduced, whereas activity of broad-range beta band (12-30 Hz) along with two different subbeta bands, that is, low (12-30 Hz) and high (20-30 Hz) beta band and gamma band, was higher in MCtx and SMCtx than in sham-lesioned controls (N = 7). This was, to some extent, reverted toward control level by STN DBS during and after stimulation. No major differences were found between contacts of the electrode grid or between MCtx and SMCtx. CONCLUSION Loss of nigrostriatal dopamine leads to abnormal oscillatory activity in both MCtx and SMCtx, which is compensated by STN stimulation, suggesting that parkinsonism-related oscillations in the cortex and BG are linked through their anatomic connections.
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Affiliation(s)
- Arif Abdulbaki
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany.
| | - Theodor Doll
- Fraunhofer Institute for Toxicology and Experimental Medicine, Hannover, Germany
| | - Simeon Helgers
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Hans E Heissler
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Jürgen Voges
- Department of Stereotactic Neurosurgery, University Hospital Magdeburg, Magdeburg, Germany
| | - Joachim K Krauss
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Kerstin Schwabe
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Mesbah Alam
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
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Lewis S, Radcliffe E, Ojemann S, Kramer DR, Hirt L, Case M, Holt-Becker AB, Raike R, Kern DS, Thompson JA. Pilot Study to Investigate the Use of In-Clinic Sensing to Identify Optimal Stimulation Parameters for Deep Brain Stimulation Therapy in Parkinson's Disease. Neuromodulation 2024; 27:509-519. [PMID: 36797194 DOI: 10.1016/j.neurom.2023.01.006] [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: 10/26/2022] [Revised: 12/19/2022] [Accepted: 01/09/2023] [Indexed: 02/16/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) programming is time intensive. Recent advances in sensing technology of local field potentials (LFPs) may enable improvements. Few studies have compared the use of this technology with standard of care. OBJECTIVE/HYPOTHESIS Sensing technology of subthalamic nucleus (STN) DBS leads in Parkinson's disease (PD) is reliable and predicts the optimal contacts and settings as predicted by clinical assessment. MATERIALS AND METHODS Five subjects with PD (n = 9 hemispheres) with bilateral STN DBS and sensing capable battery replacement were recruited. An LFP sensing review of all bipolar contact pairs was performed three times. Contact with the maximal beta peak power (MBP) was then clinically assessed in a double-blinded fashion, and five conditions were tested: 1) entry settings, 2) off stimulation, 3) MBP at 30 μs, 4) MBP at 60 μs, and 5) MBP at 90 μs. RESULTS Contact and frequency of the MBP power in all hemispheres did not differ across sessions. The entry settings matched with the contact with the MBP power in 5 of 9 hemispheres. No clinical difference was evident in the stimulation conditions. The clinician and subject preferred settings determined by MBP power in 7 of 9 and 5 of 7 hemispheres, respectively. CONCLUSIONS This study indicates that STN LFPs in PD recorded directly from contacts of the DBS lead provide consistent recordings across the frequency range and a reliably detected beta peak. Furthermore, programming based on the MBP power provides at least clinical equivalence to standard of care programming with STN DBS.
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Affiliation(s)
- Sydnei Lewis
- Biomedical Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Erin Radcliffe
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Steven Ojemann
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Daniel R Kramer
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Lisa Hirt
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Michelle Case
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic, Plc, Minneapolis, MN, USA
| | - Abbey B Holt-Becker
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic, Plc, Minneapolis, MN, USA
| | - Robert Raike
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic, Plc, Minneapolis, MN, USA
| | - Drew S Kern
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - John A Thompson
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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10
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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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11
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O'Keeffe AB, Merla A, Ashkan K. Deep brain stimulation of the subthalamic nucleus in Parkinson disease 2013-2023: where are we a further 10 years on? Br J Neurosurg 2024:1-9. [PMID: 38323603 DOI: 10.1080/02688697.2024.2311128] [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: 08/14/2023] [Accepted: 01/23/2024] [Indexed: 02/08/2024]
Abstract
Deep brain stimulation has been in clinical use for 30 years and during that time it has changed markedly from a small-scale treatment employed by only a few highly specialized centers into a widespread keystone approach to the management of disorders such as Parkinson's disease. In the intervening decades, many of the broad principles of deep brain stimulation have remained unchanged, that of electrode insertion into stereotactically targeted brain nuclei, however the underlying technology and understanding around the approach have progressed markedly. Some of the most significant advances have taken place over the last decade with the advent of artificial intelligence, directional electrodes, stimulation/recording implantable pulse generators and the potential for remote programming among many other innovations. New therapeutic targets are being assessed for their potential benefits and a surge in the number of deep brain stimulation implantations has given birth to a flourishing scientific literature surrounding the pathophysiology of brain disorders such as Parkinson's disease. Here we outline the developments of the last decade and look to the future of deep brain stimulation to attempt to discern some of the most promising lines of inquiry in this fast-paced and rapidly evolving field.
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Affiliation(s)
| | - Anca Merla
- King's College Hospital Department of Neurosurgery, Kings College Hospital, Denmark
| | - Keyoumars Ashkan
- King's College Hospital Department of Neurosurgery, Kings College Hospital, Denmark
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12
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Spiliotis K, Butenko K, Starke J, van Rienen U, Köhling R. Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model. J Neural Eng 2024; 20:066045. [PMID: 37988747 DOI: 10.1088/1741-2552/ad0e7c] [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: 02/01/2023] [Accepted: 11/21/2023] [Indexed: 11/23/2023]
Abstract
Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.
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Affiliation(s)
| | - Konstantin Butenko
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jens Starke
- Institute of Mathematics, University of Rostock, Rostock, Germany
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Department Life, Light and Matter, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
| | - Rüdiger Köhling
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany
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13
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Bosley KM, Luo Z, Amoozegar S, Acedillo K, Nakajima K, Johnson LA, Vitek JL, Wang J. Effect of subthalamic coordinated reset deep brain stimulation on Parkinsonian gait. Front Neuroinform 2023; 17:1185723. [PMID: 37692361 PMCID: PMC10483836 DOI: 10.3389/fninf.2023.1185723] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/01/2023] [Indexed: 09/12/2023] Open
Abstract
Introduction Coordinated Reset Deep Brain Stimulation (CR DBS) is a novel DBS approach for treating Parkinson's disease (PD) that uses lower levels of burst stimulation through multiple contacts of the DBS lead. Though CR DBS has been demonstrated to have sustained therapeutic effects on rigidity, tremor, bradykinesia, and akinesia following cessation of stimulation, i.e., carryover effect, its effect on Parkinsonian gait has not been well studied. Impaired gait is a disabling symptom of PD, often associated with a higher risk of falling and a reduced quality of life. The goal of this study was to explore the carryover effect of subthalamic CR DBS on Parkinsonian gait. Methods Three non-human primates (NHPs) were rendered Parkinsonian and implanted with a DBS lead in the subthalamic nucleus (STN). For each animal, STN CR DBS was delivered for several hours per day across five consecutive days. A clinical rating scale modified for NHP use (mUPDRS) was administered every morning to monitor the carryover effect of CR DBS on rigidity, tremor, akinesia, and bradykinesia. Gait was assessed quantitatively before and after STN CR DBS. The stride length and swing speed were calculated and compared to the baseline, pre-stimulation condition. Results In all three animals, carryover improvements in rigidity, bradykinesia, and akinesia were observed after CR DBS. Increased swing speed was observed in all the animals; however, improvement in stride length was only observed in NHP B2. In addition, STN CR DBS using two different burst frequencies was evaluated in NHP B2, and differential effects on the mUPDRS score and gait were observed. Discussion Although preliminary, our results indicate that STN CR DBS can improve Parkinsonian gait together with other motor signs when stimulation parameters are properly selected. This study further supports the continued development of CR DBS as a novel therapy for PD and highlights the importance of parameter selection in its clinical application.
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Affiliation(s)
- Kai M. Bosley
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Ziling Luo
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Sana Amoozegar
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Kit Acedillo
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Kanon Nakajima
- Neuroscience Program, Macalester College, Saint Paul, MN, United States
| | - Luke A. Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
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14
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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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15
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Mirzac D, Kreis SL, Luhmann HJ, Gonzalez-Escamilla G, Groppa S. Translating Pathological Brain Activity Primers in Parkinson's Disease Research. RESEARCH (WASHINGTON, D.C.) 2023; 6:0183. [PMID: 37383218 PMCID: PMC10298229 DOI: 10.34133/research.0183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023]
Abstract
Translational experimental approaches that help us better trace Parkinson's disease (PD) pathophysiological mechanisms leading to new therapeutic targets are urgently needed. In this article, we review recent experimental and clinical studies addressing abnormal neuronal activity and pathological network oscillations, as well as their underlying mechanisms and modulation. Our aim is to enhance our knowledge about the progression of Parkinson's disease pathology and the timing of its symptom's manifestation. Here, we present mechanistic insights relevant for the generation of aberrant oscillatory activity within the cortico-basal ganglia circuits. We summarize recent achievements extrapolated from available PD animal models, discuss their advantages and limitations, debate on their differential applicability, and suggest approaches for transferring knowledge on disease pathology into future research and clinical applications.
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Affiliation(s)
- Daniela Mirzac
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Svenja L. Kreis
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Heiko J. Luhmann
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
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16
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Rodriguez F, He S, Tan H. The potential of convolutional neural networks for identifying neural states based on electrophysiological signals: experiments on synthetic and real patient data. Front Hum Neurosci 2023; 17:1134599. [PMID: 37333834 PMCID: PMC10272439 DOI: 10.3389/fnhum.2023.1134599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 05/03/2023] [Indexed: 06/20/2023] Open
Abstract
Processing incoming neural oscillatory signals in real-time and decoding from them relevant behavioral or pathological states is often required for adaptive Deep Brain Stimulation (aDBS) and other brain-computer interface (BCI) applications. Most current approaches rely on first extracting a set of predefined features, such as the power in canonical frequency bands or various time-domain features, and then training machine learning systems that use those predefined features as inputs and infer what the underlying brain state is at each given time point. However, whether this algorithmic approach is best suited to extract all available information contained within the neural waveforms remains an open question. Here, we aim to explore different algorithmic approaches in terms of their potential to yield improvements in decoding performance based on neural activity such as measured through local field potentials (LFPs) recordings or electroencephalography (EEG). In particular, we aim to explore the potential of end-to-end convolutional neural networks, and compare this approach with other machine learning methods that are based on extracting predefined feature sets. To this end, we implement and train a number of machine learning models, based either on manually constructed features or, in the case of deep learning-based models, on features directly learnt from the data. We benchmark these models on the task of identifying neural states using simulated data, which incorporates waveform features previously linked to physiological and pathological functions. We then assess the performance of these models in decoding movements based on local field potentials recorded from the motor thalamus of patients with essential tremor. Our findings, derived from both simulated and real patient data, suggest that end-to-end deep learning-based methods may surpass feature-based approaches, particularly when the relevant patterns within the waveform data are either unknown, difficult to quantify, or when there may be, from the point of view of the predefined feature extraction pipeline, unidentified features that could contribute to decoding performance. The methodologies proposed in this study might hold potential for application in adaptive deep brain stimulation (aDBS) and other brain-computer interface systems.
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17
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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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18
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Neumann WJ, Gilron R, Little S, Tinkhauser G. Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation. Mov Disord 2023. [PMID: 37148553 DOI: 10.1002/mds.29415] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 03/27/2023] [Accepted: 04/05/2023] [Indexed: 05/08/2023] Open
Abstract
Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patient-specific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Simon Little
- Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, California, USA
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
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Averna A, Debove I, Nowacki A, Peterman K, Duchet B, Sousa M, Bernasconi E, Alva L, Lachenmayer ML, Schuepbach M, Pollo C, Krack P, Nguyen TAK, Tinkhauser G. Spectral Topography of the Subthalamic Nucleus to Inform Next-Generation Deep Brain Stimulation. Mov Disord 2023; 38:818-830. [PMID: 36987385 PMCID: PMC7615852 DOI: 10.1002/mds.29381] [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: 11/01/2022] [Revised: 01/13/2023] [Accepted: 02/27/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing-based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN). OBJECTIVES The aims were to systematically investigate the spectral topography, including a wide range of sub-bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS. METHODS STN-LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub-bands (delta, theta, alpha, low-beta, high-beta, low-gamma, high-gamma, and fast-gamma (FG) as well as low- and fast high-frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS. RESULTS The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior-superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub-bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher-frequency hot spots were predictive for the best rigidity response to DBS. CONCLUSIONS The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next-generation sensing-based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Alberto Averna
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Ines Debove
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Andreas Nowacki
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Katrin Peterman
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Benoit Duchet
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Mário Sousa
- 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
| | - Laura Alva
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Martin L. Lachenmayer
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | | | - Claudio Pollo
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Paul Krack
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Thuy-Anh K. Nguyen
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
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20
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Bingham CS, Petersen MV, Parent M, McIntyre CC. Evolving characterization of the human hyperdirect pathway. Brain Struct Funct 2023; 228:353-365. [PMID: 36708394 PMCID: PMC10716731 DOI: 10.1007/s00429-023-02610-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 01/11/2023] [Indexed: 01/29/2023]
Abstract
The hyperdirect pathway (HDP) represents the main glutamatergic input to the subthalamic nucleus (STN), through which the motor and prefrontal cerebral cortex can modulate basal ganglia activity. Further, direct activation of the motor HDP is thought to be an important component of therapeutic deep brain stimulation (DBS), mediating the disruption of pathological oscillations. Alternatively, unintended recruitment of the prefrontal HDP may partly explain some cognitive side effects of DBS therapy. Previous work describing the HDP has focused on non-human primate (NHP) histological pathway tracings, diffusion-weighted MRI analysis of human white matter, and electrophysiology studies involving paired cortical recordings with DBS. However, none of these approaches alone yields a complete understanding of the complexities of the HDP. As such, we propose that generative modeling methods hold promise to bridge anatomy and physiology results, from both NHPs and humans, into a more detailed representation of the human HDP. Nonetheless, numerous features of the HDP remain to be experimentally described before model-based methods can simulate corticosubthalamic activity with a high degree of scientific detail. Therefore, the goals of this review are to examine the experimental evidence for HDP projections from across the primate neocortex and discuss new data which are required to improve the utility of anatomical and biophysical models of the human corticosubthalamic system.
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Affiliation(s)
- Clayton S Bingham
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Martin Parent
- Department of Psychiatry and Neuroscience, Laval University, Quebec, Canada
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Department of Neurosurgery, Duke University, Durham, NC, USA.
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21
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Tatz JR, Mather A, Wessel JR. β-Bursts over Frontal Cortex Track the Surprise of Unexpected Events in Auditory, Visual, and Tactile Modalities. J Cogn Neurosci 2023; 35:485-508. [PMID: 36603039 PMCID: PMC9894628 DOI: 10.1162/jocn_a_01958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
One of the fundamental ways in which the brain regulates and monitors behavior is by making predictions about the sensory environment and adjusting behavior when those expectations are violated. As such, surprise is one of the fundamental computations performed by the human brain. In recent years, it has been well established that one key aspect by which behavior is adjusted during surprise is inhibitory control of the motor system. Moreover, because surprise automatically triggers inhibitory control without much proactive influence, it can provide unique insights into largely reactive control processes. Recent years have seen tremendous interest in burst-like β frequency events in the human (and nonhuman) local field potential-especially over (p)FC-as a potential signature of inhibitory control. To date, β-bursts have only been studied in paradigms involving a substantial amount of proactive control (such as the stop-signal task). Here, we used two cross-modal oddball tasks to investigate whether surprise processing is accompanied by increases in scalp-recorded β-bursts. Indeed, we found that unexpected events in all tested sensory domains (haptic, auditory, visual) were followed by low-latency increases in β-bursting over frontal cortex. Across experiments, β-burst rates were positively correlated with estimates of surprise derived from Shannon's information theory, a type of surprise that represents the degree to which a given stimulus violates prior expectations. As such, the current work clearly implicates frontal β-bursts as a signature of surprise processing. We discuss these findings in the context of common frameworks of inhibitory and cognitive control after unexpected events.
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Affiliation(s)
- Joshua R. Tatz
- University of Iowa,University of Iowa Hospital and Clinics
| | | | - Jan R. Wessel
- University of Iowa,University of Iowa Hospital and Clinics
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22
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Formaggio E, Tonellato M, Antonini A, Castiglia L, Gallo L, Manganotti P, Masiero S, Del Felice A. Oscillatory EEG-TMS Reactivity in Parkinson Disease. J Clin Neurophysiol 2023; 40:263-268. [PMID: 34280941 DOI: 10.1097/wnp.0000000000000881] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE A dysfunction of beta oscillatory activity is the neurophysiological hallmark of Parkinson disease (PD). How cortical activity reacts to external perturbations may provide insight into pathophysiological mechanisms. This study aims at identifying modifications in EEG rhythms after transcranial magnetic stimulation (TMS) in PD. We hypothesize that single-pulse TMS can modulate brain intrinsic oscillatory properties (e.g., beta excess). METHODS EEG data were coregistered during single-pulse TMS (100 stimuli over the primary motor cortex [M1, hotspot for Abductor Pollicis Brevis], random intertrial interval from 8 to 13 seconds). We used a time-frequency analysis based on wavelet method to characterize modification of oscillatory rhythms (delta [1-4 Hz], theta [4-7 Hz], alpha [8-12 Hz], and beta [13-30 Hz] in 15 participants with PD compared with 10 healthy controls. RESULTS An increase in beta power over the sensorimotor areas was recorded at rest in the PD group ( P < 0.05). Brain oscillations in PD transiently reset after TMS: beta power over M1 becomes comparable to that recorded in aged-matched healthy subjects in the 2 seconds following TMS. CONCLUSIONS Transcranial magnetic stimulation over the dominant motor cortex transiently normalizes cortical oscillations. More user-friendly noninvasive brain stimulation needs to be trialed, based on this proof of concept, to provide practical, portable techniques to treat motor symptoms in PD.
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Affiliation(s)
- Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Michele Tonellato
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Leonora Castiglia
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Laura Gallo
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Paolo Manganotti
- Neurology Section, Cattinara University Hospital, University of Trieste, Trieste, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
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23
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Chen PL, Chen YC, Tu PH, Liu TC, Chen MC, Wu HT, Yeap MC, Yeh CH, Lu CS, Chen CC. Subthalamic high-beta oscillation informs the outcome of deep brain stimulation in patients with Parkinson's disease. Front Hum Neurosci 2022; 16:958521. [PMID: 36158623 PMCID: PMC9493001 DOI: 10.3389/fnhum.2022.958521] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe therapeutic effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's disease (PD) is related to the modulation of pathological neural activities, particularly the synchronization in the β band (13–35 Hz). However, whether the local β activity in the STN region can directly predict the stimulation outcome remains unclear.ObjectiveWe tested the hypothesis that low-β (13–20 Hz) and/or high-β (20–35 Hz) band activities recorded from the STN region can predict DBS efficacy.MethodsLocal field potentials (LFPs) were recorded in 26 patients undergoing deep brain stimulation surgery in the subthalamic nucleus area. Recordings were made after the implantation of the DBS electrode prior to its connection to a stimulator. The maximum normalized powers in the theta (4–7 Hz), alpha (7–13 Hz), low-β (13–20 Hz), high-β (20–35 Hz), and low-γ (40–55 Hz) subbands in the postoperatively recorded LFP were correlated with the stimulation-induced improvement in contralateral tremor or bradykinesia–rigidity. The distance between the contact selected for stimulation and the contact with the maximum subband power was correlated with the stimulation efficacy. Following the identification of the potential predictors by the significant correlations, a multiple regression analysis was performed to evaluate their effect on the outcome.ResultsThe maximum high-β power was positively correlated with bradykinesia–rigidity improvement (rs = 0.549, p < 0.0001). The distance to the contact with maximum high-β power was negatively correlated with bradykinesia–rigidity improvement (rs = −0.452, p < 0.001). No significant correlation was observed with low-β power. The maximum high-β power and the distance to the contact with maximum high-β power were both significant predictors for bradykinesia–rigidity improvement in the multiple regression analysis, explaining 37.4% of the variance altogether. Tremor improvement was not significantly correlated with any frequency.ConclusionHigh-β oscillations, but not low-β oscillations, recorded from the STN region with the DBS lead can inform stimulation-induced improvement in contralateral bradykinesia–rigidity in patients with PD. High-β oscillations can help refine electrode targeting and inform contact selection for DBS therapy.
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Affiliation(s)
- Po-Lin Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Yi-Chieh Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Po-Hsun Tu
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Tzu-Chi Liu
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Department of Mathematics, National Taiwan University, Taipei, Taiwan
| | - Min-Chi Chen
- Department of Public Health, Biostatistics Consulting Center, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Hau-Tieng Wu
- Department of Mathematics, Duke University, Durham, NC, United States
- Department of Statistical Science, Duke University, Durham, NC, United States
| | - Mun-Chun Yeap
- Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Chih-Hua Yeh
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Neuroradiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Chin-Song Lu
- Professor Lu Neurological Clinic, Taoyuan, Taiwan
| | - Chiung-Chu Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- *Correspondence: Chiung-Chu Chen
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24
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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: 0] [Impact Index Per Article: 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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25
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Du T, Yuan T, Zhu G, Ma R, Zhang X, Chen Y, Zhang J. The effect of age and disease duration on the efficacy of subthalamic nuclei deep brain stimulation in Parkinson's disease patients. CNS Neurosci Ther 2022; 28:2163-2171. [PMID: 36069345 PMCID: PMC9627397 DOI: 10.1111/cns.13958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Previous studies have reported the effects of age and disease duration on the efficacy of subthalamic nuclei deep brain stimulation (STN-DBS) of Parkinson's disease (PD) patients. However, available data involving these issues are not consistent. In particular, the effect of age and disease duration on the initial efficacy of STN-DBS has not been established. METHODS A total of 51 patients with PD treated with bilateral STN-DBS were involved in the present study. They received clinical symptom evaluation during the preoperative, initial, and chronic stages of surgery. The correlations between age when undergoing surgery/age at disease onset/disease duration and outcomes of STN-DBS were measured. RESULTS The preoperative levodopa response was negatively associated with age. During the initial stage, the age when undergoing surgery and age at disease onset were negatively correlated with the effect on bradykinesia, with better symptom control of general symptoms in long-term disease patients. Similarly, patients with an early time of surgery and disease onset and long-term disease duration showed better control of bradykinesia and axial symptoms at the chronic stage. Furthermore, a long-term disease duration and early disease onset benefited from an increase of therapeutic efficacy in general, rigid, and axial symptoms with STN-DBS after a long period. Nevertheless, patients with late disease onset achieved a better relief of stigma. CONCLUSION Age and disease durations played a unique role in controlling the symptoms of PD patients treated with STN-DBS. These results may contribute to patient selection and adjustments of expectations of surgery, based on the age, disease duration, and different symptoms.
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Affiliation(s)
- Tingting Du
- Department of Functional NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
| | - Tianshuo Yuan
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xin Zhang
- Department of Functional NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
| | - Yingchuan Chen
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Jianguo Zhang
- Department of Functional NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina,Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina,Beijing Key Laboratory of NeurostimulationBeijingChina
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26
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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: 11] [Impact Index Per Article: 5.5] [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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27
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Fim Neto A, de Luccas JB, Bianqueti BL, da Silva LR, Almeida TP, Takahata AK, Teixeira MJ, Figueiredo EG, Nasuto SJ, Rocha MSG, Soriano DC, Godinho F. Subthalamic low beta bursts differ in Parkinson's disease phenotypes. Clin Neurophysiol 2022; 140:45-58. [PMID: 35728405 DOI: 10.1016/j.clinph.2022.05.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 05/20/2022] [Accepted: 05/26/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Parkinson's disease (PD) patients may be categorized into tremor-dominant (TD) and postural-instability and gait disorder (PIGD) motor phenotypes, but the dynamical aspects of subthalamic nucleus local field potentials (STN-LFP) and the neural correlates of this phenotypical classification remain unclear. METHODS 35 STN-LFP (20 PIGD and 15 TD) were investigated through continuous wavelet transform and machine-learning-based methods. The beta oscillation - the main band associated with motor impairment in PD - dynamics was characterized through beta burst parameters across phenotypes and burst intervals under specific proposed criteria for optimal burst threshold definition. RESULTS Low-frequency (13-22 Hz) beta burst probability was the best predictor for PD phenotypes (75% accuracy). PIGD patients presented higher average burst duration (p = 0.018), while TD patients exhibited higher burst probability (p = 0.014). Categorization into shorter and longer than 400 ms bursts led to significant interaction between burst length categories and the phenotypes (p < 0.050) as revealed by mixed-effects models. Long burst durations and short bursts probability positively correlated, respectively, with rigidity-bradykinesia (p = 0.029) and tremor (p = 0.038) scores. CONCLUSIONS Subthalamic low-frequency beta bursts differed between TD and PIGD phenotypes and correlated with motor symptoms. SIGNIFICANCE These findings improve the PD phenotypes' electrophysiological characterization and may define new criteria for adaptive deep brain stimulation.
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Affiliation(s)
- Arnaldo Fim Neto
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil; Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil; Department of Cosmic Rays and Chronology, Institute of Physics, University of Campinas, Campinas, Brazil.
| | - Julia Baldi de Luccas
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil; Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Bruno Leonardo Bianqueti
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil; Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Luiz Ricardo da Silva
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil
| | - Tiago Paggi Almeida
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - André Kazuo Takahata
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil; Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | | | | | | | | | - Diogo Coutinho Soriano
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil; Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Fabio Godinho
- Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil; Department of Functional Neurosurgery, Santa Marcelina Hospital, São Paulo, São Paulo, Brazil; Division of Functional Neurosurgery of Institute of Psychiatry, Department of Neurology, Medical School, University of São Paulo, São Paulo, São Paulo, Brazil
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28
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Neuroimaging signatures predicting motor improvement to focused ultrasound subthalamotomy in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:70. [PMID: 35665753 PMCID: PMC9166695 DOI: 10.1038/s41531-022-00332-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 05/13/2022] [Indexed: 11/24/2022] Open
Abstract
Subthalamotomy using transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) is a novel and promising treatment for Parkinson’s Disease (PD). In this study, we investigate if baseline brain imaging features can be early predictors of tcMRgFUS-subthalamotomy efficacy, as well as which are the post-treatment brain changes associated with the clinical outcomes. Towards this aim, functional and structural neuroimaging and extensive clinical data from thirty-five PD patients enrolled in a double-blind tcMRgFUS-subthalamotomy clinical trial were analyzed. A multivariate cross-correlation analysis revealed that the baseline multimodal imaging data significantly explain (P < 0.005, FWE-corrected) the inter-individual variability in response to treatment. Most predictive features at baseline included neural fluctuations in distributed cortical regions and structural integrity in the putamen and parietal regions. Additionally, a similar multivariate analysis showed that the population variance in clinical improvements is significantly explained (P < 0.001, FWE-corrected) by a distributed network of concurrent functional and structural brain changes in frontotemporal, parietal, occipital, and cerebellar regions, as opposed to local changes in very specific brain regions. Overall, our findings reveal specific quantitative brain signatures highly predictive of tcMRgFUS-subthalamotomy responsiveness in PD. The unanticipated weight of a cortical-subcortical-cerebellar subnetwork in defining clinical outcome extends the current biological understanding of the mechanisms associated with clinical benefits.
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29
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Pozzi NG, Palmisano C, Reich MM, Capetian P, Pacchetti C, Volkmann J, Isaias IU. Troubleshooting Gait Disturbances in Parkinson's Disease With Deep Brain Stimulation. Front Hum Neurosci 2022; 16:806513. [PMID: 35652005 PMCID: PMC9148971 DOI: 10.3389/fnhum.2022.806513] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 03/16/2022] [Indexed: 01/08/2023] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus or the globus pallidus is an established treatment for Parkinson's disease (PD) that yields a marked and lasting improvement of motor symptoms. Yet, DBS benefit on gait disturbances in PD is still debated and can be a source of dissatisfaction and poor quality of life. Gait disturbances in PD encompass a variety of clinical manifestations and rely on different pathophysiological bases. While gait disturbances arising years after DBS surgery can be related to disease progression, early impairment of gait may be secondary to treatable causes and benefits from DBS reprogramming. In this review, we tackle the issue of gait disturbances in PD patients with DBS by discussing their neurophysiological basis, providing a detailed clinical characterization, and proposing a pragmatic programming approach to support their management.
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Affiliation(s)
- Nicoló G. Pozzi
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Chiara Palmisano
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Martin M. Reich
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Philip Capetian
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Claudio Pacchetti
- Parkinson’s Disease and Movement Disorders Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Jens Volkmann
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Ioannis U. Isaias
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
- Parkinson Institute Milan, ASST Gaetano Pini-CTO, Milan, Italy
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Adam EM, Brown EN, Kopell N, McCarthy MM. Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks. Proc Natl Acad Sci U S A 2022; 119:e2120808119. [PMID: 35500112 PMCID: PMC9171607 DOI: 10.1073/pnas.2120808119] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 03/25/2022] [Indexed: 12/03/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in alleviating movement disability in patients with Parkinson’s disease (PD). However, its therapeutic mechanism of action is unknown. The healthy striatum exhibits rich dynamics resulting from an interaction of beta, gamma, and theta oscillations. These rhythms are essential to selection and execution of motor programs, and their loss or exaggeration due to dopamine (DA) depletion in PD is a major source of behavioral deficits. Restoring the natural rhythms may then be instrumental in the therapeutic action of DBS. We develop a biophysical networked model of a BG pathway to study how abnormal beta oscillations can emerge throughout the BG in PD and how DBS can restore normal beta, gamma, and theta striatal rhythms. Our model incorporates STN projections to the striatum, long known but understudied, found to preferentially target fast-spiking interneurons (FSI). We find that DBS in STN can normalize striatal medium spiny neuron activity by recruiting FSI dynamics and restoring the inhibitory potency of FSIs observed in normal conditions. We also find that DBS allows the reexpression of gamma and theta rhythms, thought to be dependent on high DA levels and thus lost in PD, through cortical noise control. Our study highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal internal BG dynamics and the ability to regulate them. It also suggests how gamma and theta oscillations can be leveraged to supplement DBS treatment and enhance its effectiveness.
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Affiliation(s)
- Elie M. Adam
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Emery N. Brown
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114
| | - Nancy Kopell
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215
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Merk T, Peterson V, Köhler R, Haufe S, Richardson RM, Neumann WJ. Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation. Exp Neurol 2022; 351:113993. [PMID: 35104499 PMCID: PMC10521329 DOI: 10.1016/j.expneurol.2022.113993] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 11/18/2021] [Accepted: 01/22/2022] [Indexed: 12/30/2022]
Abstract
Sensing enabled implantable devices and next-generation neurotechnology allow real-time adjustments of invasive neuromodulation. The identification of symptom and disease-specific biomarkers in invasive brain signal recordings has inspired the idea of demand dependent adaptive deep brain stimulation (aDBS). Expanding the clinical utility of aDBS with machine learning may hold the potential for the next breakthrough in the therapeutic success of clinical brain computer interfaces. To this end, sophisticated machine learning algorithms optimized for decoding of brain states from neural time-series must be developed. To support this venture, this review summarizes the current state of machine learning studies for invasive neurophysiology. After a brief introduction to the machine learning terminology, the transformation of brain recordings into meaningful features for decoding of symptoms and behavior is described. Commonly used machine learning models are explained and analyzed from the perspective of utility for aDBS. This is followed by a critical review on good practices for training and testing to ensure conceptual and practical generalizability for real-time adaptation in clinical settings. Finally, first studies combining machine learning with aDBS are highlighted. This review takes a glimpse into the promising future of intelligent adaptive DBS (iDBS) and concludes by identifying four key ingredients on the road for successful clinical adoption: i) multidisciplinary research teams, ii) publicly available datasets, iii) open-source algorithmic solutions and iv) strong world-wide research collaborations.
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Affiliation(s)
- Timon Merk
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Victoria Peterson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Richard Köhler
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging (BCAN), Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany.
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Rao AT, Lu CW, Askari A, Malaga KA, Chou KL, Patil PG. Clinically-derived oscillatory biomarker predicts optimal subthalamic stimulation for Parkinson's disease. J Neural Eng 2022; 19. [PMID: 35272281 DOI: 10.1088/1741-2552/ac5c8c] [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: 01/10/2022] [Accepted: 03/10/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Choosing the optimal electrode trajectory, stimulation location, and stimulation amplitude in subthalamic nucleus deep brain stimulation (STN DBS) for Parkinson's disease (PD) remains a time-consuming empirical effort. In this retrospective study, we derive a data-driven electrophysiological biomarker that predicts clinical DBS location and parameters, and we consolidate this information into a quantitative score that may facilitate an objective approach to STN DBS surgery and programming. APPROACH Random-forest feature selection was applied to a dataset of 1046 microelectrode recordings sites across 20 DBS implant trajectories to identify features of oscillatory activity that predict clinically programmed volumes of tissue activation (VTA). A cross-validated classifier was used to retrospectively predict VTA regions from these features. Spatial convolution of probabilistic classifier outputs along MER trajectories produced a biomarker score that reflects the probability of localization within a clinically optimized VTA. MAIN RESULTS Biomarker scores peaked within the VTA region and were significantly correlated with percent improvement in postoperative motor symptoms (MDS-UPRDS Part III, R = 0.61, p = 0.004). Notably, the length of STN, a common criterion for trajectory selection, did not show similar correlation (R = -0.31, p = 0.18). These findings suggest that biomarker-based trajectory selection and programming may improve motor outcomes by 9 ± 3 percentage points (p = 0.047) in this dataset. SIGNIFICANCE A clinically defined electrophysiological biomarker not only predicts VTA size and location but also correlates well with motor outcomes. Use of this biomarker for trajectory selection and initial stimulation may potentially simplify STN DBS surgery and programming.
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Affiliation(s)
- Akshay T Rao
- Biomedical Engineering, University of Michigan, 1500 East Medical Center Dr., SPC 5338, Ann Arbor, Michigan, 48109-5338, UNITED STATES
| | - Charles W Lu
- Biomedical Engineering, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, Michigan, 48109-5338, UNITED STATES
| | - Asra Askari
- Biomedical Engineering, University of Michigan, 1500 E Medical Center Drive, SPC 5338, Ann Arbor, Ann Arbor, Michigan, 48109-5338, UNITED STATES
| | - Karlo A Malaga
- Biomedical Engineering, Bucknell University, 316 Academic East Building, Lewisburg, Pennsylvania, 17837, UNITED STATES
| | - Kelvin L Chou
- Neurosurgery, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, Michigan, 48109-5338, UNITED STATES
| | - Parag G Patil
- Neurosurgery, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, Michigan, 48109-5338, UNITED STATES
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Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit. PLoS Comput Biol 2022; 18:e1009887. [PMID: 35245281 PMCID: PMC8939795 DOI: 10.1371/journal.pcbi.1009887] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 03/22/2022] [Accepted: 01/31/2022] [Indexed: 11/26/2022] Open
Abstract
Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson’s disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple “reversible lesion” effect to augment network communication. Specifically, we examined the modulation of beta band (14–30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson’s. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease. Diseases of the brain lead to a wide range of disabling symptoms for patients, by affecting their ability to move or think properly. These symptoms arise from disruption to both the organization of networks in the brain, but also the timing of neural activity that propagates around it. Treatments for disease with drugs can restore the organization of these networks to some extent, yet it is very difficult to deliver drugs with good spatial or temporal selectivity. Brain stimulation provides one way in which to improve the spatial specificity of treatment, yet understanding how to stimulate at the right time to achieve the best outcome for patients, remains an outstanding question. In this work we use simulations of an important circuit involved in Parkinson’s disease that has parameters chosen to reflect recordings made in animal models of the disease. Using this computer model, we show how brain rhythms can act as signatures of underlying changes in networks. Further, we simulate intervention with temporally precise stimulation to show how future approaches to brain stimulation can act to restore or even augment neural networks following their degeneration in disease.
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Law RG, Pugliese S, Shin H, Sliva DD, Lee S, Neymotin S, Moore C, Jones SR. Thalamocortical Mechanisms Regulating the Relationship between Transient Beta Events and Human Tactile Perception. Cereb Cortex 2022; 32:668-688. [PMID: 34401898 PMCID: PMC8841599 DOI: 10.1093/cercor/bhab221] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 04/20/2021] [Accepted: 05/25/2021] [Indexed: 12/27/2022] Open
Abstract
Transient neocortical events with high spectral power in the 15-29 Hz beta band are among the most reliable predictors of sensory perception. Prestimulus beta event rates in primary somatosensory cortex correlate with sensory suppression, most effectively 100-300 ms before stimulus onset. However, the neural mechanisms underlying this perceptual association are unknown. We combined human magnetoencephalography (MEG) measurements with biophysical neural modeling to test potential cellular and circuit mechanisms that underlie observed correlations between prestimulus beta events and tactile detection. Extending prior studies, we found that simulated bursts from higher-order, nonlemniscal thalamus were sufficient to drive beta event generation and to recruit slow supragranular inhibition acting on a 300 ms timescale to suppress sensory information. Further analysis showed that the same beta-generating mechanism can lead to facilitated perception for a brief period when beta events occur simultaneously with tactile stimulation before inhibition is recruited. These findings were supported by close agreement between model-derived predictions and empirical MEG data. The postevent suppressive mechanism explains an array of studies that associate beta with decreased processing, whereas the during-event facilitatory mechanism may demand a reinterpretation of the role of beta events in the context of coincident timing.
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Affiliation(s)
- Robert G Law
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, RI 02908, USA
- Department of Psychiatry, Harvard Medical School, Cambridge, MA 02215, USA
| | - Sarah Pugliese
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
| | - Hyeyoung Shin
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Danielle D Sliva
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
| | - Shane Lee
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, RI 02903, USA
- Norman Prince Neurosciences Institute, Rhode Island Hospital, Providence, RI 02903, USA
| | - Samuel Neymotin
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Christopher Moore
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
| | - Stephanie R Jones
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, RI 02908, USA
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35
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Karekal A, Miocinovic S, Swann NC. Novel approaches for quantifying beta synchrony in Parkinson's disease. Exp Brain Res 2022; 240:991-1004. [PMID: 35099592 DOI: 10.1007/s00221-022-06308-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/12/2022] [Indexed: 11/25/2022]
Abstract
Despite the clinical and financial burden of Parkinson's disease (PD), there is no standardized, reliable biomarker to diagnose and track PD progression. Instead, PD is primarily assessed using subjective clinical rating scales and patient self-report. Such approaches can be imprecise, hindering diagnosis and disease monitoring. An objective biomarker would be beneficial for clinical care, refining diagnosis, and treatment. Due to widespread electrophysiological abnormalities both within and between brain structures in PD, development of electrophysiologic biomarkers may be feasible. Basal ganglia recordings acquired with neurosurgical approaches have revealed elevated power in the beta frequency range (13-30 Hz) in PD, suggesting that beta power could be a putative PD biomarker. However, there are limitations to the use of beta power as a biomarker. Recent advances in analytic approaches have led to novel methods to quantify oscillatory synchrony in the beta frequency range. Here we describe some of these novel approaches in the context of PD and explore how they may serve as electrophysiological biomarkers. These novel signatures include (1) interactions between beta phase and broadband (> 50 Hz, "gamma") amplitude (i.e., phase amplitude coupling, PAC), (2) asymmetries in waveform shape, (3) beta coherence, and (4) beta "bursts." Development of a robust, reliable, and readily accessible electrophysiologic biomarker would represent a major step towards more precise and personalized care in PD.
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Affiliation(s)
- Apoorva Karekal
- Department of Human Physiology, University of Oregon, Eugene, OR, USA
| | | | - Nicole C Swann
- Department of Human Physiology, University of Oregon, Eugene, OR, USA.
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36
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Velasco S, Branco L, Abosch A, Ince NF. The Entropy of Adaptively Segmented Beta Oscillations Predict Motor Improvement in Patients with Parkinsons Disease. IEEE Trans Biomed Eng 2022; 69:2333-2341. [PMID: 35025735 DOI: 10.1109/tbme.2022.3142716] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Beta bursts of local fields potentials (LFPs) recorded from subthalamic nucleus (STN) have been recently proposed as a new temporal feature for patients with Parkinsons disease (PD). We introduce a new technique for the adaptive time-domain segmentation of STN-LFP recordings such that the constructed time segments are proportional to the duration of stationary beta activity. We investigated whether the spectral entropy of the adaptively captured beta oscillations can describe the improvement in motor signs following dopaminergic medication. METHODS STN-LFP recordings from externalized chronic deep brain stimulation (DBS) leads were obtained in 9 PD patients. During this monitoring, each patient underwent 3 medication intake cycles where short acting agents (L-DOPA equivalent dose) were administered. We analyzed 2-minute resting state LFP data in each OFF and L-DOPA-induced ON medication states and constructed time domain segmentation of LFP signal in which the length segmentations are adapted to time-varying nature of the oscillatory activity. RESULTS Adaptively constructed segments were noted to be significantly longer in OFF- and shorter in ON-state (p<0.001). Interestingly, in the OFF state, the peak frequency of long beta bursts (>375ms) was in the low range (12-23Hz) of the beta spectrum, whereas shorter beta bursts (<375ms) were widespread in the 13-30Hz band. Measured clinical improvement was highly correlated with the difference in the spectral entropy of beta bursts between OFF and ON states (r=-0.83, p<0.01). CONCLUSION AND SIGNIFICANCE Our findings suggest that beta oscillations can be adaptively segmented without the use of a predetermined amplitude threshold, thereby allowing for objective quantification of burst itself. Compared to the shorter ones, longer oscillations with duration 375ms were highly correlated with the clinical improvement, supporting a pathological role for them. Overall, these findings coupled with our adaptive approach could enable the quantitative use of temporal dynamics of beta activity in assessing severity of PD and improvements in motor features.
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37
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Mau ETK, Rosenblum M. Optimizing charge-balanced pulse stimulation for desynchronization. CHAOS (WOODBURY, N.Y.) 2022; 32:013103. [PMID: 35105136 DOI: 10.1063/5.0070036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 12/09/2021] [Indexed: 06/14/2023]
Abstract
Collective synchronization in a large population of self-sustained units appears both in natural and engineered systems. Sometimes this effect is in demand, while in some cases, it is undesirable, which calls for control techniques. In this paper, we focus on pulsatile control, with the goal to either increase or decrease the level of synchrony. We quantify this level by the entropy of the phase distribution. Motivated by possible applications in neuroscience, we consider pulses of a realistic shape. Exploiting the noisy Kuramoto-Winfree model, we search for the optimal pulse profile and the optimal stimulation phase. For this purpose, we derive an expression for the change of the phase distribution entropy due to the stimulus. We relate this change to the properties of individual units characterized by generally different natural frequencies and phase response curves and the population's state. We verify the general result by analyzing a two-frequency population model and demonstrating a good agreement of the theory and numerical simulations.
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Affiliation(s)
- Erik T K Mau
- Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam-Golm, Germany
| | - Michael Rosenblum
- Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam-Golm, Germany
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38
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Abdul Nabi Ali A, Alam M, Klein SC, Behmann N, Krauss JK, Doll T, Blume H, Schwabe K. Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism. Neural Netw 2021; 146:334-340. [PMID: 34923220 DOI: 10.1016/j.neunet.2021.11.025] [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: 06/11/2021] [Revised: 10/08/2021] [Accepted: 11/24/2021] [Indexed: 10/19/2022]
Abstract
In neurological and neuropsychiatric disorders neuronal oscillatory activity between basal ganglia and cortical circuits are altered, which may be useful as biomarker for adaptive deep brain stimulation. We investigated whether changes in the spectral power of oscillatory activity in the motor cortex (MCtx) and the sensorimotor cortex (SMCtx) of rats after injection of the dopamine (DA) receptor antagonist haloperidol (HALO) would be similar to those observed in Parkinson disease. Thereafter, we tested whether a convolutional neural network (CNN) model would identify brain signal alterations in this acute model of parkinsonism. A sixteen channel surface micro-electrocorticogram (ECoG) recording array was placed under the dura above the MCtx and SMCtx areas of one hemisphere under general anaesthesia in rats. Seven days after surgery, micro ECoG was recorded in individual free moving rats in three conditions: (1) basal activity, (2) after injection of HALO (0.5 mg/kg), and (3) with additional injection of apomorphine (APO) (1 mg/kg). Furthermore, a CNN-based classification consisting of 23,530 parameters was applied on the raw data. HALO injection decreased oscillatory theta band activity (4-8 Hz) and enhanced beta (12-30 Hz) and gamma (30-100 Hz) in MCtx and SMCtx, which was compensated after APO injection (P ¡ 0.001). Evaluation of classification performance of the CNN model provided accuracy of 92%, sensitivity of 90% and specificity of 93% on one-dimensional signals. The CNN proposed model requires a minimum of sensory hardware and may be integrated into future research on therapeutic devices for Parkinson disease, such as adaptive closed loop stimulation, thus contributing to more efficient way of treatment.
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Affiliation(s)
- Ali Abdul Nabi Ali
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Mesbah Alam
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany.
| | - Simon C Klein
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Nicolai Behmann
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Joachim K Krauss
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany
| | - Theodor Doll
- Biomaterial Engineering, Hannover Medical School and Translational Medical Engineering Fraunhofer ITEM, Hannover, D-30625, Lower Saxony, Germany
| | - Holger Blume
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Kerstin Schwabe
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany
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Wang L, Zhou C, Cheng W, Rolls ET, Huang P, Ma N, Liu Y, Zhang Y, Guan X, Guo T, Wu J, Gao T, Xuan M, Gu Q, Xu X, Zhang B, Gong W, Du J, Zhang W, Feng J, Zhang M. Dopamine depletion and subcortical dysfunction disrupt cortical synchronization and metastability affecting cognitive function in Parkinson's disease. Hum Brain Mapp 2021; 43:1598-1610. [PMID: 34904766 PMCID: PMC8886656 DOI: 10.1002/hbm.25745] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/28/2021] [Accepted: 11/29/2021] [Indexed: 12/14/2022] Open
Abstract
Parkinson's disease (PD) is primarily characterized by the loss of dopaminergic cells and atrophy in subcortical regions. However, the impact of these pathological changes on large-scale dynamic integration and segregation of the cortex are not well understood. In this study, we investigated the effect of subcortical dysfunction on cortical dynamics and cognition in PD. Spatiotemporal dynamics of the phase interactions of resting-state blood-oxygen-level-dependent signals in 159 PD patients and 152 normal control (NC) individuals were estimated. The relationships between subcortical atrophy, subcortical-cortical fiber connectivity impairment, cortical synchronization/metastability, and cognitive performance were then assessed. We found that cortical synchronization and metastability in PD patients were significantly decreased. To examine whether this is an effect of dopamine depletion, we investigated 45 PD patients both ON and OFF dopamine replacement therapy, and found that cortical synchronization and metastability are significantly increased in the ON state. The extent of cortical synchronization and metastability in the OFF state reflected cognitive performance and mediates the difference in cognitive performance between the PD and NC groups. Furthermore, both the thalamic volume and thalamocortical fiber connectivity had positive relationships with cortical synchronization and metastability in the dopaminergic OFF state, and mediate the difference in cortical synchronization between the PD and NC groups. In addition, thalamic volume also reflected cognitive performance, and cortical synchronization/metastability mediated the relationship between thalamic volume and cognitive performance in PD patients. Together, these results highlight that subcortical dysfunction and reduced dopamine levels are responsible for decreased cortical synchronization and metastability, further affecting cognitive performance in PD. This might lead to biomarkers being identified that can predict if a patient is at risk of developing dementia.
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Affiliation(s)
- Linbo Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK
| | - Edmund T Rolls
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ningning Ma
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Yuchen Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Yajuan Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingjing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ting Gao
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Min Xuan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Quanquan Gu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Weikang Gong
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Jingnan Du
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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40
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Sure M, Vesper J, Schnitzler A, Florin E. Dopaminergic Modulation of Spectral and Spatial Characteristics of Parkinsonian Subthalamic Nucleus Beta Bursts. Front Neurosci 2021; 15:724334. [PMID: 34867149 PMCID: PMC8636009 DOI: 10.3389/fnins.2021.724334] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 10/08/2021] [Indexed: 11/13/2022] Open
Abstract
In Parkinson’s disease (PD), subthalamic nucleus (STN) beta burst activity is pathologically elevated. These bursts are reduced by dopamine and deep brain stimulation (DBS). Therefore, these bursts have been tested as a trigger for closed-loop DBS. To provide better targeted parameters for closed-loop stimulation, we investigate the spatial distribution of beta bursts within the STN and if they are specific to a beta sub-band. Local field potentials (LFP) were acquired in the STN of 27 PD patients while resting. Based on the orientation of segmented DBS electrodes, the LFPs were classified as anterior, postero-medial, and postero-lateral. Each recording lasted 30 min with (ON) and without (OFF) dopamine. Bursts were detected in three frequency bands: ±3 Hz around the individual beta peak frequency, low beta band (lBB), and high beta band (hBB). Medication reduced the duration and the number of bursts per minute but not the amplitude of the beta bursts. The burst amplitude was spatially modulated, while the burst duration and rate were frequency dependent. Furthermore, the hBB burst duration was positively correlated with the akinetic-rigid UPDRS III subscore. Overall, these findings on differential dopaminergic modulation of beta burst parameters suggest that hBB burst duration is a promising target for closed-loop stimulation and that burst parameters could guide DBS programming.
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Affiliation(s)
- Matthias Sure
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Jan Vesper
- Department of Functional Neurosurgery and Stereotaxy, Medical Faculty, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.,Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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41
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Tinkhauser G, Moraud EM. Controlling Clinical States Governed by Different Temporal Dynamics With Closed-Loop Deep Brain Stimulation: A Principled Framework. Front Neurosci 2021; 15:734186. [PMID: 34858126 PMCID: PMC8632004 DOI: 10.3389/fnins.2021.734186] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/18/2021] [Indexed: 02/05/2023] Open
Abstract
Closed-loop strategies for deep brain stimulation (DBS) are paving the way for improving the efficacy of existing neuromodulation therapies across neurological disorders. Unlike continuous DBS, closed-loop DBS approaches (cl-DBS) optimize the delivery of stimulation in the temporal domain. However, clinical and neurophysiological manifestations exhibit highly diverse temporal properties and evolve over multiple time-constants. Moreover, throughout the day, patients are engaged in different activities such as walking, talking, or sleeping that may require specific therapeutic adjustments. This broad range of temporal properties, along with inter-dependencies affecting parallel manifestations, need to be integrated in the development of therapies to achieve a sustained, optimized control of multiple symptoms over time. This requires an extended view on future cl-DBS design. Here we propose a conceptual framework to guide the development of multi-objective therapies embedding parallel control loops. Its modular organization allows to optimize the personalization of cl-DBS therapies to heterogeneous patient profiles. We provide an overview of clinical states and symptoms, as well as putative electrophysiological biomarkers that may be integrated within this structure. This integrative framework may guide future developments and become an integral part of next-generation precision medicine instruments.
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Affiliation(s)
- Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Eduardo Martin Moraud
- Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland.,Defitech Center for Interventional Neurotherapies (.NeuroRestore), Ecole Polytechnique Fédérale de Lausanne and Lausanne University Hospital, Lausanne, Switzerland
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42
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Bonaiuto JJ, Little S, Neymotin SA, Jones SR, Barnes GR, Bestmann S. Laminar dynamics of high amplitude beta bursts in human motor cortex. Neuroimage 2021; 242:118479. [PMID: 34407440 PMCID: PMC8463839 DOI: 10.1016/j.neuroimage.2021.118479] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 08/12/2021] [Accepted: 08/14/2021] [Indexed: 12/28/2022] Open
Abstract
Motor cortical activity in the beta frequency range is one of the strongest and most studied movement-related neural signals. At the single trial level, beta band activity is often characterized by transient, high amplitude, bursting events rather than slowly modulating oscillations. The timing of these bursting events is tightly linked to behavior, suggesting a more dynamic functional role for beta activity than previously believed. However, the neural mechanisms underlying beta bursts in sensorimotor circuits are poorly understood. To address this, we here leverage and extend recent developments in high precision MEG for temporally resolved laminar analysis of burst activity, combined with a neocortical circuit model that simulates the biophysical generators of the electrical currents which drive beta bursts. This approach pinpoints the generation of beta bursts in human motor cortex to distinct excitatory synaptic inputs to deep and superficial cortical layers, which drive current flow in opposite directions. These laminar dynamics of beta bursts in motor cortex align with prior invasive animal recordings within the somatosensory cortex, and suggest a conserved mechanism for somatosensory and motor cortical beta bursts. More generally, we demonstrate the ability for uncovering the laminar dynamics of event-related neural signals in human non-invasive recordings. This provides important constraints to theories about the functional role of burst activity for movement control in health and disease, and crucial links between macro-scale phenomena measured in humans and micro-circuit activity recorded from animal models.
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Affiliation(s)
- James J Bonaiuto
- Institut des Sciences Cognitives Marc Jeannerod, CNRS UMR 5229, Bron, France; Université Claude Bernard Lyon 1, Université de Lyon, France; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK; Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK.
| | - Simon Little
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK; Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Samuel A Neymotin
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department of Neuroscience, Brown University, Providence, RI, USA; Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Stephanie R Jones
- Department of Neuroscience, Brown University, Providence, RI, USA; Center for Neurorestoration and Neurotechnology, Providence VAMC, Providence, RI, USA
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK
| | - Sven Bestmann
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK; Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK
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43
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Magnusson JL, Leventhal DK. Revisiting the "Paradox of Stereotaxic Surgery": Insights Into Basal Ganglia-Thalamic Interactions. Front Syst Neurosci 2021; 15:725876. [PMID: 34512279 PMCID: PMC8429495 DOI: 10.3389/fnsys.2021.725876] [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: 06/15/2021] [Accepted: 08/06/2021] [Indexed: 11/13/2022] Open
Abstract
Basal ganglia dysfunction is implicated in movement disorders including Parkinson Disease, dystonia, and choreiform disorders. Contradicting standard "rate models" of basal ganglia-thalamic interactions, internal pallidotomy improves both hypo- and hyper-kinetic movement disorders. This "paradox of stereotaxic surgery" was recognized shortly after rate models were developed, and is underscored by the outcomes of deep brain stimulation (DBS) for movement disorders. Despite strong evidence that DBS activates local axons, the clinical effects of lesions and DBS are nearly identical. These observations argue against standard models in which GABAergic basal ganglia output gates thalamic activity, and raise the question of how lesions and stimulation can have similar effects. These paradoxes may be resolved by considering thalamocortical loops as primary drivers of motor output. Rather than suppressing or releasing cortex via motor thalamus, the basal ganglia may modulate the timing of thalamic perturbations to cortical activity. Motor cortex exhibits rotational dynamics during movement, allowing the same thalamocortical perturbation to affect motor output differently depending on its timing with respect to the rotational cycle. We review classic and recent studies of basal ganglia, thalamic, and cortical physiology to propose a revised model of basal ganglia-thalamocortical function with implications for basic physiology and neuromodulation.
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Affiliation(s)
| | - Daniel K Leventhal
- Department of Neurology, University of Michigan, Ann Arbor, MI, United States.,Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States.,Parkinson Disease Foundation Research Center of Excellence, University of Michigan, Ann Arbor, MI, United States.,Department of Neurology, VA Ann Arbor Health System, Ann Arbor, MI, United States
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44
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Zhang J, Idaji MJ, Villringer A, Nikulin VV. Neuronal biomarkers of Parkinson's disease are present in healthy aging. Neuroimage 2021; 243:118512. [PMID: 34455060 DOI: 10.1016/j.neuroimage.2021.118512] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 08/23/2021] [Indexed: 10/20/2022] Open
Abstract
The prevalence of Parkinson's disease (PD) increases with aging and both processes share similar cellular mechanisms and alterations in the dopaminergic system. Yet it remains to be investigated whether aging can also demonstrate electrophysiological neuronal signatures typically associated with PD. Previous work has shown that phase-amplitude coupling (PAC) between the phase of beta oscillations and the amplitude of gamma oscillations as well as beta bursts features can serve as electrophysiological biomarkers for PD. Here we hypothesize that these metrics are also present in apparently healthy elderly subjects. Using resting state multichannel EEG measurements, we show that PAC between beta oscillation and broadband gamma activity (50-150 Hz) is elevated in a group of elderly (59-77 years) compared to young volunteers (20-35 years) without PD. Importantly, the increase of PAC is statistically significant even after ruling out confounds relating to changes in spectral power and non-sinusoidal shape of beta oscillation. Moreover, a trend for a higher percentage of longer beta bursts (> 0.2 s) along with the increase in their incidence rate is also observed for elderly subjects. Using inverse modeling, we further show that elevated PAC and longer beta bursts are most pronounced in the sensorimotor areas. Moreover, we show that PAC and longer beta bursts might reflect distinct mechanisms, since their spatial patterns only partially overlap and the correlation between them is weak. Taken together, our findings provide novel evidence that electrophysiological biomarkers of PD may already occur in apparently healthy elderly subjects. We hypothesize that PAC and beta bursts characteristics in aging might reflect a pre-clinical state of PD and suggest their predictive value to be tested in prospective longitudinal studies.
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Affiliation(s)
- Juanli Zhang
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
| | - Mina Jamshidi Idaji
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Machine Learning Group, Technical University of Berlin, Berlin, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation; Neurophysics Group, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
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45
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Takeuchi N, Izumi SI. Motor Learning Based on Oscillatory Brain Activity Using Transcranial Alternating Current Stimulation: A Review. Brain Sci 2021; 11:1095. [PMID: 34439714 PMCID: PMC8392205 DOI: 10.3390/brainsci11081095] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 08/17/2021] [Accepted: 08/18/2021] [Indexed: 12/15/2022] Open
Abstract
Developing effective tools and strategies to promote motor learning is a high-priority scientific and clinical goal. In particular, motor-related areas have been investigated as potential targets to facilitate motor learning by noninvasive brain stimulation (NIBS). In addition to shedding light on the relationship between motor function and oscillatory brain activity, transcranial alternating current stimulation (tACS), which can noninvasively entrain oscillatory brain activity and modulate oscillatory brain communication, has attracted attention as a possible technique to promote motor learning. This review focuses on the use of tACS to enhance motor learning through the manipulation of oscillatory brain activity and its potential clinical applications. We discuss a potential tACS-based approach to ameliorate motor deficits by correcting abnormal oscillatory brain activity and promoting appropriate oscillatory communication in patients after stroke or with Parkinson's disease. Interpersonal tACS approaches to manipulate intra- and inter-brain communication may result in pro-social effects and could promote the teaching-learning process during rehabilitation sessions with a therapist. The approach of re-establishing oscillatory brain communication through tACS could be effective for motor recovery and might eventually drive the design of new neurorehabilitation approaches based on motor learning.
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Affiliation(s)
- Naoyuki Takeuchi
- Department of Physical Therapy, Akita University Graduate School of Health Sciences 1-1-1, Hondo, Akita 010-8543, Japan
| | - Shin-Ichi Izumi
- Department of Physical Medicine and Rehabilitation, Tohoku University Graduate School of Medicine, Sendai 980-8575, Japan;
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46
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Duchet B, Ghezzi F, Weerasinghe G, Tinkhauser G, Kühn AA, Brown P, Bick C, Bogacz R. Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson's disease. PLoS Comput Biol 2021; 17:e1009116. [PMID: 34233347 PMCID: PMC8263069 DOI: 10.1371/journal.pcbi.1009116] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 05/26/2021] [Indexed: 11/18/2022] Open
Abstract
Parkinson's disease motor symptoms are associated with an increase in subthalamic nucleus beta band oscillatory power. However, these oscillations are phasic, and there is a growing body of evidence suggesting that beta burst duration may be of critical importance to motor symptoms. This makes insights into the dynamics of beta bursting generation valuable, in particular to refine closed-loop deep brain stimulation in Parkinson's disease. In this study, we ask the question "Can average burst duration reveal how dynamics change between the ON and OFF medication states?". Our analysis of local field potentials from the subthalamic nucleus demonstrates using linear surrogates that the system generating beta oscillations is more likely to act in a non-linear regime OFF medication and that the change in a non-linearity measure is correlated with motor impairment. In addition, we pinpoint the simplest dynamical changes that could be responsible for changes in the temporal patterning of beta oscillations between medication states by fitting to data biologically inspired models, and simpler beta envelope models. Finally, we show that the non-linearity can be directly extracted from average burst duration profiles under the assumption of constant noise in envelope models. This reveals that average burst duration profiles provide a window into burst dynamics, which may underlie the success of burst duration as a biomarker. In summary, we demonstrate a relationship between average burst duration profiles, dynamics of the system generating beta oscillations, and motor impairment, which puts us in a better position to understand the pathology and improve therapies such as deep brain stimulation.
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Affiliation(s)
- Benoit Duchet
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Filippo Ghezzi
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - Gihan Weerasinghe
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Andrea A. Kühn
- Charité - Universitätsmedizin Berlin, Department of Neurology, Movement Disorder and Neuromodulation Unit, Berlin, Germany
| | - Peter Brown
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Christian Bick
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience - Systems & Network Neuroscience, Amsterdam, the Netherlands
- Mathematical Institute, University of Oxford, Oxford, United Kingdom
- Department of Mathematics, University of Exeter, Exeter, United Kingdom
- EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom
| | - Rafal Bogacz
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
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47
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Shi K, Liu X, Hou L, Qiao D, Peng Y. Exercise Improves Movement by Regulating the Plasticity of Cortical Function in Hemiparkinsonian Rats. Front Aging Neurosci 2021; 13:695108. [PMID: 34194319 PMCID: PMC8236842 DOI: 10.3389/fnagi.2021.695108] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 05/17/2021] [Indexed: 01/03/2023] Open
Abstract
Aberrant cortical spike-local field potential (LFP) coupling leads to abnormal basal ganglia activity, disruption of cortical function, and impaired movement in Parkinson's disease (PD). Here, the primary motor cortex mediated plasticity mechanism underlying behavioral improvement by exercise intervention was investigated. Exercise alleviates motor dysfunction and induces neuroplasticity in PD. In this study, Sprague-Dawley (SD) rats were injected with 6-hydroxydopamine (6-OHDA) to induce unilateral nigrostriatal dopamine depletion. Two weeks later, a 4-week exercise intervention was initiated in the PD + exercise (Ex) group. Multichannel recording technology recorded spikes and LFPs in rat motor cortices, and balanced ability tests evaluated behavioral performance. The balanced ability test showed that the total crossing time/front leg error/input latency time was significantly lower in PD + Ex rats than in PD rats (P < 0.05). Scalograms and LFP power spectra indicated increased beta-range LFP power in lesioned hemispheres, with exercise reducing LFP power spectral density. Spike-triggered LFP waveform averages showed strong phase-locking in PD motor cortex cells, and exercise reduced spike-LFP synchronization. Our results suggest that exercise can suppress overexcitability of LFPs and minimize spike-LFP synchronization in the motor cortex, leading to motor-improving effects in PD.
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Affiliation(s)
- Kaixuan Shi
- Department of Physical Education, China University of Geosciences, Beijing, China
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Xiaoli Liu
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Lijuan Hou
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Decai Qiao
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Yuan Peng
- Department of Physical Education, China University of Geosciences, Beijing, China
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48
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Mosher CP, Mamelak AN, Malekmohammadi M, Pouratian N, Rutishauser U. Distinct roles of dorsal and ventral subthalamic neurons in action selection and cancellation. Neuron 2021; 109:869-881.e6. [PMID: 33482087 PMCID: PMC7933114 DOI: 10.1016/j.neuron.2020.12.025] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 12/12/2020] [Accepted: 12/30/2020] [Indexed: 12/11/2022]
Abstract
The subthalamic nucleus (STN) supports action selection by inhibiting all motor programs except the desired one. Recent evidence suggests that STN can also cancel an already selected action when goals change, a key aspect of cognitive control. However, there is little neurophysiological evidence for dissociation between selecting and cancelling actions in the human STN. We recorded single neurons in the STN of humans performing a stop-signal task. Movement-related neurons suppressed their activity during successful stopping, whereas stop-signal neurons activated at low-latencies near the stop-signal reaction time. In contrast, STN and motor-cortical beta-bursting occurred only later in the stopping process. Task-related neuronal properties varied by recording location from dorsolateral movement to ventromedial stop-signal tuning. Therefore, action selection and cancellation coexist in STN but are anatomically segregated. These results show that human ventromedial STN neurons carry fast stop-related signals suitable for implementing cognitive control.
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Affiliation(s)
- Clayton P Mosher
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Adam N Mamelak
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Mahsa Malekmohammadi
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
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49
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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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50
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Cook AJ, Pfeifer KJ, Tass PA. A Single Case Feasibility Study of Sensorimotor Rhythm Neurofeedback in Parkinson's Disease. Front Neurosci 2021; 15:623317. [PMID: 33613185 PMCID: PMC7890190 DOI: 10.3389/fnins.2021.623317] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/13/2021] [Indexed: 01/25/2023] Open
Abstract
Electroencephalographic activity over the sensorimotor cortex has been one of the best studied targets for neurofeedback therapy. Parkinson’s disease patients display abnormal brain rhythms in the motor cortex caused by increased synchrony in the basal ganglia-cortical pathway. Few studies have examined the effects of sensorimotor-based neurofeedback therapy in humans with PD. In this pilot study, one patient, diagnosed with Parkinson’s disease 10 years prior, participated in two consecutive days of EEG neurofeedback training to increase sensorimotor rhythm (SMR) power over the motor cortex. Using a visual display connected to ongoing EEG, the patient voluntarily manipulated SMR power, and he/she was awarded with points to positively reinforce successful increases over a predefined threshold. Recorded EEG data were source localized and analyzed for the occurrence of high amplitude bursts of SMR activity as well as bursts in the beta frequency band in the precentral cortex. The rate of SMR bursts increased with each subsequent training session, while the rate of beta bursts only increased on the final session. Relative power in the beta band, a marker of PD symptom severity, decreased over the motor cortex in the later session. These results provide first evidence for the feasibility of SMR neurofeedback training as a non-invasive therapy for reducing Parkinson’s disease related activity and upregulating SMR in the human motor cortex.
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Affiliation(s)
- Alexander J Cook
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Kristina J Pfeifer
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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