Efficient Suppression of Parkinsonian Beta Oscillations in a Closed-loop Model of Deep Brain Stimulation with Amplitude Modulation

Overview

Journal Front Hum Neurosci

Specialty Neurology

Date 2023 Feb 13

PMID 36776221

Authors

Fatemeh Bahadori-Jahromi

Sina Salehi

Mojtaba Madadi Asl

Alireza Valizadeh

Affiliations

Soon will be listed here.

Abstract

Introduction: Parkinson's disease (PD) is a movement disorder characterized by the pathological beta band (15-30 Hz) neural oscillations within the basal ganglia (BG). It is shown that the suppression of abnormal beta oscillations is correlated with the improvement of PD motor symptoms, which is a goal of standard therapies including deep brain stimulation (DBS). To overcome the stimulation-induced side effects and inefficiencies of conventional DBS (cDBS) and to reduce the administered stimulation current, closed-loop adaptive DBS (aDBS) techniques were developed. In this method, the frequency and/or amplitude of stimulation are modulated based on various disease biomarkers.

Methods: Here, by computational modeling of a cortico-BG-thalamic network in normal and PD conditions, we show that closed-loop aDBS of the subthalamic nucleus (STN) with amplitude modulation leads to a more effective suppression of pathological beta oscillations within the parkinsonian BG.

Results: Our results show that beta band neural oscillations are restored to their normal range and the reliability of the response of the thalamic neurons to motor cortex commands is retained due to aDBS with amplitude modulation. Furthermore, notably less stimulation current is administered during aDBS compared with cDBS due to a closed-loop control of stimulation amplitude based on the STN local field potential (LFP) beta activity.

Discussion: Efficient models of closed-loop stimulation may contribute to the clinical development of optimized aDBS techniques designed to reduce potential stimulation-induced side effects of cDBS in PD patients while leading to a better therapeutic outcome.

Citing Articles

Wireless closed-loop deep brain stimulation using microelectrode array probes.

Jia Q, Liu Y, Lv S, Wang Y, Jiao P, Xu W J Zhejiang Univ Sci B. 2024; 25(10):803-823.

PMID: 39420519 PMC: 11494161. DOI: 10.1631/jzus.B2300400.

Infrared neuroglial modulation of spinal locomotor networks.

Dumas N, Pecchi E, OConnor R, Bos R, Moreau D Sci Rep. 2024; 14(1):22282.

PMID: 39333287 PMC: 11437012. DOI: 10.1038/s41598-024-73577-4.

High-Throughput Microelectrode Arrays for Precise Functional Localization of the Globus Pallidus Internus.

Zhu Y, Jing L, Hu R, Mo F, Jia Q, Yang G Cyborg Bionic Syst. 2024; 5:0123.

PMID: 38784125 PMC: 11112599. DOI: 10.34133/cbsystems.0123.

Synaptic network structure shapes cortically evoked spatio-temporal responses of STN and GPe neurons in a computational model.

Kromer J, Bokil H, Tass P Front Neuroinform. 2023; 17:1217786.

PMID: 37675246 PMC: 10477454. DOI: 10.3389/fninf.2023.1217786.

References

Anderson C, Sheppard D, Huynh R, Anderson D, Polar C, Dorval A . Subthalamic deep brain stimulation reduces pathological information transmission to the thalamus in a rat model of parkinsonism. Front Neural Circuits. 2015; 9:31. PMC: 4491629. DOI: 10.3389/fncir.2015.00031. View

Gorzelic P, Schiff S, Sinha A . Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease. J Neural Eng. 2013; 10(2):026016. DOI: 10.1088/1741-2560/10/2/026016. View

Leblois A, Boraud T, Meissner W, Bergman H, Hansel D . Competition between feedback loops underlies normal and pathological dynamics in the basal ganglia. J Neurosci. 2006; 26(13):3567-83. PMC: 6673853. DOI: 10.1523/JNEUROSCI.5050-05.2006. View

Popovych O, Tass P . Adaptive delivery of continuous and delayed feedback deep brain stimulation - a computational study. Sci Rep. 2019; 9(1):10585. PMC: 6646395. DOI: 10.1038/s41598-019-47036-4. View

Swann N, de Hemptinne C, Miocinovic S, Qasim S, Wang S, Ziman N . Gamma Oscillations in the Hyperkinetic State Detected with Chronic Human Brain Recordings in Parkinson's Disease. J Neurosci. 2016; 36(24):6445-58. PMC: 5015781. DOI: 10.1523/JNEUROSCI.1128-16.2016. View

Chen Y, Gong C, Tian Y, Orlov N, Zhang J, Guo Y . Neuromodulation effects of deep brain stimulation on beta rhythm: A longitudinal local field potential study. Brain Stimul. 2020; 13(6):1784-1792. DOI: 10.1016/j.brs.2020.09.027. View

Kondabolu K, Roberts E, Bucklin M, McCarthy M, Kopell N, Han X . Striatal cholinergic interneurons generate beta and gamma oscillations in the corticostriatal circuit and produce motor deficits. Proc Natl Acad Sci U S A. 2016; 113(22):E3159-68. PMC: 4896681. DOI: 10.1073/pnas.1605658113. View

Baizabal-Carvallo J, Jankovic J . Movement disorders induced by deep brain stimulation. Parkinsonism Relat Disord. 2016; 25:1-9. DOI: 10.1016/j.parkreldis.2016.01.014. View

Madadi Asl M, Valizadeh A, Tass P . Propagation delays determine neuronal activity and synaptic connectivity patterns emerging in plastic neuronal networks. Chaos. 2018; 28(10):106308. DOI: 10.1063/1.5037309. View

10.

Guo Y, Rubin J, McIntyre C, Vitek J, Terman D . Thalamocortical relay fidelity varies across subthalamic nucleus deep brain stimulation protocols in a data-driven computational model. J Neurophysiol. 2008; 99(3):1477-92. DOI: 10.1152/jn.01080.2007. View

11.

Wang X, Buzsaki G . Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. J Neurosci. 1996; 16(20):6402-13. PMC: 6578902. View

12.

Gerstner W, Kempter R, van Hemmen J, Wagner H . A neuronal learning rule for sub-millisecond temporal coding. Nature. 1996; 383(6595):76-81. DOI: 10.1038/383076a0. View

13.

Su F, Kumaravelu K, Wang J, Grill W . Model-Based Evaluation of Closed-Loop Deep Brain Stimulation Controller to Adapt to Dynamic Changes in Reference Signal. Front Neurosci. 2019; 13:956. PMC: 6746932. DOI: 10.3389/fnins.2019.00956. View

14.

Contarino M, Bour L, Bot M, van den Munckhof P, Speelman J, Schuurman P . Tremor-specific neuronal oscillation pattern in dorsal subthalamic nucleus of parkinsonian patients. Brain Stimul. 2011; 5(3):305-314. DOI: 10.1016/j.brs.2011.03.011. View

15.

Little S, Brown P . What brain signals are suitable for feedback control of deep brain stimulation in Parkinson's disease?. Ann N Y Acad Sci. 2012; 1265:9-24. PMC: 3495297. DOI: 10.1111/j.1749-6632.2012.06650.x. View

16.

Detorakis G, Chaillet A, Palfi S, Senova S . Closed-loop stimulation of a delayed neural fields model of parkinsonian STN-GPe network: a theoretical and computational study. Front Neurosci. 2015; 9:237. PMC: 4498106. DOI: 10.3389/fnins.2015.00237. View

17.

Koos T, Tepper J . Inhibitory control of neostriatal projection neurons by GABAergic interneurons. Nat Neurosci. 1999; 2(5):467-72. DOI: 10.1038/8138. View

18.

Velisar A, Syrkin-Nikolau J, Blumenfeld Z, Trager M, Afzal M, Prabhakar V . Dual threshold neural closed loop deep brain stimulation in Parkinson disease patients. Brain Stimul. 2019; 12(4):868-876. DOI: 10.1016/j.brs.2019.02.020. View

19.

Priori A, Foffani G, Rossi L, Marceglia S . Adaptive deep brain stimulation (aDBS) controlled by local field potential oscillations. Exp Neurol. 2012; 245:77-86. DOI: 10.1016/j.expneurol.2012.09.013. View

20.

Popovych O, Tass P . Control of abnormal synchronization in neurological disorders. Front Neurol. 2015; 5:268. PMC: 4267271. DOI: 10.3389/fneur.2014.00268. View