Adaptive closed-loop control strategy inhibiting pathological basal ganglia oscillations

Wang, Kuanchuan; Wang, Jiang; Zhu, Yulin; Li, Yong; Liu, Chen; Fietkiewicz, Chris; Loparo, Kenneth A.

doi:10.1016/j.bspc.2022.103776

Cited by 5 publications

(3 citation statements)

References 69 publications

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“…The part of the graph where the minimum and maximum values overlap represents the effective suppression of oscillations. The value of the feedback gain G was experimentally found to be between -10 and 10 [16,23]. Since STN is an excitatory nucleus, positive G is valid for STN m of scheme A and scheme D, and since GPe is an inhibitory nucleus, negative G is valid for GPe m of scheme B and scheme C [23].…”

Section: The Role Of Feedback Gain G In Four Linear Delayed Feedback ...mentioning

confidence: 96%

“…Delayed feedback control strategy is a closed-loop control method to achieve suppression of β oscillations through a desynchronization mechanism, which can effectively alleviate PD symptoms by modulating the stimulation signal according to neuronal activity [16]. Since Pyragas [17] proposed that it has a desynchronization mechanism [18][19][20], the delayed feedback strategy has received wide attention.…”

Section: Introductionmentioning

confidence: 99%

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Inhibition of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model

Sun

Lü

Zhou

et al. 2023

Preprint

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Excessive neural synchronization of neural populations in the beta (β) frequency range (12-35Hz) is intimately related to the symptoms of hypokinesia in Parkinson's disease (PD). Studies have shown that delayed feedback strategies can interrupt excessive neural synchronization and thus effectively alleviate symptoms associated with PD dyskinesia. Work on optimizing delayed feedback algorithms continues to progress, yet it remains challenging to further improve the inhibitory effect with reduced energy expenditure. Therefore, we first established a neural mass model of the cortex-basal ganglia-thalamus-pedunculopontine nucleus (BGCTh-PPN) closed-loop system, which can reflect the internal properties of cortical and basal ganglia neurons and their intrinsic connections with thalamic and pedunculopontine nucleus neurons. Second, the inhibitory effects of three delayed feedback schemes based on the external globus pallidum (GPe) on β oscillations were investigated separately and compared with those based on the subthalamic nucleus (STN) only. Our results show that all four delayed feedback schemes achieve effective suppression of pathological β oscillations when using the linear delayed feedback algorithm. The comparison revealed that the three GPe-based delay strategies were able to have a greater range of oscillation suppression with reduced energy consumption, thus improving control performance effectively, suggesting that they may be more effective for the relief of Parkinson's motor symptoms in practical applications.

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Section: The Role Of Feedback Gain G In Four Linear Delayed Feedback ...mentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Inhibition of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model

Sun

Lü

Zhou

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Therefore, it is imperative to design a new DBS control method that can simultaneously address the dynamics, nonlinearity, and non-stationarity in the cortex-BG-thalamus network for PD. Recently, an adaptive PI controller has been proposed to address nonlinear neural dynamics in PD, but only tested to control limited target levels of beta oscillation power [37,38,39]. Also, it is not tested against non-stationary neural dynamics.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Deep Brain Stimulation Control of Non-Stationary Cortex-Basal Ganglia-Thalamus Network Models in Parkinson’s Disease

Fang,

Berman,

Wang

et al. 2023

Preprint

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Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinson’s disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering the accurate and robust control of PD neural dynamics using current closed-loop DBS methods. Here, we develop a new robust adaptive closed-loop DBS method for regulating cortex-BG-thalamus network dynamics in PD. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated PD neural state while reducing the system’s sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as a testbed to simulate various nonlinear and non-stationary neural dynamics for evaluating DBS methods. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms state-of-the-art on-off and LTI DBS methods. These results have implications for future designs of clinically-viable closed-loop DBS systems to treat PD and other neurological and neuropsychiatric disorders.

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Suppression of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model

et al. 2023

View full text Add to dashboard Cite

Adaptive closed-loop control strategy inhibiting pathological basal ganglia oscillations

Cited by 5 publications

References 69 publications

Inhibition of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model

Inhibition of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model

Robust Adaptive Deep Brain Stimulation Control of Non-Stationary Cortex-Basal Ganglia-Thalamus Network Models in Parkinson’s Disease

Suppression of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model

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