A Possible Explanation of How High-Frequency Deep Brain Stimulation Suppresses Low-Frequency Tremors in Parkinson's Disease

Parkinsonian Tremor as Unstable Feedback in a Physiologically Consistent Control Framework

Parkinson's disease (PD) is characterized by decreased dopamine in the basal ganglia that causes excessive tonic inhibition of the thalamus. This excessive inhibition seems to explain inhibitory motor symptoms in PD, but the source of tremor remains unclear. This paper investigates how neural inhibition may change the closed-loop characteristics of the human motor control system to determine how this established pathophysiology could produce tremor. The rate-coding model of neural signals suggests increased inhibition decreases signal amplitude, which could create a mismatch between the closed-loop dynamics and the internal models that overcome proprioceptive feedback delays. This paper aims to identify a candidate model structure with decreased-amplitude-induced tremor in PD that also agrees with previously recorded movements of healthy and cerebellar patients. The optimal feedback control theory of human motor control forms the basis of the model. Key additional elements include gating of undesired movements via the basal ganglia-thalamus-motor cortex circuit and the treatment of the efferent copy of the control input as a measurement in the state estimator. Simulations confirm the model's ability to capture tremor in PD and also demonstrate how disease progression could affect tremor and other motor symptoms, providing insight into the existence of tremor and non-tremor phenotypes. Altogether, the physiological underpinnings of the model structure and the agreement of model predictions with clinical observations provides support for the hypothesis that unstable feedback produces parkinsonian tremor. Consequently, these results also support the associated framework for the neuroanatomy of human motor control.

An Embedded Multi-Core Real-Time Simulation Platform of Basal Ganglia for Deep Brain Stimulation

Closed-loop deep brain stimulation (DBS) paradigm is gaining tremendous favor due to its potential capability of further and more efficient improvements in neurological diseases. Preclinical validation of closed-loop controller is quite necessary in order to minimize injury risks of clinical trials to patients, which can greatly benefit from real-time computational models and thus potentially reduce research and development costs and time. Here we developed an embedded multi-core real-time simulation platform (EMC-RTP) for a biological-faithful computational network model of basal ganglia (BG). The single neuron model is implemented in a highly real-time manner using a reasonable simplification. A modular mapping architecture with hierarchical routing organization was constructed to mimic the pathological neural activities of BG observed in parkinsonian conditions. A closed-loop simulation testbed for DBS validation was then set up using a host computer as the DBS controller. The availability of EMC-RTP and the testbed system was validated by comparing the performance of open-loop and proportional-integral (PI) controllers. Our experimental results showed that the proposed EMC-RTP reproduces abnormal beta bursts of BG in parkinsonian conditions while meets requirements of both real-time and computational accuracy as well. Closed-loop DBS experiments using the EMC-RTP suggested that the platform could perform reasonable output under different kinds of DBS strategies, indicating the usability of the platform.

Dopamine and Striatal Neuron Firing Respond to Frequency-Dependent DBS Detected by Microelectrode Arrays in the Rat Model of Parkinson's Disease

(1) Background: Deep brain stimulation (DBS) is considered as an efficient treatment method for alleviating motor symptoms in Parkinson’s disease (PD), while different stimulation frequency effects on the specific neuron patterns at the cellular level remain unknown. (2) Methods: In this work, nanocomposites-modified implantable microelectrode arrays (MEAs) were fabricated to synchronously record changes of dopamine (DA) concentration and striatal neuron firing in the striatum during subthalamic nucleus DBS, and different responses of medium spiny projecting neurons (MSNs) and fast spiking interneurons (FSIs) to DBS were analyzed. (3) Results: DA concentration and striatal neuron spike firing rate showed a similar change as DBS frequency changed from 10 to 350 Hz. Note that the increases in DA concentration (3.11 ± 0.67 μM) and neural spike firing rate (15.24 ± 2.71 Hz) were maximal after the stimulation at 100 Hz. The MSNs firing response to DBS was significant, especially at 100 Hz, while the FSIs remained stable after various stimulations. (4) Conclusions: DBS shows the greatest regulatory effect on DA concentration and MSNs firing rate at 100 Hz stimulation. This implantable MEA in the recording of the neurotransmitter and neural spike pattern response to DBS provides a new insight to understand the mechanism of PD at the cellular level.

Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory

Electrical excitation of neural tissue has wide applications, but how electrical stimulation interacts with neural tissue remains to be elucidated. Here, we propose a new theory, named the Circuit-Probability theory, to reveal how this physical interaction happen. The relation between the electrical stimulation input and the neural response can be theoretically calculated. We show that many empirical models, including strength-duration relationship and linear-non-linear-Poisson model, can be theoretically explained, derived, and amended using our theory. Furthermore, this theory can explain the complex non-linear and resonant phenomena and fit in vivo experiment data. In this letter, we validated an entirely new framework to study electrical stimulation on neural tissue, which is to simulate voltage waveforms using a parallel RLC circuit first, and then calculate the excitation probability stochastically.

COMPARISON OF THEORIES OF REST TREMOR MECHANISM IN PARKINSON’S DISEASE: CENTRAL OSCILLATOR (SOURCE-TRIGGERED OSCILLATIONS) AND FEEDBACK-INDUCED INSTABILITY IN THE SENSORIMOTOR LOOP (SELF-SUSTAINED OSCILLATIONS)

Rest tremor is one of the most common and disabling symptoms of Parkinson’s disease (PD). The exact neural origin of rest tremor is still not clearly understood. Understanding the origin of rest tremor is important as it may aid in optimizing existing treatment strategies such as Deep Brain Stimulation or in developing new treatment strategies for rest tremor reduction. There are broadly two theories that are gaining prominence for rest tremor generation in PD. The first theory is the central oscillator theory that states that the rest tremor is triggered by an oscillatory source in the brain. The second theory is the feedback-induced instability theory that states that the rest tremor arises out of a feedback-induced instability in the sensorimotor loop. This paper analyzes validity of the two theories based on established clinical observations of Parkinsonian rest tremor by using representative simulation examples. Finally, based on our analysis, we propose two test-worthy experiments for further validation.

The Study of Subthalamic Deep Brain Stimulation for Parkinson Disease-Associated Camptocormia

BACKGROUND Camptocormia is an axis symptom of Parkinson disease. It remains uncertain whether treatment with medications and surgery are effective. In this study, we assessed the efficacy of subthalamic nucleus deep brain stimulation (STN DBS) in Parkinson disease-associated camptocormia and explored some of its mechanisms. MATERIAL AND METHODS Parkinson disease-associated camptocormia was diagnosed by the following procedures. All patients underwent bilateral STN DBS. The patents' camptocormia was rated by degree and MDS Unified Parkinson's Disease Rating Scale (UPDRS) item 3.13 before and after DBS surgery. Rehabilitation and psychological interventions were used after surgery, in addition to adjustments of medication and stimulus parameters. The treatment effects on camptocormia were assessed comparing medication-off (presurgery) versus stimulation-on (post-surgery). Ethical approval for this study was provided through the Center of Human Research Ethics Committee (No. 2019-35). This study trial was registered in Chinese Clinical Trial Registry (No. ChiCTR1900022655). All the participants provided written informed consent. RESULTS After DBS surgery, all of study patients' symptoms were improved, with different levels of improvement. The minimum and maximum improvement rates were 20% and 100% respectively. The score of item 3.13 of the MDS-UPDRS III and the degree of camptocormia were found to be obviously improved (P<0.05). CONCLUSIONS STN DBS can improve Parkinson disease-associated camptocormia; STN DBS assisted with rehabilitation and psychological intervention appears to be more effective.