Tremor Reduction by Deep Brain Stimulation Is Associated With Gamma Power Suppression in Parkinson's Disease

A Humanized Clinically Calibrated Quantitative Systems Pharmacology Model for Hypokinetic Motor Symptoms in Parkinson's Disease

The current treatment of Parkinson’s disease with dopamine-centric approaches such as L-DOPA and dopamine agonists, although very successful, is in need of alternative treatment strategies, both in terms of disease modification and symptom management. Various non-dopaminergic treatment approaches did not result in a clear clinical benefit, despite showing a clear effect in preclinical animal models. In addition, polypharmacy is common, sometimes leading to unintended effects on non-motor cognitive and psychiatric symptoms. To explore novel targets for symptomatic treatment and possible synergistic pharmacodynamic effects between different drugs, we developed a computer-based Quantitative Systems Pharmacology (QSP) platform of the closed cortico-striatal-thalamic-cortical basal ganglia loop of the dorsal motor circuit. This mechanism-based simulation platform is based on the known neuro-anatomy and neurophysiology of the basal ganglia and explicitly incorporates domain expertise in a formalized way. The calculated beta/gamma power ratio of the local field potential in the subthalamic nucleus correlates well (R² = 0.71) with clinically observed extra-pyramidal symptoms triggered by antipsychotics during schizophrenia treatment (43 drug-dose combinations). When incorporating Parkinsonian (PD) pathology and reported compensatory changes, the computer model suggests a major increase in b/g ratio (corresponding to bradykinesia and rigidity) from a dopamine depletion of 70% onward. The correlation between the outcome of the QSP model and the reported changes in UPDRS III Motor Part for 22 placebo-normalized drug-dose combinations is R² = 0.84. The model also correctly recapitulates the lack of clinical benefit for perampanel, MK-0567 and flupirtine and offers a hypothesis for the translational disconnect. Finally, using human PET imaging studies with placebo response, the computer model predicts well the placebo response for chronic treatment, but not for acute treatment in PD.

Electrocorticography reveals beta desynchronization in the basal ganglia-cortical loop during rest tremor in Parkinson's disease

The pathophysiology of rest tremor in Parkinson's disease (PD) is not well understood, and its severity does not correlate with the severity of other cardinal signs of PD. We hypothesized that tremor-related oscillatory activity in the basal-ganglia-thalamocortical loop might serve as a compensatory mechanism for the excessive beta band synchronization associated with the parkinsonian state. We recorded electrocorticography (ECoG) from the sensorimotor cortex and local field potentials (LFP) from the subthalamic nucleus (STN) in patients undergoing lead implantation for deep brain stimulation (DBS). We analyzed differences in measures of network synchronization during epochs of spontaneous rest tremor, versus epochs without rest tremor, occurring in the same subjects. The presence of tremor was associated with reduced beta power in the cortex and STN. Cortico-cortical coherence and phase-amplitude coupling (PAC) decreased during rest tremor, as did basal ganglia-cortical coherence in the same frequency band. Cortical broadband gamma power was not increased by tremor onset, in contrast to the movement-related gamma increase typically observed at the onset of voluntary movement. These findings suggest that the cortical representation of rest tremor is distinct from that of voluntary movement, and support a model in which tremor acts to decrease beta band synchronization within the basal ganglia-cortical loop.

Assessing the synergy between cholinomimetics and memantine as augmentation therapy in cognitive impairment in schizophrenia. A virtual human patient trial using quantitative systems pharmacology

While many drug discovery research programs aim to develop highly selective clinical candidates, their clinical success is limited because of the complex non-linear interactions of human brain neuronal circuits. Therefore, a rational approach for identifying appropriate synergistic multipharmacology and validating optimal target combinations is desperately needed. A mechanism-based Quantitative Systems Pharmacology (QSP) computer-based modeling platform that combines biophysically realistic preclinical neurophysiology and neuropharmacology with clinical information is a possible solution. This paper reports the application of such a model for Cognitive Impairment In Schizophrenia (CIAS), where the cholinomimetics galantamine and donepezil are combined with memantine and with different antipsychotics and smoking in a virtual human patient experiment. The results suggest that cholinomimetics added to antipsychotics have a modest effect on cognition in CIAS in non-smoking patients with haloperidol and risperidone and to a lesser extent with olanzapine and aripiprazole. Smoking reduces the effect of cholinomimetics with aripiprazole and olanzapine, but enhances the effect in haloperidol and risperidone. Adding memantine to antipsychotics improves cognition except with quetiapine, an effect enhanced with smoking. Combining cholinomimetics, antipsychotics and memantine in general shows an additive effect, except for a negative interaction with aripiprazole and quetiapine and a synergistic effect with olanzapine and haloperidol in non-smokers and haloperidol in smokers. The complex interaction of cholinomimetics with memantine, antipsychotics and smoking can be quantitatively studied using mechanism-based advanced computer modeling. QSP modeling of virtual human patients can possibly generate useful insights on the non-linear interactions of multipharmacology drugs and support complex CNS R&D projects in cognition in search of synergistic polypharmacy.

Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson's Disease During Deep Brain Stimulation

Parkinson's disease is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. It is associated with pathological, oscillatory neural activity in the basal ganglia. Deep brain stimulation (DBS) is often successfully used to treat medically refractive Parkinson's disease. However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters. This study explores fourth-order, control theory-based models of oscillatory activity in the basal ganglia. Describing function analysis is applied to examine possible mechanisms for the generation of oscillations in interacting nuclei and to investigate the suppression of oscillations with high-frequency stimulation. The theoretical results for the suppression of the oscillatory activity obtained using both the fourth-order model, and a previously described second-order model, are optimized to fit clinically recorded local field potential data obtained from Parkinsonian patients with implanted DBS. Close agreement between the power of oscillations recorded for a range of stimulation amplitudes is observed ( R(2)=0.69-0.99 ). The results suggest that the behavior of the system and the suppression of pathological neural oscillations with DBS is well described by the macroscopic models presented. The results also demonstrate that in this instance, a second-order model is sufficient to model the clinical data, without the need for added complexity. Describing the system behavior with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.

Closed-loop stimulation of a delayed neural fields model of parkinsonian STN-GPe network: a theoretical and computational study

Several disorders are related to pathological brain oscillations. In the case of Parkinson's disease, sustained low-frequency oscillations (especially in the β-band, 13-30 Hz) correlate with motor symptoms. It is still under debate whether these oscillations are the cause of parkinsonian motor symptoms. The development of techniques enabling selective disruption of these β-oscillations could contribute to the understanding of the underlying mechanisms, and could be exploited for treatments. A particularly appealing technique is Deep Brain Stimulation (DBS). With clinical electrical DBS, electrical currents are delivered at high frequency to a region made of potentially heterogeneous neurons (the subthalamic nucleus (STN) in the case of Parkinson's disease). Even more appealing is DBS with optogenetics, which is until now a preclinical method using both gene transfer and deep brain light delivery and enabling neuromodulation at the scale of one given neural network. In this work, we rely on delayed neural fields models of STN and the external Globus Pallidus (GPe) to develop, theoretically validate and test in silico a closed-loop stimulation strategy to disrupt these sustained oscillations with optogenetics. First, we rely on tools from control theory to provide theoretical conditions under which sustained oscillations can be attenuated by a closed-loop stimulation proportional to the measured activity of STN. Second, based on this theoretical framework, we show numerically that the proposed closed-loop stimulation efficiently attenuates sustained oscillations, even in the case when the photosensitization effectively affects only 50% of STN neurons. We also show through simulations that oscillations disruption can be achieved when the same light source is used for the whole STN population. We finally test the robustness of the proposed strategy to possible acquisition and processing delays, as well as parameters uncertainty.