Biology subjects

Molnar, G. F.

Publications and source records attributed to Molnar, G. F..

3 recordsLinked to original sources

bioRxiv2021

Controlling pallidal oscillations in real-time in Parkinson's disease using evoked interference deep brain stimulation (eiDBS): proof of concept in the human

Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 8-35 Hz ("beta band") oscillatory dynamics in the manifestation of Parkinsons disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical pulse with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequencyspecific (16-22 Hz) neural activity in a PD patient. Our results highlight the utility of eiDBS to characterize the role of oscillatory dynamics in PD and other brain conditions, and to develop personalized neuromodulation systems.

neuroscience↗

bioRxiv2021

Quantifying Viscous Damping and Stiffness in Parkinsonism Using Data-Driven Model Estimation

Rigidity of upper and lower limbs in Parkinsons disease (PD) is typically assessed via a clinical rating scale that is subject to biases inherent to human perception. Methodologies and systems to systematically quantify changes in rigidity associated with angular position (stiffness) or velocity (viscous damping) are needed to enhance our understanding of PD pathophysiology and objectively assess therapies. We developed a robotic system and a model-based approach to estimate viscous damping and stiffness of the elbow. Our methodology enables the subject to freely rotate the elbow, while torque perturbations tailored to identify the arm dynamics are delivered. The viscosity and stiffness are calculated based on the experimental data using least-squares optimization. We validated our technique using computer simulations of the arm dynamics and experiments with a nonhuman animal model of PD in the presence and absence of deep brain stimulation (DBS) therapy. Computer simulations of the arm demonstrate that the proposed approach can accurately estimate viscous damping and stiffness. The experimental data show that both viscosity and stiffness significantly decreased when DBS was delivered. Computer simulations and experiments showed that stiffness and viscosity measurements obtained with the proposed methodology could better differentiate changes in rigidity than scores previously used for research, including the work score, impulse score, and modified Unified Parkinsons Disease Rating Scale (mUPDRS). The proposed estimation method is suitable to quantify the effect of therapies on viscous damping and stiffness and study the pathophysiological mechanisms underlying rigidity in PD.

bioengineering↗

bioRxiv2020

Suppressing and amplifying neural oscillations in real-time using phase-locked electrical stimulation: concept, optimization and in-vivo testing

BackgroundApproaches to predictably control neural oscillations are needed to understand their causal role in brain function in healthy or diseased states and to advance the development of neuromodulation therapies. In this study, we present a closed-loop neural control and optimization framework to actively suppress or amplify low-frequency neural oscillations observed in local field potentials in real-time by using electrical stimulation. Objective/HypothesisThe rationale behind this control approach and our working hypothesis is that neural oscillatory activity evoked by electrical pulses can suppress or amplify spontaneous oscillations via destructive or constructive interference when stimulation pulses are continuously delivered with appropriate amplitudes and at precise phases of these oscillations in a closed-loop scheme. MethodsWe tested our hypothesis in two nonhuman primates that exhibited a robust increase in low-frequency (8-30 Hz) oscillatory power in the subthalamic nucleus (STN) following administration of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). To test our neural control approach, we targeted 8-17 Hz oscillations and used electrode arrays and electrical stimulation waveforms similar to those used in humans chronically implanted with brain stimulation systems. Stimulation parameters that maximize the suppression or amplification of neural oscillations were predicted using mathematical models of the stimulation evoked oscillations. ResultsOur neural control and optimization approach was capable of actively and robustly suppressing or amplifying oscillations in the targeted frequency band (8-17 Hz) in real-time in the studied subjects. ConclusionsThe results from this study support our hypothesis and suggest that the proposed neural control framework allows one to characterize in controlled experiments the functional role of frequency-specific neural oscillations by using electrodes and stimulation waveforms currently being employed in humans.

neuroscience↗