BackgroundAbnormal synchronization of neuronal activity in dopaminergic circuits is related to motor impairment in Parkinson’s disease (PD). Vibrotactile coordinated reset (vCR) fingertip stimulation aims to counteract excessive synchronization and induce sustained unlearning of pathologic synaptic connectivity and neuronal synchrony. Here, we report two clinical feasibility studies that examine the effect of regular and noisy vCR stimulation on PD motor symptoms. Additionally, in one clinical study (study 1), we examine cortical beta band power changes in the sensorimotor cortex. Lastly, we compare these clinical results in relation to our computational findings.MethodsStudy 1 examines six PD patients receiving noisy vCR stimulation and their cortical beta power changes after 3 months of daily therapy. Motor evaluations and at-rest electroencephalographic (EEG) recordings were assessed off medication pre- and post-noisy vCR. Study 2 follows three patients for 6+ months, two of whom received daily regular vCR and one patient from study 1 who received daily noisy vCR. Motor evaluations were taken at baseline, and follow-up visits were done approximately every 3 months. Computationally, in a network of leaky integrate-and-fire (LIF) neurons with spike timing-dependent plasticity, we study the differences between regular and noisy vCR by using a stimulus model that reproduces experimentally observed central neuronal phase locking.ResultsClinically, in both studies, we observed significantly improved motor ability. EEG recordings observed from study 1 indicated a significant decrease in off-medication cortical sensorimotor high beta power (21—30 Hz) at rest after 3 months of daily noisy vCR therapy. Computationally, vCR and noisy vCR cause comparable parameter-robust long-lasting synaptic decoupling and neuronal desynchronization.ConclusionIn these feasibility studies of eight PD patients, regular vCR and noisy vCR were well tolerated, produced no side effects, and delivered sustained cumulative improvement of motor performance, which is congruent with our computational findings. In study 1, reduction of high beta band power over the sensorimotor cortex may suggest noisy vCR is effectively modulating the beta band at the cortical level, which may play a role in improved motor ability. These encouraging therapeutic results enable us to properly plan a proof-of-concept study.
Several brain disorders are characterized by abnormally strong synchronization of neuronal activity. In Parkinson's patients, permanent high-frequency deep brain stimulation is used to suppress symptoms. To specifically counteract synchronized neuronal activity with a substantially reduced amount of stimulation current, theory-based desynchronizing stimulation techniques were developed, e.g., coordinated reset stimulation. Desynchronizing stimulation may shift adaptive networks from attractors with strong synchronization and strong synaptic coupling to attractors with weak synchronization and weak coupling. This is to cause stimulation effects that persist after cessation of stimulation. Corresponding preclinical and clinical studies reported long-lasting desynchronization and related symptom relief. However, desynchronizing stimulation requires parameters to be adapted to characteristics of the synchronized neuronal activity. Furthermore, desynchronization does not guarantee long-lasting change of network activity. We here present a qualitatively different approach to induce long-lasting, sustained changes of neuronal network dynamics: decoupling stimulation. Instead of primarily desynchronizing neuronal activity, decoupling stimulation employs synaptic plasticity mechanisms to specifically decouple neuronal networks. In this way, neuronal networks get robustly shifted to attractors with desynchronized neuronal activity. We present a theoretical framework that explains how neuronal responses to single stimuli as well as to spatiotemporally correlated stimulus sequences impact on network connectivity. This provides a theoretical base for designing effectively decoupling stimulation protocols. To overcome limitations of primarily desynchronizing stimulation, we present a random reset stimulation protocol, which uses spatiotemporal stimulus randomization to effectively decouple neurons. Theoretical predictions of random reset-induced decoupling as opposed to desynchronization-induced decoupling achieved by coordinated reset stimulation are compared to simulations of networks of integrate-and-fire neurons with spike-timing-dependent plasticity. Decoupling and related long-lasting desynchronization effects achieved by random reset stimulation are more robust with respect to parameter changes than those for coordinated reset stimulation. For both random reset and coordinated reset stimulation, simulation results and theoretically predicted decoupling rates show good quantitative agreement for sufficiently strong stimulation amplitudes. Intriguingly, single stimulus-related mechanisms may have a stronger decoupling impact than stimulus sequence-related mechanisms. We discuss scope and limitations of our decoupling approach for different types of synaptic plasticity and its application to deep brain stimulation.
Among the distinctive features of quasicrystals-structures with long-range order but without periodicity-are phasons. Phasons are hydrodynamic modes that, like phonons, do not cost free energy in the long-wavelength limit. For light-induced colloidal quasicrystals, we analyze the collective rearrangements of the colloids that occur when the phasonic displacement of the light field is changed. The colloidal model system is employed to study the link between the continuous description of phasonic modes in quasicrystals and collective phasonic flips of atoms. We introduce characteristic areas of reduced phononic and phasonic displacements and use them to predict individual colloidal trajectories. In principle, our method can be employed with all quasicrystalline systems in order to derive collective rearrangements of particles from the continuous description of phasons.
To navigate their surroundings, cells rely on sensory input that is corrupted by noise. In cells performing chemotaxis, such noise arises from the stochastic binding of signalling molecules at low chemoattractant concentrations. We reveal a fundamental relationship between the speed of chemotactic steering and the strength of directional fluctuations that result from the amplification of noise in a chemical input signal. This relation implies a trade-off between steering that is slow and reliable, and steering that is fast but less reliable. We show that dynamic switching between these two modes of steering can substantially increase the probability to find a target, such as an egg to be found by sperm cells. This decision making confers no advantage in the absence of noise, but is beneficial when chemical signals are detectable, yet characterized by low signal-to-noise ratios. The latter applies at intermediate distances from a target, where signalling molecules are diluted, thus defining a ‘noise zone’ that cells have to cross. Our results explain decision making observed in recent experiments on sea urchin sperm chemotaxis. More generally, our theory demonstrates how decision making enables chemotactic agents to cope with high levels of noise in gradient sensing by dynamically adjusting the persistence length of a biased random walk.
Excessive neuronal synchrony is a hallmark of several neurological disorders, e.g., Parkinson’s disease. An established treatment for medically refractory Parkinson’s disease is high-frequency deep brain stimulation. However, it provides only acute relief, and symptoms return shortly after cessation of stimulation. A theory-based approach called coordinated reset (CR) has shown great promise in achieving long-lasting effects. During CR stimulation, phase-shifted stimuli are delivered to multiple stimulation sites to counteract neuronal synchrony. Computational studies in plastic neuronal networks reported that synaptic weights reduce during stimulation, which may cause sustained structural changes leading to stabilized desynchronized activity even after stimulation ceases. Corresponding long-lasting effects were found in recent preclinical and clinical studies. We study long-lasting desynchronization by CR stimulation in excitatory recurrent neuronal networks of integrate-and-fire neurons with spike-timing-dependent plasticity (STDP). We focus on the impact of the stimulation frequency and the number of stimulation sites on long-lasting effects. We compare theoretical predictions to simulations of plastic neuronal networks. Our results are important regarding CR calibration for two reasons. We reveal that long-lasting effects become most pronounced when stimulation parameters are adjusted to the characteristics of STDP—rather than to neuronal frequency characteristics. This is in contrast to previous studies where the CR frequency was adjusted to the dominant neuronal rhythm. In addition, we reveal a nonlinear dependence of long-lasting effects on the number of stimulation sites and the CR frequency. Intriguingly, optimal long-lasting desynchronization does not require larger numbers of stimulation sites.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.