Zeitschriftenaufsätze

Background - Cognitive, and motor performance are reduced in aging, especially with respect to acquisition of new knowledge, which is associated with a neural plasticity decline. Animal models show a reduction of long-term potentiation, but not long-term depression, in higher age. Findings in humans are more heterogeneous, with some studies showing respective deficits, but others not, or mixed results, for plasticity induced by non-invasive brain stimulation. One reason for these heterogeneous results might be the inclusion of different age ranges in these studies. In addition, a systematic detailed comparison of the age-dependency of neural plasticity in humans is lacking so far. - Objective - We aimed to explore age-dependent plasticity alterations in adults systematically by discerning between younger and older participants in our study. - Methods - We recruited three different age groups (Young: 18-30, Pre-Elderly: 50-65, and Elderly: 66-80 years). Anodal, cathodal, or sham transcranial direct current stimulation (tDCS) was applied over the primary motor cortex with 1 mA for 15 min to induce neuroplasticity. Cortical excitability was monitored by single-pulse transcranial magnetic stimulation as an index of plasticity. - Results - For anodal tDCS, the results show a significant excitability enhancement, as compared to sham stimulation, for both, Young and the Pre-Elderly groups, while no LTP-like plasticity was obtained in the Elderly group by the applied stimulation protocol. Cathodal tDCS induced significant excitability-diminishing plasticity in all age groups. - Conclusion - Our study provides further insight in age-related differences of plasticity in healthy humans, which are similar to those obtained in animal models. The decline of LTP-like plasticity in higher age could contribute to cognitive deficits observed in aging.

The present work introduces combination of superparamagnetic iron oxides (SPIONs) and hexamolybdenum cluster ([{Mo6I8}I6]2−) units within amino-decorated silica nanoparticles (SNs) as promising design of the hybrid SNs as efficient cellular contrast and therapeutic agents. The heating generated by SNs doped with SPIONs (Fe3O4SNs) under alternating magnetic field is characterized by high specific absorption rate (SAR = 446 W/g). The cluster units deposition onto both Fe3O4@SNs and “empty” silica nanoparticles (SNs) results in Fe3O4@SNs[{Mo6I8}I6] and SNs[{Mo6I8}I6] with red cluster-centered luminescence and ability to generate reactive oxygen species (ROS) under the irradiation. The monitoring of spin-trapped ROS by ESR spectroscopy technique indicates that the ROS-generation decreases in time for SNs[{Mo6I8}I6] and [{Mo6I8}I6]2− in aqueous solutions, while it remains constant for Fe3O4@SNs[{Mo6I8}I6]. The cytotoxicity is low for both Fe3O4@SNs[{Mo6I8}I6] and SNs[{Mo6I8}I6], while the flow cytometry indicates preferable cellular uptake of the former versus the latter type of the nanoparticles. Moreover, entering into nucleus along with cytoplasm differentiates the intracellular distribution of Fe3O4@SNs[{Mo6I8}I6] from that of SNs[{Mo6I8}I6], which remain in the cell cytoplasm only. The exceptional behavior of Fe3O4@SNs[{Mo6I8}I6] is explained by residual amounts of iron ions at the silica surface.

Bursting plays an important role in neural communication. At the population level, macroscopic bursting has been identified in populations of neurons that do not express intrinsic bursting mechanisms. For the analysis of phase transitions between bursting and non-bursting states, mean-field descriptions of macroscopic bursting behavior are a valuable tool. In this article, we derive mean-field descriptions of populations of spiking neurons and examine whether states of collective bursting behavior can arise from short-term adaptation mechanisms. Specifically, we consider synaptic depression and spike-frequency adaptation in networks of quadratic integrate-and-fire neurons. Analyzing the mean-field model via bifurcation analysis, we find that bursting behavior emerges for both types of short-term adaptation. This bursting behavior can coexist with steady-state behavior, providing a bistable regime that allows for transient switches between synchronized and nonsynchronized states of population dynamics. For all of these findings, we demonstrate a close correspondence between the spiking neural network and the mean-field model. Although the mean-field model has been derived under the assumptions of an infinite population size and all-to-all coupling inside the population, we show that this correspondence holds even for small, sparsely coupled networks. In summary, we provide mechanistic descriptions of phase transitions between bursting and steady-state population dynamics, which play important roles in both healthy neural communication and neurological disorders.