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    Identifying controlling nodes in neuronal networks in different scales
    (San Francisco, CA : Public Library of Science (PLoS), 2012) Tang, Y.; Gao, H.; Zou, W.; Kurths, J.
    Recent studies have detected hubs in neuronal networks using degree, betweenness centrality, motif and synchronization and revealed the importance of hubs in their structural and functional roles. In addition, the analysis of complex networks in different scales are widely used in physics community. This can provide detailed insights into the intrinsic properties of networks. In this study, we focus on the identification of controlling regions in cortical networks of cats' brain in microscopic, mesoscopic and macroscopic scales, based on single-objective evolutionary computation methods. The problem is investigated by considering two measures of controllability separately. The impact of the number of driver nodes on controllability is revealed and the properties of controlling nodes are shown in a statistical way. Our results show that the statistical properties of the controlling nodes display a concave or convex shape with an increase of the allowed number of controlling nodes, revealing a transition in choosing driver nodes from the areas with a large degree to the areas with a low degree. Interestingly, the community Auditory in cats' brain, which has sparse connections with other communities, plays an important role in controlling the neuronal networks.
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    The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control
    (San Francisco, California, US : PLOS, 2018) Wang, Weiping; Yu, Xin; Luo, Xiong; Wang, Long; Li, Lixiang; Kurths, Jürgen; Zhao, Wenbing; Xiao, Jiuhong
    In this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampled-data control. We use the input delay method to turn the sampling system into a continuous time-delaying system. Then we analyze the exponential stability and asymptotic stability of the equilibrium points for this model. By constructing a suitable Lyapunov function, using the Lyapunov stability theorem and some inequality techniques, some sufficient criteria for ensuring the stability of equilibrium points are obtained. Finally, numerical examples are given to demonstrate the effectiveness of our results.
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    Technical feasibility study for production of tailored multielectrode arrays and patterning of arranged neuronal networks
    (San Francisco, CA : Public Library of Science (PLoS), 2018) Schürmann, M.; Shepheard, N.; Frese, N.; Geishendorf, K.; Sudhoff, H.; Gölzhäuser, A.; Rückert, U.; Kaltschmidt, C.; Kaltschmidt, B.; Thomas, A.
    In this manuscript, we first reveal a simple ultra violet laser lithographic method to design and produce plain tailored multielectrode arrays. Secondly, we use the same lithographic setup for surface patterning to enable controlled attachment of primary neuronal cells and help neurite guidance. For multielectrode array production, we used flat borosilicate glass directly structured with the laser lithography system. The multi layered electrode system consists of a layer of titanium coated with a layer of di-titanium nitride. Finally, these electrodes are covered with silicon nitride for insulation. The quality of the custom made multielectrode arrays was investigated by light microscopy, electron microscopy and X-ray diffraction. The performance was verified by the detection of action potentials of primary neurons. The electrical noise of the custom-made MEA was equal to commercially available multielectrode arrays. Additionally, we demonstrated that structured coating with poly lysine, obtained with the aid of the same lithographic system, could be used to attach and guide neurons to designed structures. The process of neuron attachment and neurite guidance was investigated by light microscopy and charged particle microscopy. Importantly, the utilization of the same lithographic system for MEA fabrication and poly lysine structuring will make it easy to align the architecture of the neuronal network to the arrangement of the MEA electrode.. In future studies, this will lead to multielectrode arrays, which are able to specifically attach neuronal cell bodies to their chemically defined electrodes and guide their neurites, gaining a controlled connectivity in the neuronal network. This type of multielectrode array would be able to precisely assign a signal to a certain neuron resulting in an efficient way for analyzing the maturation of the neuronal connectivity in small neuronal networks.