Search Results
Identifying controlling nodes in neuronal networks in different scales
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.
Individual nodes contribution to the mesoscale of complex networks
2014, Klimm, F., Borge-Holthoefer, J., Wessel, N., Kurths, J., Zamora-Lopez, G.
The analysis of complex networks is devoted to the statistical characterization of the topology of graphs at different scales of organization in order to understand their functionality. While the modular structure of networks has become an essential element to better apprehend their complexity, the efforts to characterize the mesoscale of networks have focused on the identification of the modules rather than describing the mesoscale in an informative manner. Here we propose a framework to characterize the position every node takes within the modular configuration of complex networks and to evaluate their function accordingly. For illustration, we apply this framework to a set of synthetic networks, empirical neural networks, and to the transcriptional regulatory network of the Mycobacterium tuberculosis. We find that the architecture of both neuronal and transcriptional networks are optimized for the processing of multisensory information with the coexistence of well-defined modules of specialized components and the presence of hubs conveying information from and to the distinct functional domains.
A novel patch micro electrode array for sensing ionic membrane currents
2011, Aryasomayajula, A., Perike, S., Hensel, R., Posseckardt, J., Gerlach, G., Funk, R.H.W.
Ionic membrane currents play an important role during regeneration of nerve cells, embryonic development and wound healing processes. Measuring the intracellular ion currents across the cell membrane is important in understanding the cellular functions related to the ion activities. A novel patch micro electrode array (p-MEA) for measuring the ionic membrane currents without poisoning the cells due to emitting metal ions is described in this paper. Results on biocompatibility of the device are presented. We discuss the fabrication and working principle of p-MEA.
Bicyclic RGD peptides enhance nerve growth in synthetic PEG-based Anisogels
2021, Vedaraman, Sitara, Bernhagen, Dominik, Haraszti, Tamas, Licht, Christopher, Castro Nava, Arturo, Omidinia Anarkoli, Abdolrahman, Timmerman, Peter, De Laporte, Laura
Nerve regeneration scaffolds often consist of soft hydrogels modified with extracellular matrix (ECM) proteins or fragments, as well as linear and cyclic peptides. One of the commonly used integrin-mediated cell adhesive peptide sequences is Arg-Gly-Asp (RGD). Despite its straightforward coupling mechanisms to artificial extracellular matrix (aECM) constructs, linear RGD peptides suffer from low stability towards degradation and lack integrin selectivity. Cyclization of RGD improves the affinity towards integrin subtypes but lacks selectivity. In this study, a new class of short bicyclic peptides with RGD in a cyclic loop and 'random screened' tri-amino acid peptide sequences in the second loop is investigated as a biochemical cue for cell growth inside three-dimensional (3D) synthetic poly(ethylene glycol) (PEG)-based Anisogels. These peptides impart high integrin affinity and selectivity towards either αvβ3 or α5β1 integrin subunits. Enzymatic conjugation of such bicyclic peptides to the PEG backbone enables the formulation of an aECM hydrogel that supports nerve growth. Furthermore, different proteolytic cleavable moieties are incorporated and compared to promote cell migration and proliferation, resulting in enhanced cell growth with different degradable peptide crosslinkers. Mouse fibroblasts and primary nerve cells from embryonic chick dorsal root ganglions (DRGs) show superior growth in bicyclic RGD peptide conjugated gels selective towards αvβ3 or α5β1, compared to monocyclic or linear RGD peptides, with a slight preference to αvβ3 selective bicyclic peptides in the case of nerve growth. Synthetic Anisogels, modified with bicyclic RGD peptides and containing short aligned, magneto-responsive fibers, show oriented DRG outgrowth parallel to the fibers. This report shows the potential of PEG hydrogels coupled with bicyclic RGD peptides as an aECM model and paves the way for a new class of integrin selective biomolecules for cell growth and nerve regeneration.
Adaptive elimination of synchronization in coupled oscillator
2017, Zhou, S., Ji, P., Zhou, Q., Feng, J., Kurths, J., Lin, W.
We present here an adaptive control scheme with a feedback delay to achieve elimination of synchronization in a large population of coupled and synchronized oscillators. We validate the feasibility of this scheme not only in the coupled Kuramoto's oscillators with a unimodal or bimodal distribution of natural frequency, but also in two representative models of neuronal networks, namely, the FitzHugh-Nagumo spiking oscillators and the Hindmarsh-Rose bursting oscillators. More significantly, we analytically illustrate the feasibility of the proposed scheme with a feedback delay and reveal how the exact topological form of the bimodal natural frequency distribution influences the scheme performance. We anticipate that our developed scheme will deepen the understanding and refinement of those controllers, e.g. techniques of deep brain stimulation, which have been implemented in remedying some synchronization-induced mental disorders including Parkinson disease and epilepsy.
Synthetic 3D PEG-Anisogel Tailored with Fibronectin Fragments Induce Aligned Nerve Extension
2019, Licht, Christopher, Rose, Jonas C., Anarkoli, Abdolrahman Omidinia, Blondel, Delphine, Roccio, Marta, Haraszti, Tamás, Gehlen, David B., Hubbell, Jeffrey A., Lutolf, Matthias P., De Laporte, Laura
An enzymatically cross-linked polyethylene glycol (PEG)-based hydrogel was engineered to promote and align nerve cells in a three-dimensional manner. To render the injectable, otherwise bioinert, PEG-based material supportive for cell growth, its mechanical and biochemical properties were optimized. A recombinant fibronectin fragment (FNIII9*-10/12-14) was coupled to the PEG backbone during gelation to provide cell adhesive and growth factor binding domains in close vicinity. Compared to full-length fibronectin, FNIII9*-10/12-14 supports nerve growth at similar concentrations. In a 3D environment, only the ultrasoft 1 w/v% PEG hydrogels with a storage modulus of ∼10 Pa promoted neuronal growth. This gel was used to establish the first fully synthetic, injectable Anisogel by the addition of magnetically aligned microelements, such as rod-shaped microgels or short fibers. The Anisogel led to linear neurite extension and represents a large step in the direction of clinical translation with the opportunity to treat acute spinal cord injuries.
Lévy noise improves the electrical activity in a neuron under electromagnetic radiation
2017, Wu, J., Xu, Y., Ma, J.
As the fluctuations of the internal bioelectricity of nervous system is various and complex, the external electromagnetic radiation induced by magnet flux on membrane can be described by the non-Gaussian type distribution of Levy noise. Thus, the electrical activities in an improved Hindmarsh-Rose model excited by the external electromagnetic radiation of Levy noise are investigated and some interesting modes of the electrical activities are exhibited. The external electromagnetic radiation of Levy noise leads to the mode transition of the electrical activities and spatial phase, such as from the rest state to the firing state, from the spiking state to the spiking state with more spikes, and from the spiking state to the bursting state. Then the time points of the firing state versus Levy noise intensity are depicted. The increasing of Levy noise intensity heightens the neuron firing. Also the stationary probability distribution functions of the membrane potential of the neuron induced by the external electromagnetic radiation of Levy noise with different intensity, stability index and skewness papremeters are analyzed. Moreover, through the positive largest Lyapunov exponent, the parameter regions of chaotic electrical mode of the neuron induced by the external electromagnetic radiation of Levy noise distribution are detected.