TY - JOUR A1 - De Blasi, Stefano A1 - Ciba, Manuel A1 - Bahmer, Andreas A1 - Thielemann, Christiane T1 - Total spiking probability edges: A cross-correlation based method for effective connectivity estimation of cortical spiking neurons JF - Journal of Neuroscience Methods N2 - Background: Connectivity is a relevant parameter for the information flow within neuronal networks. Network connectivity can be reconstructed from recorded spike train data. Various methods have been developed to estimate connectivity from spike trains. New method: In this work, a novel effective connectivity estimation algorithm called Total Spiking Probability Edges (TSPE) is proposed and evaluated. First, a cross-correlation between pairs of spike trains is calculated. Second, to distinguish between excitatory and inhibitory connections, edge filters are applied on the resulting cross-correlogram. Results: TSPE was evaluated with large scale in silico networks and enables almost perfect reconstructions (true positive rate of approx. 99% at a false positive rate of 1% for low density random networks) depending on the network topology and the spike train duration. A distinction between excitatory and inhibitory connections was possible. TSPE is computational effective and takes less than 3 min on a high-performance computer to estimate the connectivity of an 1 h dataset of 1000 spike trains. Comparison of existing methods: TSPE was compared with connectivity estimation algorithms like Transfer Entropy based methods, Filtered and Normalized Cross-Correlation Histogram and Normalized Cross-Correlation. In all test cases, TSPE outperformed the compared methods in the connectivity reconstruction accuracy. Conclusions: The results show that the accuracy of functional connectivity estimation of large scale neuronal networks has been enhanced by TSPE compared to state of the art methods. Furthermore, TSPE enables the classification of excitatory and inhibitory synaptic effects. KW - Connectivity Estimation KW - Neuronal Networks KW - Parallel Spike Trains KW - Inhibitory and Excitatory KW - Neuronales Netz Y1 - 2019 U6 - https://doi.org/10.1016/j.jneumeth.2018.11.013 VL - 312 IS - 312 SP - 169 EP - 181 ER - TY - GEN A1 - Ciba, Manuel A1 - Mayer, Margot A1 - Thielemann, Christiane T1 - Experimental setup to investigate the effect of psychedelics on in vitro neuronal networks N2 - Experimental setup to investigate the effect of psychedelics on in vitro neuronal networks: A demonstration of the application of in vitro neuronal networks on high-density-microelectrode arrays (HDMEA) to study electrophysiological properties of neuronal networks in response to psychedelics. N2 - Poster KW - Neuronales Netz Y1 - 2019 UR - https://doi.org/10.6084/m9.figshare.11980434.v1 U6 - https://doi.org/10.6084/m9.figshare.11980434.v1 ER - TY - JOUR A1 - Körbitzer, Berit Silke A1 - Krauß, Peter A1 - Belle, Stefan A1 - Schneider, Jörg A1 - Thielemann, Christiane T1 - Electrochemical Characterization of Graphene Microelectrodes for Biological Applications JF - ChemNanoMat N2 - Graphene is a promising material both as a coating for existing neural electrodes as well as for transparent electrodes made exclusively from graphene. We studied graphene‐based microelectrodes by investigating their recording and stimulation properties in order to evaluate their suitability for neuronal implants. In this work, we compare three different electrode material compositions. Microelectrode arrays (MEA) with an electrode size of about 700 μm2 were prepared of gold, graphene on gold, and plain graphene on glass substrate. In order to reduce polymer contamination during graphene transfer, we employed a polymer‐free transfer and lift‐off process. Impedance studies revealed a value of 2.3 MΩ at 1 kHz for plain, and 0.88 MΩ for graphene on gold. Neuronal recording experiments showed a sufficient SNR for both graphene‐based materials and a stable impedance, unaffected by surface degradation metal electrodes are known for. Stimulation measurements yielded a charge injection capacity of 0.15 mC/cm2 using biphasic pulses of 1 ms and 1 μA transparent graphene electrodes. Cyclic voltammetry revealed a large voltage range of −1.4 V to +1.6 V before water electrolysis occurs. Graphene‐coated gold microelectrodes show enhanced recording properties, whereas plain graphene electrodes might be better suited for stimulation applications. KW - Graphene KW - Microelectrodes KW - Stimulation KW - Neural Recording KW - Neural Interface KW - Mikroelektrode KW - Array Y1 - 2019 U6 - https://doi.org/10.1002/cnma.201800652 VL - 2019 IS - 5:4 SP - 427 EP - 435 ER - TY - JOUR A1 - Flachs, Dennis A1 - Emmerich, Florian A1 - Roth, Gian-Luca A1 - Hellmann, Ralf A1 - Thielemann, Christiane T1 - Laser-bonding of FEP/FEP interfaces for a flexiblemanufacturing process of ferroelectrets JF - Journal of Physics: Conference Series N2 - This paper presents an optimized laser-bonding process for piezoelectric energy-harvesters based on thin fluorinated-ethylene-propylene (FEP) foils, using an ultra-short-pulse(USP) laser. Due to the minimized thermal stress in the material during bonding, achieved bypulse durations of few picoseconds, we created seams down to 40μm width without generatingholes in the 12.5μm thick FEP-foils. Using a galvanometer scanning system allowed for fastbonding-speed up to several centimeters per second, making the process also suitable for largestructures and areas. The achieved bond strength of the seams under influence of shearingstress was examined using tensile testing, which showed a sufficient strength of about 25 % of the maximum strength of an unbonded, single layer of FEP. KW - Ultrakurzzeitlaser KW - Piezoelektrizität Y1 - 2019 U6 - https://doi.org/10.1088/1742-6596/1407/1/012107 VL - 1407 IS - 012107 SP - 1 EP - 5 ER -