TY - GEN A1 - De Blasi, Stefano T1 - Simulation of Large Scale Neural Networks for Evaluation Applications T2 - 22nd International Student Conference on Electrical Engineering POSTER 2018 N2 - Understanding the complexity of biological neural networks like the human brain is one of the scientific challenges of our century. The organization of the brain can be described at different levels, ranging from small neural networks to entire brain regions. Existing methods for the description of functionally or effective connectivity are based on the analysis of relations between the activities of different neural units by detecting correlations or information flow. This is a crucial step in understanding neural disorders like Alzheimer’s disease and their causative factors. To evaluate these estimation methods, it is necessary to refer to a neural network with known connectivity, which is typically unknown for natural biological neural networks. Therefore, network simulations, also in silico, are available. In this work, the in silico simulation of large scale neural networks is established and the influence of different topologies on the generated patterns of neuronal signals is investigated. The goal is to develop standard evaluation methods for neurocomputational algorithms with a realistic large scale model to enable benchmarking and comparability of different studies. N2 - Poster KW - biological neural network KW - evaluation method KW - in silico KW - spike trains KW - Neuronales Netz Y1 - 2018 VL - 2018 IS - POSTER 2018 SP - 1 EP - 6 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 -