@article{SallumAlvesThielemannetal.2024, author = {Sallum, Loriz Francisco and Alves, Caroline L. and Thielemann, Christiane and Rodrigues, Francisco A.}, title = {Revealing patterns in major depressive disorder with machine learning and networks}, series = {medrxiv}, volume = {2024}, journal = {medrxiv}, number = {1}, doi = {doi.org/10.1101/2024.06.07.24308619}, pages = {1 -- 17}, year = {2024}, abstract = {Major depressive disorder (MDD) is a multifaceted condition that affects millions of people worldwide and is a leading cause of disability. There is an urgent need for an automated and objective method to detect MDD due to the limitations of traditional diagnostic approaches. In this paper, we propose a methodology based on machine and deep learning to classify patients with MDD and identify altered functional connectivity patterns from EEG data. We compare several connectivity metrics and machine learning algorithms. Complex network measures are used to identify structural brain abnormalities in MDD. Using Spearman correlation for network construction and the SVM classifier, we verify that it is possible to identify MDD patients with high accuracy, exceeding literature results. The SHAP (SHAPley Additive Explanations) summary plot highlights the importance of C4-F8 connections and also reveals dysfunction in certain brain areas and hyperconnectivity in others. Despite the lower performance of the complex network measures for the classification problem, assortativity was found to be a promising biomarker. Our findings suggest that understanding and diagnosing MDD may be aided by the use of machine learning methods and complex networks.}, subject = {Depression}, language = {en} } @article{NickJoshiSchneideretal.2012, author = {Nick, Christoph and Joshi, Ravi and Schneider, J{\"o}rg and Thielemann, Christiane}, title = {Three-Dimensional Carbon Nanotube Electrodes for Extracellular Recording of Cardiac Myocytes}, series = {Biointerphases, 2012}, volume = {7}, journal = {Biointerphases, 2012}, publisher = {Springer-Verl.}, doi = {10.1007/s13758-012-0058-2}, pages = {58}, year = {2012}, abstract = {Three-Dimensional Carbon Nanotube Electrodes for Extracellular Recording of Cardiac Myocytes}, subject = {Kohlenstoff-Nanor{\"o}hre}, language = {en} } @article{AlvesCuryRosteretal.2022, author = {Alves, Caroline L. and Cury, Rubens G. and Roster, Kirstin and Pineda, Aruane M. and Rodrigues, Francisco A. and Thielemann, Christiane and Ciba, Manuel}, title = {Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments}, series = {PLOS ONE}, volume = {2022}, journal = {PLOS ONE}, number = {12}, doi = {https://doi.org/10.1371/journal. pone.0277257}, pages = {1 -- 26}, year = {2022}, abstract = {Ayahuasca is a blend of Amazonian plants that has been used for traditional medicine by the inhabitants of this region for hundreds of years. Furthermore, this plant has been demon� strated to be a viable therapy for a variety of neurological and mental diseases. EEG experi� ments have found specific brain regions that changed significantly due to ayahuasca. Here, we used an EEG dataset to investigate the ability to automatically detect changes in brain activity using machine learning and complex networks. Machine learning was applied at three different levels of data abstraction: (A) the raw EEG time series, (B) the correlation of the EEG time series, and (C) the complex network measures calculated from (B). Further, at the abstraction level of (C), we developed new measures of complex networks relating to community detection. As a result, the machine learning method was able to automatically detect changes in brain activity, with case (B) showing the highest accuracy (92\%), followed by (A) (88\%) and (C) (83\%), indicating that connectivity changes between brain regions are more important for the detection of ayahuasca. The most activated areas were the frontal and temporal lobe, which is consistent with the literature. F3 and PO4 were the most impor� tant brain connections, a significant new discovery for psychedelic literature. This connec� tion may point to a cognitive process akin to face recognition in individuals during ayahuasca-mediated visual hallucinations. Furthermore, closeness centrality and assorta� tivity were the most important complex network measures. These two measures are also associated with diseases such as Alzheimer's disease, indicating a possible therapeutic mechanism. Moreover, the new measures were crucial to the predictive model and sug� gested larger brain communities associated with the use of ayahuasca. This suggests that the dissemination of information in functional brain networks is slower when this drug is present. Overall, our methodology was able to automatically detect changes in brain activity during ayahuasca consumption and interpret how these psychedelics alter brain networks, as well as provide insights into their mechanisms of action}, subject = {Ayahuasca}, language = {en} } @article{MayerArrizabalagaLiebetal.2018, author = {Mayer, Margot and Arrizabalaga, Onetsine and Lieb, Florian and Ciba, Manuel and Ritter, Sylvia and Thielemann, Christiane}, title = {Electrophysiological investigation of human embryonic stem cell derived neurospheres using a novel spike detection algorithm}, series = {Biosensors and Bioelectronics}, volume = {2018}, journal = {Biosensors and Bioelectronics}, number = {100}, doi = {10.1016/j.bios.2017.09.034}, pages = {462 -- 468}, year = {2018}, abstract = {Microelectrode array (MEA) technology in combination with three-dimensional (3D) neuronal cell models derived from human embryonic stem cells (hESC) provide an excellent tool for neurotoxicity screening. Yet, there are significant challenges in terms of data processing and analysis, since neuronal signals have very small amplitudes and the 3D structure enhances the level of background noise. Thus, neuronal signal analysis requires the application of highly sophisticated algorithms. In this study, we present a new approach optimized for the detection of spikes recorded from 3D neurospheres (NS) with a very low signal-to-noise ratio. This was achieved by extending simple threshold-based spike detection utilizing a highly sensitive algorithm named SWTTEO. This analysis procedure was applied to data obtained from hESC-derived NS grown on MEA chips. Specifically, we examined changes in the activity pattern occurring within the first ten days of electrical activity. We further analyzed the response of NS to the GABA receptor antagonist bicuculline. With this new algorithm method we obtained more reliable results compared to the simple threshold-based spike detection.}, subject = {Embryonale Stammzelle}, language = {en} } @article{KoerbitzerKraussBelleetal.2019, author = {K{\"o}rbitzer, Berit Silke and Krauß, Peter and Belle, Stefan and Schneider, J{\"o}rg and Thielemann, Christiane}, title = {Electrochemical Characterization of Graphene Microelectrodes for Biological Applications}, series = {ChemNanoMat}, volume = {2019}, journal = {ChemNanoMat}, number = {5:4}, doi = {10.1002/cnma.201800652}, pages = {427 -- 435}, year = {2019}, abstract = {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.}, subject = {Mikroelektrode}, language = {en} } @article{MoniciThielemann2023, author = {Monici, Monica and Thielemann, Christiane}, title = {How do gravity alterations affect animal and human systems at a cellular/tissue level?}, series = {nature npj Microgravity}, volume = {2023}, journal = {nature npj Microgravity}, number = {9/84}, doi = {https://doi.org/10.1038/s41526-023-00330-y}, pages = {1 -- 9}, year = {2023}, abstract = {The present white paper concerns the indications and recommendations of the SciSpacE Science Community to make progress in filling the gaps of knowledge that prevent us from answering the question: "How Do Gravity Alterations Affect Animal and Human Systems at a Cellular/Tissue Level?" This is one of the five major scientific issues of the ESA roadmap "Biology in Space and Analogue Environments". Despite the many studies conducted so far on spaceflight adaptation mechanisms and related pathophysiological alterations observed in astronauts, we are not yet able to elaborate a synthetic integrated model of the many changes occurring at different system and functional levels. Consequently, it is difficult to develop credible models for predicting long-term consequences of human adaptation to the space environment, as well as to implement medical support plans for long-term missions and a strategy for preventing the possible health risks due to prolonged exposure to spaceflight beyond the low Earth orbit (LEO). The research activities suggested by the scientific community have the aim to overcome these problems by striving to connect biological and physiological aspects in a more holistic view of space adaptation effects.}, subject = {Raumfahrt}, language = {en} } @article{KoehlerWoelfelCibaetal.2018, author = {K{\"o}hler, Tim and W{\"o}lfel, Maximilian and Ciba, Manuel and Bochtler, Ulrich and Thielemann, Christiane}, title = {Terrestrial Trunked Radio (TETRA) exposure of neuronal in vitro networks}, series = {Environmental Research}, volume = {2018}, journal = {Environmental Research}, number = {162}, doi = {10.1016/j.envres.2017.12.007}, pages = {1 -- 7}, year = {2018}, abstract = {Terrestrial Trunked Radio (TETRA) is a worldwide common mobile communication standard, used by authorities and organizations with security tasks. Previous studies reported on health effects of TETRA, with focus on the specific pulse frequency of 17.64 Hz, which affects calcium efflux in neuronal cells. Likewise among others, it was reported that TETRA affects heart rate variability, neurophysiology and leads to headaches. In contrast, other studies conclude that TETRA does not affect calcium efflux of cells and has no effect on people's health. In the present study we examine whether TETRA short- and long-term exposure could affect the electrophysiology of neuronal in vitro networks. Experiments were performed with a carrier frequency of 395 MHz, a pulse frequency of 17.64 Hz and a differential quaternary phase-shift keying (π/4 DQPSK) modulation. Specific absorption rates (SAR) of 1.17 W/kg and 2.21 W/kg were applied. In conclusion, the present results do not indicate any effect of TETRA exposure on electrophysiology of neuronal in vitro networks, neither for short-term nor long-term exposure. This applies to the examined parameters spike rate, burst rate, burst duration and network synchrony.}, subject = {Neuronales Netz}, language = {en} } @article{EmmerichThielemann2016, author = {Emmerich, Florian and Thielemann, Christiane}, title = {Real-space measurement of potential distribution in PECVD ONO electrets by Kelvin probe force microscopy}, series = {Nanotechnology}, volume = {2016}, journal = {Nanotechnology}, number = {27}, pages = {1 -- 10}, year = {2016}, abstract = {Multilayers of silicon oxide/silicon nitride/silicon oxide (ONO) are known for their good electret properties due to deep energy traps near the material interfaces, facilitating charge storage. However, measurement of the space charge distribution in such multilayers is a challenge for conventional methods if layer thickness dimensions shrink below 1 μm. In this paper, we propose an atomic force microscope based method to determine charge distributions in ONO layers with spatial resolution below 100 nm. By applying Kelvin probe force microscopy (KPFM) on freshly cleaved, corona-charged multilayers, the surface potential is measured directly along the z-axis and across the interfaces. This new method gives insights into charge distribution and charge movement in inorganic electrets with a high spatial resolution.}, subject = {Kelvin-Sonde}, language = {en} } @article{AlligMayerThielemann2018, author = {Allig, Sebastian and Mayer, Margot and Thielemann, Christiane}, title = {Workflow for bioprinting of cell-laden bioink}, series = {Lekar a technika - Clinician and Technology}, volume = {48}, journal = {Lekar a technika - Clinician and Technology}, number = {2}, pages = {46 -- 51}, year = {2018}, abstract = {Applying technologies of additive manufacturing to the field of tissue engineering created a pioneering new approach to model complex cell systems artificially. Regarding its huge potential, bioprinting is still in its infancies and many questions are still unanswered. To address this issue, an extrusion-based bioprinting (EBB) process was used to deposit human embryonic kidney (HEK) cells in a defined pattern. It was shown that the bioprinted construct featured a high degree in viability reaching up to 77\% 10 days after printing (DAP). This work displays a proof of principle for a controlled cell formation which shall later be applied to in vitro drug screening tests using various types of cells.}, subject = {Biomaterial}, language = {en} } @article{DeBlasiCibaBahmeretal.2019, author = {De Blasi, Stefano and Ciba, Manuel and Bahmer, Andreas and Thielemann, Christiane}, title = {Total spiking probability edges: A cross-correlation based method for effective connectivity estimation of cortical spiking neurons}, series = {Journal of Neuroscience Methods}, volume = {312}, journal = {Journal of Neuroscience Methods}, number = {312}, doi = {10.1016/j.jneumeth.2018.11.013}, pages = {169 -- 181}, year = {2019}, abstract = {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.}, subject = {Neuronales Netz}, language = {en} } @inproceedings{MayerArrizabalagaSchroederetal.2018, author = {Mayer, Margot and Arrizabalaga, Onetsine and Schr{\"o}der, Insa and Ritter, Sylvia and Thielemann, Christiane}, title = {Human Embryonic Stem Cell Derived Neurospheres - 2D and 3D Cell Culture in one sample}, year = {2018}, abstract = {Various studies have shown that two dimensional (2D) neuronal cell cultures does not recapitulate structure and physiology of three-dimensional (3D) in vivo tissues. These findings are of paramount importance for drug screening, since the response to neurotoxicological substances may differ for 2D und 3D cell culture models. To address this topic, we present human embryonic stem cell (hESC) derived neurospheres (NS) coupled onto microelectrode array (MEA) chips as a model system that includes a 3D NS as well as an outgrowing 2D monolayer allowing direct comparison of functionality within one culture. Preliminary results revealed an enhanced functional reactions of 3D NS to GABA receptor antagonist bicuculline compared to the 2D domain. Thus we have the first evidence that hESC derived NS are a promising model system for neurotoxicity testing enabling a direct comparison between functionality of neurons grown in 2D or 3D.}, subject = {Embryonale Stammzelle}, language = {en} } @inproceedings{CibaThielemann2018, author = {Ciba, Manuel and Thielemann, Christiane}, title = {Synchrony changes on different time-scales during in vitro neuronal network development}, year = {2018}, subject = {Neuronales Netz}, language = {en} } @article{HeselichFriessRitteretal.2018, author = {Heselich, Anja and Frieß, Johannes and Ritter, Sylvia and Benz, Naja and Layer, Paul and Thielemann, Christiane}, title = {High LET radiation shows no major cellular and functional effects on primary cardiomyocytes in vitro}, series = {Life Sciences in Space Research}, volume = {2018}, journal = {Life Sciences in Space Research}, number = {16}, doi = {10.1016/j.lssr.2018.01.001}, pages = {93 -- 100}, year = {2018}, abstract = {It is well known that ionizing radiation causes adverse effects on various mammalian tissues. However, there is little information on the biological effects of heavy ion radiation on the heart. In order to fill this gap, we systematically examined DNA-damage induction and repair, as well as proliferation and apoptosis in avian cardiomyocyte cultures irradiated with heavy ions such as titanium and iron, relevant for manned space-flight, and carbon ions, as used for radiotherapy. Further, and to our knowledge for the first time, we analyzed the effect of heavy ion radiation on the electrophysiology of primary cardiomyocytes derived from chicken embryos using the non-invasive microelectrode array (MEA) technology. As electrophysiological endpoints beat rate and field action potential duration were analyzed. The cultures clearly exhibited the capacity to repair induced DNA damage almost completely within 24 h, even at doses of 7 Gy, and almost completely recovered from radiation-induced changes in proliferative behavior. Interestingly, no significant effects on apoptosis could be detected. Especially the functionality of primary cardiac cells exhibited a surprisingly high robustness against heavy ion radiation, even at doses of up to 7 Gy. In contrast to our previous study with X-rays the beat rate remained more or less unaffected after heavy ion radiation, independently of beam quality. The only change we could observe was an increase of the field action potential duration of up to 30\% after titanium irradiation, diminishing within the following three days. This potentially pathological observation may be an indication that heavy ion irradiation at high doses could bear a long-term risk for cardiovascular disease induction.}, subject = {Zellkultur}, language = {en} } @article{SamhaberSchottdorfElHadyetal.2016, author = {Samhaber, Robert and Schottdorf, Manuel and El Hady, Ahmed and Br{\"o}king, Kai and Daus, Andreas and Thielemann, Christiane and St{\"u}hmer, Walter and Wolf, Fred}, title = {Growing neuronal islands on multi-electrode arrays using an accurate positioning-μCP device}, series = {Journal of Neuroscience Methods}, volume = {2016}, journal = {Journal of Neuroscience Methods}, number = {257}, doi = {10.1016/j.jneumeth.2015.09.022}, pages = {194 -- 203}, year = {2016}, abstract = {Background: Multi-electrode arrays (MEAs) allow non-invasive multi-unit recording in-vitro from cultured neuronal networks. For sufficient neuronal growth and adhesion on such MEAs, substrate preparation is required. Plating of dissociated neurons on a uniformly prepared MEA's surface results in the formation of spatially extended random networks with substantial inter-sample variability. Such cultures are not optimally suited to study the relationship between defined structure and dynamics in neuronal networks. To overcome these shortcomings, neurons can be cultured with pre-defined topology by spatially structured surface modification. Spatially structuring a MEA surface accurately and reproducibly with the equipment of a typical cell-culture laboratory is challenging. New method: In this paper, we present a novel approach utilizing micro-contact printing (μCP) combined with a custom-made device to accurately position patterns on MEAs with high precision. We call this technique AP-μCP (accurate positioning micro-contact printing). Comparison with existing methods: Other approaches presented in the literature using μCP for patterning either relied on facilities or techniques not readily available in a standard cell culture laboratory, or they did not specify means of precise pattern positioning. Conclusion: Here we present a relatively simple device for reproducible and precise patterning in a standard cell-culture laboratory setting. The patterned neuronal islands on MEAs provide a basis for high throughput electrophysiology to study the dynamics of single neurons and neuronal networks.}, subject = {Mehrfachelektrode}, language = {en} } @article{LiebStarkThielemann2017, author = {Lieb, Florian and Stark, Hans-Georg and Thielemann, Christiane}, title = {A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data}, series = {Journal of Neural Engineering}, volume = {2017}, journal = {Journal of Neural Engineering}, number = {14}, doi = {10.1088/1741-2552/aa654b}, pages = {1 -- 13}, year = {2017}, abstract = {Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.}, subject = {Neuronales Netz}, language = {en} } @article{SzewczykMoniciThielemann2024, author = {Szewczyk, Nathaniel J. and Monici, Monica and Thielemann, Christiane}, title = {How to obtain an integrated picture of the molecular networks involved in adaptation to microgravity in different biological systems?}, series = {npj Microgravity}, volume = {2024}, journal = {npj Microgravity}, number = {10}, doi = {DOI: 10.1038/s41526-024-00395-3}, pages = {1 -- 5}, year = {2024}, abstract = {Periodically, the European Space Agency (ESA) updates scientific roadmaps in consultation with the scientific community. The ESA SciSpacE Science Community White Paper (SSCWP) 9, "Biology in Space and Analogue Environments", focusses in 5 main topic areas, aiming to address key community-identified knowledge gaps in Space Biology. Here we present one of the identified topic areas, which is also an unanswered question of life science research in Space: "How to Obtain an Integrated Picture of the Molecular Networks Involved in Adaptation to Microgravity in Different Biological Systems?" The manuscript reports the main gaps of knowledge which have been identified by the community in the above topic area as well as the approach the community indicates to address the gaps not yet bridged. Moreover, the relevance that these research activities might have for the space exploration programs and also for application in industrial and technological fields on Earth is briefly discussed.}, subject = {Weltraumforschung}, language = {en} } @article{NickYadavJoshietal.2015, author = {Nick, Christoph and Yadav, Sandeep and Joshi, Ravi and Schneider, J{\"o}rg and Thielemann, Christiane}, title = {A three-dimensional microelectrode array composed of vertically aligned ultra-dense carbon nanotube networks}, series = {Applied Physics Letters}, volume = {2015}, journal = {Applied Physics Letters}, number = {107}, doi = {10.1063/1.4926330}, pages = {1 -- 1}, year = {2015}, abstract = {Electrodes based on carbon nanotubes are a promising approach to manufacture highly sensitive sensors with a low limit of signal detection and a high signal-to-noise ratio. This is achieved by dramatically increasing the electrochemical active surface area without increasing the overall geometrical dimensions. Typically, carbon nanotube electrodes are nearly planar and composed of randomly distributed carbon nanotube networks having a limited surface gain for a specific geometrical surface area. To overcome this limitation, we have introduced vertically aligned carbon nanotube (VACNT) networks as electrodes, which are arranged in a microelectrode pattern of 60 single electrodes. Each microelectrode features a very high aspect ratio of more than 300 and thus a dramatically increased surface area. These microelectrodes composed of VACNT networks display dramatically decreased impedance over the entire frequency range compared to planar microelectrodes caused by the enormous capacity increase. This is experimentally verified by electrochemical impedance spectroscopy and cyclic voltammetry.}, subject = {Mikroelektrode}, language = {en} } @article{KupnikThielemann2017, author = {Kupnik, Mario and Thielemann, Christiane}, title = {In vitro platform for acoustic and electrophysiological investigations of ultrasound stimulation}, series = {Brain Stimulation}, volume = {10}, journal = {Brain Stimulation}, number = {2}, doi = {10.1016/j.brs.2017.01.465}, pages = {501}, year = {2017}, abstract = {Since the first time discovered that ultrasound can influence neuronal activity - more than half a century ago - a lot of progress has been made in this field. The possibilities of ultrasound for neuromodulation have been demonstrated in many experiments such as in vivo stimulation of rodent brain or of human cochlear, Further, in vitro experiments with hippocampal slices and other cell types have been performed as well.}, subject = {Neuronales Netz}, language = {en} } @misc{CibaMayerThielemann2019, author = {Ciba, Manuel and Mayer, Margot and Thielemann, Christiane}, title = {Experimental setup to investigate the effect of psychedelics on in vitro neuronal networks}, doi = {10.6084/m9.figshare.11980434.v1}, year = {2019}, abstract = {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.}, subject = {Neuronales Netz}, language = {en} } @article{NickDausBesteletal.2013, author = {Nick, Christoph and Daus, Andreas and Bestel, Robert and Goldhammer, Michael and Steger, Frederik and Thielemann, Christiane}, title = {DrCell - a software tool for the analysis of cell signals recorded with extracellular microelectrodes}, series = {Signal processing: an international journal (SPIJ)}, volume = {7}, journal = {Signal processing: an international journal (SPIJ)}, number = {2}, pages = {96 -- 109}, year = {2013}, subject = {Mikroelektrode}, language = {de} }