Relevant bibliographies by topics / In vitro neural network

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'In vitro neural network'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "In vitro neural network"

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Boström, Marja, Malin Anderson, Dan Lindholm, et al. "Neural Network and "Ganglion" Formations In Vitro." Otology & Neurotology 28, no. 8 (2007): 1109–19. http://dx.doi.org/10.1097/mao.0b013e318159e710.

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Valderhaug, Vibeke Devold, Wilhelm Robert Glomm, Eugenia Mariana Sandru, Masahiro Yasuda, Axel Sandvig, and Ioanna Sandvig. "Formation of neural networks with structural and functional features consistent with small-world network topology on surface-grafted polymer particles." Royal Society Open Science 6, no. 10 (2019): 191086. http://dx.doi.org/10.1098/rsos.191086.

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In vitro electrophysiological investigation of neural activity at a network level holds tremendous potential for elucidating underlying features of brain function (and dysfunction). In standard neural network modelling systems, however, the fundamental three-dimensional (3D) character of the brain is a largely disregarded feature. This widely applied neuroscientific strategy affects several aspects of the structure–function relationships of the resulting networks, altering network connectivity and topology, ultimately reducing the translatability of the results obtained. As these model systems
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Kim, Eunhee, Sungwoong Jeon, Hyun-Kyu An, et al. "A magnetically actuated microrobot for targeted neural cell delivery and selective connection of neural networks." Science Advances 6, no. 39 (2020): eabb5696. http://dx.doi.org/10.1126/sciadv.abb5696.

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There has been a great deal of interest in the development of technologies for actively manipulating neural networks in vitro, providing natural but simplified environments in a highly reproducible manner in which to study brain function and related diseases. Platforms for these in vitro neural networks require precise and selective neural connections at the target location, with minimal external influences, and measurement of neural activity to determine how neurons communicate. Here, we report a neuron-loaded microrobot for selective connection of neural networks via precise delivery to a ga
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Valderhaug, Vibeke D., Kristine Heiney, Ola Huse Ramstad, et al. "Early functional changes associated with alpha-synuclein proteinopathy in engineered human neural networks." American Journal of Physiology-Cell Physiology 320, no. 6 (2021): C1141—C1152. http://dx.doi.org/10.1152/ajpcell.00413.2020.

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A patterned spread of proteinopathy represents a common characteristic of many neurodegenerative diseases. In Parkinson’s disease (PD), misfolded forms of α-synuclein proteins accumulate in hallmark pathological inclusions termed Lewy bodies and Lewy neurites. Such protein aggregates seem to affect selectively vulnerable neuronal populations in the substantia nigra and to propagate within interconnected neuronal networks. Research findings suggest that these proteinopathic inclusions are present at very early time points in disease development, even before clear behavioral symptoms of dysfunct
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Shen, Xuefei, Yi Yang, Shanshan Tian, Yu Zhao, and Tao Chen. "Microfluidic array chip based on excimer laser processing technology for the construction of in vitro graphical neuronal network." Journal of Bioactive and Compatible Polymers 35, no. 3 (2020): 228–39. http://dx.doi.org/10.1177/0883911520918395.

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To construct a graphical neural network in vitro and explore the morphological effects of neural network structural changes on neurons, this study aimed to introduce a method for fabricating microfluidic array chips with different graphical structures based on 248-nm excimer laser one-step etching. Through the comparative analysis of the graphical neural network cultured on our microfluidic array chip with the one on the glass slide, the morphological effects of the neural network on the morphology of the neurons were studied. First, the design of the chip was completed according to the specif
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Singh, Satnam, Sachin Mishra, Song Juha, Manojit Pramanik, Parasuraman Padmanabhan, and Balázs Gulyás. "Nanotechnology Facilitated Cultured Neuronal Network and Its Applications." International Journal of Molecular Sciences 22, no. 11 (2021): 5552. http://dx.doi.org/10.3390/ijms22115552.

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The development of a biomimetic neuronal network from neural cells is a big challenge for researchers. Recent advances in nanotechnology, on the other hand, have enabled unprecedented tools and techniques for guiding and directing neural stem cell proliferation and differentiation in vitro to construct an in vivo-like neuronal network. Nanotechnology allows control over neural stem cells by means of scaffolds that guide neurons to reform synaptic networks in suitable directions in 3D architecture, surface modification/nanopatterning to decide cell fate and stimulate/record signals from neurons
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Rutten, W. L. C., T. G. Ruardij, E. Marani, and B. H. Roelofsen. "Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity." Applied Bionics and Biomechanics 3, no. 1 (2006): 1–7. http://dx.doi.org/10.1155/2006/251713.

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One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA) on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island”) of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from thein vivosystem, thus allowing for an effective and selective neuron–electrode interface. As a secondary pu
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Peña-Ortega, Fernando. "Amyloid Beta-Protein and Neural Network Dysfunction." Journal of Neurodegenerative Diseases 2013 (January 30, 2013): 1–8. http://dx.doi.org/10.1155/2013/657470.

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Understanding the neural mechanisms underlying brain dysfunction induced by amyloid beta-protein (Aβ) represents one of the major challenges for Alzheimer’s disease (AD) research. The most evident symptom of AD is a severe decline in cognition. Cognitive processes, as any other brain function, arise from the activity of specific cell assemblies of interconnected neurons that generate neural network dynamics based on their intrinsic and synaptic properties. Thus, the origin of Aβ-induced cognitive dysfunction, and possibly AD-related cognitive decline, must be found in specific alterations in p
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Pigareva, Yana, Arseniy Gladkov, Vladimir Kolpakov, et al. "Experimental Platform to Study Spiking Pattern Propagation in Modular Networks In Vitro." Brain Sciences 11, no. 6 (2021): 717. http://dx.doi.org/10.3390/brainsci11060717.

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The structured organization of connectivity in neural networks is associated with highly efficient information propagation and processing in the brain, in contrast with disordered homogeneous network architectures. Using microfluidic methods, we engineered modular networks of cultures using dissociated cells with unidirectional synaptic connections formed by asymmetric microchannels. The complexity of the microchannel geometry defined the strength of the synaptic connectivity and the properties of spiking activity propagation. In this study, we developed an experimental platform to study the e
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Heider, Dominik, Jessica Appelmann, Tuygun Bayro, et al. "A Computational Approach for the Identification of Small GTPases Based on Preprocessed Amino Acid Sequences." Technology in Cancer Research & Treatment 8, no. 5 (2009): 333–41. http://dx.doi.org/10.1177/153303460900800503.

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The prediction of essential biological features based on a given protein sequence is a challenging task in computational biology. To limit the amount of in vitro verification, the prediction of essential biological activities gives the opportunity to detect so far unknown sequences with similar properties. Besides the application within the identification of proteins being involved in tumorigenesis, other functional classes of proteins can be predicted. The prediction accuracy depends on the selected machine learning approach and even more on the composition of the descriptor set used. A compu
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Dissertations / Theses on the topic "In vitro neural network"

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Xia, Yun. "Neuronal Network Analyses in vitro of Acute Individual and Combined Responses to Fluoxetine and Ethanol." Thesis, University of North Texas, 2002. https://digital.library.unt.edu/ark:/67531/metadc3191/.

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Embryonic murine neuronal networks cultured on microelectrode arrays were used to quantify acute electrophysiological effects of fluoxetine and ethanol. Spontaneously active frontal cortex cultures showed highly repeatable, dose-dependent sensitivities to both compounds. Cultures began to respond to fluoxetine at 3 µM and were shut off at 10-16 µM. EC50s mean ± S.D. for spike and burst rates were 4.1 ± 1.5 µM and 4.5 ± 1.1 µM (n=14). The fluoxetine inhibition was reversible and without effect on action potential wave shapes. Ethanol showed initial inhibition at 20 mM, with spike and burst ra
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Ortman, Robert L. "Sensory input encoding and readout methods for in vitro living neuronal networks." Thesis, Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44856.

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Establishing and maintaining successful communication stands as a critical prerequisite for achieving the goals of inducing and studying advanced computation in small-scale living neuronal networks. The following work establishes a novel and effective method for communicating arbitrary "sensory" input information to cultures of living neurons, living neuronal networks (LNNs), consisting of approximately 20 000 rat cortical neurons plated on microelectrode arrays (MEAs) containing 60 electrodes. The sensory coding algorithm determines a set of effective codes (symbols), comprised of different
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Corradini, Daniele. "Statistical characterization of cultured neural networks activity recorded via MEA." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20380/.

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In questa tesi si sono analizzate le attività di neuroni in coltura accoppiati con un Multi-Electrode Array (MEA) a 60 canali. Le reti neurali in vitro sono influenzate da diversi fattori, come la densità di coltura, l'età e l'animale di provenienza dei neuroni. Lo scopo di questa tesi è quello di caratterizzare questa variabilità attraverso varie analisi statistiche. Utilizzando un software sviluppato in Python si sono estratte 40 misure per descrivere un ampio spettro delle attività delle cellule, come lo spiking e i network bursts. Sono state caratterizzate le distribuzioni statistich
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Ham, Michael I. "Exploration of hierarchical leadership and connectivity in neural networks in vitro." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc9775/.

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Living neural networks are capable of processing information much faster than a modern computer, despite running at significantly lower clock speeds. Therefore, understanding the mechanisms neural networks utilize is an issue of substantial importance. Neuronal interaction dynamics were studied using histiotypic networks growing on microelectrode arrays in vitro. Hierarchical relationships were explored using bursting (when many neurons fire in a short time frame) dynamics, pairwise neuronal activation, and information theoretic measures. Together, these methods reveal that global network act
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Miller, Benjamin R. "Concentration-dependent Effects of D-Methylphenidate on Frontal Cortex and Spinal Cord Networks in vitro." Thesis, University of North Texas, 2004. https://digital.library.unt.edu/ark:/67531/metadc4689/.

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Spontaneously active frontal cortex and spinal cord networks grown on microelectrode arrays were used to study effects of D-methylphenidate. These central nervous system tissues have relatively low concentrations of dopaminergic and noradrenergic neurons compared to the richly populated loci, yet exhibit similar neurophysiological responses to methylphenidate. The spontaneous spike activity of both tissues was inhibited in a concentration-dependent manner by serial additions of 1-500 µM methylphenidate. Methylphenidate is non-toxic as spike inhibition was recovered following washes. The averag
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Dreosti, Elena. "Imaging synaptic activity of neuronal networks in vitro and in vivo using a fluorescent calcium indicator." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608931.

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Suri, Nikita. "Superbursts: Investigation of Abnormal Paroxysmal Bursting Activity in Nerve Cell Networks In Vitro." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1157655/.

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Superbursts (SBs) are large, seemingly spontaneous activity fluctuations often encountered in high density neural networks in vitro. Little effort has been put forth to define and analyze SBs which are paroxysmal bursting discharges. Through qualitative and quantitative means, I have described specific occurrences of superbursting activity. A complex of paroxysmal bursting has been termed a "superburst episode," and each individual SB is a "superburst event" which is comprises a fine burst structure. Quantitative calculations (employing overall spike summations and coefficient of variation (CV
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Ham, Michael I. Gross Guenter W. "Exploration of hierarchical leadership and connectivity in neural networks in vitro." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9775.

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Pardo-Figuerez, Maria M. "Designing neuronal networks with chemically modified substrates : an improved approach to conventional in vitro neural systems." Thesis, Loughborough University, 2018. https://dspace.lboro.ac.uk/2134/27941.

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Highly organised structures have been well-known to be part of the complex neuronal network presented in the nervous system, where thousands of neuronal connections are arranged to give rise to critical physiological functions. Conventional in vitro culture methods are useful to represent simplistic neuronal behaviour, however, the lack of such organisation results in random and uncontrolled neurite spreading, leading to a lack of cell directionality and in turn, resulting in inaccurate neuronal in vitro models. Neurons are highly specialised cells, known to be greatly dependent on interaction
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Jaber, Fadi. "Action potential recoording and processing from geometrically defined in-vitro neural networks." Thesis, University of Surrey, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.502671.

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Books on the topic "In vitro neural network"

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Reska, Anna. Elektrophysiologische Charakterisierung neuronaler Netzwerke von Insekten in vitro. Forschungszentrum Jülich, 2006.

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Frega, Monica. Neuronal Network Dynamics in 2D and 3D in vitro Neuroengineered Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30237-9.

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Chiappalone, Michela, Valentina Pasquale, and Monica Frega, eds. In Vitro Neuronal Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11135-9.

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Bharath, Ramachandran. Neural network computing. Windcrest/McGraw-Hill, 1994.

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Neural network principles. Prentice Hall, 1994.

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B, Demuth Howard, and Beale Mark H, eds. Neural network design. PWS Pub., 1996.

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Taylor, J. G., E. R. Caianiello, R. M. J. Cotterill, and J. W. Clark, eds. Neural Network Dynamics. Springer London, 1992. http://dx.doi.org/10.1007/978-1-4471-2001-8.

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Taylor, J. G., ed. Neural Network Applications. Springer London, 1992. http://dx.doi.org/10.1007/978-1-4471-2003-2.

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De Wilde, Philippe. Neural Network Models. Springer London, 1997. http://dx.doi.org/10.1007/978-1-84628-614-8.

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Harvey, Robert L. Neural network principles. Prentice-Hall International, 1994.

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Book chapters on the topic "In vitro neural network"

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Hettiarachchi, Imali T., Asim Bhatti, Paul A. Adlard, and Saeid Nahavandi. "Multivariate Autoregressive-based Neuronal Network Flow Analysis for In-vitro Recorded Bursts." In Neural Information Processing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26561-2_39.

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Hussain, Ajaz S. "Artificial Neural Network Based in Vitro-in Vivo Correlations." In Advances in Experimental Medicine and Biology. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4684-6036-0_12.

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Ulinski, Philip S., Linda Larson-Prior, and N. Traverse Slater. "Cellular and Network Determinants of Visual Motion Properties in Cortical Neurons: Studies with an In Vitro Preparation of Visual Cortex." In Neural Systems: Analysis and Modeling. Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-3560-7_16.

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Dowell, James A., Ajaz S. Hussain, Paul Stark, John Devane, and David Young. "Development of in Vitro-in Vivo Correlations Using Various Artificial Neural Network Configurations." In Advances in Experimental Medicine and Biology. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4684-6036-0_22.

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Gloveli, Tengis, Nancy Kopell, and Tamar Dugladze. "Neuronal Activity Patterns During Hippocampal Network Oscillations In Vitro." In Hippocampal Microcircuits. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-0996-1_8.

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Danter, W. R., D. Gregson, K. A. Ferguson, M. R. Danter, and J. Bend. "A Hybrid Classification Tree and Artificial Neural Network Model for Predicting the In vitro Response of the Human Immunodeficiency Virus (HIV1) to Anti-Viral Drug Therapy." In Artificial Neural Networks in Medicine and Biology. Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0513-8_35.

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Marinaro, Maria, and Silvia Scarpetta. "Modeling of Spontaneous Bursting Activity Observed in In-Vitro Neural Networks." In From Synapses to Rules. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0705-5_11.

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Uchida, Kento, Shota Saito, Panca Dewi Pamungkasari, et al. "Joint Optimization of Convolutional Neural Network and Image Preprocessing Selection for Embryo Grade Prediction in In Vitro Fertilization." In Advances in Visual Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33723-0_2.

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Frega, Monica. "In Vitro Neuronal Networks." In Springer Theses. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30237-9_3.

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Derr, Torsten, Thomas Els, Michael Gyngell, and Dieter Leibfritz. "Characterisation of tumorous tissue in rat brain by in vitro magnetic resonance spectroscopy and Artificial Neural Networks." In Artificial Intelligence in Medicine. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0029479.

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Conference papers on the topic "In vitro neural network"

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Khoyratee, Farad, Stephany Mai Nishikawa, Luo Zhongyue, et al. "Biomimetic Spiking Neural Network (SNN) Systems for ‘In Vitro’ Cells Stimulation." In 2019 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2019. http://dx.doi.org/10.1109/iscas.2019.8702407.

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Schmidt, Stephen L., A. Alban Foulser, and Flavio Frohlich. "Brain stimulation by network resonance with weak electric fields probed by optogenetics in vitro." In 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2013. http://dx.doi.org/10.1109/ner.2013.6696151.

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Pigareva, Yana, Anton Bukatin, Victor Kazantsev, et al. "Heterogeneous Architecture of Neural Networks in Vitro with Precise Unidirectional Synaptic Connectivity." In 2019 12th International Conference on Developments in eSystems Engineering (DeSE). IEEE, 2019. http://dx.doi.org/10.1109/dese.2019.00105.

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Imfeld, K., A. Garenne, S. Martinoia, M. Koudelka-Hep, and L. Berdondini. "Motivations and APS-based solution for high-resolution extracellular recording from in-vitro neuronal networks." In 2007 3rd International IEEE/EMBS Conference on Neural Engineering. IEEE, 2007. http://dx.doi.org/10.1109/cne.2007.369652.

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Pastore, Vito Paolo, Daniele Poli, Sergio Martinoia, and Paolo Massobrio. "A new connectivity toolbox to infer topological features of in-vitro neural networks." In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7318981.

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Mateo, F., A. Medina, Eva M. Mateo, F. M. Valle-Algarra, and M. Jiménez. "Capacity of neural network models to predict deoxynivalenol build-up in barley grain contaminated in vitro with Fusarium culmorum." In Proceedings of the III International Conference on Environmental, Industrial and Applied Microbiology (BioMicroWorld2009). WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814322119_0146.

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Kudoh, Suguru N., Minori Tokuda, Ai Kiyohara, Chie Hosokawa, Takahisa Taguchi, and Isao Hayashi. "Vitroid - a robot with link between living neuronal network in vitro and robot body." In 2008 IEEE International Conference on Mechatronics and Automation (ICMA) (Formerly ICIMA). IEEE, 2008. http://dx.doi.org/10.1109/icma.2008.4798783.

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Frega, Monica, Mariateresa Tedesco, Paolo Massobrio, et al. "3D engineered neural networks coupled to Micro-Electrode Arrays: Development of an innovative in-vitro experimental model for neurophysiological studies." In 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER 2013). IEEE, 2013. http://dx.doi.org/10.1109/ner.2013.6696094.

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Ghezzi, Diego, Andrea Menegon, Alessandra Pedrocchi, Sara Mantero, Flavia Valtorta, and Giancarlo Ferrigno. "PhotoMEA: A New Step Towards Total Optical Analysis of In Vitro Neuronal Networks." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95218.

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Light stimulation of neurons is a promising approach for investigating the molecular mechanisms at the basis of neuronal physiology and plasticity. In particular, flash photolysis of caged compounds offers the unique advantage of allowing to quickly change the concentration of either intracellular or extracellular bioactive molecules, such as neurotransmitters or second messengers, for the stimulation or modulation of neuronal activity. In this field of research, we describe a simple laser-based set-up for the local activation of caged compounds. The coupling of a UV laser diode to a small-cor
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Valenza, Gaetano, Gianluca Vannucci, Enzo Wanke, and Enzo Pasquale Scilingo. "Stochastic modeling of spontaneous bursting activity to simulate neural responses of in-vitro networks on multielectrode arrays." In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2016. http://dx.doi.org/10.1109/embc.2016.7591022.

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Reports on the topic "In vitro neural network"

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Wilensky, Gregg, Narbik Manukian, Joseph Neuhaus, and Natalie Rivetti. Neural Network Studies. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada271593.

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Pollack, Randy B. Neural Network Technologies. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada262576.

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Barto, Andrew. Adaptive Neural Network Architecture. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada190114.

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McDonnell, J. R., and D. Waagen. Evolving Neural Network Connectivity. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada273134.

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McDonnell, John R., and Don Waagen. Evolving Neural Network Architecture. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada264802.

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Saavedra, Gary, and Aidan Thompson. Neural Network Interatomic Potentials. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1678825.

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Mark A. Rhode. Tampa Electric Neural Network Sootblowing. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/896962.

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Mark A. Rhode. Tampa Electric Neural Network Sootblowing. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/900191.

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Mark A. Rhode. Tampa Electric Neural Network Sootblowing. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/900192.

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Mark A. Rhode. Tampa Electric Neural Network Sootblowing. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/903064.

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