Relevant bibliographies by topics / Neuron

Contents

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

Academic literature on the topic 'Neuron'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Neuron"

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Cau, E., G. Gradwohl, C. Fode, and F. Guillemot. "Mash1 activates a cascade of bHLH regulators in olfactory neuron progenitors." Development 124, no. 8 (1997): 1611–21. http://dx.doi.org/10.1242/dev.124.8.1611.

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The lineage of olfactory neurons has been relatively well characterized at the cellular level, but the genes that regulate the proliferation and differentiation of their progenitors are currently unknown. In this study, we report the isolation of a novel murine gene, Math4C/neurogenin1, which is distantly related to the Drosophila proneural gene atonal. We show that Math4C/neurogenin1 and the basic helix-loop-helix gene Mash1 are expressed in the olfactory epithelium by different dividing progenitor populations, while another basic helix-loop-helix gene, NeuroD, is expressed at the onset of ne
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Iyoda, Eduardo Masato, Hajime Nobuhara, and Kaoru Hirota. "Translated Multiplicative Neuron: An Extended Multiplicative Neuron that can Translate Decision Surfaces." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 5 (2004): 460–68. http://dx.doi.org/10.20965/jaciii.2004.p0460.

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A multiplicative neuron model called translated multiplicative neuron (πt-neuron) is proposed. Compared to the traditional π-neuron, the πt-neuron presents 2 advantages: (1) it can generate decision surfaces centered at any point of its input space; and (2) πt-neuron has a meaningful set of adjustable parameters. Learning rules for πt-neurons are derived using the error backpropagation procedure. It is shown that the XOR and N-bit parity problems can be perfectly solved using only 1 πt-neuron, with no need for hidden neurons. The πt-neuron is also evaluated in Hwang's regression benchmark prob
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Masuda, Naoki, and Kazuyuki Aihara. "Spatiotemporal Spike Encoding of a Continuous External Signal." Neural Computation 14, no. 7 (2002): 1599–628. http://dx.doi.org/10.1162/08997660260028638.

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Interspike intervals of spikes emitted from an integrator neuron model of sensory neurons can encode input information represented as a continuous signal from a deterministic system. If a real brain uses spike timing as a means of information processing, other neurons receiving spatiotemporal spikes from such sensory neurons must also be capable of treating information included in deterministic interspike intervals. In this article, we examine functions of neurons modeling cortical neurons receiving spatiotemporal spikes from many sensory neurons. We show that such neuron models can encode sti
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Cheng, Lifang, and Hongjun Cao. "Synchronization Dynamics of Two Heterogeneous Chaotic Rulkov Neurons with Electrical Synapses." International Journal of Bifurcation and Chaos 27, no. 02 (2017): 1730009. http://dx.doi.org/10.1142/s0218127417300099.

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Two heterogeneous chaotic Rulkov neurons with electrical synapses are investigated in this paper. First, we study the ability of the second neuron to modify the dynamics of the first neuron. It is shown that when the parameters of the first neuron are located at the vicinity of the Neimark–Sacker bifurcation curves the first firing neuron can be controlled into the quiescent state when coupled with the second neuron. While the parameters of the first neuron are near the flip bifurcation curves the first firing neuron cannot be suppressed. Second, we discuss burst synchronization for two bursti
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Weaver, Adam L., and Scott L. Hooper. "Follower Neurons in Lobster (Panulirus interruptus) Pyloric Network Regulate Pacemaker Period in Complementary Ways." Journal of Neurophysiology 89, no. 3 (2003): 1327–38. http://dx.doi.org/10.1152/jn.00704.2002.

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Distributed neural networks (ones characterized by high levels of interconnectivity among network neurons) are not well understood. Increased insight into these systems can be obtained by perturbing network activity so as to study the functions of specific neurons not only in the network's “baseline” activity but across a range of network activities. We applied this technique to study cycle period control in the rhythmic pyloric network of the lobster, Panulirus interruptus. Pyloric rhythmicity is driven by an endogenous oscillator, the Anterior Burster (AB) neuron. Two network neurons feed ba
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Martella, Giuseppina. "Molecular Mechanisms of Synaptic Plasticity: Dynamic Changes in Neuron Functions." International Journal of Molecular Sciences 24, no. 16 (2023): 12567. http://dx.doi.org/10.3390/ijms241612567.

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The human brain has hundreds of billions of neurons and at least 7 million dendrites have been hypothesized to exist for each neuron, with over 100 trillion neuron–neuron, neuron–muscle, and neuron–endocrine cell synapses [...]
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Gupta, Pallavi, Nandhini Balasubramaniam, Hwan-You Chang, Fan-Gang Tseng, and Tuhin Subhra Santra. "A Single-Neuron: Current Trends and Future Prospects." Cells 9, no. 6 (2020): 1528. http://dx.doi.org/10.3390/cells9061528.

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The brain is an intricate network with complex organizational principles facilitating a concerted communication between single-neurons, distinct neuron populations, and remote brain areas. The communication, technically referred to as connectivity, between single-neurons, is the center of many investigations aimed at elucidating pathophysiology, anatomical differences, and structural and functional features. In comparison with bulk analysis, single-neuron analysis can provide precise information about neurons or even sub-neuron level electrophysiology, anatomical differences, pathophysiology,
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Quinlan, E. M., K. Gregory, and A. D. Murphy. "An identified glutamatergic interneuron patterns feeding motor activity via both excitation and inhibition." Journal of Neurophysiology 73, no. 3 (1995): 945–56. http://dx.doi.org/10.1152/jn.1995.73.3.945.

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1. Previously we demonstrated that glutamate is an important neurotransmitter in the CNS of Helisoma. Exogenous glutamate applied to the buccal ganglia mimicked both the excitatory and inhibitory effects of subunit 2 (S2) of the tripartite central pattern generator (CPG) on S2 postsynaptic motor neurons. Here we identify buccal interneuron B2 as an S2 interneuron by utilizing a combination of electrophysiology, pharmacology, and intracellular staining. In addition, neurons that were electrophysiologically and morphologically characterized as neuron B2 demonstrated antiglutamate immunoreactivit
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Goto, Toichiro, Nahoko Kasai, Rick Lu, Roxana Filip, and Koji Sumitomo. "Scanning Electron Microscopy Observation of Interface Between Single Neurons and Conductive Surfaces." Journal of Nanoscience and Nanotechnology 16, no. 4 (2016): 3383–87. http://dx.doi.org/10.1166/jnn.2016.12311.

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Interfaces between single neurons and conductive substrates were investigated using focused ion beam (FIB) milling and subsequent scanning electron microscopy (SEM) observation. The interfaces play an important role in controlling neuronal growth when we fabricate neuron-nanostructure integrated devices. Cross sectional images of cultivated neurons obtained with an FIB/SEM dual system show the clear affinity of the neurons for the substrates. Very few neurons attached themselves to indium tin oxide (ITO) and this repulsion yielded a wide interspace at the neuron-ITO interface. A neuron-gold in
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Xing, Hong, Jennifer Ling, Meng Chen, and Jianguo G. Gu. "Chemical and Cold Sensitivity of Two Distinct Populations of TRPM8-Expressing Somatosensory Neurons." Journal of Neurophysiology 95, no. 2 (2006): 1221–30. http://dx.doi.org/10.1152/jn.01035.2005.

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The cold- and menthol-sensing TRPM8 receptor has been proposed to have both nonnociceptive and nociceptive functions. However, one puzzle is how this single type of receptor may be used by somatosensory neurons to code for two distinct sensory modalities. Using acutely dissociated rat dorsal root ganglion (DRG) neurons without culture, we show that TRPM8 receptors are expressed on two distinct classes of somatosensory neurons. One class is sensitive to menthol and features nonnociceptive neuron properties, including capsaicin-insensitive, ATP-insensitive, transient acid response, and expressio
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Dissertations / Theses on the topic "Neuron"

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Moonens, Sofie. "Mirror Neurons : The human mirror neuron system." Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-6103.

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This literature review explores human mirror neurons from several angles. First it retells mirror neuron history, from the initial discovery in the macaque monkey research through to the experiments determining if there is a human brain homologue. Then the merits of two opposing evolutionary views – mirror neurons as an adaptation or an association, here referring to an adaptation’s byproduct – are discussed. Lastly the autistic mirror neuron dysfunction hypothesis – stating that a faulty mirror neuron system is at the basis of autistic behavioral patterns – is examined for its validity but ul
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Steinbush, H. W. M. "Het neuron als bruggenbouwer "bridging disciplines by neurons" /." Maastricht : Maastricht : Instituut hersenen en gedrag ; University Library, Universiteit Maastricht [host], 1999. http://arno.unimaas.nl/show.cgi?fid=12984.

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Viñoles, Serra Mireia. "Dynamics of Two Neuron Cellular Neural Networks." Doctoral thesis, Universitat Ramon Llull, 2011. http://hdl.handle.net/10803/9154.

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Les xarxes neuronals cel·lulars altrament anomenades CNNs, són un tipus de sistema dinàmic que relaciona diferents elements que s'anomenen neurones via unes plantilles de paràmetres. Aquest sistema queda completament determinat coneixent quines són les entrades a la xarxa, les sortides i els paràmetres o pesos. En aquest treball fem un estudi exhaustiu sobre aquest tipus de xarxa en el cas més senzill on només hi intervenen dues neurones. Tot i la simplicitat del sistema, veurem que pot tenir una dinàmica molt rica. <br/><br/>Primer de tot, revisem l'estabilitat d'aquest sistema des de dos pun
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Xu, Shuxiang, University of Western Sydney, and of Informatics Science and Technology Faculty. "Neuron-adaptive neural network models and applications." THESIS_FIST_XXX_Xu_S.xml, 1999. http://handle.uws.edu.au:8081/1959.7/275.

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Artificial Neural Networks have been widely probed by worldwide researchers to cope with the problems such as function approximation and data simulation. This thesis deals with Feed-forward Neural Networks (FNN's) with a new neuron activation function called Neuron-adaptive Activation Function (NAF), and Feed-forward Higher Order Neural Networks (HONN's) with this new neuron activation function. We have designed a new neural network model, the Neuron-Adaptive Neural Network (NANN), and mathematically proved that one NANN can approximate any piecewise continuous function to any desired accuracy
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Xu, Shuxiang. "Neuron-adaptive neural network models and applications." Thesis, [Campbelltown, N.S.W. : The Author], 1999. http://handle.uws.edu.au:8081/1959.7/275.

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Artificial Neural Networks have been widely probed by worldwide researchers to cope with the problems such as function approximation and data simulation. This thesis deals with Feed-forward Neural Networks (FNN's) with a new neuron activation function called Neuron-adaptive Activation Function (NAF), and Feed-forward Higher Order Neural Networks (HONN's) with this new neuron activation function. We have designed a new neural network model, the Neuron-Adaptive Neural Network (NANN), and mathematically proved that one NANN can approximate any piecewise continuous function to any desired accuracy
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Xu, Shuxiang. "Neuron-adaptive neural network models and applications /." [Campbelltown, N.S.W. : The Author], 1999. http://library.uws.edu.au/adt-NUWS/public/adt-NUWS20030702.085320/index.html.

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Boatin, William. "Characterization of neuron models." Thesis, Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-04182005-181732/.

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Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2006.<br>Dr. Robert H. Lee, Committee Member ; Dr. Kurt Wiesenfeld, Committee Member ; Dr Robert J. Butera, Committee Member.
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Stoller, Jonathan (Jonathan M. ). "Online neuron reconstruction." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106377.

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Thesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (page 47).<br>In this thesis, I designed an algorithm that traces neurons through the images of various datasets extracted from mouse brains. The algorithm is implemented in Python and relies on
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Regehr, Wade G. Pine Jerry Rutledge David B. "Neuron-microdevice connections /." Diss., Pasadena, Calif. : California Institute of Technology, 1988. http://resolver.caltech.edu/CaltechETD:etd-11092007-084226.

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Benda, Jan. "Single neuron dynamics." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2002. http://dx.doi.org/10.18452/14684.

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Das Neuron ist das zentrale Element in der Informationsverarbeitung im Nervensystem. In dieser Arbeit werden verschiedene Aspekte der Spikegenerierung sowohl theoretisch als auch experimentell untersucht. Phasen-Rotatoren verschiedener Komplexität werden zur Vorhersage von Spikezeitpunkten vorgestellt. Die Kennlinie eines Neurons wird dabei als wichtiger Parameter für diese Modelle verwendet, damit diese leicht auf echte Neurone anwendbar sind. Die Phasenantwortkurve als ein zweiter wichtiger Aspekt der Spikedynamik wird zur Erweiterung der Modelle verwendet. Solange ein Neuron in seinem über
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Books on the topic "Neuron"

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Gerstner, Wulfram. Spiking neuron models: Single neurons, populations, plasticity. Cambridge University Press, 2002.

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Richard, Durbin, Miall Christopher, Mitchison Graeme, and King's College (University of Cambridge). Research Centre., eds. The Computing neuron. Addison-Wesley Pub. Co., 1989.

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Talbot, Kevin. Motor neuron disease. Oxford University Press, 2008.

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Krisch, Brigitte, and Rolf Mentlein, eds. The Peptidergic Neuron. Birkhäuser Basel, 1996. http://dx.doi.org/10.1007/978-3-0348-9010-6.

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Pineda, Jaime A., ed. Mirror Neuron Systems. Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-479-7.

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Leigh, P. N., and Michael Swash, eds. Motor Neuron Disease. Springer London, 1995. http://dx.doi.org/10.1007/978-1-4471-1871-8.

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Joseph, R. The Naked Neuron. Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-6008-5.

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Greenwood, Priscilla E., and Lawrence M. Ward. Stochastic Neuron Models. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26911-5.

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C, Williams A., ed. Motor neuron disease. New York, 1994.

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B, Krisch, Mentlein R, and International Symposium on Neurosecretion (12th : 1995 : Kiel, Germany), eds. The peptidergic neuron. Birkhäuser Verlag, 1996.

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Book chapters on the topic "Neuron"

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Capinera, John L., Marjorie A. Hoy, Paul W. Paré, et al. "Neuron." In Encyclopedia of Entomology. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_2203.

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Colello, Raymond J. "Neuron." In Encyclopedia of Clinical Neuropsychology. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_342.

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Bährle-Rapp, Marina. "Neuron." In Springer Lexikon Kosmetik und Körperpflege. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71095-0_6929.

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De Couck, Marijke. "Neuron." In Encyclopedia of Behavioral Medicine. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_1675.

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Tiro, Jasmin, Simon J. Craddock Lee, Steven E. Lipshultz, et al. "Neuron." In Encyclopedia of Behavioral Medicine. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1675.

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Colello, Raymond J. "Neuron." In Encyclopedia of Clinical Neuropsychology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_342-2.

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Webb, Geoffrey I., Eamonn Keogh, Risto Miikkulainen, Risto Miikkulainen, and Michele Sebag. "Neuron." In Encyclopedia of Machine Learning. Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_590.

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Miikkulainen, Risto. "Neuron." In Encyclopedia of Machine Learning and Data Science. Springer US, 2022. http://dx.doi.org/10.1007/978-1-4899-7502-7_595-2.

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Clausen, Torben, José Luis Trejo, Mark P. Mattson, et al. "Neuron." In Encyclopedia of Exercise Medicine in Health and Disease. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-540-29807-6_2756.

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Gooch, Jan W. "Neuron." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_14307.

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Conference papers on the topic "Neuron"

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Bolshakov, Denis I., Mikhail A. Mishchenko, Daniil V. Chindarev, and Valery V. Matrosov. "Recursive map neuron model." In 2024 8th Scientific School Dynamics of Complex Networks and their Applications (DCNA). IEEE, 2024. http://dx.doi.org/10.1109/dcna63495.2024.10718599.

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Cong, Shuang. "A Quantum Phase Neuron." In 2025 13th International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2025. https://doi.org/10.1109/icicip64458.2025.10898106.

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Duan, Bin, Yuzhang Shang, Dawen Cai, and Yan Yan. "Online Multispectral Neuron Tracing." In 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI). IEEE, 2025. https://doi.org/10.1109/isbi60581.2025.10981059.

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Farhat, Nabil H., and Mostafa Eldefrawy. "The bifurcating neuron." In OSA Annual Meeting. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.mk3.

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Present neural network models ignore temporal considerations, and hence synchronicity in neural networks, by representing neuron response with a transfer function relating frequency of action potentials (firing frequency) to activation potential. Models of living neuron based on the Hudgkin-Huxley model of the excitable membrane of the squid’s axon and its Fitzhugh-Nagumo approximation, exhibit much more complex and rich behavior than that described by firing frequency-activation potential models. We describe the theory, operation, and properties of an integrate-and-fire neuron which we call t
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Rohlev, Anton, Christian Radehaus, Jacques I. Pankove, R. F. Carson, and G. Borglis. "Optoelectronic Neuron." In Optical Computing. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/optcomp.1991.me5.

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In analogy to biological neurons that interact with other neurons both electrically and chemically, the optoelectronic neurons interact with other optoelectronic neurons electrically and/or optically. Like a biological neuron, the optoelectronic neuron can have multiple input and thresholding. While the chemical interaction between biological neurons can employ different neurotransmitters, the optical interaction between optoelectronic neurons can employ photons of different wavelengths.
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Howard, R. V., W. K. Chai, and H. S. Tzou. "Modal Voltages of Linear and Nonlinear Structures Using Distributed Artificial Neurons." In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-0547.

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Abstract Laminated or embedded distributed neurons on structural components serve as in-situ sensors monitoring structure’s dynamic state and health status. Thin film piezoelectric patches are perfect candidates for this purpose. A generic piezoelectric neuron concept is introduced first, followed by definitions of neural signals generated by an arbitrary neuron laminated on a generic nonlinear double-curvature elastic shell. This generic neuron theory can be applied to a large class of linear and nonlinear common geometries, e.g., spheres, cylindrical shells, plates, etc. To demonstrate the n
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Krishnamoorthy, Ashok V., Gökçe Yayla, Gary C. Marsden, and Sadik Esener. "Free-space optoelectronic neural system prototype." In OSA Annual Meeting. Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.mqq2.

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We have previously designed a freespace optoelectronic neural system1 based on the D-STOP architecture.2 The neural architecture minimizes the number of required light transmitters and provides full connectivity between neurons, flexible functionality neurons and synapses, low signal timing skew, and accurate electronic fan-in with dendritic processing capability. Neural signals are encoded by using a combination of pulse-width modulating optical neurons and pulse-amplitude modulating electronic synapses. The neural system prototype consists of a 16-node input layer, a four-neuron hidden layer
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Lee, Yun-Jhu, Mehmet Berkay On, Luis El Srouji, Li Zhang, Mahmoud Abdelghany, and S. J. Ben Yoo. "Demonstration of Neural Heterogeneity with Programmable Brain-Inspired Optoelectronic Spiking Neurons." In Optical Fiber Communication Conference. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/ofc.2024.tu3f.4.

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Neural heterogeneity enables spiking neural networks to implement complex functions with fewer neurons. We designed, simulated, and demonstrated programmable optoelectronic spiking neurons that can achieve multiple neuron characteristics based on external tuning voltages.
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Wright, John A., Svetlana Tatic-Lucic, Yu-Chong Tai, Michael P. Maher, Hannah Dvorak, and Jerome Pine. "Towards a Functional MEMS Neurowell by Physiological Experimentation." In ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-1370.

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Abstract Specificity in neuron targeting during stimulation and recording is essential in executing complex neuronal network studies. Physiological experiments have shown that young (less than one week old) cultured neurons can escape through a 0.5 μm-square hole. Through iterative physiological experimentation, a functional MEMS structure we call a canopy neurowell has been developed. Essentially a micromechanical cage, the structure consists of a well, an electrode bottom, and a nitride canopy cover with integrated micro-tunnels. It is able to physically confine, and make electrical contact
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Xu, Yeyin, and Peihua Feng. "On Periodic Firing Activities of a Hindmarsh-Rose Neuron Model With External Periodic Stimulus." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-68278.

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Abstract In the paper, periodic firing phenomenon of a Hindmarsh-Rose neuron model is explored by the discrete mapping method. The continuous nonlinear differential equations are discretized to form implicit mappings for periodic firing motions of neurons. Periodic firing and period doubling firing activities are investigated by changing the external excitation frequency. The influence of bifurcations on the periodic firing patterns is discussed. Time series membrane potential and adaptive current of such a modified Hindmarsh-Rose neuron model are presented. Fast-varying spikes and slow-varyin
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Reports on the topic "Neuron"

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Tessler, Alan R. Factors that Contribute to Neuron Survival and Neuron Growth after Injury. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada263256.

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Alltop, W. O. Neuron Requirements for Classification. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada238003.

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Bongsebandhu-phubhakdi, Saknan, and Anan Srikiatkhachorn. On-media axon branching and adhesion investigation of neurons as stimulated by modulated potentials on micro-patterned gold substrate. Faculty of Medicine, Chulalongkorn University, 2016. https://doi.org/10.58837/chula.res.2016.22.

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The main focus of this research paper is on-media axon branching and adhesion investigation of neurons as stimulated by modulated potentials on micro-patterned gold substrate. Due to the prolonged and inefficient procedures of nerve repair, it is essential that we effectively incorporate different parameters and techniques as well as investigate cell-cell and cell-substrate interactions to explore new boundaries. This could lead to more operational options for nerve regeneration. Initially, the behavior of cell growth is first observed. 3T3 and Neuro2A cells are grown according to specific pro
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Li, Nianzhen. Nitric Oxide in Astrocyte-Neuron Signaling. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/803739.

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Tarasenko, Andrii O., Yuriy V. Yakimov, and Vladimir N. Soloviev. Convolutional neural networks for image classification. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3682.

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This paper shows the theoretical basis for the creation of convolutional neural networks for image classification and their application in practice. To achieve the goal, the main types of neural networks were considered, starting from the structure of a simple neuron to the convolutional multilayer network necessary for the solution of this problem. It shows the stages of the structure of training data, the training cycle of the network, as well as calculations of errors in recognition at the stage of training and verification. At the end of the work the results of network training, calculatio
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Baudry, Michel, Theodore W. Berger, Eun Sok Kim, Charles E. McKenna, and Mark E. Thompson. Sensing of Neuron Signals Using Microelectromechanical Systems. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada414552.

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Mueller, Paul. Hardware Implementation of Neuron Nets and Synapses. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada237704.

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Carvey, Paul M. Mechanism for Prenatal LPS-Induced DA Neuron Loss. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada434851.

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Lee, Benjamin Yen Kit. Automated neuron explanation for code-trained language models. Iowa State University, 2024. http://dx.doi.org/10.31274/cc-20240624-267.

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Przedborski, Serge E. Role of Nitric Oxide in MPTP Induced Dopaminergic Neuron. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada384796.

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