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Gotowe bibliografie tematyczne / Neuronal network activity

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Gotowa bibliografia na temat „Neuronal network activity”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Neuronal network activity"

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Shimono, Masanori, and John M. Beggs. "Mesoscopic neuronal activity and neuronal network architecture." Neuroscience Research 71 (September 2011): e304. http://dx.doi.org/10.1016/j.neures.2011.07.1326.

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Дегтерев, А. А., and A. A. Degterev. "Simulation of Spontaneous Activity in Neuronal Cultures with Long-Term Plasticity." Mathematical Biology and Bioinformatics 10, no. 1 (2015): 234–44. http://dx.doi.org/10.17537/2015.10.234.

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Existence of spontaneous population bursts is a widely studied phenomenon observed in neuronal cultures in vitro. Recent models of neuronal cultures network activity consist of a number of burst generating mechanisms such as synaptic noise and presence of pacemaker neurons in the network. In the previous simulations of bursting in neuronal cultures synaptic weights change in accordance with the rule of short-term plasticity whereas the long-term values of them, and hence the network structure, remain unchanged. In this paper we reproduce neuronal network models with static synapses, and then i

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Fletcher, Jack McKay, and Thomas Wennekers. "From Structure to Activity: Using Centrality Measures to Predict Neuronal Activity." International Journal of Neural Systems 28, no. 02 (2018): 1750013. http://dx.doi.org/10.1142/s0129065717500137.

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It is clear that the topological structure of a neural network somehow determines the activity of the neurons within it. In the present work, we ask to what extent it is possible to examine the structural features of a network and learn something about its activity? Specifically, we consider how the centrality (the importance of a node in a network) of a neuron correlates with its firing rate. To investigate, we apply an array of centrality measures, including In-Degree, Closeness, Betweenness, Eigenvector, Katz, PageRank, Hyperlink-Induced Topic Search (HITS) and NeuronRank to Leaky-Integrate

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Maier, N., A. Draguhn, D. Schmitz, and M. Both. "Fast network oscillations in the hippocampus." e-Neuroforum 19, no. 1 (2013): 1–10. http://dx.doi.org/10.1007/s13295-013-0038-0.

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AbstractNeuronal networks often express coherent oscillatory activity. These rhythms can provide a temporal reference for the activity of single neurons and allow the formation of spatiotemporal activity patterns with a defined phase relationship of action potentials. In a single brain nucleus, oscillations at different frequencies might be simultaneously generated, but isolated rhythms might also be characteristic for specific functional brain states. During the last two decades the mammalian hippocampus has become an important model system for the study of neuronal network oscillations

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van Drongelen, Wim. "Modeling Neural Activity." ISRN Biomathematics 2013 (March 7, 2013): 1–37. http://dx.doi.org/10.1155/2013/871472.

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This paper provides an overview of different types of models for studying activity of nerve cells and their networks with a special emphasis on neural oscillations. One part describes the neuronal models based on the Hodgkin and Huxley formalism first described in the 1950s. It is discussed how further simplifications of this formalism enable mathematical analysis of the process of neural excitability. The focus of the paper’s second component is on network activity. Understanding network function is one of the important frontiers remaining in neuroscience. At present, experimental techniques

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Kudoh, Suguru N., Chie Hosokawa, Ai Kiyohara, Takahisa Taguchi, and Isao Hayashi. "Biomodeling System - Interaction Between Living Neuronal Networks and the Outer World." Journal of Robotics and Mechatronics 19, no. 5 (2007): 592–600. http://dx.doi.org/10.20965/jrm.2007.p0592.

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Rat hippocampal neurons reorganized into complex networks in a culture dish with 64 planar microelectrodes and the electrical activity of neurons were recorded from individual sites. Multi-site recording system for extracellular action potentials was used for recording the activity of living neuronal networks and for applying input from the outer world to the network. The living neuronal network was able to distinguish among patterns of evoked action potentials based on different input, suggesting that the living neuronal network can express several pattern independently, meaning that it has f

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Gleichmann, Marc, and Mark P. Mattson. "Alzheimer’s Disease and Neuronal Network Activity." NeuroMolecular Medicine 12, no. 1 (2009): 44–47. http://dx.doi.org/10.1007/s12017-009-8100-3.

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Araque, Alfonso, and Marta Navarrete. "Glial cells in neuronal network function." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1551 (2010): 2375–81. http://dx.doi.org/10.1098/rstb.2009.0313.

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Numerous evidence demonstrates that astrocytes, a type of glial cell, are integral functional elements of the synapses, responding to neuronal activity and regulating synaptic transmission and plasticity. Consequently, they are actively involved in the processing, transfer and storage of information by the nervous system, which challenges the accepted paradigm that brain function results exclusively from neuronal network activity, and suggests that nervous system function actually arises from the activity of neuron–glia networks. Most of our knowledge of the properties and physiological conseq

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Ivenshitz, Miriam, and Menahem Segal. "Neuronal Density Determines Network Connectivity and Spontaneous Activity in Cultured Hippocampus." Journal of Neurophysiology 104, no. 2 (2010): 1052–60. http://dx.doi.org/10.1152/jn.00914.2009.

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The effects of neuronal density on morphological and functional attributes of the evolving networks were studied in cultured dissociated hippocampal neurons. Plating at different densities affected connectivity among the neurons, such that sparse networks exhibited stronger synaptic connections between pairs of recorded neurons. This was associated with different patterns of spontaneous network activity with enhanced burst size but reduced burst frequency in the sparse cultures. Neuronal density also affected the morphology of the dendrites and spines of these neurons, such that sparse neurons

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Illes, Sebastian, Martin Jakab, Felix Beyer, et al. "Intrinsically Active and Pacemaker Neurons in Pluripotent Stem Cell-Derived Neuronal Populations." Stem Cell Reports 2, no. 3 (2014): 323–36. https://doi.org/10.1016/j.stemcr.2014.01.006.

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Neurons generated from pluripotent stem cells (PSCs) self-organize into functional neuronal assemblies in vitro, generating synchronous network activities. Intriguingly, PSC-derived neuronal assemblies develop spontaneous activities that are independent of external stimulation, suggesting the presence of thus far undetected intrinsically active neurons (IANs). Here, by using mouse embryonic stem cells, we provide evidence for the existence of IANs in PSC-neuronal networks based on extracellular multielectrode array and intracellular patch-clamp recordings. IANs remain activ

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Rozprawy doktorskie na temat "Neuronal network activity"

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Balakumar, Nikhil. "A Computational Model of Neuronal Cluster Activity." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1329936494.

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Gómez, Orlandi Javier. "Noise, coherent activity and network structure in neuronal cultures." Doctoral thesis, Universitat de Barcelona, 2015. http://hdl.handle.net/10803/346925.

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In this thesis we apply a multidisciplinary approach, based on statistical physics and complex systems, to the study of neuronal dynamics. We focus on understanding, using theoretical and computational tools, how collective neuronal activity emerges in a controlled system, a neuronal culture. We show how the interplay between noise and network structure defines the emergent collective behavior of the system. We build, using theory and simulation, a framework that takes carefully describes spontaneous activity in neuronal cultures by taking into account the underlying network structure of n

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Bhavaraju, Srilaya. "Using machine learning for analysis of neuronal network activity." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129131.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020<br>Cataloged from student-submitted PDF of thesis.<br>Includes bibliographical references (pages 75-77).<br>Analyzing neuronal activity in developing neuronal networks can improve our understanding of neuronal dysfunctions underlying conditions such as Rett syndrome. Two-photon calcium imaging is used to capture neuronal network activity over time. This method produces large sets of images that are typically manually analyzed by skilled neuroscientists. Because thi

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Samson, Andrew James. "Rapid neuronal responses during spreading neurotoxic and neuroprotective network activity." Thesis, University of Dundee, 2016. https://discovery.dundee.ac.uk/en/studentTheses/8c797952-eda1-4c03-a38a-15c2679e984f.

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Glutamate is the major excitatory neurotransmitter in the mammalian central nervous system, playing critical roles in basal synaptic transmission and the molecular correlates of learning and memory, long-term potentiation and long-term depression. However, glutamate is also neurotoxic during prolonged exposure and the dysfunction of the glutamatergic system has been implicated in most neurological disorders, including stroke and epilepsy, and in certain neurodegenerative diseases, including Alzheimer’s disease. In these conditions, an increased concentration of extracellular glutamate causes a

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Prokic, Emma. "Modulation of neuronal network activity in the primary motor cortex." Thesis, Aston University, 2012. http://publications.aston.ac.uk/16496/.

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In the present study I investigated the mechanisms of modulation of neuronal network activity in rat primary motor cortex using pharmacological manipulations employing the in vitro brain slice technique. Preparation of the brain slice in sucrose-based aCSF produced slices with low viability. Introducing the neuroprotectants N-acetyl-cysteine, taurine and aminoguanidine to the preparatory method saw viability of slices increase significantly. Co-application of low dose kainic acid and carbachol consistently generated beta oscillatory activity in M1. Analyses indicated that network activity in M

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Yamawaki, Naoki. "Beta frequency neuronal network activity in the primary motor cortex." Thesis, Aston University, 2009. http://publications.aston.ac.uk/15408/.

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In this study I investigated the mechanisms of neuronal network oscillatory activity in rat M1 using pharmacological manipulations and electrical stimulation protocols, employing the in vitro brain slice technique in rat and magnetoencephalography (MEG) in man. Co-application of kainic acid and carbachol generated in vitro beta oscillatory activity in all layers in M1. Analyses indicated that oscillations originated from deep layers and indicated significant involvement of GABAA receptors and gap junctions. A modulatory role of GABAB, NMDA, and dopamine receptors was also evident. Intracellula

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Calderini, Matias. "Linear Discriminant Analysis and Noise Correlations in Neuronal Activity." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39962.

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The effects of noise correlations on neuronal stimulus discrimination have been the subject of sustained debate. Both experimental and computational work suggest beneficial and detrimental contributions of noise correlations. The aim of this study is to develop an analytically tractable model of stimulus discrimination that reveals the conditions leading to improved or impaired performance from model parameters and levels of noise correlation. We begin with a mean firing rate integrator model as an approximation of underlying spiking activity in neuronal circuits. We consider two independent

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Zhou, Pengcheng. "Computational Tools for Identification and Analysis of Neuronal Population Activity." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/1015.

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Recently-developed technologies for monitoring activity in populations of neurons make it possible for the first time, in principle, to ask many basic questions in neuroscience. However, computational tools for analyzing newly available data need to be developed. The goal of this thesis is to contribute to this effort by focusing on two specific problems. First, we used a point-process regression framework to provide a methodology for statistical assessment of the link between neural spike synchrony and network-wide oscillations. In simulations, we showed that our method can recover ground-tru

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Lamanauskas, Nerijus. "Approaches to regulate neuronal network activity of hypoglossal motoneurons: nAChR agonists and riluzole." Doctoral thesis, SISSA, 2007. http://hdl.handle.net/20.500.11767/4675.

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Mammalian brainstem nuclei control vital functions of the body via the III-XII cranial nerves. The nucleus hypoglossus (XII nucleus) i1mervates the tongue musculature and, therefore, regulates several motor behaviors, including mastication, swallowing, sucking, and speech and is involved in respiration. These motor commands are generated by hypoglossal motoneuron (HM) network activity, which employs mainly glutamatergic nemotransmission. Neuronal network outputs are modulated by various factors, such as nicotinic acetylcholine receptors (nAChRs), persistent inward currents (PICs) and amb

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Marissal, Thomas. "Une approche développementale de l' hétérogénéité fonctionnelle des neurones pyramidaux de CA3." Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM4001/document.

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Les neurones pyramidaux de la région CA3 de l'hippocampe présentent une diversité morphologique, physiologique, biochimique, mais aussi fonctionnelle. Une partie des caractéristiques des neurones étant acquise pendant le développement, nous avons formulé l'hypothèse que la diversité morpho-fonctionnelle des neurones pyramidaux serait déterminée aux stades embryonnaires. Pour tester cette hypothèse, nous avons utilisé des souris transgéniques pour lesquelles l'expression d'un marqueur fluorescent (GFP) est conditionnée par la date de neurogenèse des neurones glutamatergiques. Nous avons enregis

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Książki na temat "Neuronal network activity"

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Paquelet, Grace Elizabeth. Single-cell activity and network properties of dorsal raphe serotonin neurons during emotional behaviors. [publisher not identified], 2022.

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Takao, Kumazawa, Kruger Lawrence, and Mizumura Kazue, eds. The polymodal receptor: A gateway to pathological pain. Elsevier, 1996.

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McDonnell, Mark D., Joshua H. Goldwyn, and Benjamin Lindner, eds. Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity. Frontiers Media SA, 2016. http://dx.doi.org/10.3389/978-2-88919-884-9.

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Rosenbaum, Robert, Tatjana Tchumatchenko, and Ruben Moreno-Bote, eds. Correlated neuronal activity and its relationship to coding, dynamics and network architecture. Frontiers SA Media, 2014. http://dx.doi.org/10.3389/978-2-88919-357-8.

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Papanicolaou, Andrew C. The Default Mode and Other Resting State Networks. Edited by Andrew C. Papanicolaou. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.003.

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Brain activity during rest, as measured and imaged mainly by fMRI, appears to be due to a number of simultaneously active neuronal networks. The network identified first is the default mode network, which has been used as a marker of conscious awareness in patients with compromised consciousness. In this chapter, the methods of deriving this and other resting networks are outlined, the reliability of each network is assessed, and the question of the functional significance of the default mode network including its relevance to the theory of mind and morality is addressed through a critical app

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Jef ferys, John G. R. Cortical activity: single cell, cell assemblages, and networks. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199688395.003.0004.

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This chapter describes how the activity of neurons produces electrical potentials that can be recorded at the levels of single cells, small groups of neurons, and larger neuronal networks. It outlines how the movement of ions across neuronal membranes produces action potentials and synaptic potentials. It considers how the spatial arrangement of specific ion channels on the neuronal surface can produce potentials that can be recorded from the extracellular space. Finally, it outlines how the layered cellular structure of the neocortex can result in summation of signals from many neurons to be

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Draguhn, Andreas. Brain Leitmotifs: The Structure and Activity Patterns of Neuronal Networks. Springer International Publishing AG, 2024.

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Buetefisch, Cathrin M., and Leonardo G. Cohen. Use-dependent changes in TMS measures. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0018.

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Adult brains maintain the ability to reorganize throughout life. Cortical reorganization or plasticity includes modification of synaptic efficacy as well as neuronal networks that carry behavioural implications. Transcranial magnetic stimulation (TMS) allows for the study of primary motor cortex reorganization in humans. Motor-evoked potential (MEP) amplitudes change in response to practice. This article gives information about the effect of practice on TMS measures such as motor-evoked potential amplitudes, motor maps, paired-pulse measures, and behavioural measures. These changes may be acco

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Papanicolaou, Andrew C. Overview of Basic Concepts. Edited by Andrew C. Papanicolaou. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.002.

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Functional brain imaging is based on a set of assumptions. A clear appreciation of those makes it possible to form reasonable opinions regarding the potential range of application and the limits of the functional neuroimaging procedures. Exposition of these basic facts and assumptions is the primary goal of this chapter. A secondary goal is the juxtaposition of the basic concepts involved in them, such as the concept of “function,” “brain mechanism,” “neuronal network,” “activity,” and “activation”; drawing, in broad outline, a description of the methods of neuroimaging, their relative spatial

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Modulation of oscillatory activity in inhibitory neuronal networks by anesthetics: The role of receptor desensitization. National Library of Canada, 2001.

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Części książek na temat "Neuronal network activity"

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McSweeney, Danny, Jay English, Ethan Howell, Fumiko Ribbe, and ChangHui Pak. "Measuring Neuronal Network Activity Using Human Induced Neuronal Cells." In Stem Cell-Based Neural Model Systems for Brain Disorders. Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3287-1_19.

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Ramakers, G. J. A., F. Kloosterman, P. van Hulten, J. van Pelt, and M. A. Corner. "Activity-dependent regulation of neuronal network excitability." In Neural Circuits and Networks. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58955-3_11.

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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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Pankratova, Evgeniya V. "Environmentally Induced Chaos and Amplitude Death in Neuronal Network Activity." In NODYCON Conference Proceedings Series. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81170-9_46.

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Abásolo, D., L. González, and Y. Chen. "Complexity of Epileptiform Activity in a Neuronal Network and Pharmacological Intervention." In IFMBE Proceedings. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-00846-2_142.

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Biffi, E., G. Regalia, A. Menegon, G. Ferrigno, and A. Pedrocchi. "The Influence of Neuronal Density on Network Activity: A Methodological Study." In IFMBE Proceedings. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-00846-2_421.

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Genocchi, Barbara, Kerstin Lenk, and Jari Hyttinen. "Influence of Astrocytic Gap Junction Coupling on in Silico Neuronal Network Activity." In IFMBE Proceedings. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31635-8_58.

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Schirner, Michael, and Petra Ritter. "Integrating EEG–fMRI Through Brain Simulation." In EEG - fMRI. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07121-8_30.

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AbstractEEG and fMRI are thought to measure partly distinct, partly overlapping, and certainly incomplete aspects of neuronal activity. Brain network models (BNMs) are used to simulate neuronal activity, like the dynamics of postsynaptic potentials, or spike-firing activity, and may conjointly predict both, EEG and fMRI, and therefore allow for the integration and the analysis of the two signals. The usual motivation for EEG–fMRI integration is to use both techniques in a complementary fashion by combining their strengths, while ameliorating their weaknesses. For instance, EEG measures electri

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Rigas, Pavlos, Leonidas J. Leontiadis, Panagiotis Tsakanikas, and Irini Skaliora. "Spontaneous Neuronal Network Persistent Activity in the Neocortex: A(n) (Endo)phenotype of Brain (Patho)physiology." In Advances in Experimental Medicine and Biology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56246-9_19.

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Matsubara, Seiichi, Hatsuo Hayashi, and Kazuki Nakada. "Spatiotemporal Synchronization of Neuronal Activity in a Hippocampal CA3 Network Model Including the O-LM Cell." In Brain-Inspired Information Technology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-04025-2_20.

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Streszczenia konferencji na temat "Neuronal network activity"

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Pospelov, Nikita, Olga Rogozhnikova, Viktor Plusnin, et al. "Effective dimensionality of neuronal population activity in hippocampus correlates with behavior." In 2024 8th Scientific School Dynamics of Complex Networks and their Applications (DCNA). IEEE, 2024. http://dx.doi.org/10.1109/dcna63495.2024.10718588.

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Asada, Hiroki, and Suguru N. Kudoh. "Deep Learning-Based Analysis of Neuronal Signal Streams: Estimating the Activity Range of Cultured Neuronal Networks in Consecutive Stimulus Inputs Using CNN." In 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS). IEEE, 2024. https://doi.org/10.1109/scisisis61014.2024.10759936.

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Sakuta, Hiromichi, and Suguru N. Kudoh. "An Attempt at Autonomous Identification of Neuronal Activity Patterns in Dissociated Neuronal Network, by Multi-layered Artificial Neuronal Network." In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2018. http://dx.doi.org/10.1109/smc.2018.00306.

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Minoshima, Wataru, Taketo Yasuda, Kyoko Masui, and Chie Hosokawa. "Network-wide neuronal activity under optical trapping of synaptic vesicles in cultured neurons." In Optical Manipulation and Structured Materials Conference, edited by Takashige Omatsu, Síle N. Chormaic, and Kishan Dholakia. SPIE, 2023. http://dx.doi.org/10.1117/12.3008362.

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Luxem, Kevin, Falko Fuhrmann, Stefan Remy, and Pavol Bauer. "Hierarchical network analysis of behavior and neuronal population activity." In 2019 Conference on Cognitive Computational Neuroscience. Cognitive Computational Neuroscience, 2019. http://dx.doi.org/10.32470/ccn.2019.1261-0.

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Kudoh, Suguru, Keisuke Izutani, and Hidekatsu Ito. "The Stability and Periodicity of neuronal network activity pattern repertory." In 8th International Conference on Body Area Networks. ACM, 2013. http://dx.doi.org/10.4108/icst.bodynets.2013.253626.

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Suemitsu, A., and M. Morita. "Neural Network Model of Context-Dependent Neuronal Activity in Inferotemporal Cortex." In The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE, 2006. http://dx.doi.org/10.1109/ijcnn.2006.246694.

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Hayashi, Isao, and Suguru N. Kudoh. "Description of activity of living neuronal network by fuzzy bio-indicator." In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. http://dx.doi.org/10.1109/fuzz-ieee.2014.6891880.

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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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Zeringue, Henry C. "Microtechnologies for Neurobiology." In ASME 2010 First Global Congress on NanoEngineering for Medicine and Biology. ASMEDC, 2010. http://dx.doi.org/10.1115/nemb2010-13341.

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Oscillatory activity in cortical networks is thought to provide the foundation for many high-level processes including working memory and attention. It has been shown that spatial information propagation delay and connectivity density can determine the innate properties of local network activity. The initial formation of neuronal networks in the central nervous system occurs due to the interaction of the genetic programming of the cells and the presentation of external molecular cues. The activity-driven refinement that occurs later, giving rise to the highly complex networks within the brain,

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