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  • 1
    Keywords: Accretion (Astrophysics)-Congresses. ; Astrophysics-Congresses. ; Electronic books.
    Description / Table of Contents: Proceedings of the NATO Advanced Research Workshop on `Theory of Accretion Disks - 2', Garching, Germany, March 22-26, 1993.
    Type of Medium: Online Resource
    Pages: 1 online resource (417 pages)
    Edition: 1st ed.
    ISBN: 9789401108584
    Series Statement: Nato Science Series C: Series ; v.417
    DDC: 523.01
    Language: English
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  • 2
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    Keywords: Neuroplasticity. ; Electronic books.
    Description / Table of Contents: Aimed at courses in computational neuroscience, theoretical biology, biophysics, or neural networks, this 2002 text will suit students of physics, mathematics, or computer science, as well as biologists who are interested in mathematical modelling. A large number of worked examples are embedded in the profusely-illustrated text.
    Type of Medium: Online Resource
    Pages: 1 online resource (496 pages)
    Edition: 1st ed.
    ISBN: 9780511203756
    DDC: 573.8536
    Language: English
    Note: Cover -- Half-title -- Title -- Copyright -- Contents -- Preface -- Acknowledgments -- 1 Introduction -- 1.1 Elements of neuronal systems -- 1.1.1 The ideal spiking neuron -- 1.1.2 Spike trains -- 1.1.3 Synapses -- 1.2 Elements of neuronal dynamics -- 1.2.1 Postsynaptic potentials -- 1.2.2 Firing threshold and action potential -- 1.3 A phenomenological neuron model -- 1.3.1 Definition of the model SRM -- 1.3.2 Limitations of the model -- (i) Adaptation, bursting, and inhibitory rebound -- (ii) Saturating excitation and shunting inhibition -- 1.4 The problem of neuronal coding -- 1.5 Rate codes -- 1.5.1 Rate as a spike count (average over time) -- 1.5.2 Rate as a spike density (average over several runs) -- 1.5.3 Rate as a population activity (average over several neurons) -- 1.6 Spike codes -- 1.6.1 Time-to-first-spike -- 1.6.2 Phase -- 1.6.3 Correlations and synchrony -- 1.6.4 Stimulus reconstruction and reverse correlation -- 1.7 Discussion: spikes or rates? -- 1.8 Summary -- Literature -- Part one Single neuron models -- 2 Detailed neuron models -- 2.1 Equilibrium potential -- 2.1.1 Nernst potential -- 2.1.2 Reversal potential -- 2.2 Hodgkin-Huxley model -- 2.2.1 Definition of the model -- 2.2.2 Dynamics -- 2.3 The zoo of ion channels -- 2.3.1 Sodium channels -- 2.3.2 Potassium channels -- 2.3.3 Low-threshold calcium current -- 2.3.4 High-threshold calcium current and calcium-activated potassium channels -- 2.3.5 Calcium dynamics -- 2.4 Synapses -- 2.4.1 Inhibitory synapses -- 2.4.2 Excitatory synapses -- 2.5 Spatial structure: the dendritic tree -- 2.5.1 Derivation of the cable equation -- 2.5.2 Green's function (*) -- 2.5.3 Nonlinear extensions to the cable equation -- 2.6 Compartmental models -- 2.7 Summary -- Literature -- 3 Two-dimensional neuron models -- 3.1 Reduction to two dimensions -- 3.1.1 General approach. , 3.1.2 Mathematical steps (*) -- 3.2 Phase plane analysis -- 3.2.1 Nullclines -- 3.2.2 Stability of fixed points -- 3.2.3 Limit cycles -- Hopf bifurcation (*) -- 3.2.4 Type I and type II models -- 3.3 Threshold and excitability -- 3.3.1 Type I models -- 3.3.2 Type II models -- 3.3.3 Separation of time scales -- Trajectory during a pulse (*) -- 3.4 Summary -- Literature -- 4 Formal spiking neuron models -- 4.1 Integrate-and-fire model -- 4.1.1 Leaky integrate-and-fire model -- 4.1.2 Nonlinear integrate-and-fire model -- Rescaling and standard forms (*) -- 4.1.3 Stimulation by synaptic currents -- 4.2 Spik Response Model (SRM) -- 4.2.1 Definition of the SRM -- Interpretation -- Total postsynaptic potential -- Refractoriness -- Removing the dynamic threshold -- 4.2.2 Mapping the integrate-and-fire model to the SRM -- 4.2.3 Simplied model SRM -- Relation to the SRM -- Dynamic threshold interpretation -- Relation to the integrate-and-fire model -- Relation between the kernels Epsilon and Episilon (*) -- 4.3 From detailed models to formal spiking neurons -- 4.3.1 Reduction of the Hodgkin-Huxley model -- The Eta kernel -- The Kappa kernel -- The threshold Theta -- Input scenarios -- 4.3.2 Reduction of a cortical neuron model -- Reduction to a nonlinear integrate-and-fire model -- Reduction to a Spike Response Model -- 4.3.3 Limitations -- 4.4 Multicompartment integrate-and-fire model -- 4.4.1 Definition of the model -- 4.4.2 Relation to the model SRM -- 4.4.3 Relation to the full Spike Response Model (*) -- 4.5 Application: coding by spikes -- Time-to-first-spike -- Phase coding -- Correlation coding -- Decoding: synchronous versus asynchronous input -- 4.6 Summary -- Literature -- 5 Noise in spiking neuron models -- 5.1 Spike train variability -- 5.1.1 Are neurons noisy? -- 5.1.2 Noise sources -- 5.2 Statistics of spike trains. , 5.2.1 Input-dependent renewal systems -- 5.2.2 Interval distribution -- 5.2.3 Survivor function and hazard -- 5.2.4 Stationary renewal theory and experiments -- Mean firing rate -- Autocorrelation function -- Noise spectrum -- 5.2.5 Autocorrelation of a stationary renewal process -- 5.3 Escape noise -- 5.3.1 Escape rate and hazard function -- 5.3.2 Interval distribution and mean firing rate -- 5.4 Slow noise in the parameters -- 5.5 Diffusive noise -- 5.5.1 Stochastic spike arrival -- 5.5.2 Diffusion limit (*) -- 5.5.3 Interval distribution -- 5.6 The subthreshold regime -- 5.6.1 Sub- and superthreshold stimulation -- 5.6.2 Coefficient of variation C -- 5.7 From diffusive noise to escape noise -- 5.8 Stochastic resonance -- 5.9 Stochastic firing and rate models -- 5.9.1 Analog neurons -- 5.9.2 Stochastic rate model -- 5.9.3 Population rate model -- 5.10 Summary -- Literature -- Part two Population models -- 6 Population equations -- 6.1 Fully connected homogeneous network -- 6.2 Density equations -- 6.2.1 Integrate-and-fire neurons with stochastic spike arrival -- Continuity equation -- Diffusion approximation -- 6.2.2 Spike Response Model neurons with escape noise -- Integrating the partial differential equation (*) -- Numerical implementation (*) -- 6.2.3 Relation between the approaches -- From membrane potential densities to phase densities (*) -- From membrane potential densities to refractory densities (*) -- 6.3 Integral equations for the population activity -- 6.3.1 Assumptions -- 6.3.2 Integral equation for the dynamics -- Absolute refractoriness and the Wilson-Cowan integral equation -- Derivation of the Wilson-Cowan integral equation (*) -- Quasi-stationary dynamics (*) -- 6.4 Asynchronous firing -- 6.4.1 Stationary activity and mean firing rate -- 6.4.2 Gain function and fixed points of the activity -- 6.4.3 Low-connectivity networks. , 6.5 Interacting populations and continuum models -- 6.5.1 Several populations -- 6.5.2 Spatial continuum limit -- 6.6 Limitations -- 6.7 Summary -- Literature -- 7 Signal transmission and neuronal coding -- 7.1 Linearized population equation -- 7.1.1 Noise-free population dynamics (*) -- Linearization -- 7.1.2 Escape noise (*) -- The kernel…(x ) for escape noise (*) -- 7.1.3 Noisy reset (*) -- 7.2 Transients -- 7.2.1 Transients in a noise-free network -- 7.2.2 Transients with noise -- 7.3 Transfer function -- 7.3.1 Signal term -- 7.3.2 Signal-to-noise ratio -- 7.4 The significance of a single spike -- 7.4.1 The effect of an input spike -- 7.4.2 Reverse correlation - the significance of an output spike -- 7.5 Summary -- Literature -- 8 Oscillations and synchrony -- 8.1 Instability of the asynchronous state -- 8.2 Synchronized oscillations and locking -- 8.2.1 Locking in noise-free populations -- Derivation of the Locking Theorem (*) -- 8.2.2 Locking in SRM neurons with noisy reset (*) -- Pulse width in the presence of noise (*) -- 8.2.3 Cluster states -- 8.3 Oscillations in reverberating loops -- 8.3.1 From oscillations with spiking neurons to binary neurons -- 8.3.2 Mean field dynamics -- Purely excitatory projections -- Balanced excitation and inhibition -- 8.3.3 Microscopic dynamics -- Quantifying the information content (*) -- 8.4 Summary -- Literature -- 9 Spatially structured networks -- 9.1 Stationary patterns of neuronal activity -- 9.1.1 Homogeneous solutions -- 9.1.2 Stability of homogeneous states -- 9.1.3 "Blobs" of activity: inhomogeneous states -- 9.2 Dynamic patterns of neuronal activity -- 9.2.1 Oscillations -- 9.2.2 Traveling waves -- 9.3 Patterns of spike activity -- 9.3.1 Traveling fronts and waves (*) -- 9.3.2 Stability (*) -- 9.4 Robust transmission of temporal information -- Derivation of the spike packet transfer function (*). , 9.5 Summary -- Literature -- Part three Models of synaptic plasticity -- 10 Hebbian models -- 10.1 Synaptic plasticity -- 10.1.1 Long-term potentiation -- 10.1.2 Temporal aspects -- 10.2 Rate-based Hebbian learning -- 10.2.1 A mathematical formulation of Hebb's rule -- 10.3 Spike-time-dependent plasticity -- 10.3.1 Phenomenological model -- 10.3.2 Consolidation of synaptic efficacies -- 10.3.3 General framework (*) -- (i) Sharply peaked back propagating action potential -- (ii) No back propagating action potential -- 10.4 Detailed models of synaptic plasticity -- 10.4.1 A simple mechanistic model -- 10.4.2 A kinetic model based on NMDA receptors -- 10.4.3 A calcium-based model -- NMDA receptor as a coincidence detector -- The calcium control hypothesis -- Dynamics of the postsynaptic neuron -- Results -- 10.5 Summary -- Literature -- 11 Learning equations -- 11.1 Learning in rate models -- 11.1.1 Correlation matrix and principal components -- 11.1.2 Evolution of synaptic weights -- Self-averaging (*) -- 11.1.3 Weight normalization -- 11.1.4 Receptive field development -- Model architecture -- Plasticity -- Simulation results -- 11.2 Learning in spiking models -- 11.2.1 Learning equation -- 11.2.2 Spike-spike correlations -- 11.2.3 Relation of spike-based to rate-based learning -- Stabilization of postsynaptic rates -- 11.2.4 Static-pattern scenario -- 11.2.5 Distribution of synaptic weights -- 11.3 Summary -- Literature -- 12 Plasticity and coding -- 12.1 Learning to be fast -- 12.2 Learning to be precise -- 12.2.1 The model -- 12.2.2 Firing time distribution -- 12.2.3 Stationary synaptic weights -- 12.2.4 The role of the firing threshold -- 12.3 Sequence learning -- 12.4 Subtraction of expectations -- 12.4.1 Electro-sensory system of Mormoryd electric fish -- 12.4.2 Sensory image cancellation -- Neuron model -- Synaptic plasticity -- Results. , 12.5 Transmission of temporal codes.
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  • 3
    Online Resource
    Online Resource
    Karlsruhe : Univ., Fak. für Informatik
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: 28 p. = 246541 b, text
    Edition: [Electronic ed.]
    Series Statement: Interner Bericht / Universität Karlsruhe, Fakultät für Informatik 97,25
    Language: English
    Note: nIndex
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  • 4
    Online Resource
    Online Resource
    Karlsruhe : Univ., Fak. für Informatik
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: Online Ressource, 32. = 317 Kb., text
    Edition: [Elektronische Ressource]
    Language: English
    Note: nIndex p. 32. - Differences between the printed and electronic version of the document are possible , Also available as printed version , Systemvoraussetzungen: Acrobat reader.
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  • 5
    Type of Medium: Book
    Pages: 70 S , graph. Darst
    Series Statement: IBN-rapport 180
    Language: Dutch
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  • 6
    Online Resource
    Online Resource
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: Online-Ressource (PDF-Datei: 16 S., 689 KB) , graph. Darst.
    Series Statement: Wissenschaftlich-Technische Berichte / FZD, Forschungszentrum Dresden-Rossendorf 499
    DDC: 530
    Language: English
    Note: Auch als gedr. Ausg. vorh. - Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Systemvoraussetzungen: Acrobat reader.
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  • 7
    Online Resource
    Online Resource
    Karlsruhe : Univ., Fak. für Informatik
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: 52 p. = 246421 b, text
    Edition: [Electronic ed.]
    Series Statement: [Interner Bericht / Universität Karlsruhe, Fakultät für Informatik 95,17]
    Language: English
    Note: nIndex
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  • 8
    Keywords: Forschungsbericht ; Wasserwirtschaft ; Digitalisierung
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (66 Seiten, 4,14 MB) , Diagramme, Illustrationen
    Series Statement: Bericht / VDEh-Betriebsforschungsinstitut Nr. 3300.331
    Language: German , English
    Note: Förderkennzeichen BMBF 02WIK1476 C , Verbundnummer 01185322 , Forschungsvorhaben gefördert vom Bundesministerium für Bildung, Wissenschaft. Forschung und Technologie , Literaturverzeichnis: Seite 53 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Sprache der Kurzfassungen: Deutsch, Englisch
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  • 9
    ISSN: 1437-1596
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine , Law
    Type of Medium: Electronic Resource
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  • 10
    ISSN: 1520-6904
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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