Computational Neuroscience

Name: Computational Neuroscience | Trends in Research 2000
Brand: Elsevier
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Trends in Research 2000

J. M. Bower(Herausgeber*in)

Elsevier (Verlag)

1. Auflage

Erschienen am 12. Juli 2000

1164 Seiten

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Front Cover
Computational Neuroscience: Trends in Research 2000
Copyright Page
Table of Contents
Introduction
Editorial notes
Guest editorial
Part I: Subcellular
Chapter 1. Comparison of CaMKinase II activation in a dendritic spine computed with deterministic and stochastic models of the NMDA synaptic conductance
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Part II: Cellular
Chapter 2. Relating information capacity to a biophysical model for blowfly photoreceptors
Abstract
1. Introduction
2. The visual system of the fly
3. A communication channel model
4. Model details
5. Results
6. Discussion
References
Chapter 3. A single-spike model of predictive coding
Abstract
1. Introduction
2. Learning cortical representations
3. Predictive coding using volleys of single spikes
4. Conclusion
References
Chapter 4. Characterization of activity oscillations in an excitable membrane model and their potential functionality for neuronal computations
Abstract
1. Introduction
2. Description of the model
3. Results
4. Discussion
References
Chapter 5. The influence of threshold variability on the response of visual cortical neurons
Abstract
1. Introduction
2. Model
3. Results
4. Conclusion
Acknowledgements
References
Chapter 6. Characterization of the light-induced currents in Hermissenda
Abstract
1. Introduction
2. Methods
3. Results
Acknowledgements
References
Chapter 7. Interactions between slow and fast conductances in the Huber/Braun model of cold-receptor discharges
Abstract
1. Introduction
2. The Huber Braun cold-receptor model
3. Temperature characteristics of noisy and deterministic simulations
4. Interactions of slow-wave oscillations and spike-generating mechanisms
5. Conclusions
Acknowledgements
References
Chapter 8. Low correlation between random synaptic inputs impacts considerably on the output of the Hodgkin-Huxley model
Abstract
1. Introduction
2. Model
3. Results
4. Discussion
Acknowledgements
References
Chapter 9. Analysis of synchronization in the response of neurons to noisy periodic synaptic input
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion and conclusions
Acknowledgements
References
Chapter 10. Effects of presynaptic and postsynaptic resource redistribution in Hebbian weight adaptation
Abstract
1. Introduction
2. Effect of resource redistribution at different sites of the neuron
3. Discussion
4. Conclusion
References
Chapter 11. Dynamics of cortical map development in the elastic net model
Abstract
1. Introduction
2. The elastic net model of cortical mapping
3. Analysis
4. Simulations
5. Discussion
References
Chapter 12. Simulating the temporal evolution of neuronal discharge^
Abstract
1. Introduction
2. Four model Purkinje cells
3. Results
4. Conclusions
References
Chapter 13. Oscillatory behaviors in pharmacologically isolated heart interneurons from the medicinal leech
Abstract
1. Introduction
2. Results
3. Conclusions
Acknowledgements
Appendix A
References
Chapter 14. Effects of voltage trajectory on action potential voltage threshold in simulations of cat spinal motoneurons
Abstract
1. Introduction
2. Computer model
3. Results
4. Conclusion
References
Chapter 15. A combined computational and intracellular study of correlated synaptic bombardment in neocortical pyramidal neurons in vivo
Abstract
1. Introduction
2. Experimental characterization of active states
3. Computational models of active states
4. Conclusion
Acknowledgements
References
Chapter 16. Stimulation of sodium channels in taste-receptor cells provides noise that enhances taste detection
Abstract
1. Introduction
2. General methods
3. Discussion
References
Chapter 17. Random pulse input versus continuous current plus white noise: Are they equivalent?
Abstract
1. Introduction
2. Models and methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 18. Precisely timed transient synchronization by depressing synapses
Abstract
References
Chapter 19. Dependence of firing pattern on intrinsic ionic conductances: Sensitive and insensitive combinations
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 20. Effect of noise on neuron transient response
Abstract
1. Introduction
2. Theory
3. Results
4. Discussion
References
Chapter 21. Consequences of correlated synaptic bombardment on the responsiveness of neocortical pyramidal neurons
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 22. Complex dynamics of neuronal thresholds
Abstract
1. Introduction
2. Dynamical thresholds in an integrate-and-fire neuron
3. Model of two dynamic thresholds
4. Phase space analysis
Acknowledgements
References
Chapter 23. Basic computational properties of Kenyon cell in the mushroom body of honeybee
Abstract
1. Introduction
2. The model and methods
3. Results
4. Conclusion
Acknowledgements
References
Chapter 24. Simulation techniques for localising and identifying the kinetics of calcium channels in dendritic neurones
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion and conclusion
Acknowledgements
References
Chapter 25. Analysis of complex bursting in cortical pyramidal neuron models
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
References
Chapter 26. Computational model for the bushy cell of the cochlear nucleus
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 27. Cholinergic neuromodulation of an anatomically reconstructed hippocampal CA3 pyramidal cell
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 28. Branching point effects on the passive properties of the cerebellar granule cell axon
Abstract
1. Introduction
2. Model and results
3. Conclusions and significance
Acknowledgements
Appendix
References
Chapter 29. Are inhibitory synaptic conductances on thalamic relay neurons inhomogeneous? Are synapses from individual afférents clustered?
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 30. Escape rate models for noisy integrate-and-fire neurons
Abstract
1. Introduction
2. Integrate-and-fire neuron models
3. Results
References
Chapter 31. Hippocampal place cells and the generation of a temporal code
Abstract
1. Background
2. Model
3. Results
4. Discussion
Acknowledgements
References
Chapter 32. Place cell firing shows an inertia-like process
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 33. Electrosensory response mechanisms in mormyrid electric fish
Abstract
1. Introduction
2. The model
3. Results
4. Conclusion
Acknowledgements
References
Chapter 34. Driven by inhibition
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 35. Influence of dendritic morphology on axonal competition
Abstract
1. Introduction
2. Competition for neurotrophins
3. Compartmental model
4. Results
5. Discussion
References
Chapter 36. A statistical analysis of dendritic morphology's effect on neuron electrophysiology of CA3 pyramidal cells
Abstract
1. Introduction
2. Model and methods
3. Results and conclusions
4. Summary
Acknowledgements
References
Chapter 37. What do VI neurons tell us about saccadic suppression?
Abstract
1. Introduction
2. Results
3. Conclusion
Acknowledgements
References
Part III: Network
Chapter 38. Harmonic analysis of spiking neuronal pairs
Abstract
References
Chapter 39. Non-synaptic modulation of cortical network dynamics
Abstract
1. Introduction
2. A three layered cortical network model
3. Simulation results
4. Discussion
Acknowledgements
References
Chapter 40. The role of AMPA, GABA, [Ca2+]i, and calcium stores in propagating waves in neuronal networks
Abstract
1. Introduction
2. Neural network model
3. Results
4. Conclusions
Acknowledgements
References
Chapter 41. Independent dendritic domains in the thalamic circuit
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
References
Chapter 42. Phase diagrams of sparsely connected networks of excitatory and inhibitory spiking neurons
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
References
Chapter 43. Interspike interval variability for balanced networks with reversal potentials for large numbers of inputs
Abstract
1. Introduction
2. Output spike probability density
3. Results
4. Discussion and conclusions
Acknowledgements
References
Chapter 44. Dynamics of excitatory networks of bursting pacemaking neurons: Modeling and experimental studies of the respiratory central pattern generator
Abstract
References
Chapter 45. Reciprocal excitatory synapses convert pacemaker-like firing into burst firing in a simple model of coupled neurons
Abstract
References
Chapter 46. A recurrent network model for the phase invariance of complex cell responses
Abstract
1. Introduction
2. Model
3. Results
4. Conclusion
References
Chapter 47. Neuronal normalization provides effective learning through ineffective synaptic learning rules
Abstract
1. Introduction
2. The space of synaptic learning rules
3. Effective learning via neuronal weight correction
4. Neuronal regulation approximates neuronal correction
5. Conclusions
References
Chapter 48. A comparison of context-dependent hippocampal place codes in 1-layer and 2-layer recurrent networks
Abstract
1. Introduction and background
2. Theoretical issues
3. Simulations and results
4. Conclusion
Acknowledgements
References
Chapter 49. Activity of coupled excitatory and inhibitory neural populations with dynamic synapses
Abstract
1. Introduction
2. Model
3. Fixed point analysis
4. Dependence of activities on input currents
5. Conclusion
References
Chapter 50. Chaos in neural networks with dynamic synapses
Abstract
1. Introduction
2. Chaotic phenomena
3. Response of the network to external input
4. Conclusion
References
Chapter 51. Synchronization driven by correlated inputs
Abstract
1. Introduction
2. Models
3. Without interaction
Acknowledgements
References
Chapter 52. Synaptic learning models of map separation in the hippocampus
Abstract
1. Introduction
2. Map separation in the hippocampus
3. Modeling map separation
4. Learning rules
5. Discussion
References
Chapter 53. Introduction of threshold self-adjustment improves the convergence in feature-detective neural nets
Abstract
1. Introduction
2. Method
3. Results
4. Discussion
5. Conclusion
References
Chapter 54. Layer 3 patchy recurrent excitatory connections may determine the spatial organization of sustained activity in the primate prefrontal cortex
Abstract
1. Introduction
2. The network model
3. Results
References
Chapter 55. Common mechanisms govern the development of intra- and inter-hemispherical connections in visual cortex
Abstract
1. Introduction
2. The model
3. Results
4. Conclusion
Acknowledgements
References
Chapter 56. Distributed synchrony in an attractor of spiking neurons
Abstract
1. Introduction
2. The model
3. Results
4. Summary
References
Chapter 57. Quantifying the variability of patterns of orientation domains in the visual cortex of cats
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion and conclusions
References
Chapter 58. Functional significance of inhibitory interactions between inhibitory interneurons in visual cortex
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 59. Simulation of metabotropic glutamate receptor induced effects in the lamprey CPG
Abstract
1. Introduction
2. Methods
3. Results and discussion
References
Chapter 60. Modeling of plasticity of the synaptic connections in the lamprey spinal CPG - consequences for network behavior
Abstract
1. Introduction
2. Methods
3. Results and discussion
4. Conclusion
References
Chapter 61. Retinotopy and spatial phase in topographic maps
Abstract
1. Spatial phase and retinotopy
2. The ASSOM
3. Results
4. Conclusion
References
Chapter 62. Realistic computer simulation of cortical lesion induced imbalances in properties of somatotopic maps
Abstract
1. Introduction
2. The model
3. Simulation
4. Results
5. Conclusions
References
Chapter 63. Geometric modeling of local cortical networks
Abstract
1. Introduction
2. Hierarchical network models of brain connectivity
3. Web-based description of brain tissue
4. Construction of network models based on the neuroanatomy
5. Interface to multi-compartmental modeling of cortical microcircuits
Acknowledgements
References
Chapter 64. Synchronization with a periodic pulse train in an asymmetrically coupled neuronal network model
Abstract
1. Introduction
2. A neuronal network model
3. Regions of synchronization
4. Conclusions
Acknowledgements
References
Chapter 65. Spatiotemporal dynamics in a model of turtle visual cortex
Abstract
1. Introduction
2. Model description
3. Activation of a single geniculate afferent produces a propagating wave of activity in the model cortex
4. The model cortex codes the velocity of moving spatial patterns
5. Conclusion
References
Chapter 66. Fast neural network simulations with population density methods
Abstract
1. Introduction
2. The general population density formulation
3. The population density for integrate-and-fire neurons
4. Population density evolution equation
5. Conclusion
References
Chapter 67. Entorhinal/dentate excitation of CA3: A critical variable in hippocampal models
Abstract
1. Introduction
2. Methods
3. Results and discussion
4. How the network solves the problems
Acknowledgements
References
Chapter 68. A dynamic model of learning in the septo-hippocampal system
Abstract
1. Introduction
2. The Gluck and Myers (1993) model
3. Dynamic learning
4. Benchmarks
5. Blocking
6. Scopolamine
7. Conclusion
8. For further reading
References
Chapter 69. Reciprocal inhibitory connections produce desynchronizing phase lags during intrathalamic oscillations^
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
References
Chapter 70. On cell assemblies in a cortical column
Abstract
1. Introduction
2. Model assumptions and parameter estimation
3. Analysis of assembly learning and assembly ignition
4. Results
5. Conclusions
Acknowledgements
References
Chapter 71. Temporally asymmetric Hebbian learning and neuronal response variability
Abstract
1. Introduction
2. Model
3. Response variability
4. Temporally asymmetric Hebbian plasticity leads to an irregular firing state
5. Correlation-based Hebbian modification
6. Conclusion
References
Chapter 72. Effect of correlations on signal transmission in a population of spiking neurons
Abstract
1. Introduction
2. The model
3. Results
4. Conclusion
Appendix
References
Chapter 73. Auditory singularity detection by a gerbil cochlea model^
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
References
Chapter 74. Neural field description of state-dependent visual receptive field changes
Abstract
1. Introduction
2. Theory
3. Fit to experimental data
4. Conclusions
Acknowledgements
References
Chapter 75. Effects of granule cell firing properties on the temporal pattern of the CA3 pyramidal cell's firing
Abstract
1. Introduction
2. Structural background
3. Modelling framework
4. Characterization of the output
5. Characterization of the input
6. The input-output correlation
7. Results
8. Discussion
Acknowledgements
References
Chapter 76. Post-cue activity of prefrontal cortical neurons controlled by local inhibition
Abstract
1. Introduction
2. Model
3. Results
4. Conclusion
Acknowledgements
References
Chapter 77. A model of the leech segmental swim central pattern generator
Abstract
1. Introduction
2. Background
3. Model desiderata
4. Form of the model
5. Fitting to data
6. Results
7. Discussion
References
Chapter 78. Stability constraints for oscillatory neural networks
Abstract
1. Introduction
2. Network model
3. Stability of the equilibrium point for TV coupled columns
4. Conclusions
Acknowledgements
References
Chapter 79. Relationship between field potentials and spike activity in rat SI: Multi-site cortical recordings and analysis
Abstract
1. Introduction
2. Cortical data analysis
3. Results
4. Discussion
References
Chapter 80. Dynamics of spatio-temporal patterns in associative networks of spiking neurons*
Abstract
1. Introduction
2. Network model
3. Calculation of retrieval velocities
4. Instabilities of chain propagation
5. Conclusions
Acknowledgements
References
Chapter 81. On the parametric stability of a central pattern generator
Abstract
1. Introduction
2. Swim network description
3. Results
4. Discussion
References
Chapter 82. Encoding multiple orientations in a recurrent network
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Chapter 83. Model of carbachol-induced gamma-frequency oscillations in hippocampus*
Abstract
1. Introduction
2. Overview of methods
3. Summary of results
Acknowledgements
References
Chapter 84. Gain modulation of recurrent networks
Abstract
1. Introduction
2. Models and results
3. Conclusions
References
Part IV: Systems
Chapter 85. A time-dependent analysis of spatial information encoding in the rat hippocampus
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
5. Conclusions
References
Chapter 86. Single trial P3 epoch recognition in a virtual environment*
Abstract
1. Introduction
2. Experimental setup
3. Experiments
4. Recognizing single trials in an immersive environment
5. Discussion
References
Chapter 87. The ecology of gaze shifts
Abstract
1. Introduction
2. Concepts
3. Results
4. Discussion
References
Chapter 88. Modeling dopamine modulation of delay-period activity in prefrontal cortex during working memory processes
Abstract
1. Introduction and methods
2. The effect of D-receptor agonists and antagonists
References
Chapter 89. Task dependence of human theta: The case for multiple cognitive functions
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
References
Chapter 90. Global vs. local processing of compressed representations: A computational model of visual search
Abstract
References
Chapter 91. Implications of synaptic digitisation and error for neocortical function
Abstract
References
Chapter 92. Behavioral considerations suggest an average reward TD model of the dopamine system^
Abstract
1. Introduction
2. TD models of dopamine
3. Behavioral tests of discounting
4. An average reward TD model of dopamine and behavior
5. Discussion
References
Chapter 93. A biologically plausible computational model of classical conditioning induced reorganization of tonotopic maps in the auditory cortex^
Abstract
1. Introduction
2. The model
3. Simulations
4. Results
5. Discussion and conclusions
References
Chapter 94. Neurodynamical mechanism of binding and selective attention for visual search
Abstract
1. Introduction
2. Neurodynamical model
3. Simulations of visual search tasks
References
Chapter 95. Localization of brain activity - blind separation for fMRI data
Abstract
1. Introduction
2. Data analysis
3. The experiment
4. Results
5. Conclusion
Acknowledgements
References
Chapter 96. Phase-based cerebellar learning of dynamic signals
Abstract
1. Introduction
2. Mathematical model of the cerebellar module with direct action of PC on CFC
3. Simulation results
4. Role of transformation of PCs signals by small nuclear cells on the way to CFCs
5. Discussion
Acknowledgements
References
Chapter 97. Probing the retino-geniculate circuit in cat using circular spot stimuli
Abstract
1. Introduction
2. Results
3. Conclusion
References
Chapter 98. Rethinking central pattern generators: A general approach
Abstract
1. Introduction
2. A five-step process used to model lamprey swimming
3. Strengths of this model and method
References
Chapter 99. Delay adaptation in the nervous system
Abstract
1. Introduction
2. Model
3. Delay shift
4. Delay selection
5. Discussion
References
Chapter 100. Proposition of cortical connectivity between 30 cytoarchitectural areas of human cerebral cortex
Abstract
1. Introduction
2. The Conel database
3. Methods
4. Result
5. Discussion
6. Conclusion
References
Chapter 101. An organizing center for planar neural excitability
Abstract
0. General introduction
1. Introduction
2. The organizing center
3. Implications
References
Chapter 102. Auditory localization using direction-dependent spectral information
Abstract
1. Introduction
2. Description of the model
3. Discussion
Acknowledgements
References
Chapter 103. Conserved temporal dynamics and vector superposition of primitives in frog wiping reflexes during spontaneous extensor deletions
Abstract
1. Introduction
2. Framework
3. Methods
4. Results
5. Discussion
Acknowledgements
References
Chapter 104. Learning predictive representations
Abstract
1. Introduction
2. The model neural network
3. Results
4. Conclusion
Acknowledgements
References
Chapter 105. Spatial neglect and paradoxical lesion effects in the cat - A model based on midbrain connectivity
Abstract
1. Introduction
2. Methods
3. Results
4. Conclusions and predictions
Acknowledgements
References
Chapter 106. Visualizing the visual system
Abstract
1. Introduction
2. Building a geometric model of gray matter
3. Building a geometric model of a chunk of visual cortex
4. Conclusions
Acknowledgements
References
Chapter 107. A role of a hierarchical dynamical map in cognition and binding different sensory modalities
Abstract
1. Introduction
2. The neural network model
3. Formation of hierarchical dynamical map
4. Priming process in hierarchical dynamical map
5. Concluding remarks
References
Chapter 108. Hebbian learning and temporary storage in the convergence-zone model of episodic memory
Abstract
1. Introduction
2. Hebbian learning and one-shot learning
3. Normalization and forgetting
4. Conclusion
References
Chapter 109. Noisy precursors of bifurcations in a neurodynamical model for disease states of mood disorders
Abstract
1. Introduction
2. Model
3. Data analysis
4. Results
5. Conclusion
Acknowledgements
References
Chapter 110. A neural model of medial geniculate body and auditory cortex detecting target distance independently of target velocity in echolocation
Abstract
1. Introduction
2. Model of the auditory brain system
3. Results
4. Optimal modulation rate of sound pulse frequency
References
Chapter 111. Neural model of temporal and stochastic properties of binocular rivalry
Abstract
1. Introduction
2. Methods
3. Results
4. Conclusions
References
Chapter 112. A positive role of noises in accurate detection of time difference by electrosensory system of weakly electric fish
Abstract
1. Introduction
2. A network model of the torus for detection of phase advances and delays (differential phase coder, DPC)
3. Results
References
Chapter 113. A role of synaptic variation depending on precise timings of pre- and postsynaptic depolarization in suppression of disturbance due to tail bending for accurate electrolocation
Abstract
1. Introduction
2. A neural network model of ELL
3. A role of synaptic modification depending on arrival timings of pre- and postsynaptic signals
References
Chapter 114. Modeling control of roll-plane body orientation in lamprey
Abstract
1. Introduction
2. Methods
3. Results and discussion
Acknowledgements
References
Chapter 115. Unifying cognitive aging: From neuromodulation to representation to cognition
Abstract
1. Introduction
2. Aging, neuromodulation and information processing
3. Modeling age-related attenuation of catecholaminergic function
4. Simulations linking catecholaminergic modulation with behavioral data
5. Conclusions
References
Chapter 116. On the tracking of dynamic functional relations in monkey cerebral cortex
Abstract
1. Introduction
2. Methods
3. Results
Acknowledgements
References
Chapter 117. Modeling neuron spatial distribution and morphology in the developing human cerebral cortex
Abstract
1. Introduction
3. Computational framework for modeling neuron morphology
4. Framing microstructure data into finite element models of the cortex
5. Web-based neuron/forest database
6. Neuroanatomical sources of data
Acknowledgements
References
Chapter 118. From hippocampus to VI: Effect of LTP on spatio-temporal dynamics of receptive fields
Abstract
1. Methods
2. Introduction
3. Results
References
Chapter 119. Modeling auditory cortical processing as an adaptive chirplet transform^
Abstract
1. Introduction
2. Adaptive chirplets
3. Conclusion
References
Chapter 120. Biologically plausible learning rules for neural networks and quantum computing
Abstract
0. Introduction
1. Hebbian rule-based learning rules for quantum learning
2. Implications
References
Chapter 121. A stimulus density-dependent normalization mechanism for modulating the range of contour integration
Abstract
1. Introduction
2. Methods
3. Results
4. Conclusions
References
Chapter 122. A model for neural representation of intervals of time
Abstract
1. Introduction
2. Model
3. Results and discussion
References
Chapter 123.Odor to sensor space transformations in biological and artificial noses
Abstract
1. Introduction
2. Linear transformations
3. Noise considerations
4. Non-linear odor space transformations
5. Conclusions
Acknowledgements
References
Chapter 124. Spike train coherence in macaque parietal cortex during a memory saccade task^
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
5. Conclusions
References
Chapter 125. Neural ensemble states in prefrontal cortex identified using a hidden Markov model with a modified EM algorithm^
Abstract
1. Introduction
2. Results
3. Conclusion
References
Chapter 126. A large-scale neuroanatomical model of attention implemented as a computer simulation
Abstract
1. Introduction
2. Method
3. Results
4. Discussion
References
Chapter 127. Associative symmetry vs. independent associations
Abstract
1. Introduction
2. A neural network model
3. Experiment
4. Simulating the experimental results
5. Conclusions
References
Chapter 128. Perceptual segmentation and neural grouping in tilt illusion
Abstract
1. Introduction
2. Perceptual segmentation
3. Neural grouping
4. Conclusions
References
Chapter 129. A palimpsest memory based on an incremental Bayesian learning rule
Abstract
1. Introduction
2. Bayesian learning
3. Results
4. Discussion
References
Chapter 130. Using computational simulations to discover optimal training paradigms
Abstract
1. Introduction
2. Description of the TP problem and training paradigms
3. Methods
4. Results and discussion
Acknowledgements
References
Part V: Methodology
Chapter 131. L-neuron: A modeling tool for the efficient generation and parsimonious description of dendritic morphology*
Abstract
1. Introduction and neuroanatomical background
2. Software development, system requirement, and source of experimental data
3. Discussion and future perspectives
Acknowledgements
References
Chapter 132. A Bayesian decision approach to evaluate local and contextual information in spike trains
Abstract
1. Introduction
2. Experiments
3. Data analysis
4. Scale-space representation
5. Conclusion
Acknowledgements
References
Chapter 133. Control and monitoring of a parallel processed neural network via the World Wide Web
Abstract
1. Introduction
2. Hardware and implementation
3. Results and discussion
Chapter 134. Natural time scales for neural encoding^
Abstract
1. Introduction
2. Preparation: The cricket cereal sensory system
3. Physiological methods
4. Analytical methods
5. Results
6. Discussion
References
Chapter 135. Estimating cortical connectivity for developing human cerebral cortex
Abstract
1. Introduction
2. Materials and method
3. Estimated cortical connectivity
4. Concluding remarks
Acknowledgements
References
Chapter 136. A large-scale model of the cerebellar cortex using PGENESIS*
Abstract
1. Introduction
2. Model of the cerebellar cortex
3. Simulation scale
4. PGENESIS
5. Results
6. Discussion
References
Chapter 137 AQuantifying information transfer in spike generation
Abstract
1. Introduction
2. Separation of PSP and the spike train
3. Information processing analysis
4. Data analysis
5. Conclusions
References
Chapter 138. Robustness of coarse graining spectral analysis in estimating frequency and Hurst exponent from mixed time series with harmonic and fractal components
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion and conclusion
Acknowledgements
References
Chapter 139. Distributed, web-based microstructure database for brain tissue
Abstract
1. Introduction
2. Volume data: Finite element decomposition
3. The neuron/forest data level
4. Network data: Geometric modeling of local cortical networks
References
Chapter 140. Symbolic time-series analysis of neural data^
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
References
Chapter 141. Non-stationary analysis of extracellular neural activity
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion and conclusion
Acknowledgements
References
Chapter 142. PARALLEL NEUROSYS: A system for the simulation of very large networks of biologically accurate neurons on parallel computers
Abstract
1. Introduction
2. The message passing interface standard for parallel computers
3. Commodity supercomputers
4. The system
5. Some example results
6. Conclusions and directions for future work
Acknowledgements
References
Chapter 143. Model-free detection of synchrony in neuronal spike trains, with an application to primate somatosensory cortex
Abstract
1. Introduction
2. Experimental methods
3. Statistical methods
4. Results
5. Discussion
Acknowledgements
References
Chapter 144. CYBERCHILD: A database of the microscopic development of the postnatal human cerebral cortex from birth to 72 months
Abstract
1. Introduction
2. The database (CYBERCHILD)
3. The quality of Conel's data
4. Principal findings arising from the CYBERCHILD database
5. Relevance of the CYBERCHILD database to computational modeling
Acknowledgements
References
Chapter 145. Blind source separation of multichannel neuromagnetic responses
Abstract
1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References
Author index to volumes 32-33 (2000)
Subject index to volumes 32-33 (2000)
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E-Book-Reader: Bookeen, Kobo, Pocketbook, Sony, Tolino u.v.a.m. (nicht Kindle)

Das Dateiformat PDF zeigt auf jeder Hardware eine Buchseite stets identisch an. Daher ist eine PDF auch für ein komplexes Layout geeignet, wie es bei Lehr- und Fachbüchern verwendet wird (Bilder, Tabellen, Spalten, Fußnoten). Bei kleinen Displays von E-Readern oder Smartphones sind PDF leider eher nervig, weil zu viel Scrollen notwendig ist.
Mit Adobe-DRM wird hier ein „harter” Kopierschutz verwendet. Wenn die notwendigen Voraussetzungen nicht vorliegen, können Sie das E-Book leider nicht öffnen. Daher müssen Sie bereits vor dem Download Ihre Lese-Hardware vorbereiten.

Bitte beachten Sie: Wir empfehlen Ihnen unbedingt nach Installation der Lese-Software diese mit Ihrer persönlichen Adobe-ID zu autorisieren!

Weitere Informationen finden Sie in unserer E-Book Hilfe.

Dateiformat: PDF
Kopierschutz: Wasserzeichen-DRM (Digital Rights Management)

Systemvoraussetzungen:

Computer (Windows; MacOS X; Linux): Verwenden Sie zum Lesen die kostenlose Software Adobe Reader, Adobe Digital Editions oder einen anderen PDF-Viewer Ihrer Wahl (siehe E-Book Hilfe).
Tablet/Smartphone (Android; iOS): Installieren Sie bereits vor dem Download die kostenlose App Adobe Digital Editions oder die App PocketBook (siehe E-Book Hilfe).
E-Book-Reader: Bookeen, Kobo, Pocketbook, Sony, Tolino u.v.a.m.

Das Dateiformat PDF zeigt auf jeder Hardware eine Buchseite stets identisch an. Daher ist eine PDF auch für ein komplexes Layout geeignet, wie es bei Lehr- und Fachbüchern verwendet wird (Bilder, Tabellen, Spalten, Fußnoten). Bei kleinen Displays von E-Readern oder Smartphones sind PDF leider eher nervig, weil zu viel Scrollen notwendig ist. Mit Wasserzeichen-DRM wird hier ein „weicher” Kopierschutz verwendet. Daher ist technisch zwar alles möglich – sogar eine unzulässige Weitergabe. Aber an sichtbaren und unsichtbaren Stellen wird der Käufer des E-Books als Wasserzeichen hinterlegt, sodass im Falle eines Missbrauchs die Spur zurückverfolgt werden kann.

Weitere Informationen finden Sie in unserer E-Book Hilfe.

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