Document Outline - Front matter
- Chapter 1
- Chapter 2
- Global Bifurcation Analysis of a Pyramidal Cell Model of the Primary Visual Cortex: Towards a Construction of Physiologically Plausible Model
- Introduction
- Cell Model
- Bifurcation Analysis
- The External Stimulation Current Iext
- The Maximum Conductance of Ca2+-Dependent Potassium Channel GKCa
- The Maximum Pumping Rate of the Ca2+ Pump Apump
- Slow/Fast Decomposition Analysis
- Conclusion
- Chapter 3
- Representation of Medial Axis from Synchronous Firing of Border-Ownership Selective Cells
- Introduction
- The Proposed Model
- Model Neurons
- Contrast Detection Stage
- BO Detection Stage
- MA Detection Stage
- Simulation Result
- A Single Square
- C-Shape
- Natural Images
- Conclusion
- References
- Chapter 4
- Neural Mechanism for Extracting Object Features Critical for Visual Categorization Task
- Introduction
- Model
- Model of Retina and LGN
- Model of V1 Network
- Model of V4 Network
- Model of PP
- Model of IT
- Model for Working Memory in PFC
- Model of Premotor Cortex
- Neural Mechanism for Extracting Diagnostic Features in Visual Categorization Task
- Categorization Task
- Neural Mechanism for Accomplishing Visual Categorization Task
- Results
- Information Processing of Visual Images in Early Visual Areas
- Information Processing of Visual Images in IT Cortex
- Mechanism for Generating Working Memory Attractor in PFC
- Concluding Remarks
- Chapter 5
- An Integrated Neuro-mechanical Model of C. elegans Forward Locomotion
- Introduction
- Background
- C. elegans Locomotion
- The Neural Model
- Physical Model
- Results
- Single Oscillating Segment
- Two Phase-Lagged Segments
- Discussion
- Chapter 6
- Applying the String Method to Extract Bursting Information from Microelectrode Recordings in Subthalamic Nucleus and Substantia Nigra
- Introduction
- Method
- Spike Detection
- The String Method
- Dependent Variables
- Statistical Analysis
- Results
- Discussion and Conclusion
- References
- Chapter 7
- Population Coding of Song Element Sequence in the Songbird Brain Nucleus HVC
- Introduction
- Material and Methods
- Animals
- Stimuli
- Recording Procedure
- Data Analysis
- Population Dynamics Analysis
- Information-Theoretic Analysis
- Results
- Selective Auditory Response to BOS
- Responses to Song Element Pair Stimuli
- Population Dynamics Analysis
- Information-Theoretic Analysis
- Conclusion
- Chapter 8
- Spontaneous Voltage Transients in Mammalian Retinal Ganglion Cells Dissociated by Vibration
- Introduction
- Methods
- Cell Dissociation
- Electrophysiology
- Results
- Discussions
- References
- Chapter 9
- Region-Based Encoding Method Using Multi-dimensional Gaussians for Networks of Spiking Neurons
- Introduction
- Multi-delay Spiking Neural Networks
- Range-Based Encoding
- Region-Based Encoding Using Multi-dimensional Gaussian Receptive Fields
- Conclusions
- Chapter 10
- Firing Pattern Estimation of Biological Neuron Models by Adaptive Observer
- Introduction
- Review of Real (Cortical) Neuron Responses
- Single Model of HR Neuron
- Dynamical Equations
- Numerical Examples
- Synaptically Coupled Model of HR Neuron
- Dynamical Equations
- Numerical Examples
- Adaptive Observer with Full States
- Construction of Adaptive Observer
- Numerical Examples
- Adaptive Observer with a Partial State
- Construction of Adaptive Observer
- Numerical Examples
- Conclusion
- References
- Chapter 11
- Thouless-Anderson-Palmer Equation for Associative Memory Neural Network Models with Fluctuating Couplings
- Introduction
- Brief Review on Effective Hamiltonian, TAP Equations and Order Parameter Equations
- Models with Effective Hamiltonian and Effective Temperature
- Conclusion
- Chapter 12
- Spike-Timing Dependent Plasticity in Recurrently Connected Networks with Fixed External Inputs
- Introduction
- Models
- Linear Poisson Neuron
- Additive STDP
- Link with the Physiology
- Theoretical Analysis
- Characterisation of the Neural Activity
- Learning Equations
- Activation Dynamics
- Network Dynamical System
- Recurrent Network with Fixed Input Weights
- Analytical Predictions
- Simulation Protocol and Results
- Discussion and Future Work
- Chapter 13
- A Comparative Study of Synchrony Measures for the Early Detection of Alzheimer’s Disease Based on EEG
- Introduction
- Synchrony Measures
- Cross-Correlation Coefficient
- Coherence
- Corr-Entropy Coefficient
- Coh-Entropy and Wav-Entropy Coefficient
- Granger Causality
- Phase Synchrony
- State Space Based Synchrony
- Information-Theoretic Measures
- Stochastic Event Synchrony (SES)
- Detection of EEG Synchrony Abnormalities in MCI Patients
- EEG Data
- Methods
- Results and Discussion
- Conclusions
- Chapter 14
- Reproducibility Analysis of Event-Related fMRI Experiments Using Laguerre Polynomials
- Introduction
- Method
- Reproducibility Analysis
- Laguerre Polynomials
- Event-Related fMRI Experiments
- Experimental Design
- Experimental Design Matrix
- Results
- Discussion
- References
- Chapter 15
- The Effects of Theta Burst Transcranial Magnetic Stimulation over the Human Primary Motor and Sensory Cortices on Cortico-Muscular Coherence
- Introduction
- Methods
- Subjects
- Determination of M1 and S1 Location
- Theta Burst Stimulation
- EEG and EMG Recording
- Data Analysis
- Results
- Discussion
- References
- Chapter 16
- Interactions between Spike-Timing-Dependent Plasticity and Phase Response Curve Lead to Wireless Clustering
- Introduction
- Self-organization of Izhikevich Neurons
- Self-organization of Hodgkin-Huxley Type Neurons
- Discussion
- Chapter 17
- A Computational Model of Formation of Grid Field and Theta Phase Precession in the Entorhinal Cells
- Introduction
- Model
- A Module of Local Path Integrator
- Grid Field Formation with Visual Cues
- Theta Phase Precession in the Grid Field
- Mathematical Formulation
- Computer Simulation of Theta Phase Precession
- Discussions and Conclusion
- References
- Chapter 18
- Working Memory Dynamics in a Flip-Flop Oscillations Network Model with Milnor Attractor
- Introduction
- A Network Model
- Structure
- Mathematical Formulation of the Model
- An Isolated Unit
- Resting State
- Constant Input Can Give Oscillations
- Two Coupled Units
- Influence of the Feedback Loop
- Influence of the Coupling Strength
- Application to Slow Selection of a Memorized Pattern
- A Small Network
- Memory Retrieval and Response Selection
- Conclusion
- Chapter 19
- Corticopetal Acetylcholine: Possible Scenarios on the Role for Dynamic Organization of Quasi-Attractors
- Introduction
- Corticopetal Acetylcholine
- Attentions, Cortical State Transitions and Cholinergic Control System from NBM
- Neural Correlate of Conscious Percepts and the Role of the Corticopetal ACh
- Neural Correlates of Conscious Percepts and Transient Synchrony
- Role of the Corticopetal ACh: A Working Hypothesis
- Do the Existing Experimental Data Support the Working Hypothesis?
- Introductory Remarks: Transient Synchronization by Virtue of Pre- and Post-synaptic ACh Modulations
- Controversy on Experimental Data
- Possible Scenarios
- Concluding Discussions
- References
- Chapter 20
- Tracking a Moving Target Using Chaotic Dynamics in a Recurrent Neural Network Model
- Introduction
- Memory Attractors and Motion Functions
- Introducing Chaotic Dynamics in RNNM
- Motion Control and Tracking Algorithm
- Simulation Results
- Performance Evaluation
- Discussion
- Summary
- Chapter 21
- A Generalised Entropy Based Associative Model
- Introduction
- Theory
- Numerical Results
- Concluding Remarks
- References
- Chapter 22
- The Detection of an Approaching Sound Source Using Pulsed Neural Network
- Introduction
- Pulsed Neuron Model
- The Proposed System
- Filtering and Frequency-Pulse Converter
- Level Difference Extractor
- Sound Source Classifier
- Experimental Results
- Level Difference Information Extraction
- Sound Source Classification
- Conclusions
- Chapter 23
- Sensitivity and Uniformity in Detecting Motion Artifacts
- Introduction
- Measuring Motion Artifacts
- Ratio Image Uniformity
- Scaled Least-Squared Difference
- Correlation Coefficient
- Joint Entropy
- Relative Entropy
- Weighted Kappa
- Mean Distance to the Principal Component
- Experimental Results
- Discussion
- References
- Chapter 24
- A Ring Model for the Development of Simple Cells in the Visual Cortex
- Introduction
- Methods
- Structure of the Model
- Correlation of Spontaneous Activities in LGN
- Initial Synaptic Weights
- Modification of the Synaptic Weights
- Visual Responses
- Parameters
- Results
- Development of Simple Receptive Fields
- Development of Labyrinthine Receptive Fields
- Discussion
- References
- Chapter 25
- Practical Recurrent Learning (PRL) in the Discrete Time Domain
- Introduction
- Practical Recurrent Learning (PRL)
- PRL in the Continuous Time Domain[1]
- PRL in the Discrete Time Domain
- Simulation of EXOR and 3-Bit Parity Problems
- Simulation of EXOR Problem
- Simulation of 3-Bit Parity Problems
- Conclusion
- References
- Chapter 26
- Learning of Bayesian Discriminant Functions by a Layered Neural Network
- Introduction
- Preliminaries
- Difficulty of Learning Posterior Probabilities
- Modified One-Hidden-Layer Neural Network
- Training of the Neural Network
- Simulations
- Conclusion and Discussions
- Chapter 27
- RNN with a Recurrent Output Layer for Learning of Naturalness
- Introduction
- Dynamics of RNN with a Recurrent Output Layer
- RNN with a Recurrent Output Layer for Naturalness Learning
- Experiments
- Data Specification
- Network Parameters
- Training and Testing
- Discussion
- Conclusion
- Chapter 28
- Using Generalization Error Bounds to Train the Set Covering Machine
- Motivation
- The Set Covering Machine
- Training
- Testing
- Generalization Error Bounds
- The Bound Set Covering Machine
- The Branch and Bound Set Covering Machine
- BBSCM($\tau$)
- Theory
- Experiments
- Conclusion
- Chapter 29
- Model of Cue Extraction from Distractors by Active Recall
- Introduction
- Model
- Results
- Discussion
- Chapter 30
- PLS Mixture Model for Online Dimension Reduction
- Introduction
- Related Work
- PLS Regression
- Proposed System
- Outline
- Linear Function
- PLS Kernel
- Online DAEM Algorithm
- Unit Manipulation
- Experiments
- Performances of Dataset Including Irrelevant Dimensions
- Performances for a Multicollinearity Dataset
- Conclusion
- Chapter 31
- Analysis on Bidirectional Associative Memories with Multiplicative Weight Noise
- Introduction
- BAM with Multiplicative Weight Noise
- BAM
- Multiplicative Weight Noise
- Analysis on BAM with Multiplicative Weight Noise
- Capacity
- Error Correction
- Simulation
- Capacity
- Error Correction
- Conclusion
- Chapter 32
- Fuzzy ARTMAP with Explicit and Implicit Weights
- Introduction
- Fuzzy ARTMAP Learned by AL-SLMAP
- FAM with Explicit and Implicit Weights
- Choice Strength for ARTa
- Explicit and Implicit Weights
- Match Tracking
- Simulation Results
- Conclusions
- Chapter 33
- Neural Network Model of Forward Shift of CA1 Place Fields Towards Reward Location
- Introduction
- Model
- Results
- Discussion
- Chapter 34
- A New Constructive Algorithm for Designing and Training Artificial Neural Networks
- Introduction
- PDCA
- Termination Criterion
- Layer Stopping Criterion
- Creation of New Training Sets
- Experimental Studies
- Comparison
- Conclusions
- Chapter 35
- Effective Learning with Heterogeneous Neural Networks
- Introduction
- Motivation
- Similarity Measures
- Heterogeneous Neural Networks
- The Heterogeneous Neuron Model
- Heterogeneous Neural Networks
- Heterogeneous Similarity Measures
- An Experimental Comparison
- Conclusions
- Chapter 36
- Pattern-Based Reasoning System Using Self-incremental Neural Network for Propositional Logic
- Introduction
- Proposed Method
- Learning Algorithm
- The Reasoning Algorithm
- Neural Network Model
- Simulation Results
- Conclusion and Future Work
- Chapter 37
- Effect of Spatial Attention in Early Vision for the Modulation of the Perception of Border-Ownership
- Introduction
- The Model
- V1 Module
- V2 Module
- Posterior Parietal (PP) Module
- Simulation Results
- Simulations and Psychophysics for Ambiguous Block Stimuli
- Simulation Results for Ambiguous Figures – A Case of Rubin’s Vase
- Discussion
- References
- Chapter 38
- Effectiveness of Scale Free Network to the Performance Improvement of a Morphological Associative Memory without a Kernel Image
- Introduction
- Scale Free Network
- Morphological Associative Memory: MAM
- Scale Free Network Type MAM
- Experimental Results
- Decision of Insert Position of a Scale Free Network
- Evaluation of MAM with Scale Free Network in Both Stages
- Conclusion
- References
- Chapter 39
- Intensity Gradient Self-organizing Map for Cerebral Cortex Reconstruction
- Introduction
- The Problem
- Methods
- The Image Intensity Gradient
- The Intensity Gradient Self-organizing Map (IGSOM) Model
- Simulation and Experiment
- Conclusions
- References
- Chapter 40
- Feature Subset Selection Using Constructive Neural Nets with Minimal Computation by Measuring Contribution
- Introduction
- The Proposed Method
- Stopping Criteria (SC)
- Measurement of Contribution
- Calculation of Network Connection
- The Algorithm
- Experimental Analysis
- Experimental Results
- Comparison with other Methods
- Discussion
- Conclusion
- References
- Chapter 41
- Dynamic Link Matching between Feature Columns for Different Scale and Orientation
- Introduction
- Concept of Scale and Rotation Invariance
- Modelling a Columnar Network
- Results
- Discussion and Conclusion
- Chapter 42
- Perturbational Neural Networks for Incremental Learning in Virtual Learning System
- Introduction
- A Virtual Learning System for a Biped Robot
- Neural Networks for Incremental Learning
- Perturbational Neural Networks
- Related Work
- Numerical Experiments
- Setup
- Experimental Results
- Conclusions
- Chapter 43
- Bifurcations of Renormalization Dynamics in Self-organizing Neural Networks
- Introduction
- Self-organizing Neural Network and Iterative Softmax
- Equilibria of SONN Renormalization Step
- Stability Analysis of Renormalization Equilibria
- Discussion -- SONN Adaptation Dynamics
- Chapter 44
- Variable Selection for Multivariate Time Series Prediction with Neural Networks
- Introduction
- Modeling Multivariate Chaotic Time Series
- Sensitivity Analysis with Neural Networks
- Simulations
- Prediction of Lorenz Time Series
- Prediction of the Rainfall Time Series
- Conclusions
- References
- Chapter 45
- Ordering Process of Self-Organizing Maps Improved by Asymmetric Neighborhood Function
- Introduction
- Methods
- SOM
- Asymmetric Neighborhood Function
- Numerical Simulations
- Topological Order and Distortion of the Feature Map
- Results
- One-Dimensional Case
- Two-Dimensional Case
- Conclusion
- Chapter 46
- A Characterization of Simple Recurrent Neural Networks with Two Hidden Units as a Language Recognizer
- Introduction
- Preliminaries
- A Necessary Condition
- An Example of a Recognizer
- Discussion
- Chapter 47
- Unbiased Likelihood Backpropagation Learning
- Introduction
- Statistical Learning
- Information Criterion and Model Selection
- Artificial Neural Network
- Regularized Maximum Likelihood Estimation
- Overfitting of the Error Backpropagation Learning
- Unbiased Likelihood Backpropagation Learning
- Unbiased Likelihood
- Regular Hierarchical Model
- Unbiased Likelihood Backpropagation Learning
- Unbiased Likelihood Backpropagation Learning for an Artificial Neural Network
- Application to Kernel Regression Model
- Kernel Regression Model
- Simulations
- Discussion
- Conclusion
- Chapter 48
- The Local True Weight Decay Recursive Least Square Algorithm
- Introduction
- TWDRLS Algorithm
- Localization of the TWDRLS Algorithm
- Simulations
- Generalized XOR Problem
- Sunspot Data Prediction
- Conclusion
- Chapter 49
- Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift
- Introduction
- Bayesian Generalization Errors with and without Covariate Shift
- Non-regular Models
- Properties of the Generalization Error without Covariate Shift
- Properties of the Generalization Error with Covariate Shift
- Experimental Generalization Errors in Some Toy Models
- Discussions
- Conclusions
- Chapter 50
- Using Image Stimuli to Drive fMRI Analysis
- Introduction
- Materials and Methods
- Scale Invariant Feature Transformation
- Methods
- Results
- Discussion
- Chapter 51
- Parallel Reinforcement Learning for Weighted Multi-criteria Model with Adaptive Margin
- Introduction
- Weighted Criterion Model
- Parallel Q-Learning for All Weights
- Interval Operations
- Experiments with a Basic Task of Weighted Criterion
- Conclusion
- Chapter 52
- Convergence Behavior of Competitive Repetition-Suppression Clustering
- Introduction
- A Kernel Based Loss Function for CoRe Clustering
- Separation Nature
- Correct Division and Location
- A Global Minimum Condition for Vector Quantization in Kernel Space
- Correct Division and Location for CoRe Clustering
- Conclusion
- Chapter 53
- Self-Organizing Clustering with Map of Nonlinear Varieties Representing Variation in One Class
- Introduction
- Adaptive Manifold Self-Organizing Map (AMSOM)
- Self-Organizing Clustering with Nonlinear Varieties
- Reproducing Kernels
- AMSOM in the Feature Space
- Experimental Results
- Conclusions
- Chapter 54
- An Automatic Speaker Recognition System
- Introduction
- Methodology
- Pre-processing
- Feature Extraction
- Mel-Frequency Cepstrum Processor
- Speech Feature Matching
- Vector Quantization
- The Testing Procedure
- Result
- Conclusion
- References
- Chapter 55
- Modified Modulated Hebb-Oja Learning Rule: A Method for Biologically Plausible Principal Component Analysis
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