Advances in Cognitive Neurodynamics (II) (eBook)

Proceedings of the Second International Conference on Cognitive Neurodynamics - 2009

Rubin Wang, Fanji Gu (Herausgeber)

eBook Download: PDF

2011 | 2011
XXII, 756 Seiten
Springer Netherland (Verlag)
978-90-481-9695-1 (ISBN)

Infos

Within our knowledge, the series of the International Conference on Cognitive Neurodynamics (ICCN) is the only conference series dedicating to cognitive neurodynamics. This volume is the proceedings of the 2nd  International Conference on Cognitive Neurodynamics held in 2009, which reviews the progress in this field since  the 1st  ICCN -2007. The topics include: Neural coding and realistic neural network dynamics, Neural population dynamics, Firing Oscillations and Patterns in Neuronal Networks, Brain imaging, EEG, MEG, Sensory and Motor Dynamics,  Global cognitive function, Multi-scalar Neurodynamics - from Physiology to Systems Theory, Neural computing, Emerging Technologies for Brain Computer Interfaces, Neural dynamics of brain disorders.

Inhalt

Preface 4
Sponsors and Organizers 6
Organizing Committee 7
Local Organization Committee 10
Contents 11
Part I Plenary Talk 21
Dynamics of Learning In Hierarchical Models Singularity and Milnor Attractor 22
1 Introduction 22
2 Dynamics of On-Line Learning 23
3 Singularities of Hierarchical Networks 24
4 Critical Singular Region 24
5 Dynamical Flow Near Singularities 25
6 Milnor Attractor 26
7 Topology of Singularity 26
8 Conclusions 27
References 27
Chaotic Dynamics, Episodic Memory, and Self-identity 29
1 Introduction 29
2 Chaotic Itinerancy in CA3 30
3 Iterated Function Systems and Cantor Coding in CA1 31
4 Rhythm and Simultaneity 32
5 Logic for Self-identity 33
References 35
Stochastic Modeling of Neuronal Responses 37
1 Introduction 37
2 Results and Discussion 38
Bibliography 40
Phase Transitions in Mesoscopic Brain Dynamics Implications for Cognition and Consciousness 41
1 Introduction 42
2 Mesoscopic Brain Dynamics 42
3 Computational Methods 43
4 Neural Network Models with Phase Transitions 44
5 Discussion 44
References 46
Anatomical and Topological Foundations of Cognitive Neurodynamics in Cerebral Cortex 48
1 Introduction 48
2 Anatomy and Topology Among Sensory and Limbic Cortices 50
3 The anatomy and Topology of Information Flows in Sensation 52
4 The Anatomy and Topology of Flows in Perception 54
References 55
Metastability of Mean Field Neuropercolation The Role of Inhibitory Populations 57
1 Introduction 57
2 Overview of Mean-Field Neuropercolation 58
3 Inhibition in Mean Field Approximation 60
4 Discussion and Conclusions 60
References 62
Spontaneous Low-Frequency Fluctuation Observed with Functional Magnetic Resonance Imaging as a Potential Biomarker in Neuropsychiatric Disorders 63
1 Introduction 63
2 Methods and Progress in Understanding Neuropsychiatric Disorders 64
2.1 Individual ROI Analysis and Progress in Understanding Neuropsychiatric Disorders 65
2.2 Local Network Analyses and Progress in Understanding Neuropsychiatric Disorders 67
2.3 Whole Brain Network Analyses and Progress in Understanding Neuropsychiatric Disorders 69
3 Conclusions 70
References 71
Part II Tamagawa-RIKEN Dynamic Brain Forum 74
Dynamical Systems and Accurate Temporal Information Transmission in Neural Networks 75
1 Introduction 75
2 Methods 76
3 Results 76
4 Discussion 77
References 78
Next Generation Large-Scale Chronically Implantable Precision Motorized Microdrive Arrays for Freely Behaving Animals 80
1 Introduction 80
2 Methods 81
2.1 Individual Motorized Microdrives 81
2.2 DC Servomotor Multiplexing Headstage 81
2.3 Headstage Control Board and Control GUI Software 83
3 Results 83
3.1 Chronically Implanted Microdrive Arrays 83
3.2 Fine Step Adjustments 83
3.3 Stability Across Multiple Days 84
4 Conclusion 85
References 85
Dynamic Receptive Fields in Auditory Cortex: Feature Selectivity and Organizational Principles 86
1 Modulation Differences Between Excitatory and Inhibitory Neurons 86
2 Laminar Organization of Spectral and Temporal Modulation Properties 87
3 Joint Encoding of Multiple Auditory Features 88
4 Conclusions 89
References 90
Top-Down Mechanism of Perception: A Scenario on the Role for Layer 1 and 2/3 Projections Viewed from Dynamical Systems Theory 91
1 Cortical Layer 1: The Crowning Mystery 91
1.1 Top-Down Projections: Two Concurrent Flows 92
2 A Dynamical Systems-Theoretic Scenario 92
2.1 FS Hypothesis 93
2.2 Attentional ACh Releases PYRs from the Ongoing Inhibitions by the Presynaptic Disinhibition: Its Consequence 93
2.3 Top-Down Glu Spike Volleys in Layer 1 '' As Indexing Signals for Designating and Binding ''Internal States'' 94
2.4 Top-Down Mechanism of Perception Viewed from Dynamical Systems Theory 94
3 Concluding Remarks 95
References 95
Beyond Sensory Coding: The Cognitive Context of Olfactory Neurodynamics 97
1 The Primary Olfactory System: Anatomy and Physiology 97
2 Two Behavioral Tasks and Two Oscillatory Modes 98
3 Cognitive and Possible Circuit Differences 100
References 100
Temporo-Parietal Network Model for 3D Mental Rotation 102
1 Introduction 102
2 Structure of the Model 103
3 Training Procedure of the Network 104
4 Results and Discussion 104
References 105
Representation of Time-Series by a Self-Similar Set in a Model of Hippocampal CA1 107
1 Introduction 107
2 Model 108
3 Cantor Coding 108
4 Summary 110
References 110
Emergence of Iterated Function Systems in the Hippocampal CA1 112
1 Introduction 112
2 Materials and Methods 113
3 Results and Conclusions 114
References 115
Frontal Theta for Executive Functions and Parietal Alpha for Storage Buffers in Visual Working Memory 116
1 Introduction 116
2 Material and Methods 117
3 Results 118
4 Discussion 118
References 119
Associative Latching Dynamics vs. Syntax 120
1 Introduction 120
2 Potts Model 121
3 Extended Potts Dynamics 121
4 BLISS Sentences 122
5 Entropy and Information 123
References 124
Category Inference and Prefrontal Cortex 125
1 Introduction 125
2 Results 126
3 Discussion 129
References 129
Is Mu Rhythm an Index of the Human Mirror Neuron System? A Study of Simultaneous fMRI and EEG 131
1 Introduction 131
2 Materials and Methods 132
3 Results and Discussion 133
References 134
Decoding Action Selectivity of Observed Images Using fMRI Pattern Analysis 136
1 Introduction 136
2 Materials and Methods 137
3 Results 138
4 Discussion 139
References 139
A Developmental Model of Infant Reaching Movement: Acquisition of Internal Visuomotor Transformations 141
1 Introduction 141
2 The Model 142
3 Simulation and Discussion 143
References 144
Interacting Humans and the Dynamics of Their Social Brains 145
1 Introduction 145
1.1 The Theoretical Framework of Coordination Dynamics 146
1.2 Dynamics: Challenge for Social Neuroscience 146
2 Self-organizing Coordination Tendencies in Human Behavior 147
2.1 Spontaneous Coordinative Tendencies 147
2.2 Symmetry Breaking and the Notion of Roles 147
3 Brain Dynamics of Interacting Human 147
3.1 Neuromarkers of Social Coordination 147
3.2 Dynamics of Social Coordination 148
3.3 Brain Patterns of Coordination, Patterns of Intrinsic Behavior 148
4 Discussion and Outlook 148
References 149
State-Dependent Cortical Synchronization Networks Revealed by TMS-EEG Recordings 150
1 Introduction 150
2 Methods 151
3 Results and Discussion 152
References 153
Part III Neural Coding and Realistic Neural Network Dynamics 154
Stimulation Induced Transitions in Spontaneous Firing Rates in Cultured Neuronal Networks also Occur in the Presence of Synaptic Plasticity Blocker KN93 155
1 Introduction 155
2 Methods 156
3 Results 157
4 Discussion 158
References 158
Attractors in Neurodynamical Systems 160
1 Introduction 160
2 Visualization of Attractors 161
3 Discussion 164
References 164
Combining Supervised, Unsupervised, and Reinforcement Learning in a Network of Spiking Neurons 165
1 Introduction 165
1.1 Determining the Reward or Punishment 166
1.2 Solving the Distal Reward Problem 167
1.3 Switching from LTP to LTD Depending on Reward or Punishment 167
2 Methods 168
2.1 Network Configuration 168
2.2 Neuron Model 168
2.3 Neuron Types 168
2.4 Synapse Model 169
2.5 Synaptic Plasticity 169
2.6 Experiments 171
3 Results 172
3.1 Unsupervised Learning 172
3.2 Supervised Learning 173
3.3 Reinforcement Learning 174
3.4 Comparison 175
4 Discussion and Conclusion 176
References 177
Concerted Activities in Frog Retinal Ganglion Cells 179
1 Introduction 179
2 Methods 180
2.1 Electrophysiology Recording 180
2.2 Data Analysis 180
3 Results 181
4 Discussion 182
References 182
Gamma-Frequency Synaptic Input Enhances Gain Modulation of the Layer V Pyramidal Neuron Model 184
1 Introduction 184
2 Methods 185
3 Results 185
4 Conclusion 187
References 187
Zinc Modulation of Calcium-Permeable AMPA Receptors on Carp Retinal Horizontal Cells 189
1 Introduction 189
2 Methods 190
2.1 Preparation 190
2.2 Whole-Cell Recording and Drug Application 190
3 Results 191
3.1 The CP-AMPARs Mediated the Majority of the Glutamatergic Response 191
3.2 Zinc Inhibitory Effect on CP-AMPAR-Mediated Current 191
4 Summary 192
References 193
Spectral Characteristics of Firing Pattern in Retinal Ganglion Cells 194
1 Introduction 194
2 Methods 195
2.1 Electrophysiology Recording 195
2.2 Stimulus 195
2.3 Power Spectral Density (PSD) 195
2.4 Partial Directed Coherence (PDC) 195
3 Results 196
3.1 Power Spectral Density of Responses of RGCs 196
3.2 Partial Directed Coherence Analysis 197
4 Discussion 198
References 198
The Firing Pattern Properties in Retinal Ganglion Cells 199
1 Introduction 199
2 Meterial and Methods 200
2.1 Experimental Procedure 200
2.2 Cross-Correlation Function and LZ Distance 200
3 Results 201
References 203
The Spatiotemporal Structure of Receptive Field of Ganglion Cells in Bullfrog Retina 204
1 Introduction 204
2 Material and Methods 205
2.1 Experimental Procedure 205
2.2 Spike-Triggered Average (STA) 205
3 Results 205
References 208
Part IV Neural Population Dynamics 209
Dynamics of Hierarchical Neural Networks 210
1 Introduction 210
2 Methods 211
3 Results 212
4 Discussion 213
References 213
Effects of Additive Gaussian Noise on Neuronal Firings in a Heterogeneous Neuronal Network 215
1 Introduction 215
2 Equations of the Network 216
3 Measurement 216
4 Results 217
5 Conclusions 218
References 219
Stochastic Evolution Model of Neuronal Oscillator Population Under the Condition of the Variable Higher Order Coupling 220
1 Introduction 220
2 Stochastic Evolution Model of Neuronal Oscillator Population Under the Condition of the Variable Higher Order Coupling 221
3 Analysis of the Numerical Calculation Results 222
4 Conclusion 224
References 225
Qualitative Analysis in Locally Coupled Neural Oscillator Network 226
1 Introduction 226
2 Mathematical Model 227
3 Model analysis 228
3.1 Oscillating Conditions for Single Oscillator 228
3.2 Synchronization of Locally Coupled Wilson--Cowan Oscillators 229
4 Conclusions 230
References 230
Determination of the Number Ratio Between Excitation Neurons and Inhibitory Neurons in Activities of Neural Networks 231
1 Introduction 231
2 Dynamic Model in Spontaneous Behavior 232
3 Analysis on Stability 232
3.1 Critical State 232
3.2 Balance Value Changes in Subarea 235
4 Conclusion 235
References 236
Part V Firing Oscillations and Patterns in Neuronal Networks 237
Transition Mechanisms Between Periodic and Chaotic Bursting Neurons 238
1 Introduction 238
2 Dynamics Behavior of Bursting Neurons 239
3 Poincar Maps 240
4 Conclusions and Discussion 241
References 242
Dynamical Characteristics of the Fractional-Order FitzHugh-Nagumo Model Neuron 243
1 Introduction 243
2 Bifurcation Behavior of the Fractional-Order Model Neuron 244
3 Firing Frequency of the Fractional-Order Model Neuron 246
4 Conclusion 247
References 248
Dynamics Analysis of the Hyperpolarized Model for Bursting Calcium Oscillations in Non-excitable Cells 249
References 253
Effect of Temperature on Synchronization Phenomena in Coupled Spiking Neuron Models 254
1 Introduction 254
2 A Pair of Coupled Neurons 255
3 Effects of Temperature on Firing Duration, PRC and Synchrony 255
4 Conclusion 257
References 257
Synchronization Transitions of Small-World Neuronal Networks 259
1 Introduction 259
2 Model Description 260
3 Impact of Delay on Synchronization 260
4 Conclusion 262
References 262
Bursting Regularity in Complex Networks of Neurons with Chemical Synapses 264
1 Introduction 264
2 Rhythm Dynamics of the Bursting Neurons 265
3 Rhythm Dynamics of the Complex Neural Networks 265
4 Conclusion 267
References 267
Burst Synchronization in a Small-World Neuronal Network with Coupling Delays 269
1 Introduction 269
2 Model 270
3 Main Results and Discussion 270
3.1 Phase Synchronization and Burst Synchronization 270
3.2 The Effect of Noise on Phase Synchronization and Burst Synchronization 271
References 274
Correlation-Induced Phase Synchronization in Bursting Neurons 275
1 Introduction 275
2 Model 276
3 Results and Discussion 276
4 Summary 278
References 279
Synchronization of Small-World Neuronal Networks with Synapse Plasticity 280
1 Introduction 280
2 The Mathematical Model 281
3 Simulation Results 281
4 Conclusion 284
References 284
A Modeling Study of Glutamate Release of NMDA Receptors 285
1 Introduction 285
2 Model 286
3 Results 286
References 288
Experimental Discovery of a Complex Bifurcation Scenario from Period 1 Bursting to Period 1 Spiking 290
1 Introduction 290
2 Theoretical Model and Simulation Results 291
3 Experimental Model and Results 292
4 Discussion and Conclusion 293
References 293
Exploring the Asymmetrical Cortical Activity in Motor Areas Using Support Vector Machines 294
1 Introduction 294
2 Methods 295
2.1 SVM 295
2.2 Permutation Test, Dimensionality Reduction and Pre-processing 296
3 Applying SVM with Different Inputs to fMRI Data 296
3.1 Material 296
3.2 SVM with the Input of the Average Volume 296
3.3 SVM with the Input of a Single Volume 297
4 Conclusion 297
References 297
Strange Non-chaotic Attractors in Noisy FitzHugh-Nagumo Neuron Model 298
1 Introduction 298
2 The Bifurcation Characteristic of the Periodically Driven FHN Neuron Model 299
3 The Strange Non-chaotic Attractor in FHN Neuron 299
4 Conclusions 303
References 303
Pattern Discrimination on Deterministic and Noise-Induced Impulses in Neural Spike Trains 304
1 Introduction 304
2 The ISI-Distance Method and Analysis 305
3 Conclusion 306
References 307
Desynchrony in Two Chaotic Neurons with Uncertain Couple and Mix-Adaptive Feedback 309
1 Introduction 309
2 Main Result 310
3 Numerical Simulation 311
References 313
Outer Synchronization of Coupled Discrete-Time Networks with Time Delay 314
1 Introduction 314
2 Model Presentation and Synchronization Analysis 315
3 Numerical Example 316
4 Conclusion 317
References 317
Part VI Brain Imaging, EEG, MEG 318
Phase Resetting on Scalp EEG, Study on Its Synchrony and Distribution 319
1 Introduction 319
2 Materials and Methods 320
3 Results 320
4 Conclusions 322
References 322
The Interaction Between the Parietal and Motor Areas in Dynamic Imagery Manipulation: An fMRI Study 324
1 Introduction 324
2 Materials and Methods 325
3 Results 326
4 Discussion 327
References 328
An fMRI Investigation of the Mental Perspective Shift in Language Comprehension 329
1 Introduction 329
2 Materials and Methods 330
2.1 Participants 330
2.2 Task Procedures 330
2.3 Functional MRI and Image Analysis 331
3 Results and Discussion 331
References 332
Neural Representation of Space for Sound-Source Localization: An fMRI Study 334
1 Introduction 334
2 Materials and Methods 335
3 Results and Discussion 336
References 337
Investigating Causality Between Interacting Brain Areas with Multivariate Autoregressive Models of MEG Sensor Data 338
1 Introduction 338
2 Multivariate Modelling of MEG Data 339
3 Simulated Brain Dipole 340
4 Confidence Intervals of PDC 341
5 Stationarity Assessment 341
6 Results 342
6.1 PDC from Projected MAR Model Is Close to Ideal 342
6.2 PDC Deviation from Ideal w.r.t Environment Noise, N of Samples and Model Order 342
6.3 More Principal Components Do Not Improve PDC 344
6.4 Confidence Intervals for PDC 346
7 Conclusions 347
References 347
EEG Feature Extraction During Mental Fatigue and Relaxation by Principal Component Analysis 348
1 Introduction 348
2 Methods 349
2.1 Subjects and Recording Condition 349
2.2 EEG Spectrum Variables 349
2.3 Principal Component Analysis 350
3 Results 350
4 Conclusions 351
References 351
Kernel Granger Causality Mapping Effective Connectivity: A Resting fMRI Study 352
1 Introduction 352
2 Methods 353
2.1 Subjects and Data Acquisition 353
2.2 Data Processing 353
3 Results 353
4 Discussion and Conclusions 354
References 356
EEG Source Localization Based on Multiple fMRI Spatial Patterns 357
1 Introduction 357
2 Methods 358
3 Result 359
4 Discussions 360
References 360
ICA Analysis for Decision-Making Task on fMRI 362
1 Introduction 362
2 Material and Methods 363
2.1 Spatial ICA Model 363
2.2 Decision-Making Task 363
2.3 Data Acquisition and Analysis 364
3 Results 364
4 Conclusion 365
References 365
Single Trial Extraction of Cognitive Evoked Potential by Using EMD Based Method 367
1 Introduction 367
2 EMD-Based Method 368
3 Discuss 369
4 Concluding Remarks 370
References 370
Multiple Neural Networks Involved in Chewing Gum: A Functional MRI Study Using Group-ICA 372
1 Introduction 372
2 Materials and Method 373
2.1 Subjects and Task Paradigm 373
2.2 Data Acquisition 373
2.3 Data Analysis 374
3 Results 375
4 Discussions 375
5 Conclusions 377
References 377
Part VII Sensory and Motor Dynamics 379
Dynamic Form Templates Determine Sensitivity to Biological Motion 380
1 Motion Integration for Simple and Biological Motion 380
2 Template Model for Biological Motion Perception 381
3 Human Experiments and Model Simulations 382
4 Discussion and Conclusion 383
References 383
Bistable Alternation of Point-Light Biological Motion 385
1 Introduction 385
2 Methods 386
3 Results 387
4 Discussion 388
References 389
Influence of Feedback Signals from Cats Area 21a on Contrast Response Function of Area 17 Neurons 390
1 Introduction 390
2 Results and Discussion 391
References 395
Compensating Neural Transmission Delays by Dynamical Routing 397
1 Introduction 397
2 Dynamical Routing in Visual Information Processing 398
3 Conclusions 401
References 401
Retinotopic Sparse Representation of Natural Images 402
1 Introduction 402
2 Retinotopic Sparse Representation Method 403
3 Simulations 404
4 Conclusions 405
References 405
A Neural Network Model for Image Formation of the Face Through Double-Touch Without Visual Information 407
1 Introduction 407
2 Outline of the Model 408
3 Detail of the Model 409
3.1 Location Pathway 409
3.2 Shape Pathway 410
3.3 Integration of Two Kinds of Information 410
4 Results and Discussion 410
References 411
Population Responses of A-Fiber Nociceptors with Hypothetical Spatial Distributions on Human Forearm 412
1 Introduction 412
2 Methods 413
3 Results and Discussion 414
4 Conclusion 415
References 416
Optimal Model for Selecting Human Arm Posture During Reaching Movement 417
1 Introduction 417
2 Optimization Models for Arm Posture Selection 418
3 Method 419
3.1 Measurement Conditions 420
3.2 Filtering and Analysis 421
3.3 Real-Coded Genetic Algorithms (RCGA) 421
4 Results and Discussion 421
5 Conclusion 422
References 422
Decoding the Grid Cells for Metric Navigation Using the Residue Numeral System 423
1 Introduction 423
2 Model 424
2.1 The Initial Idea 424
2.2 TRC-Based Model 426
3 Discussion and Conclusion 426
References 428
Discussion on Rhythmic Gait Movement Affected by Cerebral Cortex Signal 429
1 Introduction 429
2 Biology CPG Model 430
3 Modified CPG Model 431
4 Simulation Results 432
References 435
Re-optimization Contributes to the Adaption of External VF Field 436
1 Introduction 436
2 Materials and Model 437
3 Results 438
4 Conclusion 439
References 439
Vector Sum of Two Eyes Images Might Be an Important Cue in Human Visual System 441
1 Introduction 441
2 Perceptual Performance of an Approaching Object 442
2.1 Perceptual Performance of an Approaching Object in Periphery Visual Field 442
2.2 Perceptual Performance of an Approaching Object in Central Visual Field 444
3 Conclusion 444
References 445
A Spatial Temporal Integration Model of Primary Visual Cortex Concerning Directional Selectivity 446
1 Introduction 446
2 Model Description 447
2.1 Feedforward Afferent 448
2.2 Short-Range Competition 448
2.3 Long-Range Interaction 448
3 Results 449
4 Conclusion 451
References 452
Periodic Motion Control of Human Arm Movement Based on CPG model 453
1 Introduction 453
2 Rotate Crank Device and CPG Model 454
2.1 Rotate Crank Device 454
2.2 CPG Model of Human Arm 455
3 Comparison 457
4 Conclusion 457
References 458
Part VIII Global Cognitive Function 459
A Neurodynamical Approach to Visual Affordances: The Selective Attention for Action Model (SAAM) 460
1 Introduction 460
2 The Selective Attention for Action Model (SAAM) 461
3 Studies: Single-Object Inputs and Two-Object Inputs 462
4 Conclusion and Outlook 463
References 464
A Comparative Analysis on Adaptive Modelling of Induced Feelings 465
1 Introduction 465
2 Dynamics of Emotional Responses and Feelings 466
3 Integrating Adaptation Models for the Induction Strengths 469
4 Example Simulation Results 470
5 Comparative Analysis of the Three Adaptation Models 474
5.1 Comparison of Simulation Results 475
5.2 Equilibrium for Activation Level of Preparation State 476
5.3 Hebbian Approach 477
5.4 Temporal Discounting Approach 478
5.5 Memory Traces Approach 478
6 Discussion 479
References 480
Modelling Trust Dynamics from a Neurological Perspective 481
1 Introduction 481
2 On the Interaction Between Affective and Cognitive Aspects 482
3 Incorporating Affective Aspects in a Trust Model 484
4 The Hebbian Adaptation Process 488
5 Example Simulation Results 488
6 Verification of Functional Properties of Trust 490
7 Discussion 492
References 493
Novel Bionic Model for Pattern Recognition 495
1 Introduction 495
2 Model Description 496
2.1 Network Dynamics 496
2.2 Network Learning 497
3 Results 497
4 Conclusions 498
References 498
Local Self-Adaptation Mechanisms for Large-Scale Neural System Building 500
1 Introduction 500
2 Dynamic Neural Fields 501
3 Experimental Setup 502
4 Dynamic Adaptation of Membrane Potential 503
4.1 Experiments and Results 503
5 Dynamic Adaptation of Firing Rates 503
5.1 Experiments and Results 505
6 Combination of Dynamic Adaptation Methods 505
7 Discussion 506
8 Conclusion 507
References 507
Functions of Shallow vs. Deep Theta-Nested Gamma in Object Recognition 509
1 Introduction 509
2 Material and Methods 510
2.1 Subject and Experimental Recordings 510
2.2 Model 510
3 Results 512
3.1 Computational vs. Experimental Results 512
3.2 Functions of Shallow Theta-Nested Gamma Rhythm 514
4 Discussion 515
References 515
Part IX Multiscalar Neurodynamics From Physiology to Systems Theory 517
Modelling the Hypothalamic Control of Thalamic Synchronization Along the Sleep-Wake Cycles 518
1 Introduction 518
2 Model Structure and Equations 519
3 Simulation Results 522
4 Discussion 523
References 524
Stochastic Resonance and Stochastic Encoding: Cooperative Effects of Noise and Intrinsic Dynamics in a Model Neuron with Subthreshold Oscillations 526
1 Introduction 526
2 Methods: Model Equations 527
3 Results 528
4 Discussion 529
References 529
Attention Modulation of Sensory Systems 531
1 Introduction 531
2 Models 532
2.1 Neural Network of Insect Antennal Lobe 532
2.2 Population Model of Olfactory Cortex 533
2.3 Network Model of Visual Cortex 533
3 Simulation Results 534
3.1 Attention Modulation Enhances System Sensitivity 534
3.2 Neuromodulation Enhances Learning and Memory 535
3.3 Attention Effects During Visual Stimulation 536
4 Discussion 537
References 537
Evidence for a Spatiotemporal Singularity in Percept Formation by Cerebral Cortex 538
1 Introduction 538
2 Methods 539
2.1 Experimental Methods 539
2.2 Theoretical Methods 540
3 Results 541
3.1 Experimental Results 541
3.2 Theoretical Results 544
4 Discussion 545
4.1 A Proposed Neural Mechanism of the Null Spike 545
4.2 Interpretation of the Role of the Null Spike in Perception 546
References 548
Nonequilibrium Behavior in Neural Networks: Criticality and Optimal Performance 550
1 Introduction 550
2 Model and Results 551
References 556
Part X Neural Computing 557
A Hierarchial Model for Visual Perception 558
1 Introduction 558
2 The Hierarchical Model 559
2.1 Local Sparse Feature Encoding 559
2.2 Population Feature Encoding 560
2.3 Perceptual Space Embedding 561
3 The Experiment 561
3.1 Image Retrieval 563
4 Discussion and Conclusion 563
References 564
An Orientational Sensitive Vision Model Based on Biological Retina 565
1 Introduction 565
2 Retina Cells 566
3 Receptive Fields 567
4 Results 568
5 Discussions 569
References 569
Recurrent Neural Networks for Local Model Prediction 570
1 Introduction 570
2 Vector Quantization and Forecasting 571
3 RNN with Local Approach 572
4 Experimental Results 575
5 Conclusion 576
References 576
Single-Trial Electrical Perception Recognition via Single-Channel Electroencephalogram 578
1 Introduction 578
2 Methods 579
2.1 Data Acquisition 579
2.2 Templet Set-Up and EEG Segment 579
2.3 Feature Extraction 580
2.4 Single-Trial Estimation Based on BP Neural Network 581
3 Conclusion 581
References 582
Sleep Quality Analysis Based on HHT 583
1 Introduction 583
2 Experiment and Results 584
3 Conclusion and Discussions 586
References 586
Modelling the Stroop Effect: Dynamics in Inhibition of Automatic Stimuli Processing 588
1 Introduction 588
2 Methods 589
3 Results 591
4 Conclusions 592
References 592
A New Support Vector Machine Algorithm with Scalable Penalty Coefficients for Training Samples 593
1 Introduction 593
2 Algorithms Design 594
2.1 Determination of Ci 594
2.2 Modification to the SMO Algorithm 596
3 Experiment and Result Analysis 596
4 Conclusion 597
References 597
Recognition of Epileptic EEG Using Support Vector Machines 598
1 Introduction 598
2 Support Vector Machine 599
3 Methods 599
3.1 Clinical Data 599
3.2 Processing of EEG Using DWT 600
3.3 Approximate Entropy (ApEn) Estimation 600
4 Experimental Results 600
5 Conclusion and Future Work 601
References 601
Image Denoising Using Noisy Chaotic Neural Networks 603
1 Introduction 603
2 The Noisy Chaotic Neural Network for Image Denoising 604
3 Conclusion 606
References 606
Increase Productivity in Circuit Board Manufacturing Through Support Vectors 607
1 Introduction 607
2 Surface Mount Technology Production Line Components 608
3 SVM Used in SMT-Based Production Line 609
4 Discussions 611
References 611
Part XI Emerging Technologies for Brain Computer Interfaces 612
Towards Affective BCI/BMI Paradigms Analysis of fEEG and fNIRS Brain Responses to Emotional Speech and Facial Videos 613
1 Introduction 613
2 Methods 614
3 Conclusions 616
References 617
Imagery Movement Paradigm User Adaptation Improvement with Quasi-movements Phenomenon 618
1 Introduction 618
2 Methods 619
3 Results and Conclusions 620
References 622
High Resolution Common Spatial Frequency Filters for Classifying Multi-class EEG 623
1 Introduction 623
2 Method 624
3 Results and Discussions 625
4 Conclusion 628
References 628
Suitable ICA Algorithm for Extracting Saccade-Related EEG Signals 629
1 Introduction 629
2 Experimental Settings 630
3 Experimental Results 631
4 Conclusion 632
References 633
EEG Based Brain-Computer Interface System for Remote Vehicle Controlling 634
1 Introduction 634
2 Methods 635
3 System Design and Experiments 635
3.1 System Architecture 635
3.2 Experiments and Data Acquisition 636
4 Results and Analysis 636
5 Discussion 638
References 638
Channel Selection for Motor Imagery-Based BCIs: A Semi-supervised SVM Algorithm 639
1 Introduction 639
2 A Semi-supervised SVM Algorithm for Channel Selection 640
3 Data Analysis 641
4 Conclusions 642
References 643
Part XII Neural Dynamics of Brain Disorders 644
On the Early Diagnosis of Alzheimers Disease from EEG Signals: A Mini-Review 645
1 Introduction 645
2 Analysis of EEG of MCI and AD Patients 646
2.1 Slowing of EEG 646
2.2 Reduced Complexity of EEG Signals 646
2.3 Perturbations in EEG Synchrony 647
3 Discussion 647
4 Conclusions 648
References 649
Analysis of EEG Time Series Recorded from Alzheimer Patients Based on Their Spectral Content 653
1 Introduction 653
2 Method 654
2.1 Model 654
2.2 Computation 655
3 Results 655
4 Conclusion 656
References 657
Modeling Transient Oscillations in the EEG of Patients with Mild Cognitive Impairment 658
1 Introduction 658
2 Methods 659
3 Results and Discussion 660
References 662
Discrimination of the Sleeping EEG by the Adaptive Rhythmic Component Extraction 663
1 Introduction 663
2 Rhythmic Component Extraction 664
3 Experimental Procedure 664
4 Results and Discussions 665
5 Conclusions 666
References 666
Analyzing EEG of Quasi-brain-death Based on Approximate Entropy Measures 668
1 Introduction 668
2 EEG Analysis with Complexity Measures 669
3 EEG Data Analysis with Active Complexity 670
3.1 EEG Signals and Brain Activity 670
3.2 ApEn of Patients in Coma and Quasi-brain-death States 670
3.3 Dynamic Complexity for Coma and Quasi-brain-death 670
3.4 Evaluation of All Patients' EEG ApEn Results 671
4 Conclusion 672
References 672
Complexity Analysis of EEG Data with Multiscale Permutation Entropy 673
1 Introduction 673
2 Materials and Methods 674
2.1 Animal Experiments and EEG Series 674
2.2 Multiscale Permutation Entropy (MPE) 674
3 Results 675
3.1 Numerical Simulation Analysis of Chaotic System 675
3.2 MPE Analysis of EEG 676
4 Conclusions 677
References 677
Cueing-Dependent Activity in Bilateral M1 in Parkinsons Disease 678
1 Introduction 678
2 Methods 679
2.1 Procedure and Data Acquisition 679
2.2 Data Analysis 680
2.2.1 Source reconstruction 680
2.2.2 Time-frequency analysis 680
2.3 Statistics 681
3 Results 681
4 Conclusion 682
References 683
Index 684

Produkt-Details

• Erscheint lt. Verlag: 6.1.2011
• Reihe/Serie: Advances in Cognitive Neurodynamics
• Zusatzinfo: XXII, 756 p.
• Verlagsort: Dordrecht
• Sprache: englisch
• Themenwelt: Geisteswissenschaften
• Themenwelt: Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
• Themenwelt: Studium ► 1. Studienabschnitt (Vorklinik) ► Biochemie / Molekularbiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Humanbiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Zoologie
• Themenwelt: Naturwissenschaften ► Physik / Astronomie
• Themenwelt: Technik
• Schlagworte: Cogintion • Computational Neuroscience • Neural Engineering • Neurodynamics • Realistic neural network
• ISBN-10: 90-481-9695-7 / 9048196957
• ISBN-13: 978-90-481-9695-1 / 9789048196951