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Natural and Artificial Computation for Biomedicine and Neuroscience

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Cover of 'Natural and Artificial Computation for Biomedicine and Neuroscience'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Robot’s and Human’s Self: A Computational Perspective
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    Chapter 2 A Neurologically Inspired Network Model for Graziano’s Attention Schema Theory for Consciousness
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    Chapter 3 Multilevel Darwinist Brain: Context Nodes in a Network Memory Inspired Long Term Memory
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    Chapter 4 Motivational Engine for Cognitive Robotics in Non-static Tasks
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    Chapter 5 Execution of Written Tasks by a Biologically-Inspired Artificial Brain
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    Chapter 6 A Cognitive Architecture Framework for Critical Situation Awareness Systems
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    Chapter 7 A Conductance-Based Neuronal Network Model for Color Coding in the Primate Foveal Retina
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    Chapter 8 Simulative Models to Understand Numerical Cognition
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    Chapter 9 Restoration Model for Attenuated Low Spatial Frequencies in the Retinal Output
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    Chapter 10 Assessment and Comparison of Evolutionary Algorithms for Tuning a Bio-Inspired Retinal Model
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    Chapter 11 Efficient Localization in Edge Detection by Adapting Articial Bee Colony (ABC) Algorithm
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    Chapter 12 Electric Vehicle Charging Scheduling Using an Artificial Bee Colony Algorithm
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    Chapter 13 Protein Folding Modeling with Neural Cellular Automata Using the Face-Centered Cubic Model
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    Chapter 14 A Memetic Algorithm for Due-Date Satisfaction in Fuzzy Job Shop Scheduling
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    Chapter 15 Indicator-Based Evolutionary Level Set Approximation: Mixed Mutation Strategy and Extended Analysis
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    Chapter 16 Genetic Algorithm for Scheduling Charging Times of Electric Vehicles Subject to Time Dependent Power Availability
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    Chapter 17 Simulation of a Dynamic Prey-Predator Spatial Model Based on Cellular Automata Using the Behavior of the Metaheuristic African Buffalo Optimization
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    Chapter 18 An Innovative Tool to Create Neurofeedback Games for ADHD Treatment
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    Chapter 19 Conditional Entropy Estimates for Distress Detection with EEG Signals
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    Chapter 20 Nonlinear Symbolic Assessment of Electroencephalographic Recordings for Negative Stress Recognition
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    Chapter 21 Recent Advances and Challenges in Nonlinear Characterization of Brain Dynamics for Automatic Recognition of Emotional States
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    Chapter 22 Towards Assistive Solutions for People with Central Vision Loss
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    Chapter 23 Performance of Predicting Surface Quality Model Using Softcomputing, a Comparative Study of Results
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    Chapter 24 Temporal Dynamics of Human Emotions: An Study Combining Images and Music
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    Chapter 25 Memory Effect in Expressed Emotions During Long Term Group Interactions
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    Chapter 26 Setting the Parameters for an Accurate EEG (Electroencephalography)-Based Emotion Recognition System
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    Chapter 27 Exploring the Physiological Basis of Emotional HRI Using a BCI Interface
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    Chapter 28 Preliminary Study on Unilateral Sensorineural Hearing Loss Identification via Dual-Tree Complex Wavelet Transform and Multinomial Logistic Regression
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    Chapter 29 On a Heavy-Tailed Intensity Normalization of the Parkinson’s Progression Markers Initiative Brain Database
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    Chapter 30 Case-Based Statistical Learning: A Non Parametric Implementation Applied to SPECT Images
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    Chapter 31 PET Image Classification Using HHT-Based Features Through Fractal Sampling
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    Chapter 32 A 3D Convolutional Neural Network Approach for the Diagnosis of Parkinson’s Disease
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    Chapter 33 Non-linear Covariance Estimation for Reconstructing Neural Activity with MEG/EEG Data
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    Chapter 34 Automatic Separation of Parkinsonian Patients and Control Subjects Based on the Striatal Morphology
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    Chapter 35 Emotion Assessment Based on Functional Connectivity Variability and Relevance Analysis
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    Chapter 36 MRI-Based Feature Extraction Using Supervised General Stochastic Networks in Dementia Diagnosis
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    Chapter 37 Influence of Population Dependent Forward Models on Distributed EEG Source Reconstruction
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    Chapter 38 Influence of Anisotropic Blood Vessels Modeling on EEG Source Localization
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    Chapter 39 Brain White Matter Lesion Segmentation with 2D/3D CNN
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    Chapter 40 Circadian Modulation of Sleep-Wake Dynamics Evaluated by Transition Probabilities
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    Chapter 41 EEG Source Imaging Based on Dynamic Sparse Coding as ADHD Biomarker
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    Chapter 42 Identification of Nonstationary Brain Networks Using Time-Variant Autoregressive Models
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    Chapter 43 Detection of EEG Dynamic Changes Due to Stimulus-Related Activity in Motor Imagery Recordings
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    Chapter 44 Sleep Stages Clustering Using Time and Spectral Features of EEG Signals
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    Chapter 45 Segment Clustering for Holter Recordings Analysis
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    Chapter 46 Towards a Deep Learning Model of Retina: Retinal Neural Encoding of Color Flash Patterns
Attention for Chapter 33: Non-linear Covariance Estimation for Reconstructing Neural Activity with MEG/EEG Data
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Chapter title
Non-linear Covariance Estimation for Reconstructing Neural Activity with MEG/EEG Data
Chapter number 33
Book title
Natural and Artificial Computation for Biomedicine and Neuroscience
Published by
Springer, Cham, June 2017
DOI 10.1007/978-3-319-59740-9_33
Book ISBNs
978-3-31-959739-3, 978-3-31-959740-9
Authors

L. Duque-Muñoz, J. D. Martinez-Vargas, G. Castellanos-Dominguez, J. F. Vargas-Bonilla, J. D. López

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 20%
Student > Bachelor 1 20%
Student > Doctoral Student 1 20%
Unknown 2 40%
Readers by discipline Count As %
Engineering 3 60%
Unknown 2 40%