Brain Informatics

Name: Brain Informatics | International Conference, BI 2017, Beijing, China, November 16-18, 2017, Proceedings
Brand: Springer
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International Conference, BI 2017, Beijing, China, November 16-18, 2017, Proceedings

Yi Zeng Yong He Jeanette Hellgren Kotaleski Maryann Martone Bo Xu Hanchuan Peng Qingming Luo(Editor)

Springer (Publisher)

Published on 2. November 2017

XVI, 336 pages

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978-3-319-70772-3 (ISBN)

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Content

Intro
Preface
Organization
Contents
Cognitive and Computational Foundations of Brain Science
Speech Emotion Recognition Using Local and Global Features
1 Introduction
2 Materials and Methods
2.1 Database
2.2 Features for Speech Emotion Recognition
3 Results/Discussion
3.1 Classification Results for EMODB
3.2 Classification Results for RAVDESS
3.3 SFFS
4 Conclusions
References
Advertisement and Expectation in Lifestyle Changes: A Computational Model
1 Introduction
2 Temporal-Causal Modeling
3 The Computational Model
3.1 Graphical Representation of the Model
3.2 Numerical Representations and Parameters
4 Simulation Experiments
4.1 Hypotheses
4.2 Scenarios and Results
4.3 Explanation
5 Conclusion
References
A Computational Cognitive Model of Self-monitoring and Decision Making for Desire Regulation
Abstract
1 Introduction
2 Background
3 Conceptual Representation of the Model
3.1 Desire Generation and Choosing Actions
3.2 Self-monitoring and Regulation Strategies
3.3 Numerical Representation of the Model
4 Simulation Results
5 Conclusion
References
Video Category Classification Using Wireless EEG
Abstract
1 Introduction
2 Experimental Setup and Data Acquisition Techniques
2.1 Demographics of Subjects
2.2 EEG Recordings
2.3 Experimental Setup
3 Experimental Study and Findings
3.1 Algorithms and Methods
3.2 Experimental Results
4 Discussion
5 Conclusion
References
Learning Music Emotions via Quantum Convolutional Neural Network
1 Introduction
2 Related Work on Quantum Information
3 Quantum Convolutional Neural Network for Music Emotion Analysis
3.1 Rationale
3.2 Quantum Convolutional Neural Network
4 Experiments
5 Conclusions
References
Supervised EEG Source Imaging with Graph Regularization in Transformed Domain
1 Introduction
2 Inverse Problem
3 Graph Regularized EEG Source Imaging in Transformed Domain
3.1 EEG Source Imaging in Transformed Domain
3.2 Discriminative Source Reconstruction with Graph Regularization
4 Optimization with ADMM Algorithm
5 Numerical Experiment
6 Conclusion
References
Insula Functional Parcellation from FMRI Data via Improved Artificial Bee-Colony Clustering
1 Introduction
2 Related Content
2.1 Insula Functional Parcellation Based on FMRI Data
2.2 Artificial Bee Colony (ABC) Algorithm
3 DABCC Algorithm
3.1 Food Source Representation
3.2 Initialization
3.3 Self-adaptive Multidimensional Search Mechanism Based on Difference Bias for Employed Bee Search
3.4 Algorithm Description
4 Experimental Results and Analysis
4.1 Data Description and Preprocessing
4.2 Evaluation Metrics
4.3 Search Capability
4.4 Parcellation Results
4.5 Functional Consistency
5 Conclusion
References
EEG-Based Emotion Recognition via Fast and Robust Feature Smoothing
1 Introduction
2 Related Work
3 Moving Average Smoothing on Statistical Feature Set
3.1 Feature Extraction
3.2 Moving Average Smoothing on Extracted Features
3.3 Classification Algorithm
4 Emotion Recognition on DEAP Dataset
4.1 Experimental Setup
4.2 Results and Discussions
5 Conclusion
References
Human Information Processing Systems
Stronger Activation in Widely Distributed Regions May not Compensate for an Ineffectively Connected Neural Network When Reading a Second Language
Abstract
1 Introduction
2 Methods
2.1 Participants
2.2 Materials
2.3 Experimental Procedure
2.4 Data Acquisition
2.5 Data Processing
3 Results
4 Discussion
4.1 Assimilated and Accommodated Neural Network for L2
4.2 Stronger Activation but an Ineffectively Connected Neural Network
Acknowledgments
References
Objects Categorization on fMRI Data: Evidences for Feature-Map Representation of Objects in Human Brain
Abstract
1 Introduction
2 Method
2.1 Subjects and fMRI Data Acquisition
2.2 Stimuli and Experimental Procedure
2.3 Data Preprocessing
2.4 Voxel Selection
2.5 SVM Method
3 Results
3.1 Classification Results for One vs. One Classifiers
3.2 Classification Results for One vs. Two Classifiers
3.3 Classification Results for Two vs. Two Classifiers
3.4 Classification Results for Regions Maximally Responsive to One Category of Objects
4 Discussion and Conclusions
Acknowledgments
References
Gender Role Differences of Female College Students in Facial Expression Recognition: Evidence from N170 and VPP
Abstract
1 Introduction
2 Materials and Methods
2.1 Participants
2.2 Stimuli
2.3 Experimental Procedure
2.4 Behavioral Data Analysis
2.5 EEG Recordings and Analysis
3 Results
3.1 Behavioral Results
3.2 ERP Results
4 Discussion
4.1 Gender Role Differences on Facial Expression Recognition: Evidence on Early ERP Components
4.2 Emotional Negativity Bias: Evidence on VPP
4.3 Emotion Congruency: Evidence on Behavior
5 Conclusion
Acknowledgments
References
Brain Big Data Analytics, Curation and Management
Overview of Acquisition Protocol in EEG Based Recognition System
Abstract
1 Introduction
2 Signal Acquisition
2.1 The Noninvasive Electroencephalography Method
3 EEG Signal Based Recognition System
3.1 Relaxation
3.2 Motor/Non-motor Imaginary
3.3 Exposed to Stimuli (Evoked Potentials)
4 Analysis and Discussions
5 Conclusion
Acknowledgments
References
A Study on Automatic Sleep Stage Classification Based on Clustering Algorithm
Abstract
1 Introduction
2 Related Work
3 Automatic Sleep Staging Classification Algorithm Based on K-Means Clustering
3.1 Denoising
3.2 Feature Extraction and Feature Selection
3.3 Automatic Sleep Stage Classification Based on Improving K-Means Algorithm
4 Experimental Results and Analysis
4.1 Sleep Data Set
4.2 Evaluation Metrics
4.3 Experimental Results and Discussion
5 Conclusion
References
Speaker Verification Method Based on Two-Layer GMM-UBM Model in the Complex Environment
1 Introduction
2 Methods
2.1 Voice Data Acquisition and Preprocessing
2.2 Feature Extraction
2.3 Speaker Verification Architecture Based on Two-Layer GMM-UBM Model
3 Results
3.1 Evaluation Criterion
3.2 GMM-UBM Speaker Verification Based on Segmented Voice Data
3.3 GMM-UBM Speaker Verification Based on Continuous Long-Term Voice Data
4 Discussion
References
Emotion Recognition from EEG Using Rhythm Synchronization Patterns with Joint Time-Frequency-Space Correlation
1 Introduction
2 Architecture of Emotional Recognition Model Based on Rhythm Synchronization Patterns (RSP-ERM)
2.1 Functions of Each Layer
2.2 Defining Emotional States - Class Label
3 Experimental Design
3.1 Data Description
3.2 Learning and Testing Process
3.3 Contrast Methods
4 Experimental Results and Discussion
5 Conclusions
References
Informatics Paradigms for Brain and Mental Health
Patients with Major Depressive Disorder Alters Dorsal Medial Prefrontal Cortex Response to Anticipation with Different Saliences
Abstract
1 Introduction
2 Methods
2.1 Subjects
2.2 Task Design
2.3 Data Acquisition and Analysis
3 Results
3.1 Anticipation Period Findings
3.2 The Findings of Anticipation Effect on Picture Viewing
4 Discussion
Acknowledgment
References
Abnormal Brain Activity in ADHD: A Study of Resting-State fMRI
Abstract
1 Introduction
2 Method
2.1 Dataset
2.2 Image Processing
3 Statistics Analysis
4 Result
4.1 The Comparison of ALFF, fALFF and ReHo Between Two Groups
4.2 The Comparison of ALFF, fALFF and ReHo of Two Age Groups
5 Discussion
Acknowledgements
References
Wearable EEG-Based Real-Time System for Depression Monitoring
1 Introduction
2 Related Work
3 Methodology
4 Making Sense of the Raw Data
4.1 Hardware
4.2 Resting EEG
4.3 Stimulus
4.4 Real-Time Signal Preprocessing
4.5 Feature Extraction
4.6 Classification
4.7 Visualization
5 Experiment
5.1 Participants
5.2 Results
6 Conclusions and Future Work
References
Group Guided Sparse Group Lasso Multi-task Learning for Cognitive Performance Prediction of Alzheimer's Disease
1 Introduction
2 Proposed Method
2.1 Group Guided Sparse Group Lasso Multi-task Learning
2.2 Optimization
3 Experimental Results
3.1 Data and Experimental Setting
3.2 The Results of Comparing with the Comparable Methods
3.3 Identification of MRI Biomarkers
4 Conclusions
References
A Novel Deep Learning Based Multi-class Classification Method for Alzheimer's Disease Detection Using Brain MRI Data
1 Introduction
2 Related Work
3 Proposed Network Architecture
4 Experiments
4.1 Dataset
4.2 Implementation Details
4.3 Results
5 Conclusion
References
A Quantitative Analysis Method for Objectively Assessing the Depression Mood Status Based on Portable EEG and Self-rating Scale
1 Introduction
2 Material and Method
2.1 Experimental Design
2.2 Data Analysis
3 Results
3.1 Depressive Mood Status Assessment Based on POMS-BCN Data
3.2 Validity Test for the Personalized Objective Quantification Model
4 Discussion
References
Workshop on Affective, Psychological and Physiological Computing (APPC 2017)
Social Events Forecasting in Microblogging
Abstract
1 Introduction
2 Related Work
3 Method
3.1 Feature Extraction
3.2 Feature Selection
3.3 Regression Methods
4 Experiment
4.1 Dataset and Labels
4.2 Performance
5 Conclusion
Acknowledgements
References
Study on Depression Classification Based on Electroencephalography Data Collected by Wearable Devices
Abstract
1 Introduction
2 Related Work
3 Experiment Analysis
3.1 Experiment Design
3.2 EEG Data Collection
4 Methodology
4.1 Data Preprocessing and Feature Extraction
4.2 Feature Selection and Classification
5 Results and Discussion
5.1 Results of Depression Classification Accuracy
5.2 Results of Feature Selection
6 Conclusion
Acknowledgment
References
Corticospinal Tract Alteration is Associated with Motor Performance in Subacute Basal Ganglia Stroke
Abstract
1 Introduction
2 Method and Subjects
2.1 Patients
2.2 Image Acquisition
2.3 Motor Evaluation
2.4 Image Process
2.5 Statistical Analysis
3 Results
4 Discussion
References
Detecting Depression in Speech Under Different Speaking Styles and Emotional Valences
Abstract
1 Introduction
2 Method
2.1 Participants
2.2 Experiment
2.3 Data Collection
2.4 Data Preprocessing and Feature Extraction
2.5 Data Analysis
2.5.1 Classification on All-Feature Set
2.5.2 Classification on Interactive Feature Set
2.5.3 Classification on Normalized Feature Set
3 Results
3.1 Performance on All-Feature Set
3.2 Performance on Interactive Feature Set
3.3 Performance on Normalized Feature Set
4 Discussion
5 Conclusion
Acknowledgments
References
Scientific Advances on Consciousness
Abstract
1 Scientific Questions and Relevant Conclusions on Consciousness
2 Modeling Consciousness
3 Discovery of Functional Cells for Consciousness
4 Quantum Uncertainty of Consciousness
5 Interface to Brain in Many Ways
References
Workshop on Big Data and Visualization for Brainsmatics (BDVB 2017)
BECA: A Software Tool for Integrated Visualization of Human Brain Data
Abstract
1 Introduction
2 Design and Implementation
2.1 Architecture
2.2 DTI Tractography Visualization
2.3 sMRI Visualization
2.4 fMRI Visualization
2.5 GPU Accelerated Genome Browser
3 Conclusion
Acknowledgements
References
Workshop on Semantic Technology for eHealth (STeH 2017)
Knowledge Graphs in the Quality Use of Antidepressants: A Perspective from Clinical Research Applications
Abstract
1 Introduction
2 Quality Use of Antidepressants and Information Management Approaches
3 Implementation of Knowledge Graphs
3.1 Analyze Adverse Drug Reactions for Single Antidepressants
3.2 Analyze Single Adverse Drug Reactions
3.3 Analyze Adverse Drug Reactions of Polypharmacy
4 System Evaluation
5 Discussion
References
Using Knowledge Graph for Analysis of Neglected Influencing Factors of Statin-Induced Myopathy
Abstract
1 Background
2 Case Presentation
3 Analysis
4 Conclusion
Acknowledgement
References
Workshop on Mesoscopic Brainformatics (MBAI 2017)
Mesoscopic Brainformatics
Abstract
1 Introduction
2 Meso-Scale Brainformatics
3 The Scope of BraInformatics
4 Brain Information Acquisition and EEG Zero-Reference Technique
5 Brain Information Decoding and Brainwave Music
6 Exploratory Application of Brainformatics and Apparatus-Brain Conversation
7 The Opportunities
8 Potential Challenges
9 Conclusions
Acknowledgements
References
Special Session on Brain Informatics in Neurogenetics (BIN 2017)
The Development and Application of Biochemical Analysis of Saliva in the Assessment of the Activity of Nervous System
Abstract
1 Introduction
2 The Development of Flow Injection Analysis of Salivary-a-Amylase and Its Application in the Evaluation of Stress and Anxiety
3 The Development of HPLC Analysis of Salivary Amino Acids and Its Application in the Assessment of Emotional Reactions During Visual Task
4 The Development of Flow Injection Analysis of Salivary Histidine and Its Application in Assessing Stress
5 Discussion and Conclusion
Acknowledgement
References
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Brain Informatics

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