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Brain Informatics and Health

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Cover of 'Brain Informatics and Health'

Table of Contents

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    Book Overview
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    Chapter 1 Robust Neuron Counting Based on Fusion of Shape Map and Multi-cue Learning
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    Chapter 2 Identification of Relevant Inter-channel EEG Connectivity Patterns: A Kernel-Based Supervised Approach
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    Chapter 3 Computational Role of Astrocytes in Bayesian Inference and Probability Distribution Encoding
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    Chapter 4 An Automatic Neuron Tracing Method Based on Mean Shift and Minimum Spanning Tree
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    Chapter 5 Graph Theoretic Compressive Sensing Approach for Classification of Global Neurophysiological States from Electroencephalography (EEG) Signals
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    Chapter 6 Fast Marching Spanning Tree: An Automatic Neuron Reconstruction Method
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    Chapter 7 On Simple Models of Associative Memory: Network Density Is Not Required for Provably Complex Behavior
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    Chapter 8 Human Emotion Variation Analysis Based on EEG Signal and POMS Scale
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    Chapter 9 Visual Information Processing Mechanism Revealed by fMRI Data
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    Chapter 10 Research About Alpha EEG Asymmetry and Self-consciousness in Depression
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    Chapter 11 The Situation Model in Text Reading: Evidence from an Eye Movement Study
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    Chapter 12 Alterations in Emotional and Salience Responses to Positive Stimuli in Major Depressive Disorder
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    Chapter 13 Pattern Classification and Analysis of Memory Processing in Depression Using EEG Signals
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    Chapter 14 A Comprehensive Feature and Data Mining Study on Musician Memory Processing Using EEG Signals
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    Chapter 15 Thought Chart: Tracking Dynamic EEG Brain Connectivity with Unsupervised Manifold Learning
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    Chapter 16 User Interests Analysis and Its Application on the Linked Brain Data Platform
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    Chapter 17 Content-Based fMRI Brain Maps Retrieval
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    Chapter 18 A Domain-Driven Literature Retrieval Method for Systematic Brain Informatics
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    Chapter 19 A Provenance Driven Approach for Systematic EEG Data Analysis
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    Chapter 20 Concept Recognition of Depression Drugs in Biomedical Literatures Using the Domain Relevance Measure
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    Chapter 21 Brain Knowledge Graph Analysis Based on Complex Network Theory
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    Chapter 22 Relation Inference and Type Identification Based on Brain Knowledge Graph
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    Chapter 23 A Simple Distance Based Seizure Onset Detection Algorithm Using Common Spatial Patterns
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    Chapter 24 A Conversational Agent for an Online Mental Health Intervention
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    Chapter 25 Acute Stress Detection Using Recurrence Quantification Analysis of Electroencephalogram (EEG) Signals
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    Chapter 26 Prediction of Seizure Spread Network via Sparse Representations of Overcomplete Dictionaries
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    Chapter 27 A Novel Mutual-Information-Guided Sparse Feature Selection Approach for Epilepsy Diagnosis Using Interictal EEG Signals
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    Chapter 28 Clique Identification and Propagation for Multimodal Brain Tumor Image Segmentation
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    Chapter 29 Cross Subject Mental Work Load Classification from Electroencephalographic Signals with Automatic Artifact Rejection and Muscle Pruning
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    Chapter 30 EEG Topography and Tomography (sLORETA) in Analysis of Abnormal Brain Region for Mild Depression
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    Chapter 31 Evaluation of Depression Severity in Speech
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    Chapter 32 A Noninvasive Real-Time Solution for Driving Fatigue Detection Based on Left Prefrontal EEG and Eye Blink
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    Chapter 33 Detection of SNr Recordings Basing upon Spike Shape Classes and Signal’s Background
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    Chapter 34 Influence of Spatial Learning Perspectives on Navigation Through Virtual Reality Environment
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    Chapter 35 Brain-Inspired Obstacle Detection Based on the Biological Visual Pathway
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    Chapter 36 A Probabilistic Method for Linking BI Provenances to Open Knowledge Base
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    Chapter 37 Using Decision Trees to Analyse Brain Signals in Spacial Activities
Attention for Chapter 5: Graph Theoretic Compressive Sensing Approach for Classification of Global Neurophysiological States from Electroencephalography (EEG) Signals
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13 Mendeley
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Chapter title
Graph Theoretic Compressive Sensing Approach for Classification of Global Neurophysiological States from Electroencephalography (EEG) Signals
Chapter number 5
Book title
Brain Informatics and Health
Published in
Lecture notes in computer science, September 2016
DOI 10.1007/978-3-319-47103-7_5
Book ISBNs
978-3-31-947102-0, 978-3-31-947103-7
Authors

Mohammad Samie Tootooni, Miaolin Fan, Rajesh Sharma Sivasubramony, Chun-An Chou, Vladimir Miskovic, Prahalada K. Rao

Editors

Giorgio A. Ascoli, Michael Hawrylycz, Hesham Ali, Deepak Khazanchi, Yong Shi

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 38%
Researcher 2 15%
Professor 1 8%
Lecturer 1 8%
Student > Master 1 8%
Other 1 8%
Unknown 2 15%
Readers by discipline Count As %
Engineering 4 31%
Computer Science 2 15%
Linguistics 1 8%
Physics and Astronomy 1 8%
Psychology 1 8%
Other 0 0%
Unknown 4 31%