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Brain Informatics

Overview of attention for book
Cover of 'Brain Informatics'

Table of Contents

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    Book Overview
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    Chapter 1 Speech Emotion Recognition Using Local and Global Features
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    Chapter 2 Advertisement and Expectation in Lifestyle Changes: A Computational Model
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    Chapter 3 A Computational Cognitive Model of Self-monitoring and Decision Making for Desire Regulation
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    Chapter 4 Video Category Classification Using Wireless EEG
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    Chapter 5 Learning Music Emotions via Quantum Convolutional Neural Network
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    Chapter 6 Supervised EEG Source Imaging with Graph Regularization in Transformed Domain
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    Chapter 7 Insula Functional Parcellation from FMRI Data via Improved Artificial Bee-Colony Clustering
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    Chapter 8 EEG-Based Emotion Recognition via Fast and Robust Feature Smoothing
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    Chapter 9 Stronger Activation in Widely Distributed Regions May not Compensate for an Ineffectively Connected Neural Network When Reading a Second Language
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    Chapter 10 Objects Categorization on fMRI Data: Evidences for Feature-Map Representation of Objects in Human Brain
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    Chapter 11 Gender Role Differences of Female College Students in Facial Expression Recognition: Evidence from N170 and VPP
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    Chapter 12 Overview of Acquisition Protocol in EEG Based Recognition System
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    Chapter 13 A Study on Automatic Sleep Stage Classification Based on Clustering Algorithm
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    Chapter 14 Speaker Verification Method Based on Two-Layer GMM-UBM Model in the Complex Environment
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    Chapter 15 Emotion Recognition from EEG Using Rhythm Synchronization Patterns with Joint Time-Frequency-Space Correlation
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    Chapter 16 Patients with Major Depressive Disorder Alters Dorsal Medial Prefrontal Cortex Response to Anticipation with Different Saliences
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    Chapter 17 Abnormal Brain Activity in ADHD: A Study of Resting-State fMRI
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    Chapter 18 Wearable EEG-Based Real-Time System for Depression Monitoring
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    Chapter 19 Group Guided Sparse Group Lasso Multi-task Learning for Cognitive Performance Prediction of Alzheimer’s Disease
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    Chapter 20 A Novel Deep Learning Based Multi-class Classification Method for Alzheimer’s Disease Detection Using Brain MRI Data
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    Chapter 21 A Quantitative Analysis Method for Objectively Assessing the Depression Mood Status Based on Portable EEG and Self-rating Scale
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    Chapter 22 Social Events Forecasting in Microblogging
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    Chapter 23 Study on Depression Classification Based on Electroencephalography Data Collected by Wearable Devices
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    Chapter 24 Corticospinal Tract Alteration is Associated with Motor Performance in Subacute Basal Ganglia Stroke
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    Chapter 25 Detecting Depression in Speech Under Different Speaking Styles and Emotional Valences
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    Chapter 26 Scientific Advances on Consciousness
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    Chapter 27 BECA: A Software Tool for Integrated Visualization of Human Brain Data
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    Chapter 28 Knowledge Graphs in the Quality Use of Antidepressants: A Perspective from Clinical Research Applications
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    Chapter 29 Using Knowledge Graph for Analysis of Neglected Influencing Factors of Statin-Induced Myopathy
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    Chapter 30 Mesoscopic Brainformatics
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    Chapter 31 The Development and Application of Biochemical Analysis of Saliva in the Assessment of the Activity of Nervous System
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Title
Brain Informatics
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-70772-3
ISBNs
978-3-31-970771-6, 978-3-31-970772-3
Editors

Yi Zeng, Yong He, Jeanette Hellgren Kotaleski, Maryann Martone, Bo Xu, Hanchuan Peng, Qingming Luo

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 2%
Student > Master 1 2%
Unknown 63 97%
Readers by discipline Count As %
Neuroscience 1 2%
Engineering 1 2%
Unknown 63 97%

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