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Brain Informatics

International Conference, BI 2018, Arlington, TX, USA, December 7–9, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Shouyi Wang

    1. University of Texas at Arlington, Arlington, USA

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  2. Vicky Yamamoto

    1. University of Southern California, West Hollywood, USA

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  3. Jianzhong Su

    1. Department of Mathematics, University of Texas at Arlington, Arlington, USA

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  4. Yang Yang

    1. Maebashi Institute of Technology, Gunma, Japan

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  5. Erick Jones

    1. The University of Texas at Arlington, Arlington, USA

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  6. Leon Iasemidis

    1. Louisiana Tech University, Arlington, USA

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  7. Tom Mitchell

    1. Carnegie Mellon University, Pittsburgh, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11309)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: BI 2018.

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About this book

This book constitutes the refereed proceedings of the International Conference on Brain Informatics, BI 2018, held in Arlington, TX, USA, in December 2018. The 46 revised full papers were carefully reviewed and selected from 53 submissions. The papers are grouped thematically on cognitive and computational foundations of brain science, human information processing systems, brain big data analysis, curation and management, informatics paradigms for brain and mental health research, brain-machine intelligence and brain-inspired computing.

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Table of contents (46 papers)

  1. Front Matter

    Pages I-XVII
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  2. Cognitive and Computational Foundations of Brain Science

    1. Front Matter

      Pages 1-1
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    2. Emotion Recognition Based on Gramian Encoding Visualization

      • Jie-Lin Qiu, Xin-Yi Qiu, Kai Hu
      Pages 3-12

    3. EEG Based Brain Mapping by Using Frequency-Spatio-Temporal Constraints

      • Pablo Andrés Muñoz-Gutiérrez, Juan David Martinez-Vargas, Sergio Garcia-Vega, Eduardo Giraldo, German Castellanos-Dominguez
      Pages 13-21

    4. An EEG-Based Emotion Recognition Model with Rhythm and Time Characteristics

      • Jianzhuo Yan, Sinuo Deng
      Pages 22-31

    5. Influence of Realistic Head Modeling on EEG Forward Problem

      • Ernesto Cuartas Morales, Yohan Ricardo Céspedes Villar, Héctor Fabio Torres Cardona, Carlos Daniel Acosta, German Castellanos Dominguez
      Pages 32-40

    6. Computational Model for Reward-Based Generation and Maintenance of Motivation

      • Fawad Taj, Michel C. A. Klein, Aart van Halteren
      Pages 41-51

    7. Current Design with Minimum Error in Transcranial Direct Current Stimulation

      • Jing Qin, Yushan Wang, Wentai Liu
      Pages 52-62

    8. Assessment of Source Connectivity for Emotional States Discrimination

      • J. D. Martinez-Vargas, D. A. Nieto-Mora, P. A. Muñoz-Gutiérrez, Y. R. Cespedes-Villar, E. Giraldo, G. Castellanos-Dominguez
      Pages 63-73

    9. Rich Dynamics Induced by Synchronization Varieties in the Coupled Thalamocortical Circuitry Model

      • Denggui Fan, Jianzhong Su, Ariel Bowman
      Pages 74-84

  3. Human Information Processing Systems

    1. Front Matter

      Pages 85-85
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    2. Humans Have a Distributed, Molecular Long-Term Memory

      • John L. Pfaltz
      Pages 87-98

    3. Functional Connectivity Analysis Using the Oddball Auditory Paradigm for Attention Tasks

      • Juana Valeria Hurtado-Rincón, Francia Restrepo, Jorge Ivan Padilla, Hector Fabio Torres, German Castellanos-Dominguez
      Pages 99-108

    4. Perspective Taking vs Mental Rotation: CSP-Based Single-Trial Analysis for Cognitive Process Disambiguation

      • Christoforos Christoforou, Adamantini Hatzipanayioti, Marios Avraamides
      Pages 109-118

    5. Using the Partial Directed Coherence to Understand Brain Functional Connectivity During Movement Imagery Tasks

      • Myriam Alanis-Espinosa, David Gutiérrez
      Pages 119-128

    6. Combining fMRI Data and Neural Networks to Quantify Contextual Effects in the Brain

      • Nora Aguirre-Celis, Risto Miikkulainen
      Pages 129-140

    7. Network Analysis of Brain Functional Connectivity in Mental Arithmetic Using Task-Evoked fMRI

      • Xiaofei Zhang, Yang Yang, Ming-Hui Zhang, Ning Zhong
      Pages 141-152

    8. The Astrocytic Microdomain as a Generative Mechanism for Local Plasticity

      • Ioannis Polykretis, Vladimir Ivanov, Konstantinos P. Michmizos
      Pages 153-162

    9. Determining the Optimal Number of MEG Trials: A Machine Learning and Speech Decoding Perspective

      • Debadatta Dash, Paul Ferrari, Saleem Malik, Albert Montillo, Joseph A. Maldjian, Jun Wang
      Pages 163-172

  4. Brain Big Data Analytics, Curation and Management

    1. Front Matter

      Pages 173-173
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Other volumes

  1. Brain Informatics

Editors and Affiliations

  • University of Texas at Arlington, Arlington, USA

    Shouyi Wang

  • University of Southern California, West Hollywood, USA

    Vicky Yamamoto

  • Department of Mathematics, University of Texas at Arlington, Arlington, USA

    Jianzhong Su

  • Maebashi Institute of Technology, Gunma, Japan

    Yang Yang

  • The University of Texas at Arlington, Arlington, USA

    Erick Jones

  • Louisiana Tech University, Arlington, USA

    Leon Iasemidis

  • Carnegie Mellon University, Pittsburgh, USA

    Tom Mitchell

Bibliographic Information

  • Book Title: Brain Informatics

  • Book Subtitle: International Conference, BI 2018, Arlington, TX, USA, December 7–9, 2018, Proceedings

  • Editors: Shouyi Wang, Vicky Yamamoto, Jianzhong Su, Yang Yang, Erick Jones, Leon Iasemidis, Tom Mitchell

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-05587-5

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2018

  • Softcover ISBN: 978-3-030-05586-8Published: 07 December 2018

  • eBook ISBN: 978-3-030-05587-5Published: 06 December 2018

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XVII, 498

  • Number of Illustrations: 65 b/w illustrations, 163 illustrations in colour

  • Topics: Artificial Intelligence, Computer Imaging, Vision, Pattern Recognition and Graphics

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