Brain Informatics - 17th International Conference, BI 2024, Bangkok, Thailand, December 13-15, 2024, Proceedings, Part I

This book constitutes the proceedings of the 17th International Conference on Brain Informatics, BI 2024, which was held in Bangkok, Thailand, during December 13-15, 2024.
The 35 full papers and 17 workshop papers presented in this book were carefully reviewed and selected from 126 submissions. These papers have been organized in the following topical sections:
Pat I- Cognitive and Computational Foundations of Brain Science; Investigations of Human Information Processing Systems; Brain Big Data Analytics, Curation and Management; Informatics Paradigms for Brain and Mental Health Research; Brain-Machine Intelligence and Brain-Inspired Computing.
Part II- The International Workshop on Generative AI Empowers Brain Signal Processing (GAIEBSP 2024); The International Workshop on Web Intelligence meets Brain Informatics (WImeetsBI 2024); The 4th Workshop on Environmental Adaptation and Mental Health (EAMH 2024); The International Workshop on Application of Artificial Intelligence and Innovative Technologies in Brain Informatics and Health (AAIITBIH 2024); The International Workshop on Reconstruction and Modeling of the Brain at the Single-Cell Level (RMBSCL 2024); The International Workshop on Mesoscopic Brain-wide Connectivity Atlas in Brainsmatics (MBCAB 2024); The 4th Special Session on Explainable Artificial Intelligence for Unveiling the Brain: From the Black-Box to the Glass-Box (XAIB 2024); The International Workshop on Elucidation of Mechanistic Information using Neuroimaging for Psychiatric Disorders (EMINPD 2024).

List of contents

.- Cognitive and Computational Foundations of Brain Science. 
.- Gossamer: Scaling Image Processing and Reconstruction to Whole Brains.
.- Comparison of Haloperidol- Versus Phenazepam-induced Anxiolytic Effect on Rodent Behavior.
.- Effect of Temporal Correlation on Motion Direction Flips in Bistable Stimuli.
.- Unveiling the Role of Memory in Shaping Visual Perception: Empirical Insights.
.- An Auxiliary Diagnosis Method for Mild Cognitive Impairment Based on Structural Magnetic Resonance Image.
.- The Role of Executive Functions in Emotional Coregulation: Insights from an Adaptive Network Model.
.- Identification and Evaluation of Multimodal Connectomics in Early Alzheimer's Dementia.
.- Investigations of Human Information Processing Systems. 
.- Multiscale Temporal-convolution and Attention improved Neural Network for Biased Mental State Recognition.
.- Sleep Apnea Detection from Single-lead ECG Signal using Hybrid Deep CNN.
.- When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny.
.- Developing a Multi-Site Hyperscanning Procedure for Investigating Interbrain Synchrony Underlying Remote Social Interaction.
.- Dual-Structural Representation Learning with Attention-Based Graph Fusion for Hierarchical MCI-AD Diagnosis.
.- Neurocomputational Modelling of EEG Connectivity: Links Between Depression, Inflammation, and Gut Microbiome.
.- Brain Big Data Analytics, Curation and Management. 
.- Design of an Iterative Method for Integrating Multi-Omic Data and Clinical Insights in Brain Disease Research.
.- Multimodal Physiological Signal Analysis using Attention-Based Feature and Model Fusion.
.- Topological and Graph Theoretical Analysis of Dynamic Functional Connectivity for Autism Spectrum Disorder.
.- Deep Learning Methods to Evaluate Privacy and Quality of Skull-Stripped Brain Image.
.- Topological Inference for Seizure Lateralization.
.- Explainable GRU with Hybrid Attention and Memory-Augmented Network (xGRAM) for Cell Types Classification in Alzheimer's Disease Using Single-Nucleus Transcriptomics.
.- BRAINEX: A Systematic Framework for CNN Models Evaluation and XAI Methods Comparison in Brain Age Prediction.
.- Replication of the Hermann Grid Illusion By U-Net Deep Learning Architecture Performing Deblurring: A Low-Level Visual Task.
.- SmartStitcher: A Terabyte-level 3D Microscopic Image Stitching Tool Based on Mixed-Max-Resolution.
.- Informatics Paradigms for Brain and Mental Health Research. 
.- A Comparison of ANN-Optimization and Logistic Regression? - An Example of the Acceptance of EEG Devices.
.- The Dynamics of Epigenetic Influence in Insomnia: A Higher-Order Adaptive Modeling Perspective.
.- Higher-order Adaptive Dynamical System Modeling for the Role of Environmental Neurotoxic Pesticide Paraquat on the Epigenetics of Neurodegeneration in N27 Dopaminergic Cells.
.- Advancing Mental Health Problems with Machine Learning and Genetic Algorithms for Anxiety Classification in Bangladeshi University Students.
.- Empirical Insights into the Value of a Novel Compositional Data Approach for Analyzing Bipolar Likert Scale Data.
.- From Alzheimer's Disease to Frontotemporal Dementia: Transfer Learning in EEG-based Diagnosis of Dementia.
.- Brain-Machine Intelligence and Brain-Inspired Computing. 
.- A Novel Class Incremental Learning Method via Multi-granularity Balance Inspired by Human Granular Cognition Mechanism.
.- A Computational Model for Estimating NMDA Properties from Local Field Potential Spectra.
.- Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics.
.- Evaluating the Potential of Low-Cost BCI Devices for Online Classification of Four-Class Motor Imagery States.
.- Gradient Ascent Activity-based Credit Assignment with History-dependent Reward.
.- EEG Biomarkers based on Microstates and RQA.
.- Evaluating Feature Importance in the Context of Simulation-Based Inference for Cortical Circuit Parameter Estimation.

Product details

• Assisted by: Giorgio A Ascoli (Editor), Giorgio Ascoli (Editor), Giorgio A. Ascoli (Editor), Sirawaj Itthipuripat (Editor), Hongzhi Kuai (Editor), Anan Li (Editor), Anan Li et al (Editor), Narun Pat (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.05.2025
• EAN: 9789819632930
• ISBN: 978-981-9632-93-0
• No. of pages: 467
• Illustrations: XIX, 467 p. 153 illus., 141 illus. in color.
• Series: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT