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Brain Informatics 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings
Title
Brain Informatics [electronic resource] : 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings / edited by Feng Liu, Yu Zhang, Hongzhi Kuai, Emily P. Stephen, Hongjun Wang.
ISBN
9783031430756
Edition
1st ed. 2023.
Publication
Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Physical Description
1 online resource (XIII, 479 p.) 194 illus., 173 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book constitutes the proceedings of the 16th International Conference on Brain Informatics, BI 2023, which was held in Hoboken, NJ, USA, during August 1-3, 2023. The 40 full papers presented in this book were carefully reviewed and selected from 101 submissions. The papers are divided into the following topical sections: 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; and the 5th international workshop on cognitive neuroscience of thinking and reasoning.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
September 19, 2023
Series
Lecture Notes in Artificial Intelligence, 13974
Contents
Cognitive and Computational Foundations of Brain Science: Fusing Structural and Functional Connectivity using Disentangled VAE for Detecting MCI
Modulation of Beta Power as a Function of Attachment Style and Feedback Valence
Harnessing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry
A Model of the Contribution of Interneuron Diversity to Recurrent Network Oscillation Generation and Information Coding
Measuring Stimulus-Related Redundant and Synergistic Functional Connectivity with Single Cell Resolution in Auditory Cortex
Fusing Simultaneously Acquired EEG and fMRI via Hierarchical Deep Transcoding
Investigations of Human Information Processing Systems: Decoding Emotion Dimensions Arousal and Valence Elicited on EEG Responses to Videos and Images: A Comparative Evaluation
Stabilize Sequential Data Representation via Attractor Module
Investigating the Generative Dynamics of Energy-Based Neural Networks
Exploring Deep Transfer Learning Ensemble for Improved Diagnosis and Classification of Alzheimer's Disease
Brain Big Data Analytics, Curation and Management: Effects of EEG Electrode Numbers on Deep Learning-Based Source Imaging
Graph Diffusion Reconstruction Model for Addictive Brain-Network Computing
MR Image Super-Resolution using Wavelet Diffusion for Predicting Alzheimer's Disease
Classification of Event-Related Potential Signals with a Variant of UNet Algorithm using a Large P300 Dataset
Dyslexia Data Consortium Repository: A Data Sharing and Delivery Platform for Research
Conversion from Mild Cognitive Impairment to Alzheimer's Disease: A Comparison of Tree-based Machine Learning Algorithms for Survival Analysis
Predicting Individual Differences from Brain Responses to Music: A Comparison of Functional Connectivity Measure
Multiplex Temporal Networks for Rapid Mental Workload Classification
Super-Resolution MRH Reconstruction for Mouse Models
Bayesian Time Series Classifier for Decoding Simple Visual Stimuli from Intracranial Activity
Variability of Non-parametric HRF in Interconnectedness and its Association in Deriving Resting State Network
BrainSegNeT: A Lightweight Brain Tumor Segmentation Model based on U-Net and Progressive Neuron Expansion
Improving Prediction Quality of Face Image Preference using Combinatorial Fusion Algorithm
MMDF-ESI: Multi-Modal Deep Fusion of EEG and MEG for Brain Source Imaging
Rejuvenating Classical Source Localization Methods with Spatial Graph Filters
Prediction of Cannabis Addictive Patients with Graph Neural Networks
Unsupervised Sparse-view Backprojection via Convolutional and Spatial Transformer Networks
Latent Neural Source Recovery via Transcoding of Simultaneous EEG-fMRI
Informatics Paradigms for Brain and Mental Health Research: Increasing the Power of Two-Sample T-Tests in Health Psychology using a Compositional Data Approach
Estimating Dynamic Posttraumatic Stress Symptom Trajectories with Functional Data Analysis
Comparison Between Explainable AI Algorithms for Alzheimer's Disease Prediction Using EfficientNet Models
Social and Non-social Reward Learning Contexts for Detection of Major Depressive Disorder using EEG: A Machine Learning Approach
Transfer Learning-Assisted DementiaNet: A Four Layer Deep CNN for Accurate Alzheimer's Disease Detection from MRI Images
Multimodal Approaches for Alzheimer's Detection Using Patients' Speech and Transcript
Brain-Machine Intelligence and Brain-Inspired Computing
Exploiting Approximate Joint Diagonalization for Covariance Estimation in Imagined Speech Decoding
Automatic Sleep-Wake Scoring with Optimally Selected EEG Channels from High-Density EEG
EEG Source Imaging of Hand Movement-Related Areas: An Evaluation of the Reconstruction Accuracy with Optimized Channels
Bagging the Best: A Hybrid SVM-KNN Ensemble for Accurate and Early Detection of Alzheimer's and Parkinson's Diseases
Roe: A Computational-Efficient Anti-Hallucination Fine-Tuning Technology for Large Language Model Inspired by Human Learning Process
The 5th International Workshop on Cognitive Neuroscience of Thinking and Reasoning: Brain Intervention Therapy Dilemma: Functional Recovery versus Identity.
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