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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.

Contributor(s): Liu, Feng [editor.] | Zhang, Yu [editor.] | Kuai, Hongzhi [editor.] | Stephen, Emily P [editor.] | Wang, Hongjun [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Artificial Intelligence: 13974Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023.Description: XIII, 479 p. 194 illus., 173 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031430756.Subject(s): Artificial intelligence | Social sciences -- Data processing | Education -- Data processing | Computer engineering | Computer networks  | Artificial Intelligence | Computer Application in Social and Behavioral Sciences | Computers and Education | Computer Engineering and NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

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