Brain Informatics
Springer International Publishing (Verlag)
978-3-031-43074-9 (ISBN)
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.
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.
| Erscheinungsdatum | 13.09.2023 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | XIII, 479 p. 194 illus., 173 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 753 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | Artificial Intelligence (AI) • cognitive science • Data Science • Information and Communication Technology (ICT) • machine learning • Neuroscience |
| ISBN-10 | 3-031-43074-3 / 3031430743 |
| ISBN-13 | 978-3-031-43074-9 / 9783031430749 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
