El. knyga: Brain Informatics: 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings

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 Alzheimers
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 Alzheimers
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 Alzheimers 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 Alzheimers 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 Alzheimers 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.