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16th Brain Informatics 2023: Hoboken, NJ, USA
- Feng Liu, Yu Zhang, Hongzhi Kuai, Emily P. Stephen, Hongjun Wang:
Brain Informatics - 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings. Lecture Notes in Computer Science 13974, Springer 2023, ISBN 978-3-031-43074-9
Cognitive and Computational Foundations of Brain Science
- Qiankun Zuo, Yanfei Zhu, Libin Lu, Zhi Yang, Yuhui Li, Ning Zhang:
Fusing Structural and Functional Connectivities Using Disentangled VAE for Detecting MCI. 3-13 - Dor Mizrahi, Ilan Laufer, Inon Zuckerman:
Modulation of Beta Power as a Function of Attachment Style and Feedback Valence. 14-20 - Kostas Georgiadis, Fotis P. Kalaganis, Vangelis P. Oikonomou, Spiros Nikolopoulos, Nikolaos A. Laskaris, Ioannis Kompatsiaris:
Harneshing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry. 21-32 - Gabriel Matías Lorenz, Pablo Martínez-Cañada, Stefano Panzeri:
A Model of the Contribution of Interneuron Diversity to Recurrent Network Oscillation Generation and Information Coding. 33-44 - Loren Koçillari, Marco Celotto, Nikolas A. Francis, Shoutik Mukherjee, Behtash Babadi, Patrick O. Kanold, Stefano Panzeri:
Measuring Stimulus-Related Redundant and Synergistic Functional Connectivity with Single Cell Resolution in Auditory Cortex. 45-56 - Xueqing Liu, Paul Sajda:
Fusing Simultaneously Acquired EEG and fMRI via Hierarchical Deep Transcoding. 57-67
Investigations of Human Information Processing Systems
- Luis Alfredo Moctezuma, Kazuki Sato, Marta Molinas, Takashi Abe:
Decoding Emotion Dimensions Arousal and Valence Elicited on EEG Responses to Videos and Images: A Comparative Evaluation. 71-82 - Petr Kuderov, Evgenii Dzhivelikian, Aleksandr I. Panov:
Stabilize Sequential Data Representation via Attraction Module. 83-95 - Lorenzo Tausani, Alberto Testolin, Marco Zorzi:
Investigating the Generative Dynamics of Energy-Based Neural Networks. 96-108 - Tanjim Mahmud, Koushick Barua, Anik Barua, Sudhakar Das, Nanziba Basnin, Mohammad Shahadat Hossain, Karl Andersson, M. Shamim Kaiser, Nahed Sharmen:
Exploring Deep Transfer Learning Ensemble for Improved Diagnosis and Classification of Alzheimer's Disease. 109-120
Brain Big Data Analytics, Curation and Management
- Jesse Rong, Rui Sun, Yuxin Guo, Bin He:
Effects of EEG Electrode Numbers on Deep Learning-Based Source Imaging. 123-132 - Changhong Jing, Changwei Gong, Zuxin Chen, Shuqiang Wang:
Graph Diffusion Reconstruction Network for Addictive Brain-Networks Identification. 133-145 - Guoli Huang, Xuhang Chen, Yanyan Shen, Shuqiang Wang:
MR Image Super-Resolution Using Wavelet Diffusion for Predicting Alzheimer's Disease. 146-157 - Maryam Khoshkhooy Titkanlou, Roman Moucek:
Classification of Event-Related Potential Signals with a Variant of UNet Algorithm Using a Large P300 Dataset. 158-166 - Roshan Bhandari, Rishikesh V. Phatangare, Mark A. Eckert, Kenneth I. Vaden Jr., James Zijun Wang:
Dyslexia Data Consortium Repository: A Data Sharing and Delivery Platform for Research. 167-178 - Alessia Sarica, Federica Aracri, Maria Giovanna Bianco, Maria Grazia Vaccaro, Andrea Quattrone, Aldo Quattrone:
Conversion from Mild Cognitive Impairment to Alzheimer's Disease: A Comparison of Tree-Based Machine Learning Algorithms for Survival Analysis. 179-190 - Arihant Jain, Petri Toiviainen, Vinoo Alluri:
Predicting Individual Differences from Brain Responses to Music: A Comparison of Functional Connectivity Measures. 191-202 - Arya Teymourlouei, Joshua Stone, Rodolphe J. Gentili, James A. Reggia:
Multiplex Temporal Networks for Rapid Mental Workload Classification. 203-214 - Juhyung Ha, Nian Wang, Surendra Maharjan, Xuhong Zhang:
Super-Resolution MRH Reconstruction for Mouse Models. 215-226 - Navid Ziaei, Reza Saadatifard, Ali Yousefi, Behzad Nazari, Sydney S. Cash, Angelique C. Paulk:
Bayesian Time-Series Classifier for Decoding Simple Visual Stimuli from Intracranial Neural Activity. 227-238 - Sukesh Das, Pratik Jain, Anil Kumar Sao, Bharat B. Biswal:
Variability of Non-parametric HRF in Interconnectedness and Its Association in Deriving Resting State Network. 239-248 - Partho Ghose, Milon Biswas, Loveleen Gaur:
BrainSegNeT: A Lightweight Brain Tumor Segmentation Model Based on U-Net and Progressive Neuron Expansion. 249-260 - Zihan Zhang, Christina Schweikert, Shinsuke Shimojo, D. Frank Hsu:
Improving Prediction Quality of Face Image Preference Using Combinatorial Fusion Algorithm. 261-272 - Meng Jiao, Shihao Yang, Boyu Wang, Xiaochen Xian, Yevgeniy R. Semenov, Guihong Wan, Feng Liu:
MMDF-ESI: Multi-Modal Deep Fusion of EEG and MEG for Brain Source Imaging. 273-285 - Shihao Yang, Meng Jiao, Jing Xiang, Daphne Kalkanis, Hai Sun, Feng Liu:
Rejuvenating Classical Source Localization Methods with Spatial Graph Filters. 286-296 - Shulin Wen, Shihao Yang, Xinglong Ju, Ting Liao, Feng Liu:
Prediction of Cannabis Addictive Patients with Graph Neural Networks. 297-307 - Xueqing Liu, Paul Sajda:
Unsupervised Sparse-View Backprojection via Convolutional and Spatial Transformer Networks. 308-317 - Xueqing Liu, Paul Sajda:
Latent Neural Source Recovery via Transcoding of Simultaneous EEG-fMRI. 318-330
Informatics Paradigms for Brain and Mental Health Research
- Rene Lehmann, Bodo Vogt:
Increasing the Power of Two-Sample T-tests in Health Psychology Using a Compositional Data Approach. 333-347 - Chia-Hao Shih, Methsarani Premathilaka, Hong Xie, Xin Wang, Rong Liu:
Estimating Dynamic Posttraumatic Stress Symptom Trajectories with Functional Data Analysis. 348-356 - Sobhana Jahan, Md. Rawnak Saif Adib, Mufti Mahmud, M. Shamim Kaiser:
Comparison Between Explainable AI Algorithms for Alzheimer's Disease Prediction Using EfficientNet Models. 357-368 - Philopateer Ghattas, Mai Gamal, Seif Eldawlatly:
Social and Non-social Reward Learning Contexts for Detection of Major Depressive Disorder Using EEG: A Machine Learning Approach. 369-382 - Sultana Umme Habiba, Tanoy Debnath, Md. Khairul Islam, Lutfun Nahar, Mohammad Shahadat Hossain, Nanziba Basnin, Karl Andersson:
Transfer Learning-Assisted DementiaNet: A Four Layer Deep CNN for Accurate Alzheimer's Disease Detection from MRI Images. 383-394 - Hongmin Cai, Xiaoke Huang, Zhengliang Liu, Wenxiong Liao, Haixing Dai, Zihao Wu, Dajiang Zhu, Hui Ren, Quanzheng Li, Tianming Liu, Xiang Li:
Multimodal Approaches for Alzheimer's Detection Using Patients' Speech and Transcript. 395-406
Brain-Machine Intelligence and Brain-Inspired Computing
- Fotis P. Kalaganis, Kostas Georgiadis, Vangelis P. Oikonomou, Spiros Nikolopoulos, Nikolaos A. Laskaris, Ioannis Kompatsiaris:
Exploiting Approximate Joint Diagonalization for Covariance Estimation in Imagined Speech Decoding. 409-419 - Karoline Seljevoll Herleiksplass, Luis Alfredo Moctezuma, Junya Furuki, Yoko Suzuki, Takashi Abe, Marta Molinas:
Automatic Sleep-Wake Scoring with Optimally Selected EEG Channels from High-Density EEG. 420-431 - Andrés Felipe Soler, Eduardo Giraldo, Marta Molinas:
EEG Source Imaging of Hand Movement-Related Areas: An Evaluation of the Reconstruction Accuracy with Optimized Channels. 432-442 - Noushath Shaffi, Viswan Vimbi, Mufti Mahmud, Karthikeyan Subramanian, Faizal Hajamohideen:
Bagging the Best: A Hybrid SVM-KNN Ensemble for Accurate and Early Detection of Alzheimer's and Parkinson's Diseases. 443-455 - Xueqing Liu, Paul Sajda:
Roe: A Computational-Efficient Anti-hallucination Fine-Tuning Technology for Large Language Model Inspired by Human Learning Process. 456-463
The 5th International Workshop on Cognitive Neuroscience of Thinking and Reasoning
- Kenta Kitamura, Mhd Irvan, Rie Shigetomi Yamaguchi:
Brain Intervention Therapy Dilemma: Functional Recovery versus Identity. 467-475
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