Human Brain and Artificial Intelligence: Third International Workshop, HBAI 2022, Held in Conjunction with IJCAI-ECAI 2022,Vienna, Austria, July 23, 2022 Revised Selected Papers

Description

This book constitutes the refereed proceedings of the Third International Workshop on Human Brain and Artificial Intelligence, HBAI 2022, held in conjunction with IJCAI-ECAI 2022, Vienna, Austria, on July 23, 2022.  The 19 full papers presented were carefully reviewed and selected from 21 submissions. The papers present most recent research in the fields of brain-inspired computing, brain-machine interfaces, computational neuroscience, brain-related health, neuroimaging, cognition and behavior, learning, and memory, neuron modulation, and closed-loop brain stimulation. Preface Organization Contents AI for Brain Related Data Analysis Classification of EEG Signals Based on GA-ELM Optimization Algorithm 1 Introduction 2 Optimization of Extreme Learning Machine by Genetic Algorithm 3 The Experiment Design 3.1 Experimental System Framework 3.2 Data Acquisition 4 The Data Analysis 4.1 Preprocessing 4.2 Feature Extraction 4.3 Genetic Algorithm Optimized Parameter Setting 5 Results 6 Discussion 7 Conclusion References Delving into Temporal-Spectral Connections in Spike-LFP Decoding by Transformer Networks 1 Introduction 2 Methods 2.1 Temporal Connection Learning with Spikes 2.2 Spectral Connection Learning with LFPs 2.3 Temporal-Spectral Connection Learning with Spike-LFPs 2.4 Task-Related Output Layer 3 Experiments and Results 3.1 Clinical Dataset 3.2 Spike-LFP Fusion Improves Neural Decoding Accuracy 3.3 Temporal Connections Improve Robustness to Temporal Shifts 3.4 Temporal-Spectral Connections Improve Robustness to Noises 4 Conclusion A Detail Settings Of Neural Decoders B Estimating Movement Conduction Durations With Neuron Responses C Robustness To Gaussian Noises References A Mask Image Recognition Attention Network Supervised by Eye Movement 1 Introduction 2 Methods 2.1 Datasets 2.2 The Generation of Gaze Heat Map 2.3 Network Architecture 3 Results 3.1 Eye Movement Heat Map 3.2 Network Performance 3.3 Network Attention Visualization 4 Conclusion References DFC-SNN: A New Approach for the Recognition of Brain States by Fusing Brain Dynamics and Spiking Neural Network 1 Introduction 2 Methods 2.1 DFC-SNN Framework 2.2 Dataset 3 Results 4 Conclusion References DSNet: EEG-Based Spatial Convolutional Neural Network for Detecting Major Depressive Disorder 1 Introduction 2 Materials and Methods 2.1 Dataset and Data Preprocessing 2.2 The Architecture of DSNet 2.3 Baseline Methods 2.4 Model Implementation and Experimental Evaluation 3 Results and Discuss 4 Conclusion References SE-1DCNN-LSTM: A Deep Learning Framework for EEG-Based Automatic Diagnosis of Major Depressive Disorder and Bipolar Disorder 1 Introduction 2 Materials and Methods 2.1 Data and Preprocessing 2.2 1DCNN and LSTM Network 2.3 Channel Attention 2.4 Evaluation Metrics and Parameters 3 Results and Discussion 3.1 Comparison with Baseline Method 3.2 Ablation Study 3.3 Interpretability Analysis of Channel Attention 3.4 Effects of Window Size 4 Conclusion References Emotion Recognition from EEG Using All-Convolution Residual Neural Network 1 Introduction 2 Methods 2.1 Pre-processing and Feature Extraction 2.2 3D Input Construction 2.3 The All-Convolutional Neural Network 2.4 Deep Residual Learning Framework 3 Experiments 3.1 DEAP Dataset 3.2 Model Implementation 3.3 Parameter Setting 4 Experimental Results and Discussion 5 Conclusions and Future Works References Salient Object Detection with Fusion of RGB Image and Eye Tracking Data 1 Introduction 2 Method 2.1 Acquisition of ETSM 2.2 Cross-Modal Fusion Module 2.3 Improved Cascade Decoder 2.4 Optimization Module 3 Experimental Setup and Result Analysis 3.1 Experimental Details 3.2 Evaluation Indicators 3.3 Performance Comparison with Other Algorithms 4 Conclusion References Multi-source Domain Adaptation Based on Data Selector with Soft Actor-Critic 1 Introduction 2 Related Work 3 Method 3.1 Reinforcement Learning Data Selector 3.2 Soft Actor-Critic 4 Experiments 4.1 Datasets and Experiment Settings 4.2 Comparison with the Latest Technology 4.3 Training Efficiency of DSAC 4.4 Source to Single-Target Adaptation 5 Conclusion References Transfer Learning to Decode Brain States Reflecting the Relationship Between Cognitive Tasks 1 Introduction 2 Related Work 2.1 Cognitive Task Relations from Neuroscience Perspective 2.2 Cognitive Task Relations From Transfer Learning Perspective 3 Methods 3.1 HCP Tasks 3.2 Transfer Learning 3.3 Validation of Cognitive Taskonomy 4 Results 4.1 Affinity Matrix of Cognitive Tasks 4.2 Compare with Task-Specific Networks 4.3 Brain Decoding Accuracy with Transfer Learning 5 Discussion References AI and Brain Interface Brain Network Analysis of Hand Motor Execution and Imagery Based on Conditional Granger Causality 1 Introduction 2 Methods 2.1 Conditional Granger Causality Analysis 3 Data Collection and Processing 3.1 Data Collection 3.2 Data Processing 4 Result 5 Discussion References A Hybrid Brain-Computer Interface for Smart Car Control 1 Introduction 2 Materials and Methods 2.1 System Overview 2.2 Signal Acquisition 3 Experiments and Results 3.1 Experiment I: Single-Mode Control 3.2 Experiment II: Multimodal Car Control 3.3 Results 4 Conclusions References A Spiking Neural Network for Brain-Computer Interface of Four Classes Motor Imagery 1 Introduction 2 Methods 2.1 BSA Based on Parameter-Wise Gradient Descent Optimization Method 2.2 LIF Model and ALIF Model 2.3 The Architecture of SNN 2.4 Surrogate Gradient 2.5 Channel-Wise Normalization 3 Experiments 3.1 Dataset and the Selection of Experimental Data 3.2 The Performance of PW-GD Optimizing for BSA 3.3 The Performance of SNN in MI Classification 3.4 Comparison of Training Effects of MG and Slayer 4 Conclusion References Virtual Drone Control Using Brain-Computer Interface Based on Motor Imagery Brain Magnetic Fields 1 Introduction 2 Brain Magentic Fields Based BCI System Description 2.1 Helmet Design 2.2 Experimental Environment Construction 3 Experiment Content and Data Processing 3.1 Subject Training 3.2 Data Collection and Processing 4 Machine Learning and Result 4.1 Data for Machine Learning 4.2 Model Training 4.3 Test Result 4.4 Virtual Drone Controlling 5 Conclusion and Future Work References Brain Controlled Manipulator System Based on Improved Target Detection and Augmented Reality Technology 1 Introduction 2 Experimental and System Structure Design 2.1 Experimental Design 2.2 System Structure Design 3 Methods 3.1 Improvement of Faster-RCNN 3.2 AR Technology Generates Stimulation Interface 3.3 EEG Signal Analysis 4 Experimental results 4.1 Target Detection Model Test 4.2 EEG Recognition Results Using AR 4.3 System Test 5 Concludes References Optimization of Stimulus Color for SSVEP-Based Brain-Computer Interfaces in Mixed Reality 1 Introduction 1.1 A Subsection Sample 2 Methods and Materials 2.1 Experimental Protocol 2.2 Participants 2.3 EEG Acquisition and Data Pre-processing 2.4 Classification Algorithm 2.5 Calculation of Color Contrast 3 Result and Analysis 4 Conclusion References Brain Related Research White Matter Maturation and Hemispheric Asymmetry During Childhood Based on Chinese Population 1 Introduction 2 Method 2.1 Participants 2.2 Image Acquisition 2.3 Image Analysis 2.4 Tractography Regions of Interest 2.5 Statistical Analysis 3 Results 3.1 Age-Related White Matter Maturation 3.2 Asymmetry Effects 4 Discussion 4.1 Age-Related White Matter Maturation 4.2 Asymmetry Effects 5 Conclusions References A Digital Gaming Intervention Combing Multitasking and Alternating Attention for ADHD: A Preliminary Study 1 Introduction 2 Methods 2.1 Trial Design 2.2 Participants 2.3 Randomization and Blinding 2.4 Interventions 2.5 Outcomes 2.6 Data Analysis 3 Results 3.1 Study Participation 3.2 Primary Outcomes 3.3 Secondary Outcomes 3.4 Adverse Events 4 Discussion 5 Conclusion References A BCI Speller with 120 Commands Encoded by Hybrid P300 and SSVEP Features 1 Introduction 2 Methods and Experiments 2.1 Subjects 2.2 Hybrid Paradigm Design and Implementation 2.3 BCI Experiment 2.4 EEG Recording and Processing 2.5 Classification Algorithm and Decision Fusion Method 2.6 System Performance Evaluation 3 Results and Discussion 3.1 Subjects EEG Feature Analysis 3.2 Offline BCI Performance Analysis 3.3 Online BCI Performance Analysis 4 Conclusion References Author Index