Computational Neuroscience: Third Latin American Workshop, LAWCN 2021, São Luís, Brazil, December 8–10, 2021, Revised Selected Papers (Communications in Computer and Information Science, 1519)

Description

This book constitutes the refereed proceedings of the Third Latin American Workshop, LAWCN 2021, held in Sao Luis do Maranhao, Brazil, during December 8–10, 2021. The 13 full papers and 3 short papers included in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections as follows: Interdisciplinary applications of Artificial Intelligence (AI) and Machine Learning (ML); AI and ML applied to robotics; AI and ML applied to biomedical sciences; Health issues and computational neuroscience; Software and hardware implementations in neuroscience; and Neuroengineering – science and technology. Preface Organization Contents Interdisciplinary Applications of Artificial Intelligence (AI) and Machine Learning (ML) Semantic Segmentation of the Cultivated Area of Plantations with U-Net 1 Introduction 2 Related Works 3 Methodology 3.1 Building the Dataset 3.2 Preprocessing 3.3 Segmentation with U-Net Architecture 3.4 Hyperparameter Optimization 3.5 Performance Evaluation 4 Experiments and Results 4.1 Data Description 4.2 Hyperparameter Test 4.3 Segmentation of Plantation Areas 5 Conclusion References Use and Interpretation of Item Response Theory Applied to Machine Learning 1 Introduction 2 Item Response Theory 3 Methodology 3.1 Data 3.2 Experiment Design 4 Results and Discussion 4.1 Experiment 1 4.2 Experiment 2 5 Conclusion References AI and ML Applied to Robotics Towards Loop Closure Detection for SLAM Applications Using Bag of Visual Features: Experiments and Simulation 1 Introduction 2 Related Works 3 Proposed Approach 3.1 Bag of Visual Features 3.2 Multilayer Perceptron 4 Experimental Setup and Results 4.1 Experimental Setup 4.2 Results 4.3 Other Results 5 Discussion and Future Works References Loss Function Regularization on the Iterated Racing Procedure for Automatic Tuning of RatSLAM Parameters 1 Introduction 2 The RatSLAM Algorithm 2.1 RatSLAM Structure 2.2 RatSLAM Parameters 3 Improved Tuning Process 4 Experimental Setup 4.1 Environment Setup 4.2 irace Setup 5 Results 6 Discussion 7 Conclusion References Controlling the UR3 Robotic Arm Using a Leap Motion: A Comparative Study 1 Introduction 2 Related Works 3 Materials and Methods 3.1 Overview 3.2 Leap Motion 3.3 Experimental Scenarios 3.4 Experimental Procedure 3.5 Coded Control 3.6 Open Control 4 Results 5 Conclusions References AI and ML Applied to Biomedical Sciences Web Service Based Epileptic Seizure Detection by Applying Machine Learning Techniques 1 Introduction 2 Methodology 2.1 Database 2.2 Preprocessing 2.3 Feature Extraction 2.4 Machine Learning 2.5 Web Service 3 Results 3.1 Model Optimization 3.2 Model Selection 3.3 Web Service 4 Conclusion References Health Issues and Computational Neuroscience Machine Learning Search of Novel Selective NaV1.2 and NaV1.6 Inhibitors as Potential Treatment Against Dravet Syndrome 1 Introduction 2 Methods 2.1 Dataset Collection, Curation, and Labeling 2.2 Dataset Partitioning into Training and Test Sets 2.3 Molecular Descriptor Calculation and Modeling Procedure 2.4 Ensemble Learning 2.5 Retrospective Screening 2.6 Use of Positive Predictive Value Surfaces to Choose a Score Threshold for the Prospective Screen 2.7 Prospective Virtual Screen 3 Results and Discussion 4 Conclusions References Implementation of Intra and Extracellular Nonperiodic Scale-Free Stimulation in silicofor the NEURON Simulator 1 Introduction 2 Methodology 2.1 Intracellular Stimulation Using Point-Processes 2.2 Extracellular Stimulation Using Field Propagation 2.3 Temporal-Patterned Stimuli 3 Results 3.1 Single Neuron Response to Intracellular Stimulation 3.2 Network Response to Extracellular Stimulation 4 Discussion and Conclusions References In silicoInvestigation of the Effects of Distinct Temporal Patterns of Electrical Stimulation to the Amygdala Using a Network of Izhikevich Neurons 1 Introduction 1.1 General 2 Methodology 2.1 Network of Izhikevich Neurons 2.2 Induction of Ictogenesis 2.3 Temporal-Patterned Stimuli 2.4 Experimental Protocol and Assessment of Effects on Synchronization 2.5 Interspike Intervals (ISI) and Coefficient of Variation (CV) 3 Results 4 Discussion and Conclusions References Software and Hardware Implementations in Neuroscience Brain Connectivity Measures in EEG-Based Biometry for Epilepsy Patients: A Pilot Study 1 Introduction 2 Subjects, Materials and Methods 2.1 Data Acquisition and Pre-processing 2.2 Connectivity Measures 2.3 Classification 3 Results and Discussion 4 Conclusion References A Multiplatform Output Stage for the Development of Current-Fixed Electrical Stimulators Applied to Neural Electrophysiology 1 Introduction 2 Materials and Methods 2.1 Electronic Circuit Design 2.2 Circuit Tests 2.3 Circuit Assembly 3 Results 3.1 Positive and Negative Current Test 3.2 Polarity Test 3.3 Dead Time Test 4 Discussions and Conclusions References Neuroengineering – Science and Technology Physiological Self-regulation Using Biofeedback Training: From Concept to Clinical Applicability 1 Introduction 2 Principles of System Operation 2.1 Inputs 2.2 Features from Input Signals 3 Real-Time Signal Processing 4 Output Signals: Feedback Stimulation 5 Biofeedback Training Protocols 6 Underlying Mechanisms 7 Clinical Applicability of Biofeedback 8 Final Considerations References Movement-Related Electroencephalography in Stroke Patients Across a Brain-Computer Interface-Based Intervention 1 Introduction 2 Materials and Methods 2.1 Patients 2.2 Intervention 2.3 BCI System 2.4 EEG Signal Acquisition 2.5 EEG Signal Processing 2.6 Statistical Analysis 3 Results 3.1 Patients’ Clinical Assessment 3.2 ERD/ERS Brain Topographic Maps 3.3 ERD/ERS Comparisons 3.4 Comparison Between Clinical Recovery and ERD/ERS 4 Discussion References Resting-State Exaggerated Alpha Rhythm from Subthalamic Nucleus Discriminates Freezers from Non-freezers Phenotypes in Parkinson’s Disease: Possible Association to Attentional Circuits 1 Introduction 2 Materials and Methods 2.1 Patients 2.2 Surgery 2.3 Signal Processing 2.4 Statistical Analysis 3 Results 4 Discussion References Effect of Hand Dominance When Decoding Motor Imagery Grasping Tasks 1 Introduction 2 Materials and Methods 2.1 Data Acquisition 2.2 Data Processing 2.3 Feature Extraction, Selection, and Classification 2.4 Experiments 3 Results and Discussion 3.1 Future Work 4 Summary and Conclusion References Kinematic Responses as a Control Strategy to Visual Occlusion 1 Introduction 2 Methods 2.1 Participants 2.2 Instruments and Task 2.3 Study Design 2.4 Data Analysis 2.5 Statistical Analysis 3 Results 4 Discussion 5 Conclusion References Author Index