Computational Neuroscience

Chapter 1 Application of Machine Learning Approaches to Identify New Anticonvulsant Compounds Active in the 6 Hz Seizure Model

Chapter 2 Motor Learning and Machine Learning: Predicting the Amount of Sessions to Learn the Tracing Task

Chapter 3 Kernel-Spectral-Clustering-Driven Motion Segmentation: Rotating-Objects First Trials

Chapter 4 A New Granular Approach for Multivariate Forecasting

Chapter 6 Influence of Contact Network Topology on the Spread of Tuberculosis

Chapter 7 Association Between Fast and Slow Learning and Molecular Processes in Repetitive Practice: A Post Hoc Analysis

Chapter 8 Reading Span Test for Brazilian Portuguese: An Eye-Tracking Implementation

Chapter 9 Multi-harmonic Analysis Using Magnitude-Squared Coherence and Its Application to Detection of Auditory Steady-State Responses

Chapter 10 EEG Classification of Epileptic Patients Based on Signal Morphology

Chapter 11 Epileptiform Spike Detection in Electroencephalographic Recordings of Epilepsy Animal Models Using Variable Threshold

Chapter 12 Graph Model Evolution During Epileptic Seizures: Linear Model Approach

Chapter 13 A Parallel RatSlam C++ Library Implementation

Chapter 14 Method for the Improvement of Knee Angle Accuracy Based on Kinect and IMU: Preliminary Results

Chapter 15 Eye-Tracking Data Analysis During Cognitive Task

Chapter 16 Towards a Roadmap for Machine Learning and EEG-Based Brain Computer Interface

Chapter 17 Considerations on the Individualization of Motor Imagery Neurofeedback Training

Chapter 18 The Muscle-Machine Interface After Stroke in Improvement of Hand Extension: Case Report

Chapter 19 Electrographic Spectral Signatures of Animals Submitted to Pentylenetetrazole-Induced Seizures and Treated with Bilateral Asynchronous Non-periodic Stimulation

Chapter 20 On the Validity of Using Probing Stimuli for Seizure Prediction in the Epileptor Model