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Computational Neuroscience

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Cover of 'Computational Neuroscience'

Table of Contents

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    Book Overview
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    Chapter 1 Application of Machine Learning Approaches to Identify New Anticonvulsant Compounds Active in the 6 Hz Seizure Model
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    Chapter 2 Motor Learning and Machine Learning: Predicting the Amount of Sessions to Learn the Tracing Task
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    Chapter 3 Kernel-Spectral-Clustering-Driven Motion Segmentation: Rotating-Objects First Trials
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    Chapter 4 A New Granular Approach for Multivariate Forecasting
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    Chapter 5 Interactive Analysis of the Discussion from a Virtual Community on Neuroscience
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    Chapter 6 Influence of Contact Network Topology on the Spread of Tuberculosis
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    Chapter 7 Association Between Fast and Slow Learning and Molecular Processes in Repetitive Practice: A Post Hoc Analysis
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    Chapter 8 Reading Span Test for Brazilian Portuguese: An Eye-Tracking Implementation
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    Chapter 9 Multi-harmonic Analysis Using Magnitude-Squared Coherence and Its Application to Detection of Auditory Steady-State Responses
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    Chapter 10 EEG Classification of Epileptic Patients Based on Signal Morphology
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    Chapter 11 Epileptiform Spike Detection in Electroencephalographic Recordings of Epilepsy Animal Models Using Variable Threshold
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    Chapter 12 Graph Model Evolution During Epileptic Seizures: Linear Model Approach
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    Chapter 13 A Parallel RatSlam C++ Library Implementation
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    Chapter 14 Method for the Improvement of Knee Angle Accuracy Based on Kinect and IMU: Preliminary Results
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    Chapter 15 Eye-Tracking Data Analysis During Cognitive Task
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    Chapter 16 Towards a Roadmap for Machine Learning and EEG-Based Brain Computer Interface
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    Chapter 17 Considerations on the Individualization of Motor Imagery Neurofeedback Training
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    Chapter 18 The Muscle-Machine Interface After Stroke in Improvement of Hand Extension: Case Report
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    Chapter 19 Electrographic Spectral Signatures of Animals Submitted to Pentylenetetrazole-Induced Seizures and Treated with Bilateral Asynchronous Non-periodic Stimulation
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    Chapter 20 On the Validity of Using Probing Stimuli for Seizure Prediction in the Epileptor Model
Attention for Chapter 4: A New Granular Approach for Multivariate Forecasting
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