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Computational Neuroscience

Overview of attention for book
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 10: EEG Classification of Epileptic Patients Based on Signal Morphology
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Citations

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Chapter title
EEG Classification of Epileptic Patients Based on Signal Morphology
Chapter number 10
Book title
Computational Neuroscience
Published by
Springer, Cham, November 2019
DOI 10.1007/978-3-030-36636-0_10
Book ISBNs
978-3-03-036635-3, 978-3-03-036636-0
Authors

Davi Nascimento, Jonathan Queiroz, Luis Claudio Silva, Gean Carlos de Sousa, Allan Kardec Barros, Nascimento, Davi, Queiroz, Jonathan, Silva, Luis Claudio, de Sousa, Gean Carlos, Barros, Allan Kardec

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 33%
Unknown 2 67%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 33%
Unknown 2 67%

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