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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 4: A New Granular Approach for Multivariate Forecasting
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Chapter title
A New Granular Approach for Multivariate Forecasting
Chapter number 4
Book title
Computational Neuroscience
Published by
Springer, Cham, November 2019
DOI 10.1007/978-3-030-36636-0_4
Book ISBNs
978-3-03-036635-3, 978-3-03-036636-0
Authors

Petrônio Cândido de Lima e Silva, Carlos Alberto Severiano Jr., Marcos Antônio Alves, Miri Weiss Cohen, Frederico Gadelha Guimarães, de Lima e Silva, Petrônio Cândido, Severiano Jr., Carlos Alberto, Alves, Marcos Antônio, Cohen, Miri Weiss, Guimarães, Frederico Gadelha

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Professor > Associate Professor 2 20%
Student > Ph. D. Student 1 10%
Student > Bachelor 1 10%
Researcher 1 10%
Other 1 10%
Unknown 1 10%
Readers by discipline Count As %
Computer Science 3 30%
Economics, Econometrics and Finance 1 10%
Energy 1 10%
Engineering 1 10%
Unknown 4 40%

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