Atjaunināt sīkdatņu piekrišanu

E-grāmata: Computational Neuroscience

  • Formāts - PDF+DRM
  • Cena: 154,06 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This book represents a collection of recent advances in computational studies in neuroscience research that practically applies to a collaborative and integrative environment in engineering and medical domains. This work has been designed to address the explosion of interest by academic researchers and practitioners in highly-effective coordination between computational models and tools and quantitative investigation of neuroscientific data. To bridge the vital gap between science and medicine, this book brings together diverse research areas ranging from medical signal processing, image analysis, and data mining to neural network modeling, regulation of gene expression, and brain dynamics. We hope that this work will also be of value to investigators and practitioners in academic institutions who become involved in computational modeling as an aid in translating information in neuroscientific data to their colleagues in medical - main. This volume will be very appealing to graduate (and advanced undergraduate) students, researchers, and practitioners across a wide range of industries (e. g. , pharmaceutical, chemical, biological sciences), who require a detailed overview of the practical aspects of computational modeling in real-life neuroscience problems. For this reason, our audience is assumed to be very diverse and heterogenous, including: vii viii Preface researchers from engineering, computer science, statistics, and mathematics - mains as well as medical and biological scientists; physicians working in scienti c research to understand how basic science can be linked with biological systems.

Recenzijas

From the book reviews:

This text has a broad overlapping content concerning the biophysics, basic and clinical neurophysiology and neurosurgical approaches to computation. I recommend this fascinating book for neurologists, neurosurgeons, physiologists, and intermediate students seeking to augment their knowledge in this burgeoning field of computation. (Joseph J. Grenier, Amazon.com, August, 2014)

Part I Data Mining
1 Optimization in Reproducing Kernel Hilbert Spaces of Spike Trains
3(28)
Antonio R. C. Paiva
Il Park
Jose C. Principe
2 Investigating Functional Cooperation in the Human Brain Using Simple Graph-Theoretic Methods
31(12)
Michael L. Anderson
Joan Brumbaugh
Aysu Suben
3 Methodological Framework for EEG Feature Selection Based on Spectral and Temporal Profiles
43(14)
Vangelis Sakkalis
Michalis Zervakis
4 Blind Source Separation of Concurrent Disease-Related Patterns from EEG in Creutzfeldt-Jakob Disease for Assisting Early Diagnosis
57(18)
Chih-I. Hung
Po-Shan Wang
Bing-Wen Soong
Shin Teng
Jen-Chuen Hsieh
Yu-Te Wu
5 Comparison of Supervised Classification Methods with Various Data Preprocessing Procedures for Activation Detection in fMRI Data
75(10)
Mahdi Ramezani
Emad Fatemizadeh
6 Recent Advances of Data Biclustering with Application in Computational Neuroscience
85(28)
Neng Fan
Nikita Boyko
Panos M. Pardalos
7 A Genetic Classifier Account for the Regulation of Expression
113(14)
Tsvi Achler
Eyal Amir
Part II Modeling
8 Neuroelectromagnetic Source Imaging of Brain Dynamics
127(30)
Rey R. Ramirez
David Wipf
Sylvain Baillet
9 Optimization in Brain? - Modeling Human Behavior and Brain Activation Patterns with Queuing Network and Reinforcement Learning Algorithms
157(24)
Changxu Wu
Marc Berman
Yili Liu
10 Neural Network Modeling of Voluntary Single-Joint Movement Organization I. Normal Conditions
181(12)
Vassilis Cutsuridis
11 Neural Network Modeling of Voluntary Single-Joint Movement Organization II. Parkinson's Disease
193(20)
Vassilis Cutsuridis
12 Parametric Modeling Analysis of Optical Imaging Data on Neuronal Activities in the Brain
213(14)
Shigeharu Kawai
Yositaka Oku
Yasumasa Okada
Fumikazu Miwakeichi
Makio Ishiguro
Yoshiyasu Tamura
13 Advances Toward Closed-Loop Deep Brain Stimulation
227(28)
Stathis S. Leondopulos
Evangelia Micheli-Tzanakou
14 Molecule-Inspired Methods for Coarse-Grain Multi-System Optimization
255(16)
Max H. Garzon
Andrew J. Neel
Part III Brain Dynamics/Synchronization
15 A Robust Estimation of Information Flow in Coupled Nonlinear Systems
271(14)
Shivkumar Sabesan
Konstantinos Tsakalis
Andreas Spanias
Leon Iasemidis
16 An Optimization Approach for Finding a Spectrum of Lyapunov Exponents
285(20)
Panos M. Pardalos
Vitaliy A. Yatsenko
Alexandre Messo
Altannar Chinchuluun
Petros Xanthopoulos
17 Dynamical Analysis of the EEG and Treatment of Human Status Epilepticus by Antiepileptic Drugs
305(12)
Aaron Faith
Shivkumar Sabesan
Norman Wang
David Treiman
Joseph Sirven
Konstantinos Tsakalis
Leon Iasemidis
18 Analysis of Multichannel EEG Recordings Based on Generalized Phase Synchronization and Cointegrated VAR
317(24)
Alla R. Kammerdiner
Panos M. Pardalos
19 Antiepileptic Therapy Reduces Coupling Strength Among Brain Cortical Regions in Patients with Unverricht-Lundborg Disease: A Pilot Study
341(16)
Chang-Chia Liu
Petros Xanthopoulos
Vera Tomaino
Kazutaka Kobayashi
Basim M. Uthman
Panos M. Pardalos
20 Seizure Monitoring and Alert System for Brain Monitoring in an Intensive Care Unit
357
J. Chris Sackellares
Deng-Shan Shiau
Alla R. Kammerdiner
Panos M. Pardalos