Get 40% off select Statistics books or choose from thousands of Archive eBooks at 9.99 each!

Springer Proceedings in Mathematics & Statistics

Studies in Neural Data Science

StartUp Research 2017, Siena, Italy, June 25–27

Editors: Canale, A., Durante, D., Paci, L., Scarpa, B. (Eds.)

Free Preview
  • Outlines novel contributions on the statistical modeling of recent multimodality imaging data from Neuroscience
  • Includes a contribution by experts on Statistics for Neuroscience, discussing new and relevant research directions
  • Provides findings and new research questions to stimulate future promising research in Neural Data Science
  •  
see more benefits

Buy this book

eBook $129.00
price for USA in USD (gross)
  • ISBN 978-3-030-00039-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-030-00038-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This volume presents a collection of peer-reviewed contributions arising from StartUp Research: a stimulating research experience in which twenty-eight early-career researchers collaborated with seven senior international professors in order to develop novel statistical methods for complex brain imaging data. During this meeting, which was held on June 25–27, 2017 in Siena (Italy), the research groups focused on recent multimodality imaging datasets measuring brain function and structure, and proposed a wide variety of methods for network analysis, spatial inference, graphical modeling, multiple testing, dynamic inference, data fusion, tensor factorization, object-oriented analysis and others. The results of their studies are gathered here, along with a final contribution by Michele Guindani and Marina Vannucci that opens new research directions in this field. The book offers a valuable resource for all researchers in Data Science and Neuroscience who are interested in the promising intersections of these two fundamental disciplines.


About the authors

Antonio Canale is an Assistant Professor of Statistics at the Department of Statistical Sciences, University of Padova (Italy). His research covers Bayesian non-parametric methods, functional data analysis, statistical learning and data mining. He is the author of a number of papers on methodological and applied statistics, and has served on the scientific committees of national and international conferences. He was the coordinator of the young group of the Italian Statistical Society (y-SIS) in 2015.

Daniele Durante is an Assistant Professor of Statistics at the Department of Decision Sciences, Bocconi University (Italy), and a Research Affiliate at the Bocconi Institute for Data Science. His research is characterized by an interdisciplinary approach at the intersection of Bayesian methods, modern applications, and statistical learning to develop flexible and computationally tractable models for complex data. He is the coordinator of the young group of the Italian Statistical Society (y-SIS).

Lucia Paci is an Assistant Professor of Statistics at the Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan (Italy). Her research focuses mainly on spatial and spatiotemporal modeling under the Bayesian framework, with applications in the environmental and economic sciences. She was the coordinator of the young group of the Italian Statistical Society (y-SIS) in 2016. 

Bruno Scarpa is an Associate Professor of Statistics at the Department of Statistical Sciences, University of Padova (Italy). He teaches data mining at the master level and statistical methods for big data at the undergraduate level. His research interests include methodological developments motivated by real data applications. He is the author or coauthor of numerous papers and books in the fields of methodological and applied statistics and data mining.

 


Table of contents (8 chapters)

Table of contents (8 chapters)
  • Understanding Dependency Patterns in Structural and Functional Brain Connectivity Through fMRI and DTI Data

    Pages 1-22

    Crispino, Marta (et al.)

  • Hierarchical Graphical Model for Learning Functional Network Determinants

    Pages 23-36

    Aliverti, Emanuele (et al.)

  • Three Testing Perspectives on Connectome Data

    Pages 37-55

    Cabassi, Alessandra (et al.)

  • An Object Oriented Approach to Multimodal Imaging Data in Neuroscience

    Pages 57-73

    Cappozzo, Andrea (et al.)

  • Curve Clustering for Brain Functional Activity and Synchronization

    Pages 75-90

    Bertarelli, Gaia (et al.)

Buy this book

eBook $129.00
price for USA in USD (gross)
  • ISBN 978-3-030-00039-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-030-00038-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Studies in Neural Data Science
Book Subtitle
StartUp Research 2017, Siena, Italy, June 25–27
Editors
  • Antonio Canale
  • Daniele Durante
  • Lucia Paci
  • Bruno Scarpa
Series Title
Springer Proceedings in Mathematics & Statistics
Series Volume
257
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-00039-4
DOI
10.1007/978-3-030-00039-4
Hardcover ISBN
978-3-030-00038-7
Series ISSN
2194-1009
Edition Number
1
Number of Pages
XI, 156
Number of Illustrations
36 b/w illustrations, 26 illustrations in colour
Topics