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Studies in Neural Data Science = Sta...
~
Canale, Antonio.
Studies in Neural Data Science = StartUp Research 2017, Siena, Italy, June 25–27 /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Studies in Neural Data Science/ edited by Antonio Canale, Daniele Durante, Lucia Paci, Bruno Scarpa.
Reminder of title:
StartUp Research 2017, Siena, Italy, June 25–27 /
other author:
Canale, Antonio.
Description:
XI, 156 p. 62 illus., 26 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Statistics . -
Online resource:
https://doi.org/10.1007/978-3-030-00039-4
ISBN:
9783030000394
Studies in Neural Data Science = StartUp Research 2017, Siena, Italy, June 25–27 /
Studies in Neural Data Science
StartUp Research 2017, Siena, Italy, June 25–27 /[electronic resource] :edited by Antonio Canale, Daniele Durante, Lucia Paci, Bruno Scarpa. - 1st ed. 2018. - XI, 156 p. 62 illus., 26 illus. in color.online resource. - Springer Proceedings in Mathematics & Statistics,2572194-1009 ;. - Springer Proceedings in Mathematics & Statistics,125.
1 S. Ranciati et al, Understanding Dependency Patterns in Structural and Functional Brain Connectivity through fMRI and DTI Data -- 2 E. Aliverti et al, Hierarchical Graphical Model for Learning Functional Network Determinants -- 3 A. Cabassi et al, Three Testing Perspectives on Connectome Data -- 4 A. Cappozzo et al, An Object Oriented Approach to Multimodal Imaging Data in Neuroscience -- 5 G. Bertarelli et al, Curve Clustering for Brain Functional Activity and Synchronization -- 6 F. Gasperoni and A. Luati, Robust Methods for Detecting Spontaneous Activations in fMRI Data -- 7 A. Caponera et al, Hierarchical Spatio-Temporal Modeling of Resting State fMRI Data -- 8 M. Guindani and M. Vannucci, Challenges in the Analysis of Neuroscience Data.
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.
ISBN: 9783030000394
Standard No.: 10.1007/978-3-030-00039-4doiSubjects--Topical Terms:
1253516
Statistics .
LC Class. No.: QA276-280
Dewey Class. No.: 519.5
Studies in Neural Data Science = StartUp Research 2017, Siena, Italy, June 25–27 /
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