Studies in Neural Data Science : StartUp Research 2017, Siena, Italy, June 25–27 / edited by Antonio Canale, Daniele Durante, Lucia Paci, Bruno Scarpa

Mitwirkende(r):

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Springer Proceedings in Mathematics & Statistics ; 257 | Springer eBook Collection | SpringerLink BücherVerlag: Cham : Springer International Publishing, 2018Beschreibung: Online-Ressource (XI, 156 p. 62 illus., 26 illus. in color, online resource)ISBN:

9783030000394

Schlagwörter:

Andere physische Formen: 9783030000387 | 9783030000400 | Erscheint auch als: 978-3-030-00038-7 Druck-Ausgabe | Printed edition: 9783030000387 | Printed edition: 9783030000400 | Erscheint auch als: Studies in neural data science. Druck-Ausgabe Cham : Springer, 2018. xi, 156 SeitenDDC-Klassifikation:

519.5

MSC: MSC: *92-06 | 92C55 | 92B20 | 92B25 | 92C20 | 62P10 | 62-07LOC-Klassifikation:

QA276-280

DOI: DOI: 10.1007/978-3-030-00039-4Online-Ressourcen:

Zusammenfassung: 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 disciplinesZusammenfassung: 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 DataPPN: PPN: 1045548065Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS

Exemplare ( 0 )
Titelinformationen ( 1 )

Dieser Titel hat keine Exemplare

Reproduktion. (Springer eBook Collection. Mathematics and Statistics)