Studies in Neural Data Science StartUp Research 2017, Siena, Italy, June 25-27 /
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 ima...
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| Médium: | Elektronický zdroj E-kniha |
|---|---|
| Jazyk: | angličtina |
| Vydáno: |
Cham :
Springer International Publishing,
2018.
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| Vydání: | 1st ed. 2018. |
| Edice: | Springer Proceedings in Mathematics & Statistics,
257 |
| Témata: | |
| ISBN: | 9783030000394 |
| ISSN: | 2194-1009 ; |
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| 020 | |a 9783030000394 | ||
| 024 | 7 | |a 10.1007/978-3-030-00039-4 |2 doi | |
| 035 | |a CVTIDW14394 | ||
| 040 | |a Springer-Nature |b eng |c CVTISR |e AACR2 | ||
| 041 | |a eng | ||
| 245 | 1 | 0 | |a Studies in Neural Data Science |h [electronic resource] : |b StartUp Research 2017, Siena, Italy, June 25-27 / |c edited by Antonio Canale, Daniele Durante, Lucia Paci, Bruno Scarpa. |
| 250 | |a 1st ed. 2018. | ||
| 260 | 1 | |a Cham : |b Springer International Publishing, |c 2018. | |
| 300 | |a XI, 156 p. 62 illus., 26 illus. in color. |b online resource. | ||
| 490 | 1 | |a Springer Proceedings in Mathematics & Statistics, |x 2194-1009 ; |v 257 | |
| 500 | |a Mathematics and Statistics | ||
| 505 | 0 | |a 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. | |
| 516 | |a text file PDF | ||
| 520 | |a 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. | ||
| 650 | 0 | |a Statistics . | |
| 650 | 0 | |a Neurosciences. | |
| 650 | 0 | |a Biostatistics. | |
| 856 | 4 | 0 | |u http://hanproxy.cvtisr.sk/han/cvti-ebook-springer-eisbn-978-3-030-00039-4 |y Vzdialený prístup pre registrovaných používateľov |
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