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...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , , , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2018.
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Έκδοση: | 1st ed. 2018. |
Σειρά: | Springer Proceedings in Mathematics & Statistics,
257 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.