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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Canale, Antonio (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Durante, Daniele (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Paci, Lucia (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Scarpa, Bruno (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
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.