Three Testing Perspectives on Connectome Data

Alessandra  Cabassi; Alessandro Casa; Matteo Fontana; Massimiliano Russo; Alessio Farcomeni

doi:10.1007/978-3-030-00039-4_3

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Three Testing Perspectives on Connectome Data

Book chapter

Peer reviewed

Three Testing Perspectives on Connectome Data

Alessandra Cabassi, Alessandro Casa, Matteo Fontana, Massimiliano Russo and Alessio Farcomeni

Studies in Neural Data Science, StartUp Research 2017, Siena, Italy, June 25–27, pp.37-55

Springer

2018

DOI: https://doi.org/10.1007/978-3-030-00039-4_3

Handle:

https://hdl.handle.net/10863/43412

Abstract

Object oriented data analysis

Bayesian statistics

Graphical lasso

Bootstrap inference

Hypothesis testing

Permutation tests

Guided by an application in the analysis of Magnetic Resonance Imaging (MRI) scans from the neuroimaging realm, we provide some perspectives on statistical techniques that are able to address issues commonly encountered when dealing with Magnetic Resonance images. The first section of the chapter is devoted to a boostrap-based inferential tool to test for correlation between anatomy and functional activity. The second provides a Bayesian framework to improve estimation of fiber counts from Diffusion Tensor Imaging (DTI) scans. The third one introduces an object-oriented framework to explore and perform testing over network-valued data.

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Details

Title: Three Testing Perspectives on Connectome Data
Creators: Alessandra Cabassi - MRC Biostatistics Unit
Alessandro Casa - University of Padua
Matteo Fontana - Politecnico di Milano
Massimiliano Russo - University of Padua
Alessio Farcomeni - Sapienza University of Rome
Publication Details: Studies in Neural Data Science, StartUp Research 2017, Siena, Italy, June 25–27, pp.37-55
Editor(s): Canale A, Durante D, Paci L, Scarpa B
ISBN: 9783030000387
EISBN: 9783030000394
Publisher: Springer
Cham
Number of pages: 19
Identifiers: 978-3-030-00038-7
(UNIBZ)66394235
991006785486601241
Web of Science ID: 000821100100003
Scopus ID: 2-s2.0-85059745095
Academic Unit: Faculty of Economics and Management
Language: English
Resource Type: Book chapter
Author Names String: Cabassi A, Casa A, Fontana M, Russo M, Farcomeni A
Additional Description: Editors/Supervisors: Canale A, Durante D, Paci L, Scarpa B

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