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Three Testing Perspectives on Connectome Data

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Studies in Neural Data Science (START UP RESEARCH 2017)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 257))

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Abstract

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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Acknowledgements

The authors are very grateful to Greg Kiar and Eric Bridgeford from NeuroData at Johns Hopkins University, who graciously pre-processed the raw DTI and R-fMRI imaging data available at http://fcon_1000.projects.nitrc.org/indi/CoRR/html/nki_1.html, using the pipelines ndmg and C-PAC. Moreover, the authors would like to thank the organizing committee of StartUp Research for the splendid management of such a beautiful event. Alessandra Cabassi and Matteo Fontana wish to thank Dr. Davide Pigoli and Prof. Piercesare Secchi for the fruitful discussions.

Author information

Authors and Affiliations

  1. MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK

    Alessandra Cabassi

  2. Department of Statistical Sciences, University of Padova, Padua, Italy

    Alessandro Casa & Massimiliano Russo

  3. Department of Management, Economics and Industrial Engineering, DIG, Politecnico di Milano, Milano, Italy

    Matteo Fontana

  4. Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy

    Alessio Farcomeni

Authors
  1. Alessandra Cabassi
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  2. Alessandro Casa
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  3. Matteo Fontana
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  4. Massimiliano Russo
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  5. Alessio Farcomeni
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Corresponding author

Correspondence to Matteo Fontana .

Editor information

Editors and Affiliations

  1. Department of Statistical Sciences, University of Padova, Padua, Italy

    Antonio Canale

  2. Department of Decision Sciences, Bocconi University, Milan, Italy

    Daniele Durante

  3. Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan, Italy

    Lucia Paci

  4. Department of Statistical Sciences, University of Padova, Padua, Italy

    Bruno Scarpa

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Cabassi, A., Casa, A., Fontana, M., Russo, M., Farcomeni, A. (2018). Three Testing Perspectives on Connectome Data. In: Canale, A., Durante, D., Paci, L., Scarpa, B. (eds) Studies in Neural Data Science. START UP RESEARCH 2017. Springer Proceedings in Mathematics & Statistics, vol 257. Springer, Cham. https://doi.org/10.1007/978-3-030-00039-4_3

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