Functional brain networks and schizophrenia analysis with fMRI by Multiset Canonical Correlation Analysis

Pietro Guccione, Luigi Mascolo, Giovanni Nico, Paolo Taurisano, Giuseppe Blasi, Leonardo Fazio, Alessandro Bertolino

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work the multivariate technique called Multiset Canonical Correlation Analysis (M-CCA) is applied to study a group of functional Magnetic Resonance Imaging (fMRI) datasets acquired during a set of working memory (WM) tasks. The examined subjects are a small group of schizophrenic patients and an equal number of controls (healthy subjects). The purpose of the paper is to show that M-CCA is able to identify specific areas of the brain network that can be related with the sources of activity during the WM task. It is also shown that the different degree of activation between the two groups allows to discriminate between Controls and Patients and then provides a promising way for a pre-screening classification of successive dataset. This result can contribute, in future, to populate a database of specific brain activation areas of mental disorders.

Original languageEnglish
Title of host publication2013 2nd International Conference on Advances in Biomedical Engineering, ICABME 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages207-210
Number of pages4
ISBN (Print)9781479902514
DOIs
Publication statusPublished - Oct 28 2013
Event2013 2nd International Conference on Advances in Biomedical Engineering, ICABME 2013 - Tripoli, Lebanon
Duration: Sep 11 2013Sep 13 2013

Other

Other2013 2nd International Conference on Advances in Biomedical Engineering, ICABME 2013
CountryLebanon
CityTripoli
Period9/11/139/13/13

ASJC Scopus subject areas

  • Biomedical Engineering

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    Guccione, P., Mascolo, L., Nico, G., Taurisano, P., Blasi, G., Fazio, L., & Bertolino, A. (2013). Functional brain networks and schizophrenia analysis with fMRI by Multiset Canonical Correlation Analysis. In 2013 2nd International Conference on Advances in Biomedical Engineering, ICABME 2013 (pp. 207-210). [6648884] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICABME.2013.6648884