Modelling cognitive loads in schizophrenia by means of new functional dynamic indexes

Angela Lombardi, Cataldo Guaragnella, Nicola Amoroso, Alfonso Monaco, Leonardo Fazio, Paolo Taurisano, Giulio Pergola, Giuseppe Blasi, Alessandro Bertolino, Roberto Bellotti, Sabina Tangaro

Research output: Contribution to journalArticle

Abstract

Functional connectivity analysis techniques have broadly applied to capture phenomenological aspects of the brain, e.g., by identifying characteristic network topologies for healthy and disease-affected populations, by highlighting several areas important for the global efficiency of the brain during some cognitive processing and at rest. However, most of the known methods for quantifying functional coupling between fMRI time series are focused on linear correlation metrics. In this work, we propose a multidimensional framework to extract multiple descriptors of the dynamic interaction among BOLD signals in their phase space. A set of metrics is extracted from the cross recurrence plots of each couple of signals to form a multilayer connectivity matrix in which each layer is related to a specific complex dynamic phenomenon. The proposed framework is used to characterize functional abnormalities during a working memory task in patients with schizophrenia. Some topological descriptors are then extracted from both multilayer connectivity matrices and the most used Pearson-based connectivity networks to perform a binary classification task of normal controls and patients. The results show that the proposed connectivity model outperforms the statistical correlation-based connectivity in accuracy, sensitivity and specificity. Moreover, the statistical analysis of the selected features highlights that several dynamic metrics could better identify disease-related dynamic states in brain activity than the statistical correlation among physiological signals.

Original languageEnglish
Pages (from-to)150-164
Number of pages15
JournalNeuroImage
Volume195
DOIs
Publication statusPublished - Jul 15 2019

Keywords

  • Cross recurrence plots
  • Dynamic connectivity
  • fMRI
  • Functional connectivity
  • Schizophrenia

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

Fingerprint Dive into the research topics of 'Modelling cognitive loads in schizophrenia by means of new functional dynamic indexes'. Together they form a unique fingerprint.

  • Cite this

    Lombardi, A., Guaragnella, C., Amoroso, N., Monaco, A., Fazio, L., Taurisano, P., Pergola, G., Blasi, G., Bertolino, A., Bellotti, R., & Tangaro, S. (2019). Modelling cognitive loads in schizophrenia by means of new functional dynamic indexes. NeuroImage, 195, 150-164. https://doi.org/10.1016/j.neuroimage.2019.03.055