Extreme brain events: Higher-order statistics of brain resting activity and its relation with structural connectivity

¹ Physics Department, Faculty of Exact and Natural Sciences, University of Buenos Aires Buenos Aires, Argentina
² Physics Department, University of Naples Federico II - Napoli, Italy
³ Biocruces Health Research Institute, Cruces University Hospital - Barakaldo, Spain
⁴ VA West Los Angeles Medical Center - Los Angeles, CA, USA
⁵ Dipartimento di Fisica, Università di Bari and INFN Sezione di Bari - Bari, Italy
⁶ BCAM - Basque Center for Applied Mathematics - Bilbao, Spain
⁷ Ikerbasque, The Basque Foundation for Science - Bilbao, Spain
⁸ Department of Cell Biology and Histology. University of the Basque Country - Leioa, Spain
⁹ Department of Industrial and Information Engineering, Second University of Naples and INFN Gr. Coll. Salerno - Aversa (CE), Italy
¹⁰ National Scientific and Technical Research Council (CONICET) - Buenos Aires, Argentina

^(b) lucilla.dearcangelis@unina2.it (corresponding author)

Received: 7 May 2015
Accepted: 15 September 2015

Abstract

The brain exhibits a wide variety of spatiotemporal patterns of neuronal activity recorded using functional magnetic resonance imaging as the so-called blood-oxygenated-level–dependent (BOLD) signal. An active area of work includes efforts to best describe the plethora of these patterns evolving continuously in the brain. Here we explore the third-moment statistics of the brain BOLD signals in the resting state as a proxy to capture extreme BOLD events. We find that the brain signal exhibits typically nonzero skewness, with positive values for cortical regions and negative values for subcortical regions. Furthermore, the combined analysis of structural and functional connectivity demonstrates that relatively more connected regions exhibit activity with high negative skewness. Overall, these results highlight the relevance of recent results emphasizing that the spatiotemporal location of the relatively large-amplitude events in the BOLD time series contains relevant information to reproduce a number of features of the brain dynamics during resting state in health and disease.