title: pFDR and pFNR estimation for brain networks construction.
abstract: Recent developments in the study of brain functional connectivity are widely based on graph theory. In the current analysis of brain networks, there is no unique way to derive the adjacency matrix, which is a useful representation for a graph. Its entries, containing information about the existence of links, are identified by thresholding the correlation between the time series that characterized the dynamic behavior of the nodes. In this work, we put forward a strategy to choose a suitable threshold on the correlation matrix considering the problem of multiple comparisons in order to control the error rates. In this context we propose to control the positive false discovery rate (pFDR) and a similar measure involving false negatives, called the positive false nondiscovery rate (pFNR). In particular, we provide point and interval estimators for pFNR and a method for balancing the two types of error, demonstrating it by using functional magnetic resonance imaging data and Monte Carlo simulations.
authors.affiliation: Department of Economics, Management and Statistics, University of Milano-Bicocca, Milan, Italy; Neuroimaging Research Unit and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
authors.forename: Sara
authors.initials: S
authors.lastname: Sala
authors.forename: Piero
authors.initials: P
authors.lastname: Quatto
authors.forename: Paola
authors.initials: P
authors.lastname: Valsasina
authors.forename: Federica
authors.initials: F
authors.lastname: Agosta
authors.forename: Massimo
authors.initials: M
authors.lastname: Filippi
mesh_terms: D003198:Computer Simulation; D005188:False Negative Reactions; D005189:False Positive Reactions; D006801:Humans; D008959:Models, Neurological; D009010:Monte Carlo Method; D009415:Nerve Net / Q000502:physiology*
keywords: Monte Carlo simulations; brain functional networks; false discovery rate; false nondiscovery rate; resting state functional magnetic resonance imaging