title: fMRI single trial discovery of spatio-temporal brain activity patterns.
abstract: There is growing interest in the description of short-lived patterns in the spatiotemporal cortical activity monitored via neuroimaging. Most traditional analysis methods, designed to estimate relatively long-term brain dynamics, are not always appropriate to capture these patterns. Here we introduce a novel data-driven approach for detecting short-lived fMRI brain activity patterns. Exploiting Density Peak Clustering (Rodriguez and Laio [2014]), our approach reveals well localized clusters by identifying and grouping together voxels whose time-series are similar, irrespective of their brain location, even when very short time windows (∼10 volumes) are used. The method, which we call Coherence Density Peak Clustering (CDPC), is first tested on simulated data and compared with a standard unsupervised approach for fMRI analysis, independent component analysis (ICA). CDPC identifies activated voxels with essentially no false-positives and proves more reliable than ICA, which is troubled by a number of false positives comparable to that of true positives. The reliability of the method is demonstrated on real fMRI data from a simple motor task, containing brief iterations of the same movement. The clusters identified are found in regions expected to be involved in the task, and repeat synchronously with the paradigm. The methodology proposed is especially suitable for the study of short-time brain dynamics and single trial experiments, where the event or task of interest cannot be repeated for the same subject, as happens, for instance, in problem-solving, learning and decision-making. A GUI implementation of our method is available for download at https://github.com/micheleallegra/CDPC. Hum Brain Mapp 38:1421-1437, 2017. © 2016 Wiley Periodicals, Inc.
authors.affiliation: SISSA-International School for Advanced Studies, Via Bonomea, Trieste, 265, Italy.
authors.forename: Michele
authors.identifier: 0000-0002-5587-1861
authors.initials: M
authors.lastname: Allegra
authors.affiliation: Psychology Department, University of Milan Bicocca, Milan, Italy.|Milan Center for Neuroscience, Milan, Italy.|Department of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
authors.forename: Shima
authors.initials: S
authors.lastname: Seyed-Allaei
authors.affiliation: SISSA-International School for Advanced Studies, Via Bonomea, Trieste, 265, Italy.|Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, the University of Southern California, Marina del Rey, California.
authors.forename: Fabrizio
authors.initials: F
authors.lastname: Pizzagalli
authors.affiliation: Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.
authors.forename: Fahimeh
authors.initials: F
authors.lastname: Baftizadeh
authors.affiliation: Medical Physics Department, AOUD S. Maria dellaMisericordia Hospital, Udine, Italy.
authors.forename: Marta
authors.initials: M
authors.lastname: Maieron
authors.affiliation: Psychology Department, University of Milan Bicocca, Milan, Italy.|Milan Center for Neuroscience, Milan, Italy.
authors.forename: Carlo
authors.initials: C
authors.lastname: Reverberi
authors.affiliation: SISSA-International School for Advanced Studies, Via Bonomea, Trieste, 265, Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Laio
authors.affiliation: SISSA-International School for Advanced Studies, Via Bonomea, Trieste, 265, Italy.
authors.forename: Daniele
authors.initials: D
authors.lastname: Amati
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology*; D001931:Brain Mapping; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D009068:Movement / Q000502:physiology; D009434:Neural Pathways / Q000000981:diagnostic imaging* / Q000502:physiology*; D010100:Oxygen / Q000097:blood; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D013997:Time Factors; D055815:Young Adult
chemical_list: D010100:Oxygen
keywords: short-lived brain activity patterns; time-dependent connectivity; unsupervised fMRI analysis