Abstract #0484

Pseudo resting-state by task-evoked functional connectivity.

Alice Giubergia¹, Sara Mascheretti², Valentina Lampis³, Tommaso Ciceri¹, Martina Villa^4,5,6, Chiara Andreola⁷, Filippo Arrigoni⁸, and Denis Peruzzo¹

¹Neuroimaging Unit, IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, ²Department of Brain and Behavioral Sciences, University of Pavia, Pavia (PV), Italy, ³Child Psychopathology Unit, IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, ⁴Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States, ⁵Institute for the Brain and Cognitive Sciences (IBACS), University of Connecticut, Storrs, CT, United States, ⁶Haskins Laboratories, New Haven, CT, United States, ⁷Laboratoire de Psychologie de Développement et de l’Éducation de l’Enfant (LaPsyDÉ), Université Paris Cité, Paris, France, ⁸Paediatric Radiology and Neuroradiology Department, V. Buzzi Children’s Hospital, Milano (MI), Italy

Synopsis

Keywords: Data Processing, Brain ConnectivityFunctional connectomics investigates how brain regions are functionally associated. Studies in literature seek to infer a “pseudo-resting” state from task data, however it should be tested whether resting-state-like connectivity can be inferred by task-fMRI data. This work investigates several preprocessings of task-evoked connectivity performing classification experiments, to test their ability to reproduce a real “resting-state” connectivity and their impact on a clinical context, namely the comparison of Typical Readers and Developmental Dyslexics. Our results suggest that a task-free “pseudo-resting” connectivity cannot be inferred from task-fMRI data and that signal preprocessing does not influence the way the classification rules are inferred.

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