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Abstract #0249

A multi-echo low-rank and sparse algorithm that reduces the bias of global fluctuations on the estimation of neuronal signal

Eneko Uruñuela1, Stefano Moia1, and César Caballero-Gaudes1
1Basque Center on Cognition, Brain and Language, Donostia - San Sebastián, Spain


This work introduces a novel multi-echo fMRI deconvolution approach that reduces the effect of global fluctuations (e.g., motion effects, physiological confounds, artefacts) on blindly mapping the brain’s response to single-trial BOLD events without prior timing information. The new sparse-plus-low-rank multi-echo multivariate paradigm free mapping (SPLORA) algorithm is compared with a trial-based known-timing GLM analysis and its predecessor multivariate multiecho paradigm free mapping (MvME-PFM) approach. This method allows exploring the brain’s functional dynamics during task, naturalistic and resting-state paradigms, being less affected by motion and physiological confounds, thus avoiding global signal regression to estimate neuronal related activity with multi-echo fMRI.

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