Mapping dependencies of BOLD signal change to end-tidal CO 2 : Linear and nonlinear modeling, and effect of physiological noise correction.

Autor: Cauzzo S; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy. Electronic address: simone.cauzzo@santannapisa.it., Callara AL; Research Center 'E. Piaggio', University of Pisa, Pisa, Italy., Morelli MS; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy., Hartwig V; Institute of Clinical Physiology, National Research Council, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy., Esposito F; Department of Advanced Medical and Surgical Sciences, University of Campania 'Luigi Vanvitelli', Napoli, Italy., Montanaro D; Fondazione Toscana Gabriele Monasterio, Pisa, Italy., Passino C; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy., Emdin M; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy., Giannoni A; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy., Vanello N; Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy.
Jazyk: angličtina
Zdroj: Journal of neuroscience methods [J Neurosci Methods] 2021 Oct 01; Vol. 362, pp. 109317. Date of Electronic Publication: 2021 Aug 08.
DOI: 10.1016/j.jneumeth.2021.109317
Abstrakt: Background: Disentangling physiological noise and signal of interest is a major issue when evaluating BOLD-signal changes in response to breath holding. Currently-adopted approaches for retrospective noise correction are general-purpose, and have non-negligible effects in studies on hypercapnic challenges.
New Method: We provide a novel approach to the analysis of specific and non-specific BOLD-signal changes related to end-tidal CO 2 (P ET CO 2 ) in breath-hold fMRI studies. Multiple-order nonlinear predictors for P ET CO 2 model a region-dependent nonlinear input-output relationship hypothesized in literature and possibly playing a crucial role in disentangling noise. We explore Retrospective Image-based Correction (RETROICOR) effects on the estimated BOLD response, applying our analysis both with and without RETROICOR and analyzing the linear and non-linear correlation between P ET CO 2 and RETROICOR regressors.
Results: The RETROICOR model of noise related to respiratory activity correlated with P ET CO 2 both linearly and non-linearly. The correction affected the shape of the estimated BOLD response to hypercapnia but allowed to discard spurious activity in ventricles and white matter. Activation clusters were best detected using non-linear components in the BOLD response model.
Comparison With Existing Method: We evaluated the side-effects of standard physiological noise correction procedure, tailoring our analysis on challenging understudied brainstem and subcortical regions. Our novel approach allowed to characterize delays and non-linearities in BOLD response.
Conclusions: RETROICOR successfully avoided false positives, still broadly affecting the estimated non-linear BOLD responses. Non-linearities in the model better explained CO 2 -related BOLD signal fluctuations. The necessity to modify the standard procedure for physiological-noise correction in breath-hold studies was addressed, stating its crucial importance.
(Copyright © 2021 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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