title: Pros and Cons of Using the Informed Basis Set to Account for Hemodynamic Response Variability with Developmental Data.
abstract: Conventional analysis of functional magnetic resonance imaging (fMRI) data using the general linear model (GLM) employs a neural model convolved with a canonical hemodynamic response function (HRF) peaking 5 s after stimulation. Incorporation of a further basis function, namely the canonical HRF temporal derivative, accounts for delays in the hemodynamic response to neural activity. A population that may benefit from this flexible approach is children whose hemodynamic response is not yet mature. Here, we examined the effects of using the set based on the canonical HRF plus its temporal derivative on both first- and second-level GLM analyses, through simulations and using developmental data (an fMRI dataset on proprioceptive mapping in children and adults). Simulations of delayed fMRI first-level data emphasized the benefit of carrying forward to the second-level a derivative boost that combines derivative and nonderivative beta estimates. In the experimental data, second-level analysis using a paired t-test showed increased mean amplitude estimate (i.e., increased group contrast mean) in several brain regions related to proprioceptive processing when using the derivative boost compared to using only the nonderivative term. This was true especially in children. However, carrying forward to the second-level the individual derivative boosts had adverse consequences on random-effects analysis that implemented one-sample t-test, yielding increased between-subject variance, thus affecting group-level statistic. Boosted data also presented a lower level of smoothness that had implication for the detection of group average activation. Imposing soft constraints on the derivative boost by limiting the time-to-peak range of the modeled response within a specified range (i.e., 4-6 s) mitigated these issues. These findings support the notion that there are pros and cons to using the informed basis set with developmental data.
authors.affiliation: Centre National de la Recherche Scientifique, Laboratoire de Neurosciences Cognitives UMR 7291, Aix-Marseille UniversitéMarseille, France; Centre National de la Recherche Scientifique, Fédération 3C (FR 3512), Aix-Marseille UniversitéMarseille, France.
authors.forename: Fabien
authors.initials: F
authors.lastname: Cignetti
authors.affiliation: Centre National de la Recherche Scientifique, Laboratoire de Neurosciences Cognitives UMR 7291, Aix-Marseille UniversitéMarseille, France; Centre National de la Recherche Scientifique, Fédération 3C (FR 3512), Aix-Marseille UniversitéMarseille, France.
authors.forename: Emilie
authors.initials: E
authors.lastname: Salvia
authors.affiliation: Centre National de la Recherche Scientifique, Centre IRM Fonctionnelle Cérébrale, Institut de Neurosciences de la Timone UMR 7289, Aix-Marseille Université Marseille, France.
authors.forename: Jean-Luc
authors.initials: JL
authors.lastname: Anton
authors.affiliation: Centre National de la Recherche Scientifique, Laboratoire de Neurosciences Cognitives UMR 7291, Aix-Marseille UniversitéMarseille, France; Centre National de la Recherche Scientifique, Fédération 3C (FR 3512), Aix-Marseille UniversitéMarseille, France.
authors.forename: Marie-Hélène
authors.initials: MH
authors.lastname: Grosbras
authors.affiliation: Centre National de la Recherche Scientifique, Laboratoire de Neurosciences Cognitives UMR 7291, Aix-Marseille UniversitéMarseille, France; Centre National de la Recherche Scientifique, Fédération 3C (FR 3512), Aix-Marseille UniversitéMarseille, France.
authors.forename: Christine
authors.initials: C
authors.lastname: Assaiante
keywords: basis set; development; fMRI; hemodynamic response; random-effects analysis; smoothness