On the importance of modeling fMRI transients when estimating effective connectivity: A dynamic causal modeling study using ASL data.
Effective connectivity is commonly assessed using blood oxygenation level-dependent (BOLD) signals. In (Havlicek et al., 2015), we presented a novel, physiologically informed dynamic causal model (P-DCM) that extends current generative models. We demonstrated the improvements afforded by P-DCM in terms of the ability to model commonly observed neuronal and vascular transients in single regions. Here, we assess the ability of the novel and previous DCM variants to estimate effective connectivity among a network of five ROIs driven by a visuo-motor task. We demonstrate that connectivity estimates depend sensitively on the DCM used, due to differences in the modeling of hemodynamic response transients; such as the post-stimulus undershoot or adaptation during stimulation. In addition, using a novel DCM for arterial spin labeling (ASL) fMRI that measures BOLD and CBF signals simultaneously, we confirmed our findings (by using the BOLD data alone and in conjunction with CBF). We show that P-DCM provides better estimates of effective connectivity, regardless of whether it is applied to BOLD data alone or to ASL time-series, and that all new aspects of P-DCM (i.e. neuronal, neurovascular, hemodynamic components) constitute an improvement compared to those in the previous DCM variants. In summary, (i) accurate modeling of fMRI response transients is crucial to obtain valid effective connectivity estimates and (ii) any additional hemodynamic data, such as provided by ASL, increases the ability to disambiguate neuronal and vascular effects present in the BOLD signal.
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200MD Maastricht, The Netherlands. Electronic address: m.havlicek@maastrichtuniversity.nl.
Martin
M
Havlicek
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200MD Maastricht, The Netherlands.
Alard
A
Roebroeck
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom.
Karl J
KJ
Friston
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200MD Maastricht, The Netherlands.
Anna
A
Gardumi
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200MD Maastricht, The Netherlands.
Dimo
D
Ivanov
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200MD Maastricht, The Netherlands. Electronic address: kamil.uludag@maastrichtuniversity.nl.
Kamil
K
Uludag
D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D008959:Models, Neurological; D009434:Neural Pathways; D013113:Spin Labels; D055815:Young Adult
D013113:Spin Labels
ASL; BOLD signal; DCM; Effective connectivity; Hemodynamic transients