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https://www.selleckchem.com/products/sch-900776.html We compare results to those found using group independent component analysis (ICA) and canonical ICA. Bootstrap analysis demonstrates increased robustness of networks found using the CP tensor approach relative to ICA-based methods.Functional magnetic resonance imaging (fMRI) based on the Blood Oxygenation Level Dependent (BOLD) contrast takes advantage of the coupling between neuronal activity and the hemodynamics to allow a non-invasive localisation of the neuronal activity. In general, fMRI experiments assume a linear relationship between neuronal activation and the observed hemodynamics. However, the relationship between BOLD responses, neuronal activity, and behaviour are often nonlinear. In addition, the nonlinearity between BOLD responses and behaviour may be related to neuronal process rather than a neurovascular uncoupling. Further, part of the nonlinearity may be driven by vascular nonlinearity effects in particular from large vessel contributions. fMRI based on cerebral blood volume (CBV), promises a higher microvascular specificity, potentially without vascular nonlinearity effects and reduced contamination of the large draining vessels compared to BOLD. In this study, we aimed to investigate differences in BOLD and VASO-CBV signal changes during a hand movement task over a broad range of movement rates. We used a double readout 3D-EPI sequence at 7T to simultaneously measure VASO-CBV and BOLD responses in the sensorimotor cortex. The measured BOLD and VASO-CBV responses increased very similarly in a nonlinear fashion, plateauing for movement rates larger than 1 Hz. Our findings show a tight relationship between BOLD and VASO-CBV responses, indicating that the overall interplay of CBV and BOLD responses are similar for the assessed range of movement rates. These results suggest that the observed nonlinearity of neuronal origin is already present in VASO-CBV measurements, and consequently shows relative

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