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On the second level (group level), FEAT was used to perform a voxel-wise statistical analysis using a mixed effects model to combine the GLM results of individual participants while accounting for intersubject variance. A cluster threshold of Z?>?2.3 and a (corrected) cluster significance threshold of P?=?0.05 were used. An anatomical mask of the primary visual cortex (V1) was created using the Juelich histological atlas within FSLView (http://www.fmrib.ox.ac.uk/fsl/fslview/index.html) with a probability threshold applied at 0.35. This mask was Rigosertib used to determine perfusion changes in the visual cortex in response to visual stimulation and the interactions between visual stimulation and respiratory loading. A region of interest approach was used to calculate mean fractional perfusion changes in response to inspiratory and expiratory loading in the whole S1PR1 brain grey matter (grey matter masks determined individually by segmenting participants' structural scans with FAST (FMRIB's Automated Segmentation Tool, http://www.fmrib.ox.ac.uk/analysis/research/fast/)), and in the individual brain areas with significantly increased perfusion demonstrated in the voxel-wise analysis. It is possible that localized CBF increases (e.g. activation due to the work of breathing against load etc.) might elevate the general global CBF change. It is also possible that a small collinearity between respiratory loading and the visual stimulation could Bleomycin price inflate the global grey matter increase. Therefore, to account for both of these potential effects, we performed a second region of interest analysis specifically excluding localized CBF increases (i.e. sensorimotor cortices and cerebellum) that were assumed to be task specific and also excluding V1. In order to compare our results to the well-known effects of CO2 on cerebral perfusion (Cohen et al., 2002), we included the natural fluctuations in PETCO2 in the statistical model (i.e. although participants attempted to keep PETCO2 constant, spontaneous fluctuations and small imperfections in performing this task were present (Wise et al., 2004)). To retrospectively evaluate the sensitivity of our study design, we used the study sample size and the standard deviations from our region of interest analyses to statistically determine the smallest grey matter and V1 perfusion increases that our study is able to detect with 80% confidence. Physiological results of the laboratory session are reported in the top part of Table?1. There was no significant difference between the first and second block of each stimulation condition, hence values are presented as averages over both blocks. Mean arterial pressure increased from 90.7?��?15.2?mm?Hg to 93.8?��?15.7?mm?Hg (p?