No abstract

Caffeine (CAF) and maltodextrin (MALT) mouth rinses (MR) improve exercise performance. The current experiment aims to determine the effect of CAF and MALT MR on cognitive performance and brain activity. Ten healthy male subjects (age 27 ± 3 yr) completed three experimental trials. Each trial included four Stroop tasks: two familiarization tasks, and one task before and one task after an MR period. The reaction time (in milliseconds) and accuracy (percent) of simple, congruent, and incongruent stimuli were assessed. Electroencephalography was applied throughout the experiment to record brain activity. The amplitudes and latencies of the P300 were determined during the Stroop tasks before and after the MR period. Subjects received MR with CAF (0.3 g/25 ml), MALT (1.6 g/25 ml), or placebo (PLAC) in a randomized, double-blind, crossover design. During MR, the brain imaging technique standardized low-resolution brain electromagnetic tomography was applied. Magnitude-based inferences showed that CAF MR is likely trivial (63.5%) and likely beneficial (36.4%) compared with PLAC MR, and compared with MALT MR likely beneficial to reaction time on incongruent stimuli (61.6%). Additionally, both the orbitofrontal and dorsolateral prefrontal cortex were activated only during CAF MR, potentially explaining the likely beneficial effect on reaction times. MALT MR increased brain activity only within the orbitofrontal cortex. However, this brain activation did not alter the reaction time. Furthermore, no significant differences in the accuracy of stimuli responses were observed between conditions. In conclusion, only CAF MR exerted a likely beneficial effect on reaction time due to the subsequent activation of both the orbitofrontal and dorsolateral prefrontal cortexes.

Highlights• A novel similarity metric for multimodal groupwise registration is proposed.• The proposed method showed equivalent or improved registration accuracy.• Pairwise mutual information is outperformed in terms of transitivity. AbstractImage registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting remains difficult, due to the lack of generally applicable similarity metrics. In this work, a novel similarity metric for such groupwise registration problems is proposed. The metric calculates the sum of the conditional entropy between each image in the group and a representative template image constructed iteratively using principal component analysis. The proposed metric is validated in extensive experiments on synthetic and intrasubject clinical image data. These experiments showed equivalent or improved registration accuracy compared to other state-of-the-art (dis)similarity metrics and improved transformation consistency compared to pairwise mutual information.