Effect of carbonation on brain processing of sweet stimuli in humans.

Little is known about how CO2 affects neural processing of taste. We used functional magnetic resonance imaging to investigate the effects of carbonation on brain processing of sweet stimuli, which has relevance to studies of food selection and satiety. The presence of carbonation produced an overall decrease in the neural processing of sweetness-related signals, especially from sucrose.

The role of a pre-load beverage on gastric volume and food intake: comparison between non-caloric carbonated and non-carbonated beverage.

Background: There is conflicting data on the effects of carbon dioxide contained in beverages on stomach functions. We aimed to verify the effect of a pre-meal administration of a 300 ml non-caloric carbonated beverage (B+CO2) compared to water or a beverage without CO2 (B-CO2), during a solid (SM) and a liquid meal (LM) on: a) gastric volume, b) caloric intake, c) ghrelin and cholecystokinin (CCK) release in healthy subjects.

Methods: After drinking the beverages (Water, B-CO2, B+CO2), ten healthy subjects (4 women, aged 22-30 years; BMI 23 ± 1) were asked to consume either an SM or an LM, at a constant rate (110 kcal/5 min).

Distributed analysis of simultaneous EEG-fMRI time-series: modeling and interpretation issues.

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) represent brain activity in terms of a reliable anatomical localization and a detailed temporal evolution of neural signals. Simultaneous EEG-fMRI recordings offer the possibility to greatly enrich the significance and the interpretation of the single modality results because the same neural processes are observed from the same brain at the same time. Nonetheless, the different physical nature of the measured signals by the two techniques renders the coupling not always straightforward, especially in cognitive experiments where spatially localized and distributed effects coexist and evolve temporally at different temporal scales.

Independent component model of the default-mode brain function: combining individual-level and population-level analyses in resting-state fMRI.

Resting-state functional magnetic resonance imaging (RS-fMRI) is a technique used to investigate the spontaneous correlations of blood-oxygen-level-dependent signals across different regions of the brain. Using functional connectivity tools, it is possible to investigate a specific RS-fMRI network, referred to as "default-mode" (DM) network, that involves cortical regions deactivated in fMRI experiments with cognitive tasks. Previous works have reported a significant effect of aging on DM regions activity.

Spatio-temporal pattern of vestibular information processing after brief caloric stimulation.

Processing of vestibular information at the cortical and subcortical level is essential for head and body orientation in space and self-motion perception, but little is known about the neural dynamics of the brain regions of the vestibular system involved in this task. Neuroimaging studies using both galvanic and caloric stimulation have shown that several distinct cortical and subcortical structures can be activated during vestibular information processing. The insular cortex has been often targeted and presented as the central hub of the vestibular cortical system.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure.