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. CO2 reduced the neural processing of sucrose more than that of artificial sweeteners. These findings might be relevant to dietary interventions that include noncaloric beverages, whereas the combination of CO2 and sucrose might increase consumption of 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). Total gastric volumes (TGV) were evaluated by Magnetic Resonance Imaging after drinking the beverage and at maximum satiety (MS). Total kcal intake at MS was evaluated. Ghrelin and CCK were measured by enzyme immunoassay until 120 min after the meal. Statistical calculations were carried out by paired T-test and analysis of variance (ANOVA). The data is expressed as mean ± SEM. RESULTS: TGV after B+CO2 consumption was significantly higher than after B-CO2 or water (p < 0.05), but at MS, it was no different either during the SM or the LM. Total kcal intake did not differ at MS after any of the beverages tested, with either the SM (Water: 783 ± 77 kcals; B-CO2: 837 ± 66; B+CO2: 774 ± 66) or the LM (630 ± 111; 585 ± 88; 588 ± 95). Area under curve of ghrelin was significantly (p < 0.05) lower (13.8 ± 3.3 ng/ml/min) during SM following B-CO2 compared to B+CO2 and water (26.2 ± 4.5; 27.1 ± 5.1). No significant differences were found for ghrelin during LM, and for CCK during both SM and LM after all beverages. CONCLUSIONS: The increase in gastric volume following a 300 ml pre-meal carbonated beverage did not affect food intake whether a solid or liquid meal was given. The consistency of the meal and the carbonated beverage seemed to influence ghrelin release, but were unable, under our experimental conditions, to modify food intake in terms of quantity. Further studies are needed to verify if other food and beverage combinations are able to modify satiation.

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. The purpose of this article is to illustrate the combination of simultaneously recorded EEG and fMRI signals exploiting the principles of EEG distributed source modeling. We define a common source space for fMRI and EEG signal projection and gather a conceptually unique framework for the spatial and temporal comparative analysis. We illustrate this framework in a graded-load working-memory simultaneous EEG-fMRI experiment based on the n-back task where sustained load-dependent changes in the blood-oxygenation-level-dependent (BOLD) signals during continuous item memorization co-occur with parametric changes in the EEG theta power induced at each single item. In line with previous studies, we demonstrate on two single-subject cases how the presented approach is capable of colocalizing in midline frontal regions two phenomena simultaneously observed at different temporal scales, such as the sustained negative changes in BOLD activity and the parametric EEG theta synchronization. We discuss the presented approach in relation to modeling and interpretation issues typically arising in simultaneous EEG-fMRI studies.

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. Since very short pulses of cold water ear irrigation can generate a strong and prolonged vestibular response and a nystagmus, we explored the effects of this type of caloric stimulation for assessing the blood-oxygen-level-dependent (BOLD) dynamics of neural vestibular processing in a whole-brain event-related functional magnetic resonance imaging (fMRI) experiment. We evaluated the spatial layout and the temporal dynamics of the activated cortical and subcortical regions in time-locking with the instant of injection and were able to extract a robust pattern of neural activity involving the contra-lateral insular cortex, the thalamus, the brainstem and the cerebellum. No significant correlation with the temporal envelope of the nystagmus was found. The temporal analysis of the activation profiles highlighted a significantly longer duration of the evoked BOLD activity in the brainstem compared to the insular cortex suggesting a functional de-coupling between cortical and subcortical activity during the vestibular response.

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. Independent component analysis (ICA) is often used for generating spatially distributed DM functional connectivity patterns from RS-fMRI data without the need for a reference region. This aspect and the relatively easy setup of an RS-fMRI experiment even in clinical trials have boosted the combined use of RS-fMRI and ICA-based DM analysis for noninvasive research of brain disorders. In this work, we considered different strategies for combining ICA results from individual-level and population-level analyses and used them to evaluate and predict the effect of aging on the DM component. Using RS-fMRI data from 20 normal subjects and a previously developed group-level ICA methodology, we generated group DM maps and showed that the overall ICA-DM connectivity is negatively correlated with age. A negative correlation of the ICA voxel weights with age existed in all DM regions at a variable degree. As an alternative approach, we generated a distributed DM spatial template and evaluated the correlation of each individual DM component fit to this template with age. Using a "leave-one-out" procedure, we discuss the importance of removing the bias from the DM template-generation process.

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. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.