Importance Increases in fructose consumption have paralleled the increasing prevalence of obesity, and high-fructose diets are thought to promote weight gain and insulin resistance. Fructose ingestion produces smaller increases in circulating satiety hormones compared with glucose ingestion, and central administration of fructose provokes feeding in rodents, whereas centrally administered glucose promotes satiety. Objective To study neurophysiological factors that might underlie associations between fructose consumption and weight gain. Design, Setting, and Participants Twenty healthy adult volunteers underwent 2 magnetic resonance imaging sessions at Yale University in conjunction with fructose or glucose drink ingestion in a blinded, random-order, crossover design. Main Outcome Measures Relative changes in hypothalamic regional cerebral blood flow (CBF) after glucose or fructose ingestion. Secondary outcomes included whole-brain analyses to explore regional CBF changes, functional connectivity analysis to investigate correlations between the hypothalamus and other brain region responses, and hormone responses to fructose and glucose ingestion. Results There was a significantly greater reduction in hypothalamic CBF after glucose vs fructose ingestion (–5.45 vs 2.84 mL/g per minute, respectively; mean difference, 8.3 mL/g per minute [95% CI of mean difference, 1.87-14.70]; P=.01). Glucose ingestion (compared with baseline) increased functional connectivity between the hypothalamus and the thalamus and striatum. Fructose increased connectivity between the hypothalamus and thalamus but not the striatum. Regional CBF within the hypothalamus, thalamus, insula, anterior cingulate, and striatum (appetite and reward regions) was reduced after glucose ingestion compared with baseline (P<.05 significance threshold, family-wise error [FWE] whole-brain corrected). In contrast, fructose reduced regional CBF in the thalamus, hippocampus, posterior cingulate cortex, fusiform, and visual cortex (P<.05 significance threshold, FWE whole-brain corrected). In whole-brain voxel-level analyses, there were no significant differences between direct comparisons of fructose vs glucose sessions following correction for multiple comparisons. Fructose vs glucose ingestion resulted in lower peak levels of serum glucose (mean difference, 41.0 mg/dL [95% CI, 27.7-54.5]; P<.001), insulin (mean difference, 49.6 μU/mL [95% CI, 38.2-61.1]; P<.001), and glucagon-like polypep-tide 1 (mean difference, 2.1 pmol/L [95% CI, 0.9-3.2]; P=.01). Conclusion and Relevance In a series of exploratory analyses, consumption of fructose compared with glucose resulted in a distinct pattern of regional CBF and a smaller increase in systemic glucose, insulin, and glucagon-like polypeptide 1 levels.

SUMMARYPurpose: This work examines the efficacy of functional magnetic resonance imaging (fMRI) for language lateralization using a comprehensive three-task language-mapping approach. Two localization methods and four different metrics for quantifying activation within hemisphere are compared and validated with Wada testing. Sources of discordance between fMRI and Wada lateralization are discussed with respect to specific patient examples. Methods: fMRI language mapping was performed in patients with epilepsy (N = 40) using reading sentence comprehension, auditory sentence comprehension, and a verbal fluency task. This was compared with the Wada procedure using both whole-brain and midline exclusion-based analyses. Different laterality scores were examined as a function of statistical threshold to investigate the sensitivity to threshold effects. Results: For the lateralized patients categorized by Wada, fMRI laterality indices (LIs) were concordant with the Wada procedure results in 83.87% patients for the reading task, 83.33% patients for the auditory task, 76.92% patients for the verbal fluency task, and in 91.3% patients for the conjunction analysis. The patients categorized as bilateral via the Wada procedure showed some hemispheric dominance in fMRI, and discrepancies between the Wada test findings and the functional laterality scores arose for a range of reasons. Discussion: Discordance was dependent upon whether whole-brain or midline exclusion method-based lateralization was calculated, and in the former case the inclusion of the occipital and other midline regions often negatively influenced the lateralization scores. Overall fMRI was in agreement with the Wada test in 91.3% of patients, suggesting its utility for clinical use with the proper consideration given to the confounds discussed in this work.

Individual differences in brain functional organization track a range of traits, symptoms and behaviours1–12. So far, work modelling linear brain–phenotype relationships has assumed that a single such relationship generalizes across all individuals, but models do not work equally well in all participants13,14. A better understanding of in whom models fail and why is crucial to revealing robust, useful and unbiased brain–phenotype relationships. To this end, here we related brain activity to phenotype using predictive models—trained and tested on independent data to ensure generalizability15—and examined model failure. We applied this data-driven approach to a range of neurocognitive measures in a new, clinically and demographically heterogeneous dataset, with the results replicated in two independent, publicly available datasets16,17. Across all three datasets, we find that models reflect not unitary cognitive constructs, but rather neurocognitive scores intertwined with sociodemographic and clinical covariates; that is, models reflect stereotypical profiles, and fail when applied to individuals who defy them. Model failure is reliable, phenotype specific and generalizable across datasets. Together, these results highlight the pitfalls of a one-size-fits-all modelling approach and the effect of biased phenotypic measures18–20 on the interpretation and utility of resulting brain–phenotype models. We present a framework to address these issues so that such models may reveal the neural circuits that underlie specific phenotypes and ultimately identify individualized neural targets for clinical intervention.

Arterial transit time (ATT), a key parameter required to calculate absolute cerebral blood flow in arterial spin labeling (ASL), is subject to much uncertainty. In this study, ASL ATTs were estimated on a per-voxel basis using data measured by both ASL and positron emission tomography in the same subjects. The mean ATT increased by 260 6 20 (standard error of the mean) ms when the imaging slab shifted downwards by 54 mm, and increased from 630 6 30 to 1220 6 30 ms for the first slice, with an increase of 610 6 20 ms over a four-slice slab when the gap between the imaging and labeling slab increased from 20 to 74 mm. When the per-slice ATTs were employed in ASL cerebral blood flow quantification and the in-slice ATT variations ignored, regional cerebral blood flow could be significantly different from the positron emission tomography measures. ATT also decreased with focal activation by the same amount for both visual and motor tasks (~80 ms). These results provide a quantitative relationship between ATT and the ASL imaging geometry and yield an assessment of the assumptions commonly used in ASL imaging. These findings should be considered in the interpretation of, and comparisons between, different ASL-based cerebral blood flow studies. The results also provide spatially specific ATT data that may aid in optimizing the ASL imaging parameters. Key words: arterial transit time; cerebral blood flow; positron emission tomography; pulsed arterial spin labeling; brain vasculature Significant efforts have been made to improve the accuracy of absolute cerebral blood flow (CBF) measurements estimated by pulsed arterial spin labeling (ASL) MRI. To improve the inversion profile and the labeling efficiency, adiabatic or hypersecant pulses and other variants have been proposed (1-4). To overcome the signal dampening due to the off-resonance effect of the inversion radiofrequency (RF) pulse, separate coils for labeling and detection have been employed (5-9). Measurement of the arterial blood proton density was suggested to minimize the nonuniformity of the brain tissue-blood partition coefficient (k) (10), and methods have been presented to reduce the sensitivity of CBF quantification to arterial transit time (ATT) effects (contamination from intravascular arterial blood water) in CBF quantification (11-13).In ASL, water in the arteries is magnetically labeled, and when it reaches the capillary bed and exchanges with the extravascular water, the labeled water induces changes in local magnetization relative to the case in which the arterial water is undisturbed. These changes are detectable by MRI and such images of the intensity changes are perfusion weighted. Absolute CBF values can be calculated based on these perfusion-weighted intensity changes. ATTs, however, are one of the key phenomena that affect the calculation of the absolute CBF from the image intensity differences. In ASL, ATT refers to the time it takes the arterial blood to travel from the labeling site to the capillaries in the tissue being imaged. By definitio...

OBJECTIVE-The hypothalamus is the central brain region responsible for sensing and integrating responses to changes in circulating glucose. The aim of this study was to determine the time sequence relationship between hypothalamic activation and the initiation of the counterregulatory hormonal response to small decrements in systemic glucose.RESEARCH DESIGN AND METHODS-Nine nondiabetic volunteers underwent two hyperinsulinemic clamp sessions in which pulsed arterial spin labeling was used to measure regional cerebral blood flow (CBF) at euglycemia (ϳ95 mg/dl) on one occasion and as glucose levels were declining to a nadir of ϳ50 mg/dl on another occasion. Plasma glucose and counterregulatory hormones were measured during both study sessions.RESULTS-CBF to the hypothalamus significantly increased when glucose levels decreased to 77.2 Ϯ 2 mg/dl compared with the euglycemic control session when glucose levels were 95.7 Ϯ 3 mg/dl (P ϭ 0.0009). Hypothalamic perfusion was significantly increased before there was a significant elevation in counterregulatory hormones.CONCLUSIONS-Our data suggest that the hypothalamus is exquisitely sensitive to small decrements in systemic glucose levels in healthy, nondiabetic subjects and that hypothalamic blood flow, and presumably neuronal activity, precedes the rise in counterregulatory hormones seen during hypoglycemia. Diabetes 58:448-452, 2009 T he brain relies on glucose as its main energy substrate, and small decrements in circulating glucose provoke an elaborate counterregulatory hormonal feedback response (1,2). Activation of the counterregulatory response requires effective detection of a falling glucose level. Although multiple glucose sensors may be involved (3-7), the hypothalamus has emerged as the dominant brain region responsible for sensing and integrating responses to changes in circulating glucose levels (8 -12). Although most prior studies have relied on animal models to study the neurophysiological response to changes in glucose, newer imaging techniques such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) provide an in vivo method to study the effect of changes in peripheral glucose levels on human brain activity. Several fMRI studies in humans have demonstrated that a rise in systemic glucose after glucose ingestion leads to an inhibition of hypothalamic activity (13-16). In addition, Musen et al. (17) recently used fMRI based on the blood oxygenation leveldependent (BOLD) contrast mechanism and found that insulin-induced hypoglycemia leads to hypothalamic activation. However, the fMRI-BOLD approach used in that study assesses only relative changes in oxygenated hemoglobin in specific brain regions and does not directly measure tissue perfusion. Magnetic resonance imaging (MRI) pulsed arterial spin labeling (PASL) provides a method for measuring absolute blood flow responses throughout the brain to changes in circulating glucose levels. PASL magnetically tags the arterial blood before entering the brain and then examines t...

Increased sugar-sweetened beverage consumption has been linked to higher rates of obesity. Using functional MRI, we assessed brain perfusion responses to drinking two commonly consumed monosaccharides, glucose and fructose, in obese and lean adolescents. Marked differences were observed. In response to drinking glucose, obese adolescents exhibited decreased brain perfusion in brain regions involved in executive function (prefrontal cortex [PFC]) and increased perfusion in homeostatic appetite regions of the brain (hypothalamus). Conversely, in response to drinking glucose, lean adolescents demonstrated increased PFC brain perfusion and no change in perfusion in the hypothalamus. In addition, obese adolescents demonstrated attenuated suppression of serum acyl-ghrelin and increased circulating insulin level after glucose ingestion; furthermore, the change in acyl-ghrelin and insulin levels after both glucose and fructose ingestion was associated with increased hypothalamic, thalamic, and hippocampal blood flow in obese relative to lean adolescents. Additionally, in all subjects there was greater perfusion in the ventral striatum with fructose relative to glucose ingestion. Finally, reduced connectivity between executive, homeostatic, and hedonic brain regions was observed in obese adolescents. These data demonstrate that obese adolescents have impaired prefrontal executive control responses to drinking glucose and fructose, while their homeostatic and hedonic responses appear to be heightened. Thus, obesity-related brain adaptations to glucose and fructose consumption in obese adolescents may contribute to excessive consumption of glucose and fructose, thereby promoting further weight gain.

Objective:The purpose of this study was to investigate functional connectivity (FC) changes in epileptogenic networks in intractable partial epilepsy obtained from resting-state fMRI by using intrinsic connectivity contrast (ICC), a voxel-based network measure of degree that reflects the number of connections to each voxel.Methods:We measured differences between intrahemispheric- and interhemispheric-ICC (ICCintra−inter) that could reveal localized connectivity abnormalities in epileptogenic zones while more global network changes would be eliminated when subtracting these values. The ICCintra−inter map was compared with the seizure onset zone (SOZ) based on intracranial EEG (icEEG) recordings in 29 patients with at least 1 year of postsurgical follow-up. Two independent reviewers blindly interpreted the icEEG and fMRI data, and the concordance rates were compared for various clinical factors.Results:Concordance between the icEEG SOZ and ICCintra−inter map was observed in 72.4% (21/29) of the patients, which was higher in patients with good surgical outcome, especially in those patients with temporal lobe epilepsy (TLE) or lateral temporal seizure localization. Concordance was also better in the extratemporal lobe epilepsy than the TLE group. In 85.7% (18/21) of the cases, the ICCintra−inter values were negative in the SOZ, indicating decreased FC within the epileptic hemisphere relative to between hemispheres.Conclusions:Assessing alterations in FC using fMRI-ICC map can help localize the SOZ, which has potential as a noninvasive presurgical diagnostic tool to improve surgical outcome. In addition, the method reveals that, in focal epilepsy, both intrahemispheric- and interhemispheric-FC may be altered, in the presence of both regional as well as global network abnormalities.

Epilepsy is a brain disorder usually associated with abnormal cortical and/or subcortical functional networks. Exploration of the abnormal network properties and localization of the brain regions involved in human epilepsy networks are critical for both the understanding of the epilepsy networks and planning therapeutic strategies. Currently, most localization of seizure networks come from ictal EEG observations. Functional MRI provides high spatial resolution together with more complete anatomical coverage compared with EEG and may have advantages if it can be used to identify the network(s) associated with seizure onset and propagation. Epilepsy networks are believed to be present with detectable abnormal signatures even during the interictal state. In this study, epilepsy networks were investigated using resting-state fMRI acquired with the subjects in the interictal state. We tested the hypothesis that social network theory applied to resting-state fMRI data could reveal abnormal network properties at the group level. Using network data as input to a classification algorithm allowed separation of medial temporal lobe epilepsy (MTLE) patients from normal control subjects indicating the potential value of such network analyses in epilepsy. Five local network properties obtained from 36 anatomically defined ROIs were input as features to the classifier. An iterative feature selection strategy based on the classification efficiency that can avoid ‘over-fitting’ is proposed to further improve the classification accuracy. An average sensitivity of 77.2% and specificity of 83.86% were achieved via ‘leave one out’ cross validation. This finding of significantly abnormal network properties in group level data confirmed our initial hypothesis and provides motivation for further investigation of the epilepsy process at the network level.