Abstract
ABSTRACTBackgroundThe reward value of palatable foods is often cited as an important influence on eating behaviors, including intake of sugars. However, human neuroimaging studies have generated conflicting evidence on the basic neural representation of taste and reward responses to caloric sweeteners (sucrose and glucose), and most relevant studies have used small subject numbers.ObjectiveWe conducted a systematic review and a coordinate-based meta-analysis of studies reporting brain responses to oral sugar solutions.MethodsA systematic search of MEDLINE, Scopus, and PsycINFO through October 2019 identified fMRI studies (in healthy human adults, including those with overweight or obesity) assessing differences in responses to purified sweet and nonsweet taste stimuli. Data were extracted with the primary objective of quantifying evidence for the activation of brain regions associated with caloric sweet taste sensation. We used activation likelihood estimation meta-analysis methods. We also performed multiple sensitivity analyses to assess the generality of effects.ResultsOf 455 unique articles, 15 met the criteria for inclusion. These contributed to 2 primary meta-analyses: 1) sucrose (13 experiments, 179 coordinates, n = 241) and 2) sucrose + glucose (16 experiments, 209 coordinates, n = 262). Consistent activation was apparent in primary taste areas: insula (69.2% of studies) and opercular cortex (76.9% of studies), precentral gyri (53.9% of studies), and globus pallidus and postcentral gyrus (30.8% of studies for each). Evidence of reward activity (caudate) was seen in the primary analyses (30.8% of studies) but not in sensitivity analysis.ConclusionsWe confirm the importance of primary taste areas for gustatory processing in human adults. We also provide tentative evidence for reward-related caudate activity in relation to the sweet taste of caloric sugars. A number of factors affect the observation and interpretation of brain responses, including reward-related activity. Firm conclusions require confirmation with large data set studies.
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