BACKGROUND There is growing evidence to suggest that the brain is an important target for insulin action and that states of insulin resistance may extend to the CNS, with detrimental effects on cognitive functioning. Although the effect of systemic insulin resistance on peripheral organs is well studied, the degree to which insulin affects brain function in vivo remains unclear.METHODS This randomized, single-blinded, 2-way–crossover, sham-controlled, pilot study determined the effects of hyperinsulinemia on functional MRI (fMRI) brain activation during a 2-back working memory task in 9 healthy older adults (aged 57–79 years). Each participant underwent 2 clamp procedures (an insulin infusion and a saline placebo infusion, with normoglycemia maintained during both conditions) to examine the effects of hyperinsulinemia on task performance and associated blood oxygen level–dependent (BOLD) signal using fMRI.RESULTS Hyperinsulinemia (compared with saline control) was associated with an increase in both the spatial extent and relative strength of task-related BOLD signal during the 2-back task. Further, the degree of increased task-related activation in select brain regions correlated with greater systemic insulin sensitivity as well as decreased reaction times and performance accuracy between experimental conditions.CONCLUSION Together, these findings provide evidence of insulin action in the CNS among older adults during periods of sustained cognitive demand, with the greatest effects noted for individuals with highest systemic insulin sensitivity.FUNDING This work was funded by the NIH (5R21AG051958, 2016).
Victoria J. Williams, Bianca A. Trombetta, Rabab Z. Jafri, Aaron M. Koenig, Chase D. Wennick, Becky C. Carlyle, Laya Ekhlaspour, Rexford S. Ahima, Steven J. Russell, David H. Salat, Steven E. Arnold
Usage data is cumulative from June 2019 through April 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.