Oromotor and somatic taste reactivity during sucrose meals reveals internal state and stimulus palatability after gastric bypass in rats
G. D. Blonde; C. M. Mathes; T. Inui; E. A. Hamel; R. K. Price; M. B. E. Livingstone; C. W. Le Roux; A. C. Spector
Year of publication
Am J Physiol Regul Integr Comp Physiol
After Roux-en-Y gastric bypass (RYGB), rats consume less high-energy foods and fluids, though whether this reflects a concomitant change in palatability remains unclear. By measuring behavior during intraorally delivered liquid meals across days (1 water, 8 sucrose sessions), we showed that RYGB rats (RYGB, n = 8/sex) consumed less 1.0 M sucrose than their sham surgery counterparts (SHAM, n = 8 males, n = 11 females) but displayed similarly high levels of ingestive taste reactivity responses at the start of infusions. Relative to water, both groups increased intake of sucrose, and ingestive responses were dominated by tongue protrusions rather than mouth movements. Thus, RYGB animals still found sucrose palatable despite consuming less than the SHAM group. As the intraoral infusion progressed but before meal termination, aversive behavior remained low and both RYGB and SHAM animals showed fewer ingestive responses, predominantly mouth movements as opposed to tongue protrusions. This shift in responsiveness unrelated to surgical manipulation suggests negative alliesthesia, or a decreased palatability, as rats approach satiation. Notably, only in RYGB rats, across sessions, there was a striking emergence of aversive behavior immediately after the sucrose meal. Thus, although lower intake in RYGB rats seems independent of the hedonic taste properties of sucrose, taste reactivity behavior in these animals immediately after termination of a liquid meal appears to be influenced by postoral events and reflects a state of nimiety or excessive consumption. Measurement of taste reactivity behaviors during an intraorally delivered meal represents a promising way to make inferences about internal state in nonverbal preclinical models.