Cognitive function tends to decrease with aging, therefore maintenance of this function in an aging society is an important issue. The role of chewing in nutrition is important. Although several studies indicate that gum chewing is thought to improve cognitive function, it remains debatable whether gum-chewing does in fact improve cognitive function. The Stroop test is a psychological tool used to measure cognition. A shorter reaction time indicates a mean higher behavioral performance and higher levels of oxy-Hb concentration. fNIRS is a powerful, non-invasive imaging technique offering many advantages, including compact size, no need for specially equipped facilities, and the potential for real-time measurement. The left dorsolateral prefrontal cortex (DLPFC) seems to be mainly involved in the Stroop task.
The aim of the present study was to investigate the hypothesis that gum-chewing changes cerebral blood flow in the left DLPFC during the Stroop test, and also changes the reaction time. Fourteen healthy volunteers (mean age 26.9 years) participated in this study after providing written informed consent. A piece of tasteless gum weighing 1.0 g was used. Each session was designed in a block manner, i.e. 4 rests (30 s) and 3 blocks of task (30 s). A computerized Stroop test was used (including both congruent and incongruent Stroop tasks) which calculates a response time automatically. The Binominal test was used for comparisons (p < 0.05). The results show activation of the left DLPFC during the Stroop task and that gum chewing significantly increases responses/oxy-Hb concentration and significantly shortens the reaction time.
Stroop test Gum- chewing Near-infrared spectroscopy The left dorsolateral prefrontal cortex Cognitive function
This is a preview of subscription content, log in to check access.
This research was partly supported by the Japan Science and Technology Agency, under the Strategic Promotion of Innovative Research and Development Program, and a Grant-in-Aid from the Ministry of Education, Culture, Sports, Sciences and Technology of Japan (23300247, 25463025, and 25463024).
Carp J, Gmeindl L, Reuter-Lorenz PA (2010) Age differences in the neural representation of working memory revealed by multi-voxel pattern analysis. Front Hum Neurosci 4:217CrossRefPubMedPubMedCentralGoogle Scholar
Onozuka M, Watanabe K, Fujita M et al (2002) Evidence for involvement of glucocorticoid response in the hippocampal changes in aged molarless SAMP8 mice. Behav Brain Res 131:125–129CrossRefPubMedGoogle Scholar
Baker JR, Bezance JB, Zellaby E et al (2004) Chewing gum can produce context-dependent effects upon memory. Appetite 43:207–210CrossRefPubMedGoogle Scholar
Tucha L, Simpson W, Evans L et al (2010) Detrimental effects of gum chewing on vigilance in children with attention deficit hyperactivity disorder. Appetite 55:679–684CrossRefPubMedGoogle Scholar
Tucha L, Simpson W (2011) The role of time on task performance in modifying the effects of gum chewing on attention. Appetite 56:299–301CrossRefPubMedGoogle Scholar
Onyper SV, Carr TL, Farrar JS et al (2011) Cognitive advantages of chewing gum. Now you see them, now you don’t. Appetite 57:321–328CrossRefPubMedGoogle Scholar
Hirano Y, Obata T, Kashikura K et al (2008) Effects of chewing in working memory processing. Neurosci Lett 436:189–192CrossRefPubMedGoogle Scholar
Takada T, Miyamoto T (2004) A fronto-parietal network for chewing of gum: a study on human subjects with functional magnetic resonance imaging. Neurosci Lett 360:137–140CrossRefPubMedGoogle Scholar
Momose I, Nishikawa J, Watanabe T et al (1997) Effect of mastication on regional cerebral blood flow in humans examined by positron-emission tomography with 15O-labelled water and magnetic resonance imaging. Arch Oral Biol 42:57–61CrossRefPubMedGoogle Scholar
Ehlis AC, Herrmann MJ, Wagener A et al (2005) Multi-channel near-infrared spectroscopy detects specific inferior-frontal activation during incongruent Stroop trials. Biol Psychol 69:315–331CrossRefPubMedGoogle Scholar
Hyodo K, Dan I, Suwabe K et al (2012) Acute moderate exercise enhances compensatory brain activation in older adults. Neurobiol Aging 33:2621–2632CrossRefPubMedGoogle Scholar
Hoshi Y (2003) Functional near-infrared optical imaging: utility and limitations in human brain mapping. Psychophysiology 40:511–520CrossRefPubMedGoogle Scholar
Jobsis FF (1977) Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science 198:1264–1267CrossRefPubMedGoogle Scholar
Hoshi Y, Kobayashi N, Tamura M (2001) Interpretation of near-infrared spectroscopy signals: a study with a newly developed perfused rat brain model. J Appl Physiol 90:1657–1662PubMedGoogle Scholar
Shibusawa M, Takeda T, Nakajima K et al (2009) Functional near-infrared spectroscopy study on primary motor and sensory cortex response to clenching. Neurosci Lett 449:98–102CrossRefPubMedGoogle Scholar
Tanida M, Sakatani K, Takano R et al (2004) Relation between asymmetry of prefrontal cortex activities and the autonomic nervous system during a mental arithmetic task: near infrared spectroscopy study. Neurosci Lett 369:69–74CrossRefPubMedGoogle Scholar
Leon-Carrion J, Damas-Lopez J, Martin-Rodriguez JF et al (2008) The hemodynamics of cognitive control: the level of concentration of oxygenated hemoglobin in the superior prefrontal cortex varies as a function of performance in a modified Stroop task. Behav Brain Res 193:248–256CrossRefPubMedGoogle Scholar
Yamada T, Umeyama S, Matsuda K (2012) Separation of fNIRS signals into functional and systemic components based on differences in hemodynamic modalities. PLoS One 7:e50271CrossRefPubMedPubMedCentralGoogle Scholar
Stephens R, Tunney RJ (2004) Role of glucose in chewing gum-related facilitation of cognitive function. Appetite 43:211–213CrossRefPubMedGoogle Scholar
Brehmer Y, Rieckmann A, Bellander M et al (2011) Neural correlates of training-related working-memory gains in old age. NeuroImage 58:1110–1120CrossRefPubMedGoogle Scholar