Neural reactivity to visual food stimuli is reduced in some areas of the brain during evening hours compared to morning hours: an fMRI study in women

Abstract

The extent that neural responsiveness to visual food stimuli is influenced by time of day is not well examined. Using a crossover design, 15 healthy women were scanned using fMRI while presented with low- and high-energy pictures of food, once in the morning (6:30–8:30 am) and once in the evening (5:00–7:00 pm). Diets were identical on both days of the fMRI scans and were verified using weighed food records. Visual analog scales were used to record subjective perception of hunger and preoccupation with food prior to each fMRI scan. Six areas of the brain showed lower activation in the evening to both high- and low-energy foods, including structures in reward pathways (P < 0.05). Nine brain regions showed significantly higher activation for high-energy foods compared to low-energy foods (P < 0.05). High-energy food stimuli tended to produce greater fMRI responses than low-energy food stimuli in specific areas of the brain, regardless of time of day. However, evening scans showed a lower response to both low- and high-energy food pictures in some areas of the brain. Subjectively, participants reported no difference in hunger by time of day (F = 1.84, P = 0.19), but reported they could eat more (F = 4.83, P = 0.04) and were more preoccupied with thoughts of food (F = 5.51, P = 0.03) in the evening compared to the morning. These data underscore the role that time of day may have on neural responses to food stimuli. These results may also have clinical implications for fMRI measurement in order to prevent a time of day bias.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. Allison, K. C., Goel, N., & Ahima, R. S. (2014). Delayed Timing of Eating: Impact on Weight and Metabolism. Current Obesity Reports , 3, 91–100.

    Article  PubMed  Google Scholar 

  2. Avants, B., Duda, J. T., Kim, J., Zhang, H., Pluta, J., Gee, J. C., & Whyte, J. (2008). Multivariate analysis of structural and diffusion imaging in traumatic brain injury. Academic Radiology, 15(11), 1360–1375. doi:10.1016/j.acra.2008.07.007.

    Article  PubMed  Google Scholar 

  3. Beechy, L., Galpern, J., Petrone, A., & Das, S. K. (2012). Assessment tools in obesity - psychological measures, diet, activity, and body composition. Physiology & Behavior, 107(1), 154–171. doi:10.1016/j.physbeh.2012.04.013.

    CAS  Article  Google Scholar 

  4. Brignell, C., Griffiths, T., Bradley, B. P., & Mogg, K. (2009). Attentional and approach biases for pictorial food cues. Influence of external eating. Appetite, 52(2), 299–306. doi:10.1016/j.appet.2008.10.007.

    Article  PubMed  Google Scholar 

  5. Bromberg-Martin, E. S., Matsumoto, M., & Hikosaka, O. (2010). Dopamine in motivational control: rewarding, aversive, and alerting. Neuron, 68(5), 815–834. doi:10.1016/j.neuron.2010.11.022.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. Bruce, A. S., Lepping, R. J., Bruce, J. M., Cherry, J. B., Martin, L. E., Davis, A. M., & Savage, C. R. (2013). Brain responses to food logos in obese and healthy weight children. Journal of Pediatrics, 162(4), 759–764. doi:10.1016/j.jpeds.2012.10.003. e752.

    Article  PubMed  Google Scholar 

  7. Conway, J. M., Ingwersen, L. A., Vinyard, B. T., & Moshfegh, A. J. (2003). Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. American Journal of Clinical Nutrition, 77(5), 1171–1178.

    CAS  PubMed  Google Scholar 

  8. Conway, J. M., Ingwersen, L. A., & Moshfegh, A. J. (2004). Accuracy of dietary recall using the USDA five-step multiple-pass method in men: An observational validation study. Journal of the American Dietetic Association, 104(4), 595–603. doi:10.1016/j.jada.2004.01.007.

    Article  PubMed  Google Scholar 

  9. Cox, R. W. (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, 29(3), 162–173.

    CAS  Article  PubMed  Google Scholar 

  10. de Castro, J. M. (2004). The time of day of food intake influences overall intake in humans. The Journal of Nutrition, 134(1), 104–111.

    PubMed  Google Scholar 

  11. Ernst, M., & Vingiano, W. (1989). Development of a graphic psychiatric self-rating scale. Comprehensive Psychiatry, 30(2), 189–194.

    CAS  Article  PubMed  Google Scholar 

  12. Fedoroff, I. C., Polivy, J., & Herman, C. P. (1997). The effect of pre-exposure to food cues on the eating behavior of restrained and unrestrained eaters. Appetite, 28(1), 33–47.

    CAS  Article  PubMed  Google Scholar 

  13. Fedoroff, I., Polivy, J., & Herman, C. P. (2003). The specificity of restrained versus unrestrained eaters' responses to food cues: general desire to eat, or craving for the cued food? Appetite, 41(1), 7–13.

    Article  PubMed  Google Scholar 

  14. Hasler, B. P., Forbes, E. E., & Franzen, P. L. (2014). Time-of-day differences and short-term stability of the neural response to monetary reward: a pilot study. Psychiatry Research, 224(1), 22–27. doi:10.1016/j.pscychresns.2014.07.005.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Holsen, L. M., Savage, C. R., Martin, L. E., Bruce, A. S., Lepping, R. J., Ko, E., & Goldstein, J. M. (2012). Importance of reward and prefrontal circuitry in hunger and satiety: Prader-Willi syndrome vs simple obesity. International Journal of Obesity, 36(5), 638–647. doi:10.1038/ijo.2011.204.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. Killgore, W. D., Young, A. D., Femia, L. A., Bogorodzki, P., Rogowska, J., & Yurgelun-Todd, D. A. (2003). Cortical and limbic activation during viewing of high- versus low-calorie foods. NeuroImage, 19(4), 1381–1394.

    Article  PubMed  Google Scholar 

  17. Lacy, J. W., Yassa, M. A., Stark, S. M., Muftuler, L. T., & Stark, C. E. (2011). Distinct pattern separation related transfer functions in human CA3/dentate and CA1 revealed using high-resolution fMRI and variable mnemonic similarity. Learning & Memory, 18(1), 15–18. doi:10.1101/lm.1971111.

    Article  Google Scholar 

  18. LeCheminant, J. D., Christenson, E., Bailey, B. W., & Tucker, L. A. (2013). Restricting night-time eating reduces daily energy intake in healthy young men: a short-term cross-over study. British Journal of Nutrition, 1–6. doi:10.1017/S0007114513001359

  19. Lumeng, J. C., & Burke, L. M. (2006). Maternal prompts to eat, child compliance, and mother and child weight status. Journal of Pediatrics, 149(3), 330–335. doi:10.1016/j.jpeds.2006.04.009.

    Article  PubMed  Google Scholar 

  20. McGonigle, D. J. (2012). Test-retest reliability in fMRI: Or how I learned to stop worrying and love the variability. NeuroImage, 62(2), 1116–1120. doi:10.1016/j.neuroimage.2012.01.023.

    Article  PubMed  Google Scholar 

  21. Motley, S. E., & Kirwan, C. B. (2012). A parametric investigation of pattern separation processes in the medial temporal lobe. Journal of Neuroscience, 32(38), 13076–13085. doi:10.1523/JNEUROSCI. 5920-11.2012.

    CAS  Article  PubMed  Google Scholar 

  22. Muranishi, M., Inokawa, H., Yamada, H., Ueda, Y., Matsumoto, N., Nakagawa, M., & Kimura, M. (2011). Inactivation of the putamen selectively impairs reward history-based action selection. Experimental Brain Research, 209(2), 235–246. doi:10.1007/s00221-011-2545-y.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Murdaugh, D. L., Cox, J. E., Cook, E. W., 3rd, & Weller, R. E. (2012). fMRI reactivity to high-calorie food pictures predicts short- and long-term outcome in a weight-loss program. NeuroImage, 59(3), 2709–2721.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Ng, J., Stice, E., Yokum, S., & Bohon, C. (2011). An fMRI study of obesity, food reward, and perceived caloric density. Does a low-fat label make food less appealing? Appetite, 57(1), 65–72. doi:10.1016/j.appet.2011.03.017.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2014). Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA, 311(8), 806–814. doi:10.1001/jama.2014.732.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. Prinsen, S., de Ridder, D. T., & de Vet, E. (2013). Eating by example. Effects of environmental cues on dietary decisions. Appetite, 70, 1–5. doi:10.1016/j.appet.2013.05.023.

    Article  PubMed  Google Scholar 

  27. Probst, Y. C., & Tapsell, L. C. (2005). Overview of computerized dietary assessment programs for research and practice in nutrition education. Journal of Nutrition Education and Behavior, 37(1), 20–26.

    Article  PubMed  Google Scholar 

  28. Rolls, E. T. (1999). The brain and emotion. Oxford: Oxford University Press.

    Google Scholar 

  29. Rothemund, Y., Preuschhof, C., Bohner, G., Bauknecht, H. C., Klingebiel, R., Flor, H., & Klapp, B. F. (2007). Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. NeuroImage, 37(2), 410–421. doi:10.1016/j.neuroimage.2007.05.008.

    Article  PubMed  Google Scholar 

  30. Stunkard, A. J., Allison, K. C., Geliebter, A., Lundgren, J. D., Gluck, M. E., & O'Reardon, J. P. (2009). Development of criteria for a diagnosis: lessons from the night eating syndrome. Comprehensive Psychiatry, 50(5), 391–399. doi:10.1016/j.comppsych.2008.09.013.

    Article  PubMed  Google Scholar 

  31. Sweet, L. H., Hassenstab, J. J., McCaffery, J. M., Raynor, H. A., Bond, D. S., Demos, K. E., & Wing, R. R. (2012). Brain response to food stimulation in obese, normal weight, and successful weight loss maintainers. Obesity (Silver Spring), 20(11), 2220–2225. doi:10.1038/oby.2012.125.

    Article  Google Scholar 

  32. Talairach, J., & Tournoux, P. (1988). Co-planar stereotaxic atlas of the human brain: 3-dimensional proportional system : an approach to cerebral imaging. Stuttgart: Georg Thieme.

    Google Scholar 

  33. Toombs, R. J., Ducher, G., Shepherd, J. A., & De Souza, M. J. (2012). The impact of recent technological advances on the trueness and precision of DXA to assess body composition. Obesity (Silver Spring), 20(1), 30–39. doi:10.1038/oby.2011.211.

    Article  Google Scholar 

  34. Yassa, M. A., Lacy, J. W., Stark, S. M., Albert, M. S., Gallagher, M., & Stark, C. E. (2011). Pattern separation deficits associated with increased hippocampal CA3 and dentate gyrus activity in nondemented older adults. Hippocampus, 21(9), 968–979. doi:10.1002/hipo.20808.

    PubMed  PubMed Central  Google Scholar 

  35. Yokum, S., Ng, J., & Stice, E. (2011). Attentional bias to food images associated with elevated weight and future weight gain: an fMRI study. Obesity (Silver Spring), 19(9), 1775–1783. doi:10.1038/oby.2011.168.

    Article  Google Scholar 

Download references

Acknowledgments

TDM, CBK, LED, and JDL designed research; TDM and CBK conducted research; TDM, CBK, and JDL analyzed data; TDM, CBK, LED and JDL wrote the paper; TDM had primary responsibility for final content. All authors read and approved the final manuscript.

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki declaration of 1975, and the applicable revisions at the time of the investigation. Informed consent was obtained from all patients for being included in the study.

Conflict of interest

Travis Masterson, James D. LeCheminant, C. Brock Kirwan, and Lance E. Davidson state that they have no conflict of interested associated with this project.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Travis D. Masterson.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplemental Table 1

(PDF 68 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Masterson, T.D., Kirwan, C.B., Davidson, L.E. et al. Neural reactivity to visual food stimuli is reduced in some areas of the brain during evening hours compared to morning hours: an fMRI study in women. Brain Imaging and Behavior 10, 68–78 (2016). https://doi.org/10.1007/s11682-015-9366-8

Download citation

Keywords

  • Visual stimuli
  • Food
  • Neural reactivity
  • fMRI
  • Time
  • Morning
  • Evening