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Cognitive regulation of food craving: effects of three cognitive reappraisal strategies on neural response to palatable foods

Abstract

Objective:

Obese versus lean individuals show greater reward region and reduced inhibitory region responsivity to food images, which predict future weight gain. Thinking of the costs of eating palatable foods and craving suppression have been found to modulate this neural responsivity, but these cognitive reappraisal studies have primarily involved lean participants. Herein we evaluated the efficacy of a broader range of reappraisal strategies in modulating neural responsivity to palatable food images among individuals who ranged from lean to obese and tested whether body mass index (BMI) moderates the effects of these strategies.

Materials and methods:

Functional magnetic resonance imaging assessed the effects of three cognitive reappraisal strategies in response to palatable food images versus an imagined intake comparison condition in a sample of adolescents (N=21; M age=15.2).

Results:

Thinking of the long-term costs of eating the food, thinking of the long-term benefits of not eating the food and attempting to suppress cravings for the food increased activation in inhibitory regions (for example, superior frontal gyrus, ventrolateral prefrontal cortex) and reduced activation in attention-related regions (for example, precuneus and posterior cingulate cortex). The reappraisal strategy focusing on the long-term benefits of not eating the food more effectively increased inhibitory region activity and reduced attention region activity compared with the other two cognitive reappraisal strategies. BMI did not moderate the effects.

Discussion:

These novel results imply that cognitive reappraisal strategies, in particular those focusing on the benefits of not eating the food, could potentially increase the ability to inhibit appetitive motivation and reduce unhealthy food intake in overweight individuals.

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References

  1. Flegal KM, Carroll MD, Kit BK, Ogden CL . Prevalence of obesity and trends in the distribution of body mass index among US adults 1999-2010. JAMA 2012; 307: 4830490.

    Article  Google Scholar 

  2. Turk MW, Yang K, Hravnak M, Sereika SM, Ewing LJ, Burke LE . Randomized clinical trials of weight loss maintenance: a review. J Cardiovasc Nurs 2009; 24: 58–80.

    Article  Google Scholar 

  3. Stice E, Shaw H, Marti CN . A meta-analytic review of obesity prevention programs for children and adolescents: the skinny on interventions that work. Psychol Bull 2006; 132: 667–691.

    Article  Google Scholar 

  4. Stoeckel LE, Weller RE, Cook EW, Twieg DB, Knowlton RC, Cox JE . Widespread reward-system activation in obese women in response to pictures of high-calorie foods. Neuroimage 2008; 41: 636–647.

    Article  Google Scholar 

  5. Laan LN, Ridder DT, Viergever MA, Smeets PA . The first taste is always with the eyes: a meta-analysis on the neural correlates of processing visual food cues. NeuroImage 2011; 55: 296–303.

    Article  Google Scholar 

  6. Bruce A, Holsen L, Chambers R, Martin L, Brooks W, Zarcone J et al. Obese children show hyperactivation to food pictures in brain networks linked to motivation, reward, and cognitive control. Int J Obes 2010; 34: 1494–1500.

    Article  CAS  Google Scholar 

  7. Stice E, Yokum S, Bohon C, Marti N, Smolen A . Reward circuitry responsivity to food predicts future increases in body mass: moderating effects of DRD2 and DRD4. Neuroimage 2010; 50: 1618–1625.

    Article  CAS  Google Scholar 

  8. Stice E, Spoor S, Bohon C, Veldhuizen MG, Small DM . Relation of reward from food intake and anticipated food intake to obesity: a functional magnetic resonance imaging study. J Abnorm Psychol 2008; 117: 924–935.

    Article  Google Scholar 

  9. Ng J, Stice E, Yokum S, Bohon C . An fMRI study of obesity, food reward, and perceived caloric density. Does a low-fat label make food less appealing? Appetite 2011; 57: 65–72.

    Article  Google Scholar 

  10. Rothemund Y, Preuschhof C, Bohner G, Bauknecht HC, Klingebiel R, Flor H et al. Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. Neuroimage 2007; 37: 410–421.

    Article  Google Scholar 

  11. Murdaugh D, Cox J, Cook E, Weller R . fMRI reactivity to high-calorie food pictures predicts short- and long-term outcome in a weight loss program. Neuroimage 2012; 59: 2709–2721.

    Article  Google Scholar 

  12. Chouinard-Decorte F, Felsted J, Small D . Increased amygdala response and decreased influence of internal state on amygdala response to food in overweight compared to healthy weight individuals. Appetite 2010; 54: 639.

    Article  Google Scholar 

  13. Demos K, Heatherton T, Kelley W . Individual differences in nucleus accumbens activity to food and sexual images predicts weight gain and sexual behavior. J Neurosci 2012; 32: 5549–5552.

    Article  CAS  Google Scholar 

  14. Yokum S, Ng J, Stice E . Attentional bias to food images associated with elevated weight and future weight gain: an fMRI study. Obesity 2011; 19: 1775–1783.

    Article  Google Scholar 

  15. Buchsbaum BR, Greer S, Chang WL, Berman KF . Meta-analysis of neuroimaging studies of the Wisconsin card-sorting task and component processes. Human Brain Mapping 2005; 25: 35–45.

    Article  Google Scholar 

  16. Simmonds DJ, Pekar JJ, Mostofsky SH . Meta-analysis of go/no-go tasks demonstrating that fMRI activation associated with response inhibition is task-dependent. Neuropsychologia 2008; 46: 224–232.

    Article  Google Scholar 

  17. Batterink L, Yokum S, Stice E . Body mass correlates inversely with inhibitory control in response to food among adolescent girls: an fMRI study. NeuroImage 2010; 52: 1696–1703.

    Article  Google Scholar 

  18. Nummenmaa L, Hirvonen J, Hannukainen JC, Immonen H, Lindroos MM, Salminen P et al. Dorsal striatum and its limbic connectivity mediate abnormal anticipatory reward processing in obesity. PLoS One 2012; 7: e31089.

    Article  CAS  Google Scholar 

  19. Epstein L, Dearing K, Temple J, Cavanaugh M . Food reinforcement and impulsivity in overweight children and their parents. Eating Behaviors 2008; 9: 319–327.

    Article  Google Scholar 

  20. Nederkoorn C, Smulders F, Havermans R, Roefs A, Jansen A . Impulsivity in obese women. Appetite 2006; 48: 253–256.

    Article  Google Scholar 

  21. Seeyave D, Coleman S, Appugliese D, Corwyn R, Bradley R, Davidson N et al. Ability to delay gratification at age 4 years and risk for overweight at age 11 years. Arch Pediatr Adolesc Med 2009; 163: 303–308.

    Article  Google Scholar 

  22. Pauli-Pott U, Albayrak O, Hebebrand J, Pott W . Does inhibitory control capacity in overweight and obese children and adolescents predict success in a weight regulation program? Eur Child Adolesc Psychiatry 2010; 19: 135–141.

    Article  Google Scholar 

  23. Kober H, Mende-Siedlecki P, Kross E, Weber J, Walter M et al. Prefrontal-striatal pathway underlies cognitive regulation of craving. Proc Natl Acad Sci USA 2010; 33: 14811–14816.

    Article  Google Scholar 

  24. Siep N, Roefs A, Roebroeck A, Havermans R, Bonte M, Jansen A . Fighting food temptations: the modulating effects of short-term cognitive reappraisal, suppression and up-regulation on mesocorticolimbic activity related to appetitive motivation. Neuroimage 2012; 60: 213–220.

    Article  Google Scholar 

  25. Hollmann M, Hellrung L, Pleger B, Schlogl H, Kabisch S, Strumvoll M et al. Neural correlates of the volitional regulation of the desire for food. Int J Obes 2012; 36: 648–655.

    Article  CAS  Google Scholar 

  26. Rothman AJ, Salovey P . Shaping perceptions to motivate healthy behavior: the role of message framing. Psychol Bull 1997; 121: 3–19.

    Article  CAS  Google Scholar 

  27. Orvaschel H . Psychiatric interviews suitable for use in research with children and adolescents. In: Mezzich JE, Jorge MR, Salloum IM, (eds) Psychiatric Epidemiology: Assessment Concepts and Methods. Johns Hopkins University Press: Baltimore, MD, USA pp 509–522 1994.

    Google Scholar 

  28. Lewinsohn PM, Rohde P, Seeley JR, Klein DN, Gotlib LH . Natural course of adolescent major depressive disorder in a community sample: predictors of recurrence in young adults. Am J Psychiatry 2000; 157: 1584–1591.

    Article  CAS  Google Scholar 

  29. Dietz WH, Robinson TN . Use of the body mass index (BMI) as a measure of overweight in children and adolescents. J Pediatr 1998; 132: 191–193.

    Article  CAS  Google Scholar 

  30. Burger KS, Cornier MA, Ingebrigtsen J, Johnson SL . Assessing food appeal and desire to eat: the effects of portion size & energy density. Int J Behav Nutr Phys Activity 2011; 8: 101.

    Article  Google Scholar 

  31. Dietary Guidelines for Americans 6 edition. US Department of Agriculture and Department of Health and Human Services.. Washington, DC, 2005.

  32. Dreher JC, Schmidt PJ, Kohn P, Furman D, Rubinow D, Berman KF . Menstrual cycle phase modulates reward-related neural function in women. Proc Natl Acad Sci USA 2007; 104: 2465–2470.

    Article  CAS  Google Scholar 

  33. Cornier MA, Salzberg AK, Endly DC, Bessesen DH, Tregellas JR . Sex-based differences in the behavioral and neuronal responses to food. Physiol Behav 2010; 99: 538–543.

    Article  CAS  Google Scholar 

  34. Uher R, Treasure J, Heining M, Brammer MJ, Campbell IC . Cerebral processing of food-related stimuli: effects of fasting and gender. Behav Brain Res 2006; 169: 111–119.

    Article  CAS  Google Scholar 

  35. Wang GJ, Volkow ND, Telang F, Jayne M, Ma Y, Pradhan K et al. Evidence of gender differences in the ability to inhibit brain activation elicited by food stimulation. Proc Natl Acad Sci USA 2009; 106: 1249–1254.

    Article  CAS  Google Scholar 

  36. Thesen S, Heid O, Mueller E, Schad LR . Prospective acquisition correction for head motion with image-based tracking for real-time fMRI. Magn Reson Med 2000; 44: 457–465.

    Article  CAS  Google Scholar 

  37. Smith SM . Fast robust automated brain extraction. Human Brain Mapping 2002; 17: 143–155.

    Article  Google Scholar 

  38. Ashburner J . A fast diffeomorphic image registration algorithm. NeuroImage 2007; 38: 95–113.

    Article  Google Scholar 

  39. Cox RW . AFNI: software for analysis and visualization of functional magnetic resonance Neuroimages. Comput Biomed Res 1996; 29: 162–173.

    Article  CAS  Google Scholar 

  40. Forman S, Cohen J, Fitzgerald M, Eddy W, Mintun M, Noll D . Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. Magn Reson Med 1995; 33: 636–647.

    Article  CAS  Google Scholar 

  41. Badre D, Wagner AD . Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia 2007; 45: 2883–2901.

    Article  Google Scholar 

  42. Fair DA, Dosenbach NU, Church JA, Cohen AL, Brahmbhatt S, Miezin FM et al. Development of distinct control networks through segregation and integration. Proc Natl Acad Sci USA 2007; 104: 13507–13512.

    Article  CAS  Google Scholar 

  43. Stoodley CJ, Valera EM, Schmahmann JD . Functional topography of the cerebellum for motor and cognitive tasks: an fMRI study. NeuroImage 2012; 59: 1560–1570.

    Article  Google Scholar 

  44. Hillis AE, Newhart M, Heidler J, Barker PB, Herskovits EH, Degaonkar M . Anatomy of spatial attention: insights from perfusion imaging and hemispatial neglect in acute stroke. J Neurosci 2005; 25: 3161–3167.

    Article  CAS  Google Scholar 

  45. Higo T, Mars RB, Boorman ED, Buch ER, Rushworth MF . Distributed and causal influence of frontal operculum in task control. Proc Natl Acad Sci USA 2011; 108: 4230–4235.

    Article  CAS  Google Scholar 

  46. Pessoa L, Gutierrez E, Bandettini PA, Ungerleider LG . Neural correlates of visual working memory: fMRI amplitude predicts task performance. Neuron 2002; 35: 975–987.

    Article  CAS  Google Scholar 

  47. Holsen LM, Zarcone JR, Thompson TI, Brooks WM, Anderson MF, Ahluwalia JS et al. Neural mechanisms underlying food motivation in children and adolescents. Neuroimage 2005; 27: 669–676.

    Article  Google Scholar 

  48. Small DM, Gitelman DR, Gregory MD, Nobre AC, Parrish TB, Mesulam MM . The posterior cingulate and medial prefrontal cortex mediate the anticipatory allocation of spatial attention. Neuroimage 2003; 18: 633–641.

    Article  CAS  Google Scholar 

  49. McCoy A N, Crowley JC, Haghighian G, Dean HL, Platt ML . Saccade reward signals in posterior cingulate cortex. Neuron 2003; 40: 1031–1040.

    Article  CAS  Google Scholar 

  50. Johnson MR, Mitchell KJ, Raye CL, D’Esposito M, Johnson MK . A brief thought can modulate activity in extrastriate visual areas: topdown effects of refreshing just-seen visual stimuli. Neuroimage 2007; 37: 290–299.

    Article  Google Scholar 

  51. Cornier M-A, Salzberg AK, Endly DC, Bessesen DH, Rojas DC, Tregellas JR . The effects of overfeeding on the neuronal response to visual food cues in thin and reduced-obese individuals. PLoS One 2009; 4: e6310.

    Article  Google Scholar 

  52. McRae K, Gross JJ, Weber J, Robertson ER, Sokol-Hessner P, Ray RD et al. The development of emotion regulation: an fMRI study of cognitive reappraisal in children, adolescents and adults. Soc Cogn Affect Neurosci 2012; 7: 11–22.

    Article  Google Scholar 

  53. Bjork JM, Smith AR, Chen G, Hommer DW . Adolescents, adults and reward: comparing motivational neurocircuitry recruitment using fMRI. Neuroimage 2010; 15: 643–657.

    Google Scholar 

  54. Geier CF, Terwilliger R, Teslovich T, Velanova K, Luna B . Immaturities in reward processing and its influence on inhibitory control in adolescence. Cereb Cortex 2010; 20: 1613–1629.

    Article  CAS  Google Scholar 

  55. Cortese S, Angriman M, Maffeis C, Isnard P, Konofal E., Lecendreux M et al. Attention-deficit/hyperactivity disorder (ADHD) and obesity: a systematic review of the literature. Crit Rev Food Sci Nutr 2008; 48: 524–537.

    Article  Google Scholar 

  56. Davis C . Attention-deficit/hyperactivity disorder: associations with overeating and obesity. Curr Psychiatry Rep 2010; 12: 389–395.

    Article  Google Scholar 

  57. O’Connell KA, Hosein VL, Schwartz JE, Leibowitz RQ . How does coping help people resist lapes during smoking cessation. Health Psychol 2007; 26: 77–84.

    Article  Google Scholar 

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Acknowledgements

This project was supported by National Institute of Diabetes and Digestive and Kidney Diseases grant (R01 DK80760, 8/09-7/14). We thank the Lewis Center for Neuroimaging at the University of Oregon for their assistance in data collection for these projects.

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Yokum, S., Stice, E. Cognitive regulation of food craving: effects of three cognitive reappraisal strategies on neural response to palatable foods. Int J Obes 37, 1565–1570 (2013). https://doi.org/10.1038/ijo.2013.39

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  • DOI: https://doi.org/10.1038/ijo.2013.39

Keywords

  • cognitive reappraisal
  • suppression
  • fMRI
  • inhibition
  • attention

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