You probably have noticed that after the intake of certain types of food and drinks, you experience a change in your mood or even a boost in your mental activity. Food intake is not only a basic human need but a reward for most people. When we eat, our brain responds instantly to the taste and smell of food as well as other sensory properties like visual appearance. Although our food choices mainly depend on homeostatic factors, there are other internal states referred to as psychological “drivers”, also playing an important role in many of our daily eating decisions. Such motivational drivers are expressed when your brain triggers goal-directed actions to consume food even without feeling hunger. While it is true that feeling hungry is not a voluntary decision, whether and how to satisfy or not hunger it is indeed voluntary. In that process, the brain handles multiple aspects of food stimuli even those that you are not aware of.
Hunger or appetite: can the brain find the difference?
Why do we decide to eat? It is just because we need food to keep us alive or because we want food to distract our senses?
Simply in a few words, we eat for two reasons:
- Homeostatic eating: the goal is to get the nutrients the brain and body need to maintain optimal levels of energy stores.
- Hedonic reward-based eating: induced by highly palatable food, eating is either motivated to satisfy a desire, to get pleasure, or to cope with certain emotions.
When we eat to restore body energy, a process known as “Leptin feedback loop”(e.g. biological moderators) automatically triggers . Within this neuocircuitry, the hypothalamus plays a central role mediating energy-expenditure aspects of leptin hormone. When this pathway is active, food-intake decisions are made fast without involving too much thinking. Thus, hunger is motivated by the instinct of survival which drives us to eat to respond a physiological need (homeostactic eating). Instead, when food-intake choices do not respond to biological motivators, the brain reward neurocircuitry —mainly driven by limbic and frontal brain centers — is taking control causing appetite (e.g. hedonic-based eating). It is important to understand that unlike hunger, appetite is selective and typically caused by an emotional feelings like when we have the desire to eat because we are bored or nervous.
As you may notice, the choices we make about food involve a complex network that is driven by biological and non-biological motivators. But clearly, deliberative decisions about food preferences are only relevant when signals from the brain lead us to ingest food in response to appetite rather than hunger. At this point, the interaction of limbic and prefrontal circuits with the hypothalamus plays a fundamental role in controlling your appetite avoiding as much as possible excessive ingestion when the body energy demands are already satisfied.
Food preference formation: why we like what we like?
Although food preferences are thought to be innate many of them are hedonic-based (see Rozin & Millman, 1987). Indeed, food preference formation is a growing awareness process that begins with flavor likes and dislikes very early in life. Later, food choices are determined also by certain modulating factors that will eventually change an individual’s food-preference. Unlike children, adult food preferences are influenced by age, gender, health status, education, and income. Given the huge variability of these modulating factors in interaction with biological determinants, predicting peoples´ food preferences casuistry over time is particularly challenging but not impossible.
Fortunately, food preferences are at some point malleable which allow us to modify unhealthy eating habits at any stage of development. The key is to identify “why”, “with who” and “where” our food preferences and choices arise.
Cognitive determinants of food choice: implicit and explicit associations
Choosing what to eat can be sometimes effortful, especially when there is excessive availability of foods like in our modern society. Even with the best of our intentions and knowing beforehand which food is good for us, still we do not always make the best choice.
Current research on the cognitive determinants underlying food choices identifies two opposing forces mediating in our decisions. On the one hand, conscious processes driven mainly by external cues (i.e. explicit associations) evaluates food options with approval or disapproval. This rational mechanism controls a small percentage of our daily food intake decision. On the other hand, an automatic process triggered by implicit associations operates unconsciously. These implicit associations most of the time represent the true nature of our food intake decisions. For example, both tea and coffee may be equally liked by a particular person; however, unlike tea, coffee is chosen predominantly at work because is related to being focused and mentally awake. Such association is the result of a past learning process that became an automatic habit through exposure and repetition.
Why the food we like the most is often not the most nutritious?
For the purpose of maintaining good health, our brain has the ability to perceive food as being advantageous or disadvantageous. Nowadays, a predominant healthy eating trend is substantially influencing food choices in many ways. However, as shown by a recent consumer research report (Nielsen, 2019), there is a gap between intentions to eat better and what people actually do.
The truth is that most of the time people don´t really pay much attention to the nutritive values of food. That happens because we are constantly making perceptual decisions, like choosing the larger of two slices of a cake. People prefer eating food that is tasty or sensory pleasant despite knowing the poor health value. In today´s modern society, it is highly difficult for our sense to resist visually attractive food – especially high-calorie foods- that are constantly showing up.
The reason for not succeeding in this “battle” has to do with an unbalance between homeostatic and hedonic systems. The hedonic-rewarding system, which is indeed highly susceptible to make perceptually-based decisions, easily overcomes the homeostatic energy-balancing system resulting in unhealthy eating. The brain literally forgets about its natural “stop” signals in favor of getting more of that delicious “shot” from food reward. For example, eating chocolate is often accompanied by positive emotions, whereby resisting eating requires inhibition. That effort your brain does may result in unpleasant feelings or discomfort. Obviously, nobody wants to feel discomfort, right? So we end-up eating that piece of chocolate until there is nothing left.
To avoid uncontrolled food reward-seeking, goal-directed and habit systems mediate in our desires. The goal-directed system selects actions that are in accordance with our desires through a rational evaluation of eating a particular food and the value of the outcome. The bad news is that it requires great effort (e.g. cognitive-cost) and unfortunately, this rational mechanism does not always succeed especially when food rewarding becomes addictive. The habit system increases efficiency in the decision-making process by automatically activating stimulus-response associations. Based on this account, a balance between these two systems, serves to optimize food choices. Importantly, dysregulation in such balance has been linked to many eating disorders (e.g. obesity, anorexia, binge eating). For instance, the brain pattern of food excessive consumption, regardless of whether it is associated with obesity, imitates the neural circuitries of addiction (see Avena, 2010; Corwin et al., 2011). Conversely, a systematic restrictive intake of food (e.g. anorexia) can overcome homeostatic rules.
Getting the right balance: from unconsciousness to awareness
Approximately 90% of the decisions we make around eating are unconscious. Identifying an effective strategy to affect our food choices is of paramount importance to maintain a healthy eating behavior. As explained above, most unhealthy food choices people take are largely guided by unconscious learned associations that escape to our control. Thus, one strategy to enhance food choices is through the modification of these implicit associations. The question here is not whether changing but how.
Based on behavioral conditioning principles, there is at least one way to induce higher awareness in our decisions. By implementing a method called “Evaluative Conditioning” we can increase our sensitivity towards a healthier food preference criteria. Through this procedure, a change in evaluating a particular food is achieved after repeatedly pairing that food with a second stimulus that holds a negative valence. For instance, in a experimental study published by King College London University , volunteers’ attitudes towards high-fat foods changed after implicitly pairing pictures of highly liked snacks with aversive images.
Although evaluative conditioning may result effective in changing attitudes towards food, by itself, does not entail a switch in behavior in the long run. The reason is because it does not impact on the neural pathways that control our actions.
If our goal is to directly modify food intake habits, neurofeedback training could result more effective since it does have a direct modulatory effect on involved neurocircuitry. The less attractive aspect of this approach is that requires high levels of perseverance and commitment, a cost that not everyone is willing to pay.
Alternatively, there are other “less painful” strategies to help us achieve higher awareness of our eating habits. From the field of Cognitive Psychology, different types of heuristics are proposed to modify people´s automatic habits, routines and rules for how and what eating. Types of cognitive heuristics include: 1) focusing on one value, 2) routinization, 3)elimination, 4) limitation, 5) substitution, 6) addition and 7) modification (Furst et al., 1996, 2001; Connors et al., 2001).
|The Heuristic||The Mental Cues||Example|
|1. Focusing on one food value or incentive||cost, taste, health, context, social relations, etc.||Eat healthier food whenever possible|
|2. Routinization||standardize, systematize, ritualize||Eat fruit every day for breakfast|
|3. Elimination||avoid, forbidden and exclude||Avoid eating desserts|
|4. Limitation||restrict, regulate and reduce||Eat only one piece of bread|
|5. Substitution||replace, exchange||Choose brown bread instead of white|
|6. Addition||Increase, include, enhance||Eat greens with every evening meal|
|7. Modification||Alter, adjust, transform||Remove fat from meats|
Finally, emerging neurotechnologies are broadening the research field scope by leaps and bounds. The combination of biometric wearables in extended reality scenarios (e.g. virtual or augmented reality) allows simulation of food choice experiences in a highly realistic way, while several neurocognitive measures are being captured. By doing so, researchers can achieve a more comprehensive analysis of specific emotional and cognitive responses affecting people´s behaviors thus, providing highly accurate clues of ongoing implicit associations. An specific research trend includes using biometric self-avatars in virtual reality to evaluate the influence of distorted visual-perceptual patterns associated to different eating-behavior phenotypes or eating disorders.
The brain drives food preferences and eating behavior by integrating many internal and external motivators whereby some of them are built on unconscious associations. Understanding the neurocognitive patterns of such learned associations is crucial to identify and modify maladaptive habits of eating from a more conscious approach. If today’s trend goes towards inclusion of more healthy eating (e.g. nutrient index), food-related decisions cannot fully rely on “auto-piloting” mechanisms. Only by questioning ourselves we can minimize the influence of any food-related unconscious associations. Indeed, self-acknowledgment activates the same brain reward-based learning processes as alcohol and cigarettes. Adopting cognitive heuristics can lead individuals to more meaningful and healthier eating routines. In top of that, innovative research with advanced neurotechnology can give us new keys to understanding why we like the food we like and how to gain control over our unconscious decisions.
Alonso-Alonso, M., Woods, S. C., Pelchat, M., Grigson, P. S., Stice, E., Farooqi, S., Khoo, C. S., Mattes, R. D., & Beauchamp, G. K. (2015). Food reward system: current perspectives and future research needs. Nutrition reviews, 73(5), 296–307. https://doi.org/10.1093/nutrit/nuv002
Bouhlal, S., McBride, C. M., Trivedi, N. S., Agurs-Collins, T., & Persky, S. (2017). Identifying eating behavior phenotypes and their correlates: A novel direction toward improving weight management interventions. Appetite, 111, 142–150. https://doi.org/10.1016/j.appet.2016.12.006
Bui, E. T., & Fazio, R. H. (2016). Generalization of evaluative conditioning toward foods: Increasing sensitivity to health in eating intentions. Health Psychol, 35(8), 852-855.
Compan, V., Walsh, B. T., Kaye, W., & Geliebter, A. (2015). How Does the Brain Implement Adaptive Decision Making to Eat?. The Journal of neuroscience : the official journal of the Society for Neuroscience, 35(41), 13868–13878. https://doi.org/10.1523/JNEUROSCI.2602-15.2015
Czyzewska, M., & Graham, R. (2008). Implicit and explicit attitudes to high- and low-calorie food in females with different BMI status. Eating Behaviors, 9(3), 303-312.
Czyzewska, M., Graham, R., & Ceballos, N. A. (2011). Explicit and implicit attitudes to food. In,
Handbook of Behavior, Food and Nutrition: Springer
De Cosmi, V., Scaglioni, S., & Agostoni, C. (2017). Early Taste Experiences and Later Food Choices. Nutrients, 9(2), 107. https://doi.org/10.3390/nu9020107
Elena Bartkiene, Vesta Steibliene, Virginija Adomaitiene, Grazina Juodeikiene, Darius Cernauskas, Vita Lele, Dovile Klupsaite, Daiva Zadeike, Laura Jarutiene, Raquel P. F. Guiné, “Factors Affecting Consumer Food Preferences: Food Taste and Depression-Based Evoked Emotional Expressions with the Use of Face Reading Technology”, BioMed Research International, vol. 2019, Article ID 2097415, 10 pages, 2019. https://doi.org/10.1155/2019/2097415
Falk LW, Sobal J, Bisogni CA, Connors M, Devine CM. Managing healthy eating: definitions, classifications, and strategies. Health Educ Behav. 2001 Aug;28(4):425-39. doi: 10.1177/109019810102800405. PMID: 11465155.
Furst T, Connors M, Bisogni CA, Sobal J, Falk LW. Food choice: a conceptual model of the process. Appetite. 1996 Jun;26(3):247-65. doi: 10.1006/appe.1996.0019. PMID: 8800481.
Haynes, A., Kemps, E., & Moffitt, R. (2015). The moderating role of state inhibitory control in the effect of evaluative conditioning on temptation and unhealthy snacking. Physiol Behav, 152(Pt A), 135-142.
Hollands, G. J., Prestwich, A., & Marteau, T. M. (2011). Using aversive images to enhance healthy food choices and implicit attitudes: An experimental test of evaluative conditioning. Health Psychology, 30(2), 195-203. doi: 10.1037/a0022261
Hütter, M., & Sweldens, S. (2013). Implicit misattribution of evaluative responses: contingency unaware conditioning requires simultaneous stimulus presentations. Journal of Experimental Psychology: General, 142(3), 638-643. doi: 10.1037/a0029989
Ihssen, N., Sokunbi, M.O., Lawrence, A.D. et al. Neurofeedback of visual food cue reactivity: a potential avenue to alter incentive sensitization and craving. Brain Imaging and Behavior 11, 915–924 (2017). https://doi.org/10.1007/s11682-016-9558-x
Jones, C. R., Fazio, R. H., & Olson, M. A. (2009). Implicit misattribution as a mechanism underlying evaluative conditioning. Journal of Personality and Social Psychology, 96(5), 933-948. doi: 10.1037/a0014747
Jones, C. R., Olson, M. A., & Fazio, R. H. (2010). Evaluative conditioning: The “How” question. In M. P. Zanna & J. M. Olson (Eds.), Advances in Experimental Social Psychology (Vol. 43, pp. 205-255). San Diego, CA: Elsevier.
Lebens, H., Roefs, A., Martijn, C., Houben, K., Nederkoorn, K., & Jansen, A. (2011). Making implicit measures of associations with snack foods more negative through evaluative conditioning. Eating Behaviors, 12(4), 249-253. doi: 10.1016/j.eatbeh.2011.07.001
Lowe MR, van Steenburgh J, Ochner C, Coletta M. Neural correlates of individual differences related to appetite. Physiol Behav. 2009 Jul 14;97(5):561-71. doi: 10.1016/j.physbeh.2009.04.001. Epub 2009 Apr 7. PMID: 19361535.
Mölbert SC, Thaler A, Mohler BJ, Streuber S, Romero J, Black MJ, Zipfel S, Karnath HO, Giel KE. Assessing body image in anorexia nervosa using biometric self-avatars in virtual reality: Attitudinal components rather than visual body size estimation are distorted. Psychol Med. 2018 Mar;48(4):642-653. doi: 10.1017/S0033291717002008. Epub 2017 Jul 26. PMID: 28745268; PMCID: PMC5964466.
Wansink B, Sobal J. Mindless Eating: The 200 Daily Food Decisions We Overlook. Environment and Behavior. 2007;39(1):106-123. doi:10.1177/0013916506295573
Wang Y, Wang G, Zhang D, Wang L, Cui X, Zhu J and Fang Y (2017) Learning to Dislike Chocolate: Conditioning Negative Attitudes toward Chocolate and Its Effect on Chocolate Consumption. Front. Psychol. 8:1468. doi: 10.3389/fpsyg.2017.01468