1. Introduction
Overweight and obesity are major health problems worldwide in present days, and how to treat the problems of overweight and obese people caused by excessive eating has become one of the public health problems in the world [1-3]. Previous neuroimaging studies have revealed that compared with normal-weight participants, obese participants showed lower sensitivity to reward in the striatum and higher reactivity in the somatosensory, gustatory and rewards-evaluation areas in anticipation and consumption of delicious foods [4-6]. In addition, studies have shown that obesity can trigger changes in brain connectivity, which may affect eating motivation, thus leading to weight gain [2]. Besides, some studies have confirmed that the reward-related brain response to high-calorie food images significantly reduced in normal-weight individuals after a meal, but when obese individuals exposed to palatable food images, there was increased activation in brain regions related to the reward system, such as the insula, amygdala, orbitofrontal cortex, and striatum, even when after a meal and self-reported satiated [1-2, 7]. This suggested that, in obese people, changes in appetite drive and reward perception induce overeating independent of physiological satiety [1, 4, 8].
In addition, impulsivity is also an important concept closely related to overeating and overweight [9]. In terms of behavior, overweight and obese individuals showed more impulsivity, had worse response inhibition abilities in motor impulse tasks, and had longer stop signal response times [10]. Experiments by Rook & Fisher [11] have shown that among the normal-weight population, impulsivity might associate with higher food intake and also appears to be linked with unhealthy food choices. Guerrier et al [12] found that more impulsive and hungry people consumed higher-calorie food products than others; impulsive shoppers were inclined to choose food based only on the taste instead of considering the long-term health condition, and also associated with a greater tendency to overeating [13].
An increasing number of studies have used neuroimaging techniques to understand the underlying neural mechanisms of obesity. However, to date, no review has included resting-state fMRI, reward dysfunction, and impulsiveness. Thus, the current literature review sought to synthesize the fMRI findings (resting fMRI, reward dysfunction, and impulsiveness) on neuro-mechanisms in obesity and overweight individuals, which could provide a better understanding of the neurobehavioral mechanisms and new insights to help develop personalized treatment.
2. Method
2.1. Search strategy
Three electronic databases were searched (Web of Science and PubMed) with the following keywords: "obesity*fMRI," "food choice*obesity," "obesity*brain function," "obesity*brain imaging," "food bias*obesity," “obesity*reward dysfunction,” “obesity*impulsive”. Only works in English and Chinese were published from January 2020 to December 2023. All the chosen articles are listed in Table 1.
2.2. Exclusion criteria
Studies with limitations were excluded in this research, such as articles not available in full-text, articles involved barbaric surgery, articles including anorexia nervosa and bulimia nervosa, articles related to child and adolescent obesity, and animal experiment studies.
3. Results
After the removal of duplicates, the initial search produced 5,882 citations (Web of Science: 3428; PubMed: 2,454); 5,869 were excluded, leaving 13 citations to be examined in more detail. All studies will be investigating in resting-fMRI, reward system, and impulsive.
3.1. Studies investigating resting-fMRI
Avery et al. [14] revealed that obese participants' hunger state was negatively correlated with ventral striatum functional connectivity, meaning that the greater their post-meal hunger decreases, the larger the increased function connectivity between the mid-insula and the ventral striatum. Another study found that the obese group showed increased functional connectivity between the bilateral anterior cingulate cortex and precuneus, while functional connectivity of the frontal gyrus was decreased [15]. In addition, another research showed that resting state activity plays a key role in how the hippocampus/amygdala respond to high-calorie food cues, with BMI influencing this relationship [16]. Thus, resting state activity in these regions may affect individual’s response of to food cues.
3.2. Studies investigating reward system
Five studies investigated reward sensitivity and revealed that obese people have higher activation in the reward system. These studies confirmed that obese people have a higher activation in the reward system when looking at pictures of food than normal-weight people, especially in high-energy food cues [4-5].
Frankfort et al. [5] found that activation of the reward system increases in normal weight individuals when viewing pictures of food; however, obese people have higher reward system activation when imagining the food taste. Obesity individuals seem to show a higher reward sensitivity to food, even in satiated conditions [4-5]. Several studies also proved that when obese people see pictures of tasty foods, the regions of the brain associated with reward, such as the insula, amygdala, orbitofrontal cortex, and striatum become more active. The activation even continues after eating [2, 7, 17]. These findings further support Schachter’s externality theory [18], which stated that obese individuals are more influenced by external cues when eating, like the appearance and smell, rather than the internal signals of hunger and fullness as seen in those with a normal weight.
In addition, Filbey et al. [19] found that high-calorie foods cues trigger heightened activity in the reward system of individuals with high BMI. This hyper-responsivity increases with a greater number of binge‐eating symptoms, similar to addiction behavior symptoms. This may explain why some people develop excessive cravings for high-calorie foods and may further lead to overeating and weight gain. Verharen, Adan & Vanderschuren [20] argued that this change in value-based decision-making could lead to substance addiction and overeating when the expected rewards outweigh the costs associated with substance use and food consumption over a long period. Due to reduced function in the prefrontal cortex, the control center for motivated behavior, obese individuals seem to have difficulty in making decisions [2].
3.3. Studies investigating impulsive
Impulsivity refers to impairments in cognitive control constructs, often defined as individuals taking swift acts without prior consideration, and they may rarely or never consider the negative impact of the consequences [21]. In the context of obesity, impulsivity may contribute to a stronger drive for food rewards and difficulties with organization and planning, which may lead to less consideration for future health and hinder weight loss [22].
One of the main characteristics of impulsivity is the tendency to seek immediate gratification and to ignore long-term negative consequences [23]. Liu et al. [10] and Stoeckel et al. [24] discovered that overweight people were more impulsive and less likely to choose delayed rewards. The higher the BMI, the less likely it is to choose delayed rewards, which is related to deficits in executive function regions of the brain [24]. In addition, in difficult and easy decision-making conditions, overweight people had lower activation in executive function brain areas such as the anterior cingulate gyrus, the frontal pole, and the inferior frontal gyrus [10]. Some studies have found that obese people may pay more attention to food vs. non-food pictures, and the bias toward food is related to the orbitofrontal cortex activation. Thus, the attentional bias to food cues, in addition to impulsivity, would cause an increase in craving for food, irrespective of internal feelings of hunger or satiety [25].
Although growing studies have indicated that impulsivity is an essential behavior process that could lead to obesity, impulsivity is a multidimensional construct that involves independent patterns of decision-making that may associated with obesity.
4. Discussion & limitation
This literature review generalized the different brain responses to food cues stimuli and functional connectivity in both resting fMRI and task fMRI between obese people and healthy normal-weight individuals and the reward dysfunction and impulsiveness among obese participants. It also reveals the mechanisms of dysfunction of homeostasis signals in obese people. In the presence of satiety, homeostasis signals (such as hunger) in obese people may still be maintained. It is important to note that the insula region plays a key role in processing internal signals related to food, such as hunger and fullness [26] so reduced insula cortical functional connectivity may reflect dysfunctional satiety signals, especially in areas associated with reward, such as the ventral striatum and prefrontal cortex. This may lead to decreased pleasure and satisfaction from eating. When food cues stimulate obese people, there is a strong association between impulsive behavior and reward dysfunction. Obese people tend to show higher impulsivity and attentional bias towards food, which can lead to increased food cravings and ignore intrinsic feelings of hunger or fullness.
Studies have revealed obesity has a correlation with the changes in the reward system. Increased activation of reward centers in response to food cues and a higher sensitivity to rewards may contribute to overeating and weight gain. These studies on the brain reward system provide insights into the complexity of obesity causes and their relationship with dietary behavior. Therefore, understanding how neural mechanisms induce obesity can help those struggling with weight management develop a series of targeted interventions and treatments.
Obese people often exhibit impulsive tendencies, making decisions based on immediate gratification without considering the long-term consequences in health, which may explain the link between obesity and impulsivity. Impulsivity is also associated with deficits in executive function, the cognitive processes that control and manage behavior, emotions, and thoughts. Overweight people tend to have less activation in executive function areas of the brain when making decisions, suggesting they may have trouble suppressing impulsive responses [24]. This relationship between impulsivity and executive function could explain why obese people struggle to control their eating habits and lose weight.
This study has several limitations. Firstly, due to individual physiological differences, we did not include bio-physiological and genetic factors. Besides, it did not include child and adolescent obesity since this might have more uncertain factors, even though they could be factors toward adult obesity. Thirdly, as Carbine et al. [27] mentioned, N2 amplitude, which is more sensitive to differentiate obese individuals' brain responses to different food types, might be considered in future studies. In addition, more different types of food cues (such as real taste and smell) could be a stimulus in future experimental studies, which could provide more evidence to understand obesity and help develop more precise treatments for the obesity population.
5. Conclusion
In conclusion, this study reveals the neural mechanisms of obesity-related reward dysfunction and impulsivity by comparing brain responses and functional connectivity in resting and task-state fMRI in obese and healthy normal-weight individuals. These studies provide an essential theoretical basis for further research on the prevention and treatment of obesity and help to develop more targeted intervention strategies for these neural mechanisms to help obese people achieve weight control and physical and mental health. Obesity has become a public health problem worldwide; therefore, understanding the neural mechanisms of obesity is critical to developing effective interventions and treatment.
References
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[3]. Simmonds, M., Llewellyn, A., Owen, C. G., & Woolacott, N. (2016). Predicting adult obesity from childhood obesity: A systematic review and meta-analysis. Obesity Reviews, 17(2), 95-107. https://doi.org/10.1111/obr.12334
[4]. Dimitropoulos, A., Tkach, J. A., Ho, A., & Kennedy, J. T. (2012). Greater corticolimbic activation to high-calorie food cues after eating in obese vs. normal-weight adults. Appetite, 58(1), 303–312. https://doi.org/10.1016/j.appet.2011.10.014
[5]. Frankort, A., Roefs, A., Siep, N., Roebroeck, A., Havermans, R. C., & Jansen, A. (2011). Reward activity in satiated overweight women is decreased during unbiased viewing but increased when imagining taste: An event-related fMRI study. International Journal of Obesity, 36(5), 627–637.
[6]. Morys, F., García-García, I., & Dagher, A. (2020). Is obesity related to enhanced neural reactivity to visual food cues? A review and meta-analysis. Social Cognitive and Affective Neuroscience, 18(1). https://doi.org/10.1093/scan/nsaa113
[7]. Devoto, F., Zapparoli, L., Bonandrini, R., Berlingeri, M., Ferrulli, A., Luzi, L., Banfi, G., & Paulesu, E. (2018). Hungry brains: A meta-analytical review of brain activation imaging studies on food perception and appetite in obese individuals. Neuroscience & Biobehavioral Reviews, 94, 271–285. https://doi.org/10.1016/j.neubiorev.2018.09.014
[8]. Stopyra, M. A., Friederich, H. C., Lavandier, N., Mönning, E., Bendszus, M., Herzog, W., & Simon, J. J. (2021). Homeostasis and food craving in obesity: A functional MRI study. International Journal of Obesity, 45, 2464–2470. https://doi.org/10.1038/s41366-021-00841-4
[9]. Burger, K. S., & Berner, L. A. (2014). A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior. Physiology & Behavior, 136, 121–127. https://doi.org/10.1016/j.physbeh.2014.04.026
[10]. Liu, X., Turel, O., Xiao, Z., He, J., & He, Q. (2022). Impulsivity and neural mechanisms that mediate preference for immediate food rewards in people with vs without excess weight. Appetite, 169, 105798. https://doi.org/10.1016/j.appet.2021.105798
[11]. Rook, D. W., & Fisher, R. J. (1995). Normative influences on impulsive buying behavior. Journal of Consumer Research, 22(3), 305–313.
[12]. Guerrieri, R., Nederkoorn, C., Stankiewicz, K., Alberts, H., Geschwind, N., Martijn, C., & Jansen, A. (2007). The influence of trait and induced state impulsivity on food intake in normal-weight healthy women. Appetite, 49(1), 66–73. https://doi.org/10.1016/j.appet.2007.01.007
[13]. Jasinska, A. J., Yasuda, M., Burant, C. F., Gregor, N., Khatri, S., Sweet, M., & Falk, E. B. (2012). Impulsivity and inhibitory control deficits are associated with unhealthy eating in young adults. Appetite, 59(3), 738-747. https://doi.org/10.1016/j.appet.2012.07.015
[14]. Avery, J. A., Powell, J. N., Breslin, F. J., Lepping, R. J., Martin, L. E., Patrician, T. M., Donnelly, J. E., Savage, C. R., & Simmons, W. K. (2017). Obesity is associated with altered mid-insula functional connectivity to limbic regions underlying appetitive responses to foods. Journal of Psychopharmacology, 31(11), 1475–1484. https://doi.org/10.1177/0269881117728429
[15]. Chao, S., Liao, Y., Chen, V. C., Li, C., McIntyre, R. S., Lee, Y., & Weng, J. (2018). Correlation between brain circuit segregation and obesity. Behavioural Brain Research, 337, 218–227. https://doi.org/10.1016/j.bbr.2017.09.017
[16]. Li, G., Hu, Y., Zhang, W., Ding, Y., Wang, Y., Jia, W., He, Y., Lv, G., Von Deneen, K. M., Zhao, Y., Chen, A., Han, Y., Cui, G., Ji, G., Manza, P., Tomasi, D., Volkow, N. D., Nie, Y., Wang, G., & Zhang, Y. (2020). Resting activity of the hippocampus and amygdala in obese individuals predicts their response to food cues. Addiction Biology, 26(3). https://doi.org/10.1111/adb.12974
[17]. Hermann, P., Gál, V., Kóbor, I., Kirwan, C. B., Kovács, P., Kitka, T., Lengyel, Z., Bálint, E., Varga, B., Csekő, C., & Vidnyánszky, Z. (2019). Efficacy of weight loss intervention can be predicted based on early alterations of fMRI food cue reactivity in the striatum. NeuroImage: Clinical, 23, 101803. https://doi.org/10.1016/j.nicl.2019.101803
[18]. Schachter, S. (1968). Obesity and eating - internal and external cues affect eating behavior of obese and normal subjects. Science, 161, 751e756.
[19]. Filbey, F. M., Myers, U. S., & DeWitt, S. J. (2012). Reward circuit function in high BMI individuals with compulsive eating. Obesity, 20(11), 2277–2283. https://doi.org/10.1038/oby.2012.105sive overeating: Similarities with addiction. NeuroImage, 63(4), 1800–1806. https://doi.org/10.1016/j.neuroimage.2012.08.073
[20]. Verharen, J. P. H., Adan, R. A., & Vanderschuren, L. J. M. J. (2019). How reward and aversion shape motivation and decision making: A computational account. The Neuroscientist, 26(1), 87–99. https://doi.org/10.1177/1073858419834517
[21]. Moeller, F. G., Barratt, E. S., Dougherty, D. M., Schmitz, J. M., & Swann, A. C. (2001). Psychiatric aspects of impulsivity. American Journal of Psychiatry, 158(11), 1783.
[22]. Ellbom, K. S., & Gunstad, J. (2012). Cognitive function and decline in obesity. In V. Frisardi & B. Imbimbo (Eds.), Journal of Alzheimer’s Disease, 30(Suppl. 2), S89–S95.
[23]. Dalley, J. W., & Robbins, T. W. (2017). Fractionating impulsivity: Neuropsychiatric implications. Nature Reviews Neuroscience, 18(3), 158–171. https://doi.org/10.1038/nrn.2017.8
[24]. Stoeckel, L. E., Murdaugh, D. L., Cox, J. E., Cook, E. W., & Weller, R. E. (2012). Greater impulsivity is associated with decreased brain activation in obese women during a delay discounting task. Brain Imaging and Behavior, 7(2), 116–128. https://doi.org/10.1007/s11682-012-9201-4
[25]. Yokum, S., Ng, J., & Stice, E. (2011). Attentional bias to food images associated with elevated weight and future weight gain: An fMRI study. Obesity, 19(9), 1775–1783. https://doi.org/10.1038/oby.2011.168
[26]. Stahl, C., Voss, A., Schmitz, F., Nuszbaum, M., Tüscher, O., Lieb, K., & Klauer, K. C. (2014). Behavioral components of impulsivity. Journal of Experimental Psychology: General, 143, 850–886. https://doi.org/10.1037/a0033981
[27]. Carbine, K. A., Duraccio, K. M., Kirwan, C. B., Muncy, N. M., LeCheminant, J. D., & Larson, M. J. (2018). A direct comparison between ERP and fMRI measurements of food-related inhibitory control: Implications for BMI status and dietary intake. NeuroImage, 166, 335–348.
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Cite this article
Feng,M. (2025). A systematic review on food-related bias and brain response in obese people. Advances in Social Behavior Research,16(1),67-73.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Boutari, C., & Mantzoros, C. S. (2022). A 2022 update on the epidemiology of obesity and a call to action: as its twin COVID-19 pandemic appears to be receding, the obesity and dysmetabolism pandemic continues to rage on. Metabolism, 133, 155217. https://doi.org/10.1016/j.metabol.2022.155217
[2]. Makaronidis, J. M., & Batterham, R. L. (2018). Obesity, body weight regulation and the brain: Insights from fMRI. The British Journal of Radiology, 20170910. https://doi.org/10.1259/bjr.20170910
[3]. Simmonds, M., Llewellyn, A., Owen, C. G., & Woolacott, N. (2016). Predicting adult obesity from childhood obesity: A systematic review and meta-analysis. Obesity Reviews, 17(2), 95-107. https://doi.org/10.1111/obr.12334
[4]. Dimitropoulos, A., Tkach, J. A., Ho, A., & Kennedy, J. T. (2012). Greater corticolimbic activation to high-calorie food cues after eating in obese vs. normal-weight adults. Appetite, 58(1), 303–312. https://doi.org/10.1016/j.appet.2011.10.014
[5]. Frankort, A., Roefs, A., Siep, N., Roebroeck, A., Havermans, R. C., & Jansen, A. (2011). Reward activity in satiated overweight women is decreased during unbiased viewing but increased when imagining taste: An event-related fMRI study. International Journal of Obesity, 36(5), 627–637.
[6]. Morys, F., García-García, I., & Dagher, A. (2020). Is obesity related to enhanced neural reactivity to visual food cues? A review and meta-analysis. Social Cognitive and Affective Neuroscience, 18(1). https://doi.org/10.1093/scan/nsaa113
[7]. Devoto, F., Zapparoli, L., Bonandrini, R., Berlingeri, M., Ferrulli, A., Luzi, L., Banfi, G., & Paulesu, E. (2018). Hungry brains: A meta-analytical review of brain activation imaging studies on food perception and appetite in obese individuals. Neuroscience & Biobehavioral Reviews, 94, 271–285. https://doi.org/10.1016/j.neubiorev.2018.09.014
[8]. Stopyra, M. A., Friederich, H. C., Lavandier, N., Mönning, E., Bendszus, M., Herzog, W., & Simon, J. J. (2021). Homeostasis and food craving in obesity: A functional MRI study. International Journal of Obesity, 45, 2464–2470. https://doi.org/10.1038/s41366-021-00841-4
[9]. Burger, K. S., & Berner, L. A. (2014). A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior. Physiology & Behavior, 136, 121–127. https://doi.org/10.1016/j.physbeh.2014.04.026
[10]. Liu, X., Turel, O., Xiao, Z., He, J., & He, Q. (2022). Impulsivity and neural mechanisms that mediate preference for immediate food rewards in people with vs without excess weight. Appetite, 169, 105798. https://doi.org/10.1016/j.appet.2021.105798
[11]. Rook, D. W., & Fisher, R. J. (1995). Normative influences on impulsive buying behavior. Journal of Consumer Research, 22(3), 305–313.
[12]. Guerrieri, R., Nederkoorn, C., Stankiewicz, K., Alberts, H., Geschwind, N., Martijn, C., & Jansen, A. (2007). The influence of trait and induced state impulsivity on food intake in normal-weight healthy women. Appetite, 49(1), 66–73. https://doi.org/10.1016/j.appet.2007.01.007
[13]. Jasinska, A. J., Yasuda, M., Burant, C. F., Gregor, N., Khatri, S., Sweet, M., & Falk, E. B. (2012). Impulsivity and inhibitory control deficits are associated with unhealthy eating in young adults. Appetite, 59(3), 738-747. https://doi.org/10.1016/j.appet.2012.07.015
[14]. Avery, J. A., Powell, J. N., Breslin, F. J., Lepping, R. J., Martin, L. E., Patrician, T. M., Donnelly, J. E., Savage, C. R., & Simmons, W. K. (2017). Obesity is associated with altered mid-insula functional connectivity to limbic regions underlying appetitive responses to foods. Journal of Psychopharmacology, 31(11), 1475–1484. https://doi.org/10.1177/0269881117728429
[15]. Chao, S., Liao, Y., Chen, V. C., Li, C., McIntyre, R. S., Lee, Y., & Weng, J. (2018). Correlation between brain circuit segregation and obesity. Behavioural Brain Research, 337, 218–227. https://doi.org/10.1016/j.bbr.2017.09.017
[16]. Li, G., Hu, Y., Zhang, W., Ding, Y., Wang, Y., Jia, W., He, Y., Lv, G., Von Deneen, K. M., Zhao, Y., Chen, A., Han, Y., Cui, G., Ji, G., Manza, P., Tomasi, D., Volkow, N. D., Nie, Y., Wang, G., & Zhang, Y. (2020). Resting activity of the hippocampus and amygdala in obese individuals predicts their response to food cues. Addiction Biology, 26(3). https://doi.org/10.1111/adb.12974
[17]. Hermann, P., Gál, V., Kóbor, I., Kirwan, C. B., Kovács, P., Kitka, T., Lengyel, Z., Bálint, E., Varga, B., Csekő, C., & Vidnyánszky, Z. (2019). Efficacy of weight loss intervention can be predicted based on early alterations of fMRI food cue reactivity in the striatum. NeuroImage: Clinical, 23, 101803. https://doi.org/10.1016/j.nicl.2019.101803
[18]. Schachter, S. (1968). Obesity and eating - internal and external cues affect eating behavior of obese and normal subjects. Science, 161, 751e756.
[19]. Filbey, F. M., Myers, U. S., & DeWitt, S. J. (2012). Reward circuit function in high BMI individuals with compulsive eating. Obesity, 20(11), 2277–2283. https://doi.org/10.1038/oby.2012.105sive overeating: Similarities with addiction. NeuroImage, 63(4), 1800–1806. https://doi.org/10.1016/j.neuroimage.2012.08.073
[20]. Verharen, J. P. H., Adan, R. A., & Vanderschuren, L. J. M. J. (2019). How reward and aversion shape motivation and decision making: A computational account. The Neuroscientist, 26(1), 87–99. https://doi.org/10.1177/1073858419834517
[21]. Moeller, F. G., Barratt, E. S., Dougherty, D. M., Schmitz, J. M., & Swann, A. C. (2001). Psychiatric aspects of impulsivity. American Journal of Psychiatry, 158(11), 1783.
[22]. Ellbom, K. S., & Gunstad, J. (2012). Cognitive function and decline in obesity. In V. Frisardi & B. Imbimbo (Eds.), Journal of Alzheimer’s Disease, 30(Suppl. 2), S89–S95.
[23]. Dalley, J. W., & Robbins, T. W. (2017). Fractionating impulsivity: Neuropsychiatric implications. Nature Reviews Neuroscience, 18(3), 158–171. https://doi.org/10.1038/nrn.2017.8
[24]. Stoeckel, L. E., Murdaugh, D. L., Cox, J. E., Cook, E. W., & Weller, R. E. (2012). Greater impulsivity is associated with decreased brain activation in obese women during a delay discounting task. Brain Imaging and Behavior, 7(2), 116–128. https://doi.org/10.1007/s11682-012-9201-4
[25]. Yokum, S., Ng, J., & Stice, E. (2011). Attentional bias to food images associated with elevated weight and future weight gain: An fMRI study. Obesity, 19(9), 1775–1783. https://doi.org/10.1038/oby.2011.168
[26]. Stahl, C., Voss, A., Schmitz, F., Nuszbaum, M., Tüscher, O., Lieb, K., & Klauer, K. C. (2014). Behavioral components of impulsivity. Journal of Experimental Psychology: General, 143, 850–886. https://doi.org/10.1037/a0033981
[27]. Carbine, K. A., Duraccio, K. M., Kirwan, C. B., Muncy, N. M., LeCheminant, J. D., & Larson, M. J. (2018). A direct comparison between ERP and fMRI measurements of food-related inhibitory control: Implications for BMI status and dietary intake. NeuroImage, 166, 335–348.
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