Effects of occasional reinforced trials during extinction on the reacquisition of conditioned responses to food cues

Akker, Karolien van den; Havermans, Remco C.; Jansen, Anita

doi:10.1016/j.jbtep.2015.02.001

Cited by 37 publications

(37 citation statements)

References 49 publications

(73 reference statements)

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“…As a treatment, CERP also reduces self-reported craving (178) and binge eating in individuals with bulimia nervosa (178,180,184,185). However, extinction of cueresponse pairings can be context-specific and may therefore still be reinstated in new environments (100, [186][187][188][189] or through incubation of craving (190), even after extinction, limiting the potential application of CERP. Consistently, clinical trials for CERP have been mixed for other eating disorders (191), obesity (192) and addictions (193,194).…”

Section: Treatment Implications For Obesity and Related Disordersmentioning

confidence: 99%

Food cue reactivity and craving predict eating and weight gain: a meta‐analytic review

2015

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Summary According to learning-based models of behavior, food cue reactivity and craving are conditioned responses that lead to increased eating and subsequent weight gain. However, evidence supporting this relationship has been mixed. We conducted a quantitative meta-analysis to assess the predictive effects of food cue reactivity and craving on eating and weight-related outcomes. Across 69 reported statistics from 45 published reports representing 3,292 participants, we found an overall medium effect of food cue reactivity and craving on outcomes (r = 0.33, p <0.001; approximately 11% of variance), suggesting that cue exposure and the experience of craving significantly influence and contribute to eating behavior and weight gain. Follow-up tests revealed a medium effect size for the effect of both tonic and cue-induced craving on eating behavior (r = 0.33). We did not find significant differences in effect sizes based on body mass index, age, or dietary restraint. However, we did find that visual food cues (e.g. pictures and videos) were associated with a similar effect size to real food exposure and a stronger effect size than olfactory cues. Overall, the present findings suggest that food cue reactivity, cue-induced craving and tonic craving systematically and prospectively predict food-related outcomes. These results have theoretical, methodological, public health and clinical implications.

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Section: Treatment Implications For Obesity and Related Disordersmentioning

confidence: 99%

Food cue reactivity and craving predict eating and weight gain: a meta‐analytic review

2015

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“…In humans, it likewise appears to be relatively easy to learn cued eating desires by means of classical conditioning procedures ( Van Gucht et al, 2008 ; Papachristou et al, 2013 ; Van den Akker et al, 2013 , 2014 , 2015 ; Bongers and Jansen, 2015 ; Bongers et al, 2015 ). After the learning of a stimulus predicting intake, the mere presence of the food-predictive stimulus is sufficient to elicit eating expectations and desires.…”

Section: Acquisition Of Food Cravingsmentioning

confidence: 99%

A Cognitive Profile of Obesity and Its Translation into New Interventions

2015

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Change your lifestyle: decrease your energy intake and increase your energy expenditure, is what obesity experts tell people who need to lose weight. Though the advice might be correct, it appears to be extremely difficult to change one’s lifestyle. Unhealthy habits usually are ingrained and hard to change, especially for people with an “obese cognitive profile.” Knowledge of the cognitive mechanisms that maintain unhealthy eating habits is necessary for the development of interventions that can change behavior effectively. This paper discusses some cognitive processes that might maintain unhealthy eating habits and make healthier eating difficult, like increased food cue reactivity, weak executive skills and attention bias. An effort is also done to translate these basic scientific findings into new interventions which aim to tackle the sabotaging cognitive processes. Preliminary studies into the effectiveness of these interventions, if available, are presented.

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“…Associated with this is the second challenge facing human appetitive conditioning research, namely, the lack of an established gold standard measurement to assess conditioned responding. A frequently implemented method to confirm successful conditioning are ratings, for example, CS valence Ebrahimi et al, 2017Ebrahimi et al, , 2019Klucken et al, 2015Klucken et al, , 2009Klucken et al, , 2013Klucken et al, , 2016Prévost et al, 2013), CS dichotomous preference (Bray & O'Doherty, 2007;Kahnt, Heinzle, Park, & Haynes, 2011;Metereau & Dreher, 2013;Prévost et al, 2013), US expectancy (van den Akker, Havermans, & Jansen, 2015), and contingency awareness (Bray & O'Doherty, 2007;Ebrahimi et al, 2017Ebrahimi et al, , 2019Klucken et al, 2015Klucken et al, , 2009Klucken et al, , 2013Klucken et al, , 2016Stussi et al, 2018;Tapia León et al, 2018). A shortcoming of ratings is that they only reflect the explicit component of learning and are prone to influences of social desirability when the learning task is simple.…”

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confidence: 99%

Pupil dilation as an implicit measure of appetitive Pavlovian learning

et al. 2019

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Appetitive Pavlovian conditioning is a learning mechanism of fundamental biological and pathophysiological significance. Nonetheless, its exploration in humans remains sparse, which is partly attributed to the lack of an established psychophysiological parameter that aptly represents conditioned responding. This study evaluated pupil diameter and other ocular response measures (gaze dwelling time, blink duration and count) as indices of conditioning. Additionally, a learning model was used to infer participants’ learning progress on the basis of their pupil dilation. Twenty‐nine healthy volunteers completed an appetitive differential delay conditioning paradigm with a primary reward, while the ocular response measures along with other psychophysiological (heart rate, electrodermal activity, postauricular and eyeblink reflex) and behavioral (ratings, contingency awareness) parameters were obtained to examine the relation among different measures. A significantly stronger increase in pupil diameter, longer gaze duration and shorter eyeblink duration was observed in response to the reward‐predicting cue compared to the control cue. The Pearce‐Hall attention model best predicted the trial‐by‐trial pupil diameter. This conditioned response was corroborated by a pronounced heart rate deceleration to the reward‐predicting cue, while no conditioning effect was observed in the electrodermal activity or startle responses. There was no discernible correlation between the psychophysiological response measures. These results highlight the potential value of ocular response measures as sensitive indices for representing appetitive conditioning.

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Effects of occasional reinforced trials during extinction on the reacquisition of conditioned responses to food cues

Abstract: It is concluded that the provision of occasional reinforced extinction trials and unpaired USs seem promising techniques to slow down reacquisition, but that additional studies are needed.

Cited by 37 publications

References 49 publications

Food cue reactivity and craving predict eating and weight gain: a meta‐analytic review

Food cue reactivity and craving predict eating and weight gain: a meta‐analytic review

A Cognitive Profile of Obesity and Its Translation into New Interventions

Pupil dilation as an implicit measure of appetitive Pavlovian learning

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