Abstract: Overconsumption of high-calorie foods has become a critical contributor to overweight and obesity, posing substantial threats to individual health and increasing societal costs. Traditional interventions, such as pharmacotherapy or surgical procedures, although somewhat effective, can be invasive and carry risks. In contrast, cognitive training approaches are noninvasive, simple to administer, and relatively easy to scale, making them promising for modifying maladaptive eating behaviors. Recent advances have shown that food-specific inhibition training, which embeds food images into a Go/No-go task, can indeed alter individuals’ choices of high-calorie foods. However, how exactly this training exerts its effects remains insufficiently understood. To address this gap, the present research proposes a dual-cognitive-pathway theoretical model and systematically investigates its behavioral and neural underpinnings.
Rather than improving general inhibitory control—an approach shown to have limited success in changing eating behaviors—food-specific inhibition training focuses on pairing specific foods with “Go” (respond) or “No-go” (inhibit) actions. Past behavioral evidence indicates that repeated “Go” actions can raise the subjective value of the paired foods, while repeated “No-go” actions can diminish it. Additionally, training may form stimulus-response (S-R) links such that “Go” foods are processed as automatically actionable, whereas “No-go” foods are associated with automatic inhibition. Building on this body of work, we propose two main pathways through which food-specific inhibition training modifies eating behavior: (1) Food Value Updating: By frequently responding to certain “Go” foods, individuals may infer that these foods are more desirable; likewise, repeated inhibition of certain “No-go” foods may decrease their subjective value.(2) Automatic Response/Inhibition Formation: By repeatedly pairing specific foods with action (Go) or inhibition (No-go), individuals form automatic links. In subsequent eating scenarios, these learned links can bias behavior toward “Go” foods and away from “No-go” foods, even without explicit conscious deliberation. We further argue that these processes are supported by distinct neural circuits: (a) a reward-related circuit that mediates value changes, and (b) conflict monitoring and control networks that help instantiate automatic action or inhibition associations.
To test our dual-pathway model, we plan four overarching studies, each with two experiments (behavioral and fMRI): (1) Study 1 (Experiments 1 & 2) examines Go-food value elevation. We predict that frequent “Go” actions raise the subjective and neural indices of these foods’ value (e.g., stronger activation in reward areas). Post-training, participants should choose these “Go” foods more often in a food-choice task. (2) Study 2 (Experiments 3 & 4) focuses on No-go-food value reduction. We expect that repeated inhibition lowers the perceived value of “No-go” foods and reduces reward-related neural responses, leading participants to select these foods less frequently. (3) Study 3 (Experiments 5 & 6) targets the Go-food-automatic-response link. We hypothesize that training repeatedly pairing certain foods with action yields faster behavioral responses to these “Go” items and, neurologically, reduced activation in conflict-related brain regions when selecting them. This translates into higher choice frequency for these “Go” foods. (4) Study 4 (Experiments 7 & 8) investigates the No-go-food-automatic-inhibition link. We propose that repeated inhibition for certain foods slows subsequent behavioral responses when individuals are unexpectedly required to “Go” for the same items, reflecting an established automatic-inhibition link. Neurally, we anticipate corresponding alterations in conflict monitoring and default-mode network connectivity, predicting lower choice rates for these “No-go” foods.
A key contribution of this research is the dual-cognitive-pathway model, which posits that food-specific inhibition training modifies eating behavior by (a) updating food value and (b) establishing automatic S-R links. Unlike prior attempts to explain training effects solely via improved inhibitory control—which often fail to translate into real-world eating behavior—our approach delineates the more plausible routes by which food-specific actions or inhibitions shape subsequent choices. On the neural level, we systematically distinguish between changes in reward-related activation (underlying value updates) and changes in activation and connectivity within conflict-monitoring and control networks (underlying automatic response/inhibition formation). This distinction may help identify precise neural targets for future interventions—such as transcranial magnetic stimulation or neurofeedback—that could enhance the effectiveness of food-specific inhibition training.
Lastly, although our immediate participants are non-obese individuals, the framework developed here will be highly relevant to clinical populations if the hypothesized mechanisms prove robust. By illuminating how simple, noninvasive cognitive tasks can alter the neural and behavioral responses to high-calorie foods, this research could inform the design of scalable, practical interventions to curb overeating and promote healthier dietary habits.

Key words: food-specific inhibition training, food value, utomatic association, neural mechanisms