Neural mechanisms of cue-approach training

Neural activity and connectivity are related to food preference changes induced by food go/no-go training

Simply withholding a response while viewing an appetizing food, over the course of many presentations (i.e., during food go/no-go training) can modify individuals' food preferences-which could, in turn, promote healthier eating behaviors. However, the neural mechanisms underlying this food go/no-go training-induced change in food preferences are still relatively unclear. We addressed this issue in the present functional magnetic resonance imaging (fMRI) study. To this end, we administered a novel passive viewing task before and after food go/no-go training to 91 participants in the scanner. Participants' food preferences were measured with a binary food choice task. At the behavioral level, we found the expected training effect on food preferences: Participants preferred go over no-go foods following training. At the neural level, we found that changes in food preferences were associated with training-related go vs. no-go differences in activity and functional connectivity, such as less activity in the anterior cingulate cortex and superior frontal gyrus but greater functional connectivity between the superior frontal gyrus and middle occipital gyrus. Critically, Dynamic causal modeling showed that this preference change effect was largely driven by top-down influence from the superior frontal gyrus to the middle occipital gyrus. Together, these findings suggest a neural mechanism of the food go/no-go training effect-namely, that the food-viewing-related interplay between prefrontal regions and visual regions might be related to the food preference change following food go/no-go training.

Detection of ASD Children through Deep-Learning Application of fMRI

Autism spectrum disorder (ASD) necessitates prompt diagnostic scrutiny to enable immediate, targeted interventions. This study unveils an advanced convolutional-neural-network (CNN) algorithm that was meticulously engineered to examine resting-state functional magnetic resonance imaging (fMRI) for early ASD detection in pediatric cohorts. The CNN architecture amalgamates convolutional, pooling, batch-normalization, dropout, and fully connected layers, optimized for high-dimensional data interpretation. Rigorous preprocessing yielded 22,176 two-dimensional echo planar samples from 126 subjects (56 ASD, 70 controls) who were sourced from the Autism Brain Imaging Data Exchange (ABIDE I) repository. The model, trained on 17,740 samples across 50 epochs, demonstrated unparalleled diagnostic metrics-accuracy of 99.39%, recall of 98.80%, precision of 99.85%, and an F1 score of 99.32%-and thereby eclipsed extant computational methodologies. Feature map analyses substantiated the model's hierarchical feature extraction capabilities. This research elucidates a deep learning framework for computer-assisted ASD screening via fMRI, with transformative implications for early diagnosis and intervention.

Neural correlates of changing food choices while bypassing values

Current theories suggest that altering choices requires value modification. To investigate this, normal-weight female participants' food choices and values were tested before and after an approach-avoidance training (AAT), while neural activity was recorded during the choice task using functional magnetic resonance imaging (fMRI). During AAT, participants consistently approached low- while avoiding high-calorie food cues. AAT facilitated low-calorie food choices, leaving food values unchanged. Instead, we observed a shift in indifference points, indicating the decreased contribution of food values in food choices. Training-induced choice shifts were associated with increased activity in the posterior cingulate cortex (PCC). In contrast, the medial PFC activity was not changed. Additionally, PCC grey matter density predicted individual differences in training-induced functional changes, suggesting anatomic predispositions to training impact. Our findings demonstrate neural mechanisms underlying choice modulation independent of valuation-related processes, with substantial theoretical significance for decision-making frameworks and translational implications for health-related decisions resilient to value shifts.

The Stroop effect involves an excitatory-inhibitory fronto-cerebellar loop

The Stroop effect is a classical, well-known behavioral phenomenon in humans that refers to robust interference between language and color information. It remains unclear, however, when the interference occurs and how it is resolved in the brain. Here we show that the Stroop effect occurs during perception of color-word stimuli and involves a cross-hemispheric, excitatory-inhibitory loop functionally connecting the lateral prefrontal cortex and cerebellum. Participants performed a Stroop task and a non-verbal control task (which we term the Swimmy task), and made a response vocally or manually. The Stroop effect involved the lateral prefrontal cortex in the left hemisphere and the cerebellum in the right hemisphere, independently of the response type; such lateralization was absent during the Swimmy task, however. Moreover, the prefrontal cortex amplified cerebellar activity, whereas the cerebellum suppressed prefrontal activity. This fronto-cerebellar loop may implement language and cognitive systems that enable goal-directed behavior during perceptual conflicts.

Memory for individual items is related to nonreinforced preference change

It is commonly assumed that memories contribute to value-based decisions. Nevertheless, most theories of value-based decision-making do not account for memory influences on choice. Recently, new interest has emerged in the interactions between these two fundamental processes, mainly using reinforcement-based paradigms. Here, we aimed to study the role memory processes play in preference change following the nonreinforced cue-approach training (CAT) paradigm. In CAT, the mere association of cued items with a speeded motor response influences choices. Previous studies with this paradigm showed that a single training session induces a long-lasting effect of enhanced preferences for high-value trained stimuli, that is maintained for several months. We hypothesized that CAT increases memory of trained items, leading to enhanced accessibility of their positive associative memories and in turn to preference changes. In two preregistered experiments, we found evidence that memory is enhanced for trained items and that better memory is correlated with enhanced preferences at the individual item level, both immediately and 1 mo following CAT. Our findings suggest that memory plays a central role in value-based decision-making following CAT, even in the absence of external reinforcements. These findings contribute to new theories relating memory and value-based decision-making and set the groundwork for the implementation of novel nonreinforced behavioral interventions that lead to long-lasting behavioral change.

Enhanced Bottom-Up and Reduced Top-Down fMRI Activity Is Related to Long-Lasting Nonreinforced Behavioral Change

Behavioral change studies and interventions focus on self-control and external reinforcements to influence preferences. Cue-approach training (CAT) has been shown to induce preference changes lasting months by merely associating items with neutral cues and speeded responses. We utilized this paradigm to study neural representation of preferences and their modification without external reinforcements. We scanned 36 participants with fMRI during a novel passive viewing task before, after and 30 days following CAT. We preregistered the predictions that activity in memory, top-down attention, and value-processing regions will underlie preference modification. While most theories associate preferences with prefrontal regions, we found that “bottom-up” perceptual mechanisms were associated with immediate change, whereas reduced “top-down” parietal activity was related to long-term change. Activity in value-related prefrontal regions was enhanced immediately after CAT for trained items and 1 month after for all items. Our findings suggest a novel neural mechanism of preference representation and modification. We suggest that nonreinforced change of preferences occurs initially in perceptual representation of items, putatively leading to long-term changes in “top-down” processes. These findings offer implementation of bottom-up instead of top-down targeted interventions for long-lasting behavioral change.

Modifying food items valuation and weight with gamified executive control training

Recent lines of research suggest that repeated executive control of motor responses to food items modifies their perceived value and in turn their consumption. Cognitive interventions involving the practice of motor control and attentional tasks have thus been advanced as potential approach to improve eating habits. Yet, their efficacy remains debated, notably due to a lack of proper control for the effects of expectations. We examined whether a one-month intervention combining the practice of Go/NoGo and Cue approach training modified the perceived palatability of food items (i.e. decrease in unhealthy and increase in healthy food items' palatability ratings), and in turn participants' weights. We assessed our hypotheses with a parallel, double-blind, randomized controlled trial. Motivation and adherence to the intervention were maximized by a professional-level gamification of the training tasks. The control intervention differed from the experimental intervention only in the biasing of the stimulus-response mapping rules, enabling to balance expectations between the two groups and thus to conclude on the causal influence of motoric control on items valuation. We found a larger decrease of the unhealthy items' palatability ratings in the experimental (20.6%) than control group (13.1%). However, we did not find any increase of the healthy items' ratings or weight loss. Overall, the present registered report confirms that the repeated inhibition of motor responses to food cues, together with the development of attentional biases away from these cues, reduces their perceived value.

Training choices toward low value options

Food decisions are driven by differences in value of choice alternatives such that high value items are preferred over low value items. However, recent research has demonstrated that by implementing the Cue-Approach Training (CAT) the odds of choosing low value items over high value items can be increased. This effect was explained by increased attention to the low value items induced by CAT. Our goal was to replicate the original findings and to address the question of the underlying mechanism by employing eye-tracking during participants’ choice making. During CAT participants were presented with images of food items and were instructed to quickly respond to some of them when an auditory cue was presented (cued items), and not without this cue (uncued items). Next, participants made choices between two food items that differed on whether they were cued during CAT (cued versus uncued) and in pre-training value (high versus low). As predicted, results showed participants were more likely to select a low value food item over a high value food item for consumption when the low value food item had been cued compared to when the low value item had not been cued. Important, and against our hypothesis, there was no significant increase in gaze time for low value cued items compared to low value uncued items. Participants did spend more time fixating on the chosen item compared to the unchosen alternative, thus replicating previous work in this domain. The present research thus establishes the robustness of CAT as means of facilitating choices for low value over high value food but could not demonstrate that this increased preference was due to increased attention for cued low value items. The present research thus raises the question how CAT may increase choices for low value options.

Enhanced striatal and prefrontal activity is associated with individual differences in nonreinforced preference change for faces

Developing effective preference modification paradigms is crucial to improve the quality of life in a wide range of behaviors. The cue‐approach training (CAT) paradigm has been introduced as an effective tool to modify preferences lasting months, without external reinforcements, using the mere association of images with a cue and a speeded button response. In the current work for the first time, we used fMRI with faces as stimuli in the CAT paradigm, focusing on face‐selective brain regions. We found a behavioral change effect of CAT with faces immediately and 1‐month after training, however face‐selective regions were not indicative of behavioral change and thus preference change is less likely to rely on face processing brain regions. Nevertheless, we found that during training, fMRI activations in the ventral striatum were correlated with individual preference change. We also found a correlation between preference change and activations in the ventromedial prefrontal cortex during the binary choice phase. Functional connectivity among striatum, prefrontal regions, and high‐level visual regions was also related to individual preference change. Our work sheds new light on the involvement of neural mechanisms in the process of valuation. This could lead to development of novel real‐world interventions.

Is ventromedial prefrontal cortex critical for behavior change without external reinforcement?

Cue-approach training (CAT) is a novel paradigm that has been shown to induce preference changes towards items without external reinforcements. In the task, the mere association of a neutral cue and a speeded button response has been shown to induce a behavioral choice preference change lasting for months. This paradigm includes several phases: after the training of individual items, behavior change is manifested in binary choices of items with similar initial values. Neuroimaging data have implicated the ventromedial prefrontal cortex (vmPFC) in the choice phase of this task. However, the neural mechanisms underlying the preference changes induced by training remain unclear. Here, we asked whether the ventromedial frontal lobe (VMF) is critical for the non-reinforced preference change induced by CAT. For this purpose, 11 participants with focal lesions involving the VMF and 30 healthy age-matched controls performed the CAT. The VMF group was similar to the healthy age-matched control group in the ranking and training phases. As a group, the healthy age-matched controls exhibited a training-induced behavior change, while the VMF group did not. However, on an individual level analysis we found that some of the VMF participants showed a significant preference shift. Thus, we find mixed evidence for the role of VMF in this paradigm. This is another step towards defining the mechanisms underlying the novel form of behavioral change that occurs with CAT.

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We tested participants with focal lesions involving ventromedial frontal lobe (VMF).

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Participants performed a behavioral change task without external reinforcements.

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The VMF group did not exhibit behavior change but some individuals in it did.

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We find mixed evidence for the role of VMF in this paradigm.

Gaze Amplifies Value in Decision Making

When making decisions, people tend to choose the option they have looked at more. An unanswered question is how attention influences the choice process: whether it amplifies the subjective value of the looked-at option or instead adds a constant, value-independent bias. To address this, we examined choice data from six eye-tracking studies ( Ns = 39, 44, 44, 36, 20, and 45, respectively) to characterize the interaction between value and gaze in the choice process. We found that the summed values of the options influenced response times in every data set and the gaze-choice correlation in most data sets, in line with an amplifying role of attention in the choice process. Our results suggest that this amplifying effect is more pronounced in tasks using large sets of familiar stimuli, compared with tasks using small sets of learned stimuli.

Promoting subjective preferences in simple economic choices during nap

Sleep is known to benefit consolidation of memories, especially those of motivational relevance. Yet, it remains largely unknown the extent to which sleep influences reward-associated behavior, in particular, whether and how sleep modulates reward evaluation that critically underlies value-based decisions. Here, we show that neural processing during sleep can selectively bias preferences in simple economic choices when the sleeper is stimulated by covert, reward-associated cues. Specifically, presenting the spoken name of a familiar, valued snack item during midday nap significantly improves the preference for that item relative to items not externally cued. The cueing-specific preference enhancement is sleep-dependent and can be predicted by cue-induced neurophysiological signals at the subject and item level. Computational modeling further suggests that sleep cueing accelerates evidence accumulation for cued options during the post-sleep choice process in a manner consistent with the preference shift. These findings suggest that neurocognitive processing during sleep contributes to the fine-tuning of subjective preferences in a flexible, selective manner.

Spacing of cue-approach training leads to better maintenance of behavioral change

The maintenance of behavioral change over the long term is essential to achieve public health goals such as combatting obesity and drug use. Previous work by our group has demonstrated a reliable shift in preferences for appetitive foods following a novel non-reinforced training paradigm. In the current studies, we tested whether distributing training trials over two consecutive days would affect preferences immediately after training as well as over time at a one-month follow-up. In four studies, three different designs and an additional pre-registered replication of one sample, we found that spacing of cue-approach training induced a shift in food choice preferences over one month. The spacing and massing schedule employed governed the long-term changes in choice behavior. Applying spacing strategies to training paradigms that target automatic processes could prove a useful tool for the long-term maintenance of health improvement goals with the development of real-world behavioral change paradigms that incorporate distributed practice principles.

The Cue-Approach Task as a General Mechanism for Long-Term Non-Reinforced Behavioral Change

Recent findings show that preferences for food items can be modified without external reinforcements using the cue-approach task. In the task, the mere association of food item images with a neutral auditory cue and a speeded button press, resulted in enhanced preferences for the associated stimuli. In a series of 10 independent samples with a total of 255 participants, we show for the first time that using this non-reinforced method we can enhance preferences for faces, fractals and affective images, as well as snack foods, using auditory, visual and even aversive cues. This change was highly durable in follow-up sessions performed one to six months after training. Preferences were successfully enhanced for all conditions, except for negative valence items. These findings promote our understanding of non-reinforced change, suggest a boundary condition for the effect and lay the foundation for development of novel applications.