Neural Indicators Of Food Cue Reactivity, Regulation, And Valuation And Their Associations With Body Composition And Daily Eating Behavior

The dynamic influence of language-switching contexts on domain-general cognitive control: An EEG study

In everyday conversation, bilingual individuals switch between their languages not only in reaction to monolinguals with different language profiles but also voluntarily and naturally. However, whether and how various switching contexts dynamically modulate domain-general cognitive control is still unclear. Using a cross-task paradigm in which a flanker task was interleaved with a language-switching task trial-by-trial, the present study examined the performance of unbalanced Chinese-English bilinguals on a flanker task in forced, voluntary, and natural switching contexts. The cross-domain interaction on the P3 component revealed an atypical flanker effect in forced switching contexts only, and the P3 amplitude of incongruent trials in forced switching contexts was smaller than in both natural and voluntary switching contexts. Furthermore, robust brain-brain and brain-behavior relationships between language control and domain-general control emerged in the forced switching context only. Altogether, our findings support the dynamic adaptation of language control to cognitive control and highlight the importance of different types of switching contexts.

Body mass index-dependent shifts along large-scale gradients in human cortical organization explain dietary regulatory success

Making healthy dietary choices is essential for keeping weight within a normal range. Yet many people struggle with dietary self-control despite good intentions. What distinguishes neural processing in those who succeed or fail to implement healthy eating goals? Does this vary by weight status? To examine these questions, we utilized an analytical framework of gradients that characterize systematic spatial patterns of large-scale neural activity, which have the advantage of considering the entire suite of processes subserving self-control and potential regulatory tactics at the whole-brain level. Using an established laboratory food task capturing brain responses in natural and regulatory conditions (N = 123), we demonstrate that regulatory changes of dietary brain states in the gradient space predict individual differences in dietary success. Better regulators required smaller shifts in brain states to achieve larger goal-consistent changes in dietary behaviors, pointing toward efficient network organization. This pattern was most pronounced in individuals with lower weight status (low-BMI, body mass index) but absent in high-BMI individuals. Consistent with prior work, regulatory goals increased activity in frontoparietal brain circuits. However, this shift in brain states alone did not predict variance in dietary success. Instead, regulatory success emerged from combined changes along multiple gradients, showcasing the interplay of different large-scale brain networks subserving dietary control and possible regulatory strategies. Our results provide insights into how the brain might solve the problem of dietary control: Dietary success may be easier for people who adopt modes of large-scale brain activation that do not require significant reconfigurations across contexts and goals.

The cerebellum and cognition: further evidence for its role in language control

The cognitive function of the human cerebellum could be characterized as enigmatic. However, researchers have attempted to detail the comprehensive role of the cerebellum in several cognitive processes in recent years. Here, using functional magnetic resonance imaging (fMRI) and transcranial direct current stimulation (tDCS), we revealed different functions of bilateral cerebellar lobules in bilingual language production. Specifically, brain activation showed the bilateral posterolateral cerebellum was associated with bilingual language control, and an effective connectivity analysis built brain networks for the interaction between the cerebellum and the cerebral cortex. Furthermore, anodal tDCS over the right cerebellum significantly optimizes language control performance in bilinguals. Together, these results reveal a precise asymmetrical functional distribution of the cerebellum in bilingual language production, suggesting that the right cerebellum is more involved in language control. In contrast, its left counterpart undertakes a computational role in cognitive control function by connecting with more prefrontal, parietal, subcortical brain areas.

Task-Dependent Effective Connectivity of the Reward Network During Food Cue-Reactivity: A Dynamic Causal Modeling Investigation

Neural reactivity to food cues may play a central role in overeating and excess weight gain. Functional magnetic resonance imaging (fMRI) studies have implicated regions of the reward network in dysfunctional food cue-reactivity, but neural interactions underlying observed patterns of signal change remain poorly understood. Fifty overweight and obese participants with self-reported cue-induced food craving viewed food and neutral cues during fMRI scanning. Regions of the reward network with significantly greater food versus neutral cue-reactivity were used to specify plausible models of task-related neural interactions underlying the observed blood oxygenation level-dependent (BOLD) signal, and a bi-hemispheric winning model was identified in a dynamic causal modeling (DCM) framework. Neuro-behavioral correlations are investigated with group factor analysis (GFA) and Pearson's correlation tests. The ventral tegmental area (VTA), amygdalae, and orbitofrontal cortices (OFC) showed significant food cue-reactivity. DCM suggests these activations are produced by largely reciprocal dynamic signaling between these regions, with food cues causing regional disinhibition and an apparent shifting of activity to the right amygdala. Intrinsic self-inhibition in the VTA and right amygdala is negatively correlated with measures of food craving and hunger and right-amygdalar disinhibition by food cues is associated with the intensity of cue-induced food craving, but no robust cross-unit latent factors were identified between the neural group and behavioral or demographic variable groups. Our results suggest a rich array of dynamic signals drive reward network cue-reactivity, with the amygdalae mediating much of the dynamic signaling between the VTA and OFCs. Neuro-behavioral correlations suggest particularly crucial roles for the VTA, right amygdala, and the right OFC-amygdala connection but the more robust GFA identified no cross-unit factors, so these correlations should be interpreted with caution. This investigation provides novel insights into dynamic circuit mechanisms with etiologic relevance to obesity, suggesting pathways in biomarker development and intervention.

Multivariate pattern analysis links drug use severity to distributed cortical hypoactivity during emotional inhibitory control in opioid use disorder

Opioid use disorder (OUD) is characterized by emotional and cognitive impairements that are associated with poor treatment outcomes. The present study investigated the neural mechanism underlying emotion evaluation and inhibitory control using an affective go/no-go (AGN) task and its association with drug use severity and craving in patients with OUD. Twenty-six recently detoxified patients with OUD underwent functional magnetic resonance imaging (fMRI) while performing the AGN task that required response to frequently presented appetitive stimuli ("go") and inhibition of response to infrequently presented aversive stimuli ("no-go"). The fMRI session was immediately followed by an injection of extended-release opioid antagonist naltrexone (XR-NTX). Participants' opioid craving was assessed immediately before fMRI and 10 ± 2 days after XR-NTX injection. Multivariate pattern analysis (MVPA) showed that drug use severity was associated with distributed brain hypoactivity in response to aversive no-go stimuli, with particularly large negative contributions from the cognitive control and dorsal attention brain networks. While drug use severity and its associated MVPA brain response pattern were both correlated with opioid craving at baseline, only the brain response pattern predicted craving during XR-NTX treatment. Our findings point to widespread functional hypoactivity in the brain networks underlying emotional inhibitory control in OUD. Such a distributed pattern is consistent with the multifaceted nature of OUD, which affects multiple brain networks. It also highlights the utility of the multivariate approach in uncovering large-scale cortical substrates associated with clinical severity in complex psychiatric disorders and in predicting treatment response.

Associations between use of self-regulatory strategies and daily eating patterns: An experience sampling study in college-aged women

Previous theorizing suggests there are multiple means by which people regulate their emotions and impulses, but that these strategies vary in the degree to which they support goal attainment. Some have proposed that proactive strategies (e.g. situation selection, distraction) may be particularly effective, while interventive strategies (e.g. suppression) are less effective. Despite these diverging predictions, researchers have yet to examine spontaneous use of these strategies and their respective and combined efficacy when applied to momentary food desires experienced in daily life. In the present study, we assessed eating patterns for one week via ecological momentary assessment in college-aged women (N = 106). Results from pre-registered analyses indicated that using a variety of strategies, including preventative strategies such as situation selection and distraction, was associated with greater self-control success, as indexed by weaker desires, higher resistance, lower likelihood of enacting desires, and less food consumed. A similar pattern was observed when participants implemented additional strategies during desire episodes, which they were more likely to do when their desires conflicted with other self-regulatory goals. All associations were observed while controlling for momentary hunger levels, dieting status, age, and body mass index. These findings are consistent with a growing body of work assessing people’s spontaneous use of emotion regulation strategies in everyday contexts, suggesting potential meta-motivational tendencies marked by flexible and adaptive use of self-regulatory strategies.

Revisiting the Neural Architecture of Adolescent Decision-Making: Univariate and Multivariate Evidence for System-Based Models

Understanding adolescent decision-making is significant for informing basic models of neurodevelopment as well as for the domains of public health and criminal justice. System-based theories posit that adolescent decision-making is guided by activity related to reward and control processes. While successful at explaining behavior, system-based theories have received inconsistent support at the neural level, perhaps because of methodological limitations. Here, we used two complementary approaches to overcome said limitations and rigorously evaluate system-based models. Using decision-level modeling of fMRI data from a risk-taking task in a sample of 2000+ decisions across 51 human adolescents (25 females, mean age = 15.00 years), we find support for system-based theories of decision-making. Neural activity in lateral PFC and a multivariate pattern of cognitive control both predicted a reduced likelihood of risk-taking, whereas increased activity in the NAcc predicted a greater likelihood of risk-taking. Interactions between decision-level brain activity and age were not observed. These results garner support for system-based accounts of adolescent decision-making behavior.SIGNIFICANCE STATEMENT Adolescent decision-making behavior is of great import for basic science, and carries equally consequential implications for public health and criminal justice. While dominant psychological theories seeking to explain adolescent decision-making have found empirical support, their neuroscientific implementations have received inconsistent support. This may be partly because of statistical approaches used by prior neuroimaging studies of system-based theories. We used brain modeling, an approach that predicts behavior from brain activity, of univariate and multivariate neural activity metrics to better understand how neural components of psychological systems guide decision behavior in adolescents. We found broad support for system-based theories such that neural systems involved in cognitive control predicted a reduced likelihood to make risky decisions, whereas value-based systems predicted greater risk-taking propensity.

Neural Substrates of Food Valuation and Its Relationship With BMI and Healthy Eating in Higher BMI Individuals

Considerable evidence points to a link between body mass index (BMI), eating behavior, and the brain's reward system. However, much of this research focuses on food cue reactivity without examining the subjective valuation process as a potential mechanism driving individual differences in BMI and eating behavior. The current pre-registered study (https://osf.io/n4c95/) examined the relationship between BMI, healthy eating, and subjective valuation of healthy and unhealthy foods in a community sample of individuals with higher BMI who intended to eat more healthily. Particularly, we examined: (1) alterations in neurocognitive measures of subjective valuation related to BMI and healthy eating; (2) differences in the neurocognitive valuation for healthy and unhealthy foods and their relation to BMI and healthy eating; (3) and whether we could conceptually replicate prior findings demonstrating differences in neural reactivity to palatable vs. plain foods. To this end, we scanned 105 participants with BMIs ranging from 23 to 42 using fMRI during a willingness-to-pay task that quantifies trial-by-trial valuation of 30 healthy and 30 unhealthy food items. We measured out of lab eating behavior via the Automated Self-Administered 24 H Dietary Assessment Tool, which allowed us to calculate a Healthy Eating Index (HEI). We found that our sample exhibited robust, positive linear relationships between self-reported value and neural responses in regions previously implicated in studies of subjective value, suggesting an intact valuation system. However, we found no relationship between valuation and BMI nor HEI, with Bayes Factor indicating moderate evidence for a null relationship. Separating the food types revealed that healthy eating, as measured by the HEI, was inversely related to subjective valuation of unhealthy foods. Imaging data further revealed a stronger linkage between valuation of healthy (compared to unhealthy) foods and corresponding response in the ventromedial prefrontal cortex (vmPFC), and that the interaction between healthy and unhealthy food valuation in this region is related to HEI. Finally, our results did not replicate reactivity differences demonstrated in prior work, likely due to differences in the mapping between food healthiness and palatability. Together, our findings point to disruptions in the valuation of unhealthy foods in the vmPFC as a potential mechanism influencing healthy eating.