App-Based Mindfulness Training Predicts Reductions in Smoking Behavior by Engaging Reinforcement Learning Mechanisms: A Preliminary Naturalistic Single-Arm Study.

Mindfulness training (MT) has been shown to influence smoking behavior, yet the involvement of reinforcement learning processes as underlying mechanisms remains unclear. This naturalistic, single-arm study aimed to examine slope trajectories of smoking behavior across uses of our app-based MT craving tool for smoking cessation, and whether this relationship would be mediated by the attenuating impact of MT on expected reward values of smoking. Our craving tool embedded in our MT app-based smoking cessation program was used by 108 participants upon the experience of cigarette cravings in real-world contexts. Each use of the tool involved mindful awareness to the experience of cigarette craving, a decision as to whether the participant wanted to smoke or ride out their craving with a mindfulness exercise, and paying mindful attention to the choice behavior and its outcome (contentment levels felt from engaging in the behavior). Expected reward values were computed using contentment levels experienced from the choice behavior as the reward signal in a Rescorla−Wagner reinforcement learning model. Multi-level mediation analysis revealed a significant decreasing trajectory of smoking frequency across MT craving tool uses and that this relationship was mediated by the negative relationship between MT and expected reward values (all ps < 0.001). After controlling for the mediator, the predictive relationship between MT and smoking was no longer significant (p < 0.001 before and p = 0.357 after controlling for the mediator). Results indicate that the use of our app-based MT craving tool is associated with negative slope trajectories of smoking behavior across uses, mediated by reward learning mechanisms. This single-arm naturalistic study provides preliminary support for further RCT studies examining the involvement of reward learning mechanisms underlying app-based mindfulness training for smoking cessation.

Reduced Fear-Conditioned Pain Modulation in Experienced Meditators: A Preliminary Study.

OBJECTIVE: Mindfulness-based practice is a form of cognitive/affective training that may help reduce suffering by attenuating maladaptive anticipatory processes. This study's objective was to examine the pain modulating impact of classical fear learning in meditation practitioners. METHODS: The hyperalgesic effects of pain expectation and uncertainty were assessed outside formal meditation in 11 experienced meditators (>1000 hours) compared with meditation-naive controls during a Pavlovian classical fear-conditioning paradigm involving two visual stimuli (CS+/CS-), one of which (CS+) co-terminated with a noxious electrical stimulus (unconditioned stimulus) on 50% of trials. A Rescorla-Wagner/Pearce-Hall hybrid model was fitted onto the conditioned skin conductance responses using computational modeling to estimate two learning parameters: expected shock probability and associability (i.e., uncertainty). RESULTS: Using a scale ranging between 0 (no pain) and 100 (extremely painful), meditators reported less pain (M = 19.9, SE = 5.1 for meditators, M = 32.4, SE = 2.4 for controls) but had comparable spinal motor responses (nociceptive flexion reflex) to the unconditioned stimulus. Multilevel mediation analyses revealed that meditators also exhibited reduced hyperalgesic effects of fear learning on higher-order pain responses but comparable effects on the nociceptive flexion reflex. These results suggest that mindfulness affects higher-order perceptual processes to a greater extent than from descending inhibitory controls. Furthermore, meditators showed reduced hyperalgesic effects of fear conditioning with no significant group difference in conditioned learning as evidenced by discriminative anticipatory skin conductance responses and learning parameters derived from computational modeling. CONCLUSIONS: These results highlight potential mechanisms underlying mindfulness-related hypoalgesia, relevant to clinical conditions in which repeated pain exposure might reinforce hyperalgesic processes through fear conditioning.

Cluster-based psychological phenotyping and differences in anxiety treatment outcomes.

The identification of markers of mental health illness treatment response and susceptibility using personalized medicine has been elusive. In the context of psychological treatment for anxiety, we conducted two studies to identify psychological phenotypes with distinct characteristics related to: psychological intervention modalities (mindfulness training/awareness), mechanism of action (worry), and clinical outcome (generalized anxiety disorder scale scores). We also examined whether phenotype membership interacted with treatment response (Study 1) and mental health illness diagnosis (Studies 1-2). Interoceptive awareness, emotional reactivity, worry, and anxiety were assessed at baseline in treatment-seeking individuals (Study 1, n = 63) and from the general population (Study 2, n = 14,010). In Study 1, participants were randomly assigned to an app-delivered mindfulness program for anxiety for two months or treatment as usual. Changes in anxiety were assessed 1 and 2 months post-treatment initiation. In studies 1-2, three phenotypes were identified: 'severely anxious with body/emotional awareness' (cluster 1), 'body/emotionally unaware' (cluster 2), and 'non-reactive and aware' (cluster 3). Study 1's results revealed a significant treatment response relative to controls (ps < 0.001) for clusters 1 and 3, but not for cluster 2. Chi-square analyses revealed that phenotypes exhibited significantly different proportions of participants with mental health diagnoses (studies 1-2). These results suggest that psychological phenotyping can bring the application of personalized medicine into clinical settings.Registry name and URL: Developing a novel digital therapeutic for the treatment of generalized anxiety disorder https://clinicaltrials.gov/ct2/show/NCT03683472?term=judson+brewer&draw=1&rank=1 .Trial registration: Registered at clinicaltrials.gov (NCT03683472) on 25/09/2018.

Impact of mindfulness on the neural responses to emotional pictures in experienced and beginner meditators.

There is mounting evidence that mindfulness meditation is beneficial for the treatment of mood and anxiety disorders, yet little is known regarding the neural mechanisms through which mindfulness modulates emotional responses. Thus, a central objective of this functional magnetic resonance imaging study was to investigate the effects of mindfulness on the neural responses to emotionally laden stimuli. Another major goal of this study was to examine the impact of the extent of mindfulness training on the brain mechanisms supporting the processing of emotional stimuli. Twelve experienced (with over 1000 h of practice) and 10 beginner meditators were scanned as they viewed negative, positive, and neutral pictures in a mindful state and a non-mindful state of awareness. Results indicated that the Mindful condition attenuated emotional intensity perceived from pictures, while brain imaging data suggested that this effect was achieved through distinct neural mechanisms for each group of participants. For experienced meditators compared with beginners, mindfulness induced a deactivation of default mode network areas (medial prefrontal and posterior cingulate cortices) across all valence categories and did not influence responses in brain regions involved in emotional reactivity during emotional processing. On the other hand, for beginners relative to experienced meditators, mindfulness induced a down-regulation of the left amygdala during emotional processing. These findings suggest that the long-term practice of mindfulness leads to emotional stability by promoting acceptance of emotional states and enhanced present-moment awareness, rather than by eliciting control over low-level affective cerebral systems from higher-order cortical brain regions. These results have implications for affect-related psychological disorders.

Awareness drives changes in reward value which predict eating behavior change: Probing reinforcement learning using experience sampling from mobile mindfulness training for maladaptive eating.

BACKGROUND AND AIMS: Maladaptive eating habits are a major cause of obesity and weight-related illness. The development of empirically-based approaches, such as mindfulness training (MT) that target accurate mechanisms of action to address these behaviors is therefore critical. Two studies were conducted to examine the impact of MT on maladaptive eating and determine the involvement of reinforcement learning mechanisms underlying these effects. METHODS: In Study1, maladaptive eating behaviors were assessed using self-report questionnaires at baseline and 8 weeks after an app-based MT intervention (n = 46). A novel mindful eating craving tool was embedded in our intervention to assess: eating behaviors (intake frequency/magnitude), and reward (contentment ratings) experienced after eating. Using a well-established reinforcement learning (Rescorla-Wagner) model, expected reward values (EV) were estimated as a function of contentment levels reported after eating. In Study2 (n = 1,119), craving tool assessments were examined in an independent sample using the app in a real-world naturalistic context. RESULTS: Study 1's results revealed a significant decrease in EV and eating behaviors across craving tool uses. In addition, changes in reward values predicted decreases in eating behaviors. Finally, Study 1's results revealed significant pre-post intervention reductions in self-reported eating behaviors. In Study2, we observed a significant decrease in EV, but not in eating behaviors, across craving tool uses. Study 2 also revealed a predictive relationship between EV and eating behaviors. DISCUSSION AND CONCLUSIONS: These results support the implementation of MT to prevent and treat maladaptive eating behaviors, which target reinforcement learning processes as mechanisms of action.

Learned expectations and uncertainty facilitate pain during classical conditioning.

Pain spontaneously activates adaptive and dynamic learning processes affecting the anticipation of, and the responses to, future pain. Computational models of associative learning effectively capture the production and ongoing changes in conditioned anticipatory responses (eg, skin conductance response), but the impact of this dynamic process on unconditional pain responses remains poorly understood. Here, we investigated the dynamic modulation of pain and the nociceptive flexion reflex by fear learning in healthy human adult participants undergoing a classical conditioning procedure involving an acquisition, reversal and extinction phase. Conditioned visual stimuli (CS+) coterminated with a noxious transcutaneous stimulation applied to the sural nerve on 50% of trials (unconditioned stimuli). Expected pain probabilities and cue associability were estimated using computational modeling by fitting a hybrid learning model to skin conductance response elicited by the CS+. Multilevel linear regression analyses confirmed that trial-by-trial changes in expected pain and associability positively predict ongoing fluctuations in pain outcomes. Mediation analysis further demonstrated that both expected probability and associability affect pain perception through a direct effect and an indirect effect mediated by descending modulatory mechanisms affecting spinal nociceptive activity. Moderation analyses further showed that hyperalgesic effects of associability were larger in individuals reporting more harm vigilance and less emotional detachment. Higher harm vigilance was also associated with a stronger mediation of hyperalgesic effects by spinal processes. These results demonstrate how dynamic changes in pain can be explained by associative learning theory and that resilient attitudes towards fear/pain can attenuate the adverse impact of adaptive aversive learning processes on pain.

Impact of meditation training on the default mode network during a restful state.

Mindfulness meditation has been shown to promote emotional stability. Moreover, during the processing of aversive and self-referential stimuli, mindful awareness is associated with reduced medial prefrontal cortex (MPFC) activity, a central default mode network (DMN) component. However, it remains unclear whether mindfulness practice influences functional connectivity between DMN regions and, if so, whether such impact persists beyond a state of meditation. Consequently, this study examined the effect of extensive mindfulness training on functional connectivity within the DMN during a restful state. Resting-state data were collected from 13 experienced meditators (with over 1000 h of training) and 11 beginner meditators (with no prior experience, trained for 1 week before the study) using functional magnetic resonance imaging (fMRI). Pairwise correlations and partial correlations were computed between DMN seed regions' time courses and were compared between groups utilizing a Bayesian sampling scheme. Relative to beginners, experienced meditators had weaker functional connectivity between DMN regions involved in self-referential processing and emotional appraisal. In addition, experienced meditators had increased connectivity between certain DMN regions (e.g. dorso-medial PFC and right inferior parietal lobule), compared to beginner meditators. These findings suggest that meditation training leads to functional connectivity changes between core DMN regions possibly reflecting strengthened present-moment awareness.

The effects of glucocorticoids on the inhibition of emotional information: A dose-response study.

There is evidence that cortisol influences cognitive and affective processes such as selective attention and memory for emotional events, yet the effects of glucocorticoids on attentional inhibition in humans remain unknown. Consequently, this double-blind study examined dose-dependent effects of exogenous glucocorticoids on the inhibition of emotional information. Sixty-three university students (14 male, 49 female) ingested either a placebo pill or hydrocortisone (10mg or 40mg), and completed a negative priming task assessing the inhibition of pictures depicting angry, sad, and happy faces. The 10mg, but not the 40mg hydrocortisone dose elicited increased inhibition for angry faces relative to placebo. Thus, moderate glucocorticoid elevations may have adaptive effects on emotional information processing, whereas high glucocorticoid elevations appear to attenuate this effect, consistent with the view that there are dose-dependent effects of glucocorticoids on cognition.