Richard J Davidson

This scoping review provides an overview of previous empirical studies that used brain imaging techniques to investigate the neural correlates of emotional well-being (EWB). We compiled evidence on this topic into one accessible and usable document as a foundation for future research into the relationship between EWB and the brain. PRISMA 2020 guidelines were followed. We located relevant articles by searching five electronic databases with 95 studies meeting our inclusion criteria. We explored EWB measures, brain imaging modalities, research designs, populations studied, and approaches that are currently in use to characterize and understand EWB across the literature. Of the key concepts related to EWB, the vast majority of studies investigated positive affect and life satisfaction, followed by sense of meaning, goal pursuit, and quality of life. The majority of studies used functional MRI, followed by EEG and event-related potential-based EEG to study the neural basis of EWB (predominantly experienced affect, affective perception, reward, and emotion regulation). It is notable that positive affect and life satisfaction have been studied significantly more often than the other three aspects of EWB (i.e., sense of meaning, goal pursuit, and quality of life). Our findings suggest that future studies should investigate EWB in more diverse samples, especially in children, individuals with clinical disorders, and individuals from various geographic locations. Future directions and theoretical implications are discussed, including the need for more longitudinal studies with ecologically valid measures that incorporate multi-level approaches allowing …

A lot has happened in the 20 years since Baer (2003) published the first meta-analysis of mindfulness-based interventions (MBIs) in Clinical Psychology: Science and Practice. The year 2003 was a time before the iPhone, before Facebook, long before the COVID-19 pandemic, and certainly before advances in artificial intelligence brought algorithm-delivered content to our digital devices and large language models could mimic human interaction disturbingly well. Yet, Baer’s meta-analysis examined the effects of MBIs on the same clinical challenges that plague us today: depression, anxiety, stress, and pain. In 2003, self-compassion was only just emerging as a term in the scientific lexicon and experimental work studying interventions based on loving-kindness and compassion meditation (LKCM) was still almost a decade away. Now that the LKCM literature has grown large enough to allow large-scale meta …

Meditation is a family of ancient and contemporary contemplative mind-body practices that can modulate psychological processes, awareness, and mental states. Over the last 40 years, clinical science has manualised meditation practices and designed various meditation interventions (MIs), that have shown therapeutic efficacy for disorders including depression, pain, addiction, and anxiety. Over the past decade, neuroimaging has examined the neuroscientific basis of meditation practices, effects, states, and outcomes for clinical and non-clinical populations. However, the generalizability and replicability of current neuroscientific models of meditation are yet to be established, as they are largely based on small datasets entrenched with heterogeneity along several domains of meditation (eg, practice types, meditation experience, clinical disorder targeted), experimental design, and neuroimaging methods (eg, preprocessing, analysis, task-based, resting-state, structural MRI). These limitations have precluded a nuanced and rigorous neuroscientific phenotyping of meditation practices and their potential benefits. Here, we present ENIGMA-Meditation, the first worldwide collaborative consortium for neuroscientific investigations of meditation practices. ENIGMA-Meditation will enable systematic meta-and mega-analyses of globally distributed neuroimaging datasets of meditation using shared, standardized neuroimaging methods and tools to improve statistical power and generalizability. Through this powerful collaborative framework, existing neuroscientific accounts of meditation practices can be extended to generate novel and rigorous …

More research is needed to understand the effects of school-based mindfulness programs in the years prior to adolescence, which represent a critical juncture and transitional period of development. The present study investigated mindfulness with elementary school students using random assignment and objective measures. The sample included 292 fifth graders from 21 classrooms randomly assigned to an 8-week mindfulness training or wait-list control group. Students were assessed at pre- and post-intervention on behavioral measures of executive functioning and teacher-rated social emotional competence, along with end of year social-emotional learning report card grades. Analyses using hierarchal linear modeling found that students in the intervention group demonstrated significant gains on a computerized task of cognitive flexibility, and end of year social-emotional learning grades controlling for prior …

Meditation apps are the most commonly used mental health apps. However, the optimal dosing of app-delivered meditation practice has not been established. We examined whether the distribution of meditation practices across a day impacted outcomes in a distressed population. We investigated the effects of meditation practice frequency in a 2-week compassion-based meditation intervention delivered via the Healthy Minds Program app. Undergraduates with clinically elevated depression and/or anxiety (N= 351) were randomized to a massed (one 20-min meditation per day) or distributed condition (two 10-min meditations per day). Psychological distress (primary outcome; composite of depression and anxiety), experiential avoidance, fear of missing out, loneliness, and self-compassion were assessed pre-and post-intervention. Psychological distress, loneliness, and informal meditation practice were also …

We investigated whether informal meditation practice (i.e., self-reported application of meditative techniques outside a period of formal meditation) was associated with outcomes in smartphone-based loving-kindness and compassion training. Meditation-naïve participants (n = 351) with clinically elevated symptoms completed measures of psychological distress, loneliness, empathy, and prosociality at baseline and following a two-week intervention. Informal practice, psychological distress, and loneliness were also assessed daily. Steeper increases in informal practice had small associations with pre-post improvements in distress (r = −.18, p = .008) and loneliness (r = −.19, p = .009) but not empathy or prosociality. Using a currently recommended approach for establishing cross-lagged effects in longitudinal data (latent curve model with structured residuals), higher current-day informal practice was …

BackgroundThe staggering morbidity associated with chronic inflammatory diseases can be reduced by psychological interventions, including Mindfulness-Based Stress Reduction (MBSR). Proposed mechanisms for MBSR’s beneficial effects include changes in salience network function. Salience network perturbations are also associated with chronic inflammation, including airway inflammation in asthma, a chronic inflammatory disease affecting approximately 10% of the population. However, no studies have examined whether MBSR-related improvements in disease control are related to changes in salience network function.MethodsAdults with asthma were randomized to 8 weeks of MBSR or a waitlist control group. Resting state functional connectivity was measured using fMRI before randomization, immediately post-intervention, and 4 months post-intervention. Using key salience network regions as seeds …

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with …