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Compassion is a key motivator of altruistic behavior, but little is known about individuals’ capacity to cultivate compassion through training. We examined whether compassion may be systematically trained by testing whether (a) short-term compassion training increases altruistic behavior and (b) individual differences in altruism are associated with training-induced changes in neural responses to suffering. In healthy adults, we found that compassion training increased altruistic redistribution of funds to a victim encountered outside of the training context. Furthermore, increased altruistic behavior after compassion training was associated with altered activation in brain regions implicated in social cognition and emotion regulation, including the inferior parietal cortex and dorsolateral prefrontal cortex (DLPFC), and in DLPFC connectivity with the nucleus accumbens. These results suggest that compassion can be cultivated with training and that greater altruistic behavior may emerge from increased engagement of neural systems implicated in understanding the suffering of other people, executive and emotional control, and reward processing.

Compassion, the emotional response of caring for another who is suffering and that results in motivation to relieve suffering, is thought to be an emotional antecedent to altruistic behavior. However, it remains unclear whether compassion enhances altruistic behavior in a uniform way or is specific to sub-types of behavior such as altruistic helping of a victim or altruistic punishment of a transgressor. We investigated the relationship between compassion and subtypes of altruistic behavior using third-party paradigms where participants (1) witnessed an unfair economic exchange between a transgressor and a victim, and (2) had the opportunity to either spend personal funds to either economically (a) help the victim or (b) punish the transgressor. In Study 1, we examined whether individual differences in self-reported empathic concern (the emotional component of compassion) was associated with greater altruistic helping or punishment behavior in two independent samples. For participants who witnessed an unfair transaction, trait empathic concern was associated with greater helping of a victim and had no relationship to punishment. However, in those who decided to punish the transgressor, participants who reported greater empathic concern decided to punish less. In Study 2, we directly enhanced compassion using short-term online compassion meditation training to examine whether altruistic helping and punishment were increased after two weeks of training. Compared to an active reappraisal training control group, the compassion training group gave more to help the victim and did not differ in punishment of the transgressor. Together, these two studies suggest that compassion is related to greater altruistic helping of victims and is not associated with or may mitigate altruistic punishment of transgressors.

Mind–body interventions such as mindfulness-based stress reduction (MBSR) may improve well-being by increasing awareness and regulation of physiological and cognitive states. However, it is unclear how practice may alter long-term, baseline physiological processes, and whether these changes reflect improved well-being. Using respiration rate (RR), which can be sensitive to effects of meditation, and 3 aspects of self-reported well-being (psychological well-being [PWB], distress, and medical symptoms), we tested pre-registered hypotheses that: (1) Lower baseline RR (in a resting, non-meditative state) would be a physiological marker associated with well-being, (2) MBSR would decrease RR, and (3) Training-related decreases in RR would be associated with improved well-being. We recruited 245 adults (age range = 18–65, M = 42.4): experienced meditators ( n  = 42), and meditation-naïve participants randomized to MBSR ( n  = 72), active control ( n  = 41), or waitlist control ( n  = 66). Data were collected at pre-randomization, post-intervention (or waiting), and long-term follow-up. Lower baseline RR was associated with lower psychological distress among long-term meditators ( p * = 0.03, b  = 0.02, 95% CI [0.01, 0.03]), though not in non-meditators prior to training. MBSR decreased RR compared to waitlist ( p  = 0.02, Cohen’s d  = − 0.41, 95% CI [− 0.78, − 0.06]), but not the active control. Decreased RR related to decreased medical symptoms, across all participants ( p * = 0.02, b  = 0.57, 95% CI [0.15, 0.98]). Post-training, lower RR was associated with higher PWB across training groups compared to waitlist ( p * = 0.01, b  = 0.06, 95% CI [0.02, 0.10]), though there were no significant differences in change in PWB between groups. This physiological marker may indicate higher physical and/or psychological well-being in those who engage in wellness practices.

Meditation practices are often used to cultivate interoception or internally-oriented attention to bodily sensations, which may improve health cognitive and emotional regulation of bodily signals. However, it remains unclear how meditation impacts internal attention (IA) states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to: (1) learn and recognize internal attentional states relevant for meditation during a directed IA task; and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls ( = 16), we first used MVPA to develop single-subject brain classifiers for five modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states [i.e., meditation-related states: breath attention, mind wandering (MW), and self-referential processing, and control states: attention to feet and sounds]. Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all volumes were tested, = 2,160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, MW, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to MW or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation.

The impact of meditation training on self-report psychological variables is well-established. Although meditation training is purported to have interpersonal impacts, whether naïve observers perceive differences associated with long- and short-term meditation training is largely unknown. The current study provided a stringent test of this possibility through observer ratings of a very thin slice of expressive behavior: still photographs. Photographs were drawn from a larger study investigating differences between long-term meditators (LTM) and meditation naïve participants (MNP) who were exposed to one of three experimental conditions. Photographs of ninety-nine targets (16 LTMs, 83 MNPs) were taken at baseline, prior to the randomization of MNPs to an eight-week mindfulness meditation course (mindfulness-based stress reduction; n = 27), an active control comparison condition (health enhancement program; n = 29), or a waitlist control group (n = 27) and again after the training period. Pre- and post-intervention photographs were then rated by 25 meditation teachers and 86 undergraduate raters on five domains theoretically linked to meditation training. Results indicated that relative to MNPs, LTMs were rated as less neurotic and more conscientious, mindful, and \"comfortable in their own skin\" at baseline (ds = 0.61 to 0.70, ps < .050), although not more agreeable or attractive. Results were largely unchanged when controlling for five observable confounds (age, gender, race/ethnicity, body mass index, attractiveness). No evidence was found supporting experimental effects of short-term meditation training on observer ratings. Thus, it seems that if meditation is associated with observable differences in facial behavior, effects may be limited to long-term training.

An individual’s affective style is influenced by many things, including the manner in which an individual responds to an emotional challenge. Emotional response is composed of a number of factors, two of which are the initial reactivity to an emotional stimulus and the subsequent recovery once the stimulus terminates or ceases to be relevant. However, most neuroimaging studies examining emotional processing in humans focus on the magnitude of initial reactivity to a stimulus rather than the prolonged response. In this study, we use functional magnetic resonance imaging to study the time course of amygdala activity in healthy adults in response to presentation of negative images. We split the amygdala time course into an initial reactivity period and a recovery period beginning after the offset of the stimulus. We find that initial reactivity in the amygdala does not predict trait measures of affective style. Conversely, amygdala recovery shows predictive power such that slower amygdala recovery from negative images predicts greater trait neuroticism, in addition to lower levels of likability of a set of social stimuli (neutral faces). These data underscore the importance of taking into account temporal dynamics when studying affective processing using neuroimaging.

Compassion is a key motivator of altruistic behavior, but little is known about individuals' capacity to cultivate compassion through training. We examined whether compassion may be systematically trained by testing whether (a) short-term compassion training increases altruistic behavior and (b) individual differences in altruism are associated with training-induced changes in neural responses to suffering. In healthy adults, we found that compassion training increased altruistic redistribution of funds to a victim encountered outside of the training context. Furthermore, increased altruistic behavior after compassion training was associated with altered activation in brain regions implicated in social cognition and emotion regulation, including the inferior parietal cortex and dorsolateral prefrontal cortex (DLPFC), and in DLPFC connectivity with the nucleus accumbens. These results suggest that compassion can be cultivated with training and that greater altruistic behavior may emerge from increased engagement of neural systems implicated in understanding the suffering of other people, executive and emotional control, and reward processing.

Compassion is a key motivator of altruistic behavior, but little is known about individuals' capacity to cultivate compassion through training. We examined whether compassion may be systematically trained by testing whether (a) short-term compassion training increases altruistic behavior and (b) individual differences in altruism are associated with training-induced changes in neural responses to suffering. In healthy adults, we found that compassion training increased altruistic redistribution of funds to a victim encountered outside of the training context. Furthermore, increased altruistic behavior after compassion training was associated with altered activation in brain regions implicated in social cognition and emotion regulation, including the inferior parietal cortex and dorsolateral prefrontal cortex (DLPFC), and in DLPFC connectivity with the nucleus accumbens. These results suggest that compassion can be cultivated with training and that greater altruistic behavior may emerge from increased engagement of neural systems implicated in understanding the suffering of other people, executive and emotional control, and reward processing.

Meditation practices are used to cultivate internally-oriented attention to bodily sensations, which may improve health via cognitive and emotion regulation of bodily signals. However, it remains unclear how meditation impacts internal attention states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to (1) learn and recognize internal attentional (IA) states relevant for meditation during a directed IA task, and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls (N=16), we first used MVPA to develop single-subject brain classifiers for 5 modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states (i.e., meditation-related states: breath attention, mind wandering, and self-referential processing, and control states: attention to feet and sounds). Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all block volumes were tested, N=2160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were then applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, mind wandering, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to mind wandering or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation. Competing Interest Statement The authors have declared no competing interest. Footnotes * This version includes additional control analyses requested by reviewers (controlling head motion and respiration within fMRI data, parsing classifier evidence in different ways).

The impact of aging on intestinal stem cells (ISCs) has not been fully elucidated. In this study, we identified widespread epigenetic and transcriptional alterations in old ISCs. Using a reprogramming algorithm, we identified a set of key transcription factors (Egr1, Irf1, FosB) that drives molecular and functional differences between old and young states. Overall, by dissecting the molecular signature of aged ISCs, our study identified transcription factors that enhance the regenerative capacity of ISCs.