The Flint Food Store Survey: combining spatial analysis with a modified Nutrition Environment Measures Survey in Stores (NEMS-S) to measure the community and consumer nutrition environments

Objective The goal of the present study was to use a methodology that accurately and reliably describes the availability, price and quality of healthy foods at both the store and community levels using the Nutrition Environment Measures Survey in Stores (NEMS-S), to propose a spatial methodology for integrating these store and community data into measures for defining objective food access. Setting Two hundred and sixty-five retail food stores in and within 2 miles (3·2 km) of Flint, Michigan, USA, were mapped using ArcGIS mapping software. Design A survey based on the validated NEMS-S was conducted at each retail food store. Scores were assigned to each store based on a modified version of the NEMS-S scoring system and linked to the mapped locations of stores. Neighbourhood characteristics (race and socio-economic distress) were appended to each store. Finally, spatial and kernel density analyses were run on the mapped store scores to obtain healthy food density metrics. Results Regression analyses revealed that neighbourhoods with higher socio-economic distress had significantly lower dairy sub-scores compared with their lower-distress counterparts (β coefficient=−1·3; P=0·04). Additionally, supermarkets were present only in neighbourhoods with \u3c60 % African-American population and low socio-economic distress. Two areas in Flint had an overall NEMS-S score of 0. Conclusions By identifying areas with poor access to healthy foods via a validated metric, this research can be used help local government and organizations target interventions to high-need areas. Furthermore, the methodology used for the survey and the mapping exercise can be replicated in other cities to provide comparable results

Enhanced response inhibition during intensive meditation training predicts improvements in self-reported adaptive socioemotional functioning.

We examined the impact of training-induced improvements in self-regulation, operationalized in terms of response inhibition, on longitudinal changes in self-reported adaptive socioemotional functioning. Data were collected from participants undergoing 3 months of intensive meditation training in an isolated retreat setting (Retreat 1) and a wait-list control group that later underwent identical training (Retreat 2). A 32-min response inhibition task (RIT) was designed to assess sustained self-regulatory control. Adaptive functioning (AF) was operationalized as a single latent factor underlying self-report measures of anxious and avoidant attachment, mindfulness, ego resilience, empathy, the five major personality traits (extroversion, agreeableness, conscientiousness, neuroticism, and openness to experience), diffi-culties in emotion regulation, depression, anxiety, and psychological well-being. Participants in Retreat 1 improved in RIT performance and AF over time whereas the controls did not. The control participants later also improved on both dimensions during their own retreat (Retreat 2). These improved levels of RIT performance and AF were sustained in follow-up assessments conducted approximately 5 months after the training. Longitudinal dynamic models with combined data from both retreats showed that improvement in RIT performance during training influenced the change in AF over time, which is consistent with a key claim in the Buddhist literature that enhanced capacity for self-regulation is an important precursor of changes in emotional well-being

Self-reported mindfulness and cortisol during a Shamatha meditation retreat.

Objective: Cognitive perseverations that include worry and rumination over past or future events may prolong cortisol release, which in turn may contribute to predisease pathways and adversely affect physical health. Meditation training may increase self-reported mindfulness, which has been linked to reductions in cognitive perseverations. However, there are no reports that directly link self-reported mindfulness and resting cortisol output. Here, the authors investigate this link. Methods: In an observational study, we measured self-reported mindfulness and p.m. cortisol near the beginning and end of a 3-month meditation retreat (N = 57). Results: Mindfulness increased from pre- to post-retreat, F(1, 56) = 36.20, p < .001. Cortisol did not significantly change. However, mindfulness was inversely related to p.m. cortisol at pre-retreat, r(53) = −.31, p < .05, and post-retreat, r(53) = −.30, p < .05, controlling for age and body mass index. Pre to postchange in mindfulness was associated with pre to postchange in p.m. cortisol, β = −.37, t(49) = 2.30, p < .05: Larger increases in mindfulness were associated with decreases in p.m. cortisol, whereas smaller increases (or slight decreases) in mindfulness were associated with an increase in p.m. cortisol. Conclusions: These data suggest a relation between self-reported mindfulness and resting output of the hypothalamic-pituitary-adrenal system. Future work should aim to replicate this finding in a larger cohort and determine stronger inference about causality by using experimental designs that include control-group conditions

The Flint Food Store Survey: combining spatial analysis with a modified Nutrition Environment Measures Survey in Stores (NEMS-S) to measure the community and consumer nutrition environments

Objective The goal of the present study was to use a methodology that accurately and reliably describes the availability, price and quality of healthy foods at both the store and community levels using the Nutrition Environment Measures Survey in Stores (NEMS-S), to propose a spatial methodology for integrating these store and community data into measures for defining objective food access. Setting Two hundred and sixty-five retail food stores in and within 2 miles (3·2 km) of Flint, Michigan, USA, were mapped using ArcGIS mapping software. Design A survey based on the validated NEMS-S was conducted at each retail food store. Scores were assigned to each store based on a modified version of the NEMS-S scoring system and linked to the mapped locations of stores. Neighbourhood characteristics (race and socio-economic distress) were appended to each store. Finally, spatial and kernel density analyses were run on the mapped store scores to obtain healthy food density metrics. Results Regression analyses revealed that neighbourhoods with higher socio-economic distress had significantly lower dairy sub-scores compared with their lower-distress counterparts (β coefficient=−1·3; P=0·04). Additionally, supermarkets were present only in neighbourhoods with \u3c60 % African-American population and low socio-economic distress. Two areas in Flint had an overall NEMS-S score of 0. Conclusions By identifying areas with poor access to healthy foods via a validated metric, this research can be used help local government and organizations target interventions to high-need areas. Furthermore, the methodology used for the survey and the mapping exercise can be replicated in other cities to provide comparable results

Enhanced response inhibition during intensive meditation training predicts improvements in self-reported adaptive socioemotional functioning

We examined the impact of training-induced improvements in self-regulation, operationalized in terms of response inhibition, on longitudinal changes in self-reported adaptive socioemotional functioning. Data were collected from participants undergoing 3 months of intensive meditation training in an isolated retreat setting (Retreat 1) and a wait-list control group that later underwent identical training (Retreat 2). A 32-min response inhibition task (RIT) was designed to assess sustained self-regulatory control. Adaptive functioning (AF) was operationalized as a single latent factor underlying self-report measures of anxious and avoidant attachment, mindfulness, ego resilience, empathy, the five major personality traits (extroversion, agreeableness, conscientiousness, neuroticism, and openness to experience), difficulties in emotion regulation, depression, anxiety, and psychological well-being. Participants in Retreat 1 improved in RIT performance and AF over time whereas the controls did not. The control participants later also improved on both dimensions during their own retreat (Retreat 2). These improved levels of RIT performance and AF were sustained in follow-up assessments conducted approximately 5 months after the training. Longitudinal dynamic models with combined data from both retreats showed that improvement in RIT performance during training influenced the change in AF over time, which is consistent with a key claim in the Buddhist literature that enhanced capacity for self-regulation is an important precursor of changes in emotional well-being

A computational approach to understanding the longitudinal changes in cortical activity associated with intensive meditation training

Manish Saggar and Risto Miikkulainen are with the Department of Computer Science, University of Texas at Austin, Austin, TX 78712, USA -- Stephen R Aichele, Baljinder K Sahdra, Phillip R Shaver, Emilio Ferrer, and George R Mangun are with the Department of Psychology, University of California-Davis, Davis, CA 95618, USA -- Stephen R Aichele, Tonya L Jacobs, Anthony P Zanesco, David A Bridwell, Katherine A Maclean, Brandon G King, Baljinder K Sahdra, Erika L Rosenberg, George R Mangun, Clifford D Saron are with the Center for Mind and Brain, University of California-Davis, Davis, CA 95618, USA -- David A Bridwell is with the Department of Cognitive Science, Univ. of California-Irvine, Irvine, CA 92697, USA -- B Alan Wallace is with the Santa Barbara Institute for Consciousness Studies, Santa Barbara, CA 93130, USA -- Katherine A Maclean is with the Department of Psychiatry and Behavioral Sciences, JHU School of Medicine, Baltimore, MD 21224, USAMeditation involves focusing one’s attention on an object or a phenomenon. Numerous studies have discovered beneficial effects of meditation. However, very few scientific studies have attempted to formally understand the underlying mechanisms. In the present study, two 3-month retreats were conducted. 88-channel EEG data was collected while participants rested with their eyes closed before and after engaging in focused attention meditation. Second-order blind source separation was used for artifact removal. Reference-free data was obtained by estimating current source density. Changes in spectral power were assessed using a nonparametric cluster-based approach. Within-session (pre-meditation rest vs. meditation) results, in the alpha band, suggest that after 3-months there is a generalization of overall cortical activity during rest, such that the “default” mode of resting came to resemble the meditation mode. To formally understand the underlying mechanisms responsible for such a cortical change during rest, a computational model was employed. Attention regulation during focused meditation is hypothesized to involve cortico-thalamo-cortical interactions. Thus, to model EEG data during rest, the presented model architecture includes cortico-thalamic and thalamo-cortical interactions (Figure-1a). This model was initially developed by [1] and is capable of modeling both spatial and temporal dynamics of cortical activity using a 2-D continuum approach with inputs from sub-cortical structures. Three computational modeling experiments were run to examine – (1) if the model can fit the 88-channel EEG data, (2) if the inverse computational modeling can provide insights about the patterns observed on the scalp, and (3) if the stability analysis of model equations can explain for the observed cortical activity changes on the scalp. As shown in Figure-1b, the model-estimated spectrum is in accordance with the experimental spectrum without crossing physiologically plausible limits for the parameter set. Further, inverse computational modeling of the estimated spectral data indicates that after three months of training intrathalamic gain was significantly reduced in the right-parietal location (Figure-1c). This reduction suggests that participants after training were more alert even during rest. This sustained alertness during rest may be reflected as a change in the “default” mode after three months of training. Lastly, the stability analysis of model equations showed that reduction in the intrathalamic gain parameter provided more overall stability to the system. Altogether, these computational experiments along with the spectral analysis provide a more insightful formal theory of what might be happening inside the brain than does the spectral analysis alone.Computer [email protected]

Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity.

The capacity to focus one's attention for an extended period of time can be increased through training in contemplative practices. However, the cognitive processes engaged during meditation that support trait changes in cognition are not well characterized. We conducted a longitudinal wait-list controlled study of intensive meditation training. Retreat participants practiced focused attention (FA) meditation techniques for three months during an initial retreat. Wait-list participants later undertook formally identical training during a second retreat. Dense-array scalp-recorded electroencephalogram (EEG) data were collected during 6 min of mindfulness of breathing meditation at three assessment points during each retreat. Second-order blind source separation, along with a novel semi-automatic artifact removal tool (SMART), was used for data preprocessing. We observed replicable reductions in meditative state-related beta-band power bilaterally over anteriocentral and posterior scalp regions. In addition, individual alpha frequency (IAF) decreased across both retreats and in direct relation to the amount of meditative practice. These findings provide evidence for replicable longitudinal changes in brain oscillatory activity during meditation and increase our understanding of the cortical processes engaged during meditation that may support long-term improvements in cognition

Intensive meditation training influences emotional responses to suffering

Meditation practices purportedly help people develop focused and sustained attention, cultivate feelings of compassionate concern for self and others, and strengthen motivation to help others who are in need. We examined the impact of 3 months of intensive meditative training on emotional responses to scenes of human suffering. Sixty participants were assigned randomly to either a 3-month intensive meditation retreat or a wait-list control group. Training consisted of daily practice in techniques designed to improve attention and enhance compassionate regard for others. Participants viewed film scenes depicting human suffering at pre- and posttraining laboratory assessments, during which both facial and subjective measures of emotion were collected. At postassessment, training group participants were more likely than controls to show facial displays of sadness. Trainees also showed fewer facial displays of rejection emotions (anger, contempt, disgust). The groups did not differ on the likelihood or frequency of showing these emotions prior to training. Self-reported sympathy—but not sadness or distress—predicted sad behavior and inversely predicted displays of rejection emotions in trainees only. These results suggest that intensive meditation training encourages emotional responses to suffering characterized by enhanced sympathetic concern for, and reduced aversion to, the suffering of others