1,721,106 research outputs found
Short-term mindfulness practice attenuates reward prediction errors signals in the brain
Get PDFActivity changes in dopaminergic neurons encode the ongoing discrepancy between expected and actual value of a stimulus, providing a teaching signal for a reward prediction process. Previous work comparing a cohort of long-term Zen meditators to controls demonstrated an attenuation of reward prediction signals to appetitive reward in the striatum. Using a cross-commodity design encompassing primary- and secondary-reward conditioning experiments, the present study asks the question of whether reward prediction signals are causally altered by mindfulness training in naive subjects. Volunteers were randomly assigned to 8 weeks of mindfulness training (MT), active control training (CT), or a one-time mindfulness induction group (MI). We observed a decreased response to positive prediction errors in the putamen in the MT group compared to CT using both a primary and a secondary-reward experiment. Furthermore, the posterior insula showed greater activation to primary rewards, independently of their predictability, in the MT group, relative to CT and MI group. These results support the notion that increased attention to the present moment and its interoceptive features - a core component of mindfulness practice - may reduce predictability effects in reward processing, without dampening (in fact, enhancing) the response to the actual delivery of the stimulus
The impact of mindfulness meditation on the wandering mind: a systematic review
No full textThrough the practice of Mindfulness Meditation (MM), meditators become familiar with the observation of ongoing spontaneous thoughts, while maintaining an attitude of openness and equanimity. The aim of this systematic review is to present a synthesis of available findings of the short and long-term effects of MM on mind wandering (MW). We included studies that considered both first-person and behavioral/physiological measures of MW. The search resulted in 2035 papers, 24 of which were eligible. Reviewed studies revealed a high heterogeneity in designs, outcome measures and interventions. Most of the pre-post intervention studies showed that a protracted practice of MM (at least 2 weeks) reduced MW, limiting its negative effects on different cognitive tasks. Cross-sectional studies highlighted differences between expert meditators and naïve individuals: meditators self-reported less MW and showed decreased Default Mode Network activity, during meditation and resting-state. Further studies are needed to replicate available findings and to more deeply explore how MW is influenced by meditation, also considering its qualitative characteristics that remain largely unexplored
Bayesian Joint Modeling of Multiple Brain Functional Networks
Get PDFInvestigating the similarity and changes in brain networks under different mental conditions has become increasingly important in neuroscience research. A standard separate estimation strategy fails to pool information across networks and hence has reduced estimation accuracy and power to detect between-network differences. Motivated by an fMRI Stroop task experiment that involves multiple related tasks, we develop an integrative Bayesian approach for jointly modeling multiple brain networks that provides a systematic inferential framework for network comparisons. The proposed approach explicitly models shared and differential patterns via flexible Dirichlet process-based priors on edge probabilities. Conditional on edges, the connection strengths are modeled via Bayesian spike-and-slab prior on the precision matrix off-diagonals. Numerical simulations illustrate that the proposed approach has increased power to detect true differential edges while providing adequate control on false positives and achieves greater network estimation accuracy compared to existing methods. The Stroop task data analysis reveals greater connectivity differences between task and fixation that are concentrated in brain regions previously identified as differentially activated in Stroop task, and more nuanced connectivity differences between exertion and relaxed task. In contrast, penalized modeling approaches involving computationally burdensome permutation tests reveal negligible network differences between conditions that seem biologically implausible. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement
Modelling of earthquake-induced tsunami in the Eastern Mediterranean Region
No full textA number of tsunamigenic zones in the Eastern Mediterranean region were investigated. Historically, the strongest tsunami waves are excited in the Hellenic and Cyprus arcs, the Aegean Sea and the Levantine coast. We modelled the generation of tsunami specifying the epicenter, the focal mechanism, and the maximum of the observed magnitude for each considered tsunamigenic zone. Our approach is based on the numerical simulations of tsunami waves, performed by the code UBO-TSUFD, developed in the University of Bologna. Initial displacement of the sea floor is calculated in accordance with Okadàs formulas. We focused our discussion on the tsunami impact on the coasts of Karpathos, Cyprus and Levantine countries. Tsunami parameters are computed for each scenario and results are used to build maps of the computed maximum tsunami heights. Synthetic mareograms are simulated for several points near some important coastal cities of the study area
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Sparse Bayesian modeling of hierarchical independent component analysis: Reliable estimation of individual differences in brain networks
No full textIndependent component analysis (ICA) is one of the leading approaches for studying brain functional networks. There is increasing interest in neuroscience studies to investigate individual differences in brain networks and their association with demographic characteristics and clinical outcomes. In this work, we develop a sparse Bayesian group hierarchical ICA model that offers significant improvements over existing ICA techniques for identifying covariate effects on the brain network. Specifically, we model the population-level ICA source signals for brain networks using a Dirichlet process mixture. To reliably capture individual differences on brain networks, we propose sparse estimation of the covariate effects in the hierarchical ICA model via a horseshoe prior. Through extensive simulation studies, we show that our approach performs considerably better in detecting covariate effects in comparison with the leading group ICA methods. We then perform an ICA decomposition of a between-subject meditation study. Our method is able to identify significant effects related to meditative practice in brain regions that are consistent with previous research into the default mode network, whereas other group ICA approaches find few to no effects
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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