If players are sparse social dilemmas are too: Importance of percolation for evolution of cooperation

Spatial reciprocity is a well known tour de force of cooperation promotion. A thorough understanding of the effects of different population densities is therefore crucial. Here we study the evolution of cooperation in social dilemmas on different interaction graphs with a certain fraction of vacant nodes. We find that sparsity may favor the resolution of social dilemmas, especially if the population density is close to the percolation threshold of the underlying graph. Regardless of the type of the governing social dilemma as well as particularities of the interaction graph, we show that under pairwise imitation the percolation threshold is a universal indicator of how dense the occupancy ought to be for cooperation to be optimally promoted. We also demonstrate that myopic updating, due to the lack of efficient spread of information via imitation, renders the reported mechanism dysfunctional, which in turn further strengthens its foundations.Comment: 6 two-column pages, 5 figures; accepted for publication in Scientific Reports [related work available at http://arxiv.org/abs/1205.0541

Different brain responses to electro-acupuncture and moxibustion treatment in patients with Crohn's disease

This study aimed to investigate changes in resting state brain activity in remissive Crohn's Disease (CD) patients after electro-acupuncture or moxibustion treatment. Fifty-two CD patients and 36 healthy subjects were enrolled, and 36 patients were equally and randomly assigned to receive either electro-acupuncture or moxibustion treatment for twelve weeks. We used resting state functional magnetic resonance imaging to assess Regional Homogeneity (ReHo) levels, and Crohn's Disease Activity Index (CDAI) and Inflammatory Bowel Disease Questionnaire (IBDQ) scores to evaluate disease severity and quality of life. The results show that (i) The ReHo levels in CD patients were significantly increased in cortical but decreased in subcortical areas, and the coupling between them was declined. (ii) Both treatments decreased CDAI, increased IBDQ scores, and normalized the ReHo values of the cortical and subcortical regions. (iii) ReHo changes in multiple cortical regions were significantly correlated with CDAI score decreases. ReHo changes in several subcortical regions in the electro-acupuncture group, and those of several cortical regions in the moxibustion group, were correlated with reduced CDAI. These findings suggest that both treatments improved cortex-subcortical coupling in remissive CD patients, but electro-acupuncture regulated homeostatic afferent processing network, while moxibustion mainly regulated the default mode network of the brain

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis

Heroes and villains of world history across cultures

© 2015 Hanke et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedEmergent properties of global political culture were examined using data from the World History Survey (WHS) involving 6,902 university students in 37 countries evaluating 40 figures from world history. Multidimensional scaling and factor analysis techniques found only limited forms of universality in evaluations across Western, Catholic/Orthodox, Muslim, and Asian country clusters. The highest consensus across cultures involved scientific innovators, with Einstein having the most positive evaluation overall. Peaceful humanitarians like Mother Theresa and Gandhi followed. There was much less cross-cultural consistency in the evaluation of negative figures, led by Hitler, Osama bin Laden, and Saddam Hussein. After more traditional empirical methods (e.g., factor analysis) failed to identify meaningful cross-cultural patterns, Latent Profile Analysis (LPA) was used to identify four global representational profiles: Secular and Religious Idealists were overwhelmingly prevalent in Christian countries, and Political Realists were common in Muslim and Asian countries. We discuss possible consequences and interpretations of these different representational profiles.This research was supported by grant RG016-P-10 from the Chiang Ching-Kuo Foundation for International Scholarly Exchange (http://www.cckf.org.tw/). Religion Culture Entropy China Democracy Economic histor

Differences in regional homogeneity between patients with Crohn's disease with and without abdominal pain revealed by resting-state functional magnetic resonance imaging

Abnormal pain processing in the central nervous system may be related to abdominal pain in patients with Crohn's disease (CD). The purpose of this study was to investigate changes in resting-state brain activity in patients with CD in remission and its relationship with the presence of abdominal pain. Twenty-five patients with CD and with abdominal pain, 25 patients with CD and without abdominal pain, and 32 healthy subjects were scanned using a 3.0-T functional magnetic resonance imaging scanner. Regional homogeneity (ReHo) was used to assess resting-state brain activity. Daily pain scores were collected 1 week before functional magnetic resonance imaging. We found that patients with abdominal pain exhibited lower ReHo values in the insula, middle cingulate cortex (MCC), and supplementary motor area and higher ReHo values in the temporal pole. In contrast, patients without abdominal pain exhibited lower ReHo values in the hippocampal/parahippocampal cortex and higher ReHo values in the dorsomedial prefrontal cortex (all P < 0.05, corrected). The ReHo values of the insula and MCC were significantly negatively correlated with daily pain scores for patients with abdominal pain (r = -0.53, P = 0.008 and r = -0.61, P = 0.002, respectively). These findings suggest that resting-state brain activities are different between remissive patients with CD with and without abdominal pain and that abnormal activities in insula and MCC are closely related to the severity of abdominal pain

An Empirical Comparison of Information-Theoretic Criteria in Estimating the Number of Independent Components of fMRI Data

BACKGROUND: Independent Component Analysis (ICA) has been widely applied to the analysis of fMRI data. Accurate estimation of the number of independent components of fMRI data is critical to reduce over/under fitting. Although various methods based on Information Theoretic Criteria (ITC) have been used to estimate the intrinsic dimension of fMRI data, the relative performance of different ITC in the context of the ICA model hasn't been fully investigated, especially considering the properties of fMRI data. The present study explores and evaluates the performance of various ITC for the fMRI data with varied white noise levels, colored noise levels, temporal data sizes and spatial smoothness degrees. METHODOLOGY: Both simulated data and real fMRI data with varied Gaussian white noise levels, first-order auto-regressive (AR(1)) noise levels, temporal data sizes and spatial smoothness degrees were carried out to deeply explore and evaluate the performance of different traditional ITC. PRINCIPAL FINDINGS: Results indicate that the performance of ITCs depends on the noise level, temporal data size and spatial smoothness of fMRI data. 1) High white noise levels may lead to underestimation of all criteria and MDL/BIC has the severest underestimation at the higher Gaussian white noise level. 2) Colored noise may result in overestimation that can be intensified by the increase of AR(1) coefficient rather than the SD of AR(1) noise and MDL/BIC shows the least overestimation. 3) Larger temporal data size will be better for estimation for the model of white noise but tends to cause severer overestimation for the model of AR(1) noise. 4) Spatial smoothing will result in overestimation in both noise models. CONCLUSIONS: 1) None of ITC is perfect for all fMRI data due to its complicated noise structure. 2) If there is only white noise in data, AIC is preferred when the noise level is high and otherwise, Laplace approximation is a better choice. 3) When colored noise exists in data, MDL/BIC outperforms the other criteria

Collegial nests can Foster Critical Thinking, Innovative Ideas, and Scientific Progress.

How can management and strategy scholars organize to generate more productive, more innovative, and more impactful research? With appropriate cultures and leaders, small and egalitarian discussion groups that we call “collegial nests” can become powerful generators of innovative ideas and creators of extraordinary scholars. Collegial nests need cultures that free participants to think critically, to cherish new viewpoints, and to speak freely without fear of ridicule. They also need leaders who model such cultures and facilitate frequent discussions. Two case examples illustrate how productive collegial nests can create better science and better scientists. To generate scientific innovation and progress on a large scale, many autonomous groups tackling related issues are desirable. Modern communication technology is making it feasible for groups to operate over large distances and to coordinate with each other at very low cost. Collegial nests offer greater potential for enhancing scholarly productivity and innovation than do attempts to regulate scholarship via hierarchical structures. Multiplicity can lower the probability of wasting resources on low-yield paths, egalitarian control can reduce the influence of vested interests, and a combination of shared goals and partial autonomy can integrate enthusiasm with sensible risk taking

Independent Component Analysis of Resting State Activity in Pediatric Obsessive-Compulsive Disorder

Obsessive-compulsive disorder (OCD) is an often severely disabling illness with onset generally in childhood or adolescence. Little is known, however, regarding the pattern of brain resting state activity in OCD early in the course of illness. We therefore examined differences in brain resting state activity in patients with pediatric OCD compared with healthy volunteers and their clinical correlates. Twenty-three pediatric OCD patients and 23 healthy volunteers (age range 9-17), matched for sex, age, handedness, and IQ completed a resting state functional magnetic resonance imaging exam at 3T. Patients completed the Children\u27s Yale Brown Obsessive Scale. Data were decomposed into 36 functional networks using spatial group independent component analysis (ICA) and logistic regression was used to identify the components that yielded maximum group separation. Using ICA we identified three components that maximally separated the groups: a middle frontal/dorsal anterior cingulate network, an anterior/posterior cingulate network, and a visual network yielding an overall group classification of 76.1% (sensitivity=78.3% and specificity=73.9%). Independent component expression scores were significantly higher in patients compared with healthy volunteers in the middle frontal/dorsal anterior cingulate and the anterior/posterior cingulate networks, but lower in patients within the visual network. Higher expression scores in the anterior/posterior cingulate network correlated with greater severity of compulsions among patients. These findings implicate resting state fMRI abnormalities within the cingulate cortex and related control regions in the pathogenesis and phenomenology of OCD early in the course of the disorder and prior to extensive pharmacologic intervention. Hum Brain Mapp 35:5306-5315, 2014. (c) 2014 Wiley Periodicals, Inc