Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training

Progressive modulation of resting‑state brain activity during neurofeedback of positive‑social emotion regulation networks

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training.publishedVersio

Social capital development strategy and collaborative knowledge creation in higher education: the UK and Turkey

The paper presents the second phase of international (four countries) study that explores the influence of social capital and personal learning networks (PLN) development approaches utilized by international students in multicultural learning environment and the types of the social and academic networks they develop on their collaborative knowledge development, in particular, on their preparation for international careers. A comparative analysis is conducted within three international programs (in Turkey, Ecuador, and the UK) that offer international education in English language for local and international students. The paper presents the preliminary results of a comparison in two locations – Turkey and UK. The study applies the concepts of collaborative knowledge development, social capital, and social networks. The study uses constructivist grounded theory, in particular, dimensional analysis to uncover the process of social capital and collaborative knowledge creation. Based on the data, collected through semi-structured interviews, and analyzed through dımensıonal analysis, the study has developed a process model, which takes into account the core social identity of the learner, as well as the existing and emergent social, personal learning ties, built on social capital. An additional goal of the study is to uncover the overlapping social and personal learning networks International and local students participate in and develop, to trace the knowledge sharing routes and to pinpoint knowledge creation hubs in these networks. As the result of the study, recommendations are developed for higher educational institutions (HEIs) and multinational enterprises (MNEs) regarding the steps they can take to promote collaborative and cross-cultural knowledge creation among their members. While we are not proposing any hypotheses or theoretical models until the completion of the continuous comparison analysis process, it is likely that the learners who are engaged in multi-dimensional and loosely connected PLN characterized by multiple networks consisted of weak ties and who utilize problem-solving models of knowledge creation are more likely to become cross/interculturally competent and are more likely to be prepared for global careers. However, the preliminary findings show that international students lack skills and desire to create functional PLN and tend to engage in multiple binding networks characterized by strong emotional bonds but limited knowledge creation. While is it premature at this stage to suggest any specific steps that IHEIs and other multicultural learning environments might take to encourage social and technological networking among international students and other members of the academic environment, some tentative recommendations are presented. The first part of the research was conducted in Turkey and Ecuador in the summer and fall of 2015 and the second part is in the spring of 2106 in UK and Turkey. Data is collected through semi-structured in-depth interviews, conducted in person and through Skype. The participants are volunteer students, both local and international, enrolled in the undergraduate programs in the participating HEIs. As the study is using Grounded Theory Method (GTM), the sampling of the interview participants is driven by theoretical developments

New Media and Youth Political Action

To rigorously consider the impact of new media on the political and civic behavior of young people, The MacArthur Research Network on Youth and Participatory Politics (YPP) developed and fielded one of the first large-scale, nationally representative studies of new media and politics among young people. The two principal researchers for the survey component of the YPP, Cathy J. Cohen of the University of Chicago and Joseph Kahne of Mills College, oversaw a research team that surveyed nearly 3,000 respondents between the ages of 15 and 25 years of age. Unlike any prior study of youth and new media, this study included large numbers of black, Latino, and Asian American respondents, which allows for unique and powerful statistical comparisons across race with a focus on young people.Until now there has been limited opportunity and data available to comprehensively explore the relationship between new media and the politics of young people. One of the few entities to engage in this type of rigorous analysis has been the Pew Internet and American Life Project. The YPP study expands on this field-leading work by including an extensive battery of items addressing participatory politics and adequate numbers of participants from different racial and ethnic groups, thus allowing for analysis of how different groups of young people were engaged with new media in the political realm.The YPP study findings suggest that fundamental changes in political expectations and practices may be occurring -- especially for youth. The analysis of the data collected reveals that youth are taking advantage of an expanded set of participatory practices in the political realm in ways that amplify their voice and sometimes their influence, thus increasing the ways young people participate in political life. The YPP researchers label this expanded set of opportunities and actions participatory politics

Peer selection and influence: Students’ interest-driven socio-digital participation and friendship networks

Digital technologies have been increasingly embedded in students’ everyday lives. Interest-driven socio-digital participation (ISDP) involves students’ pursuit of interests mediated by computers, social media, the internet, and mobile devices’ integrated systems. ISDP is likely to intertwine closely with young people’s social networks that has been scarcely studied quantitatively. To close this gap, the present paper investigated students’ peer selection and influence effects of the intensity of their ISDP and friendship networks. We collected two-wave data by administering a peer nomination to trace students’ friendship networks with peers and a self-reported questionnaire to examine students’ ISDP. Participants were 100 students in Finland (female: 53%; mean age = 13.48, in grade 7 in the first wave). Through stochastic actor-oriented modelling, the results showed that the students’ friendship ties with peers influenced the intensity of their ISDP practices to become more similar. Yet, students did not select peers as friends based on similar intensity levels of ISDP. Utilizing influence effect found in students’ ISDP and their peer networks, we suggest that connected learning (Ito et al., 2013) should be promoted to integrate students’ informal and formal learning in order to bridge the gap between students’ informal interest-related digital practices and formal educational practices.</p

Social interactions among paedophiles

The purpose of this study is to explore the range and nature of social interactions among individuals who experience a sustained and compelling attraction towards young adolescents or prepubescent children of either sex. Such an attraction, of course, is prohibited and the target of extensive social controls, legal sanctions and therapeutic efforts. Given the widespread hostility they elicit, paedophiles are generally viewed not only as social outcasts but also as social isolates. This may explain the lack of research on the social networks of paedophiles . Nonetheless, a non-trivial proportion of criminal prosecutions involve multiple co-defendants; a number of advocacy groups publicly challenge age of consent laws exist and provide favourable definitions of paedophilia; finally social learning theory typically emphasizes the influence of peer groups in maintaining high recidivism rates and the development of deviant careers. My substantive goal, here, is to analyze the variety of conditions that allow paedophiles to overcome their social isolation, seek each other out and become, as a result, embedded in a deviant quasi-community or social movement.Canadian Ministry of Justice and International Bureau for Children's Rights1. Introduction, p. 1; Pool of Motivated Adults, p. 3; Pool of Suitable Targets, p. 4; Focus of the Current Research, p. 7; 2. Data and Method, p. 8; 3. Market-Driven Subculture of Hebephiles, p. 14; Off-the-market Cliques, p. 19; 4. Web-Driven Exchange Forums for Paedophiles, p. 23; 5. Individual Commitment and Social Disclosure: Evolving Patterns, p. 32; 6. Conclusion, p. 42; References, p. 46

From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications

Fake news spreading, with the aim of manipulating individuals' perceptions of facts, is now recognized as a major problem in many democratic societies. Yet, to date, little has been understood about how fake news spreads on social networks, what the influence of the education level of individuals is, when fake news is effective in influencing public opinion, and what interventions might be successful in mitigating their effect. In this paper, starting from the recently introduced kinetic multi-agent model with competence by the first two authors, we propose to derive reduced-order models through the notion of social closure in the mean-field approximation that has its roots in the classical hydrodynamic closure of kinetic theory. This approach allows to obtain simplified models in which the competence and learning of the agents maintain their role in the dynamics and, at the same time, the structure of such models is more suitable to be interfaced with data-driven applications. Examples of different Twitter-based test cases are described and discussed.Comment: Minor changes to align the manuscript to its published versio

Transnational Network and Information Flow in African Refugees and Undocumented Migrants’ International Migration Process

This paper analyses the role of information flow under transnational (social) networks to understand African refugees and undocumented migrants’ migration to Austria. Existing research pointed to the international refugee crisis with industrialised countries targeted border governance that has prompted the emergence of the transnational (social) network, which builds (kinship-based) connectivity and interchangeable acquaintances between migrants in host and country of origin to influence and facilitate migrants’ pre and post mobility process. However, the network often faces weak ties with exploitation and subjugation to human trafficking. Based on twenty qualitative problem-centred face-face interviews, data are collected and analysed with content analysis technique to fill in the gap. The findings indicate that pre-mobility guidance, directive, and legislative decoder regulatory tools influence transnational networks with a lack of well-managed network that may impair pre and post-mobility processes to shape African refugees and undocumented migrant international migratory pathways in an information flow setting. This study demonstrated actor-based network-driven advocacy governance. The outcome points to the strategic mobilization of collective information to resource vulnerable people and refugees or undocumented migrants to meet their needs. This is relevant to collective action in contemporary neoliberal society targeting freedom and movements that may not only constrain ethnic minority group mobility, but the universal human rights principles, public policy learning process, informal institution collaborative actions, and democratic values in times of crisis-related super-diversity societies

Learning to Address Health Inequality in the United States with a Bayesian Decision Network

Life-expectancy is a complex outcome driven by genetic, socio-demographic, environmental and geographic factors. Increasing socio-economic and health disparities in the United States are propagating the longevity-gap, making it a cause for concern. Earlier studies have probed individual factors but an integrated picture to reveal quantifiable actions has been missing. There is a growing concern about a further widening of healthcare inequality caused by Artificial Intelligence (AI) due to differential access to AI-driven services. Hence, it is imperative to explore and exploit the potential of AI for illuminating biases and enabling transparent policy decisions for positive social and health impact. In this work, we reveal actionable interventions for decreasing the longevity-gap in the United States by analyzing a County-level data resource containing healthcare, socio-economic, behavioral, education and demographic features. We learn an ensemble-averaged structure, draw inferences using the joint probability distribution and extend it to a Bayesian Decision Network for identifying policy actions. We draw quantitative estimates for the impact of diversity, preventive-care quality and stable-families within the unified framework of our decision network. Finally, we make this analysis and dashboard available as an interactive web-application for enabling users and policy-makers to validate our reported findings and to explore the impact of ones beyond reported in this work.Comment: 8 pages, 4 figures, 1 table (excluding the supplementary material), accepted for publication in AAAI 201