One session of fMRI-Neurofeedback training on motor imagery modulates whole-brain effective connectivity and dynamical complexity

In the past decade, several studies have shown that Neurofeedback (NFB) by functional magnetic resonance imaging can alter the functional coupling of targeted and non-targeted areas. However, the causal mechanisms underlying these changes remain uncertain. Here, we applied a whole-brain dynamical model to estimate Effective Connectivity (EC) profiles of resting-state data acquired before and immediately after a single-session NFB training for 17 participants who underwent motor imagery NFB training and 16 healthy controls who received sham feedback. Within-group and between-group classification analyses revealed that only for the NFB group it was possible to accurately discriminate between the 2 resting-state sessions. NFB training-related signatures were reflected in a support network of direct connections between areas involved in reward processing and implicit learning, together with regions belonging to the somatomotor, control, attention, and default mode networks, identified through a recursive-feature elimination procedure. By applying a data-driven approach to explore NFB-induced changes in spatiotemporal dynamics, we demonstrated that these regions also showed decreased switching between different brain states (i.e. metastability) only following real NFB training. Overall, our findings contribute to the understanding of NFB impact on the whole brain's structure and function by shedding light on the direct connections between brain areas affected by NFB training

A social health model supporting undocumented immigrants in Italy

status: publishe

A quantitative evaluation of damage in normal appearing white matter in patients with multiple sclerosis using diffusion tensor MR imaging at 3 T

The white matter (WM) of the brain is damaged in multiple sclerosis (MS), even in areas that appear normal on standard MR imaging. The purpose of our study is to evaluate the damage of normal appearing white matter (NAWM) in patients with MS. In our study, 84 MS patients and 42 healthy adults underwent a routine brain MRI, including also diffusion tensor imaging (DTI). All studies were performed on a 3 T MRI scanner. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were obtained. The DTI parameters of NAWM were correlated with expanded disability status scales (EDSS) scores. Our results showed statistically significant differences in FA and ADC values between MS plaques and the symmetrical NAWM, as also between NAWM and the respective white matter in controls. The ADC values of the NAWM correlated with the EDSS scores. The present study demonstrated damage of the NAWM in MS patients, using DTI in 3.0 T. DTI may be used in the detection of subtle damage of the white matter

Assessment of cognition using the Rao's Brief Repeatable Battery of Neuropsychological Tests on a group of Brazilian patients with multiple sclerosis

To assess the cognition of patients with multiple sclerosis (MS) using the Rao's Brief Repeatable Battery of Neuropsychological Tests (BRB-N). METHOD: BRB-N was translated and adapted for control subjects. Subsequently, it was applied to a group of patients with relapsing-remitting (RR) MS. RESULTS: The assessment on the healthy controls (n=47) showed that the correlation between tests on the same cognitive domain was high and that there was a five-factor solution that explained 90% of the total variance. Except for the Word List Generation subset of tests, the performance of patients with RRMS (n=39) was worse than that of the healthy controls. CONCLUSION: BRB-N is a relatively simple method to assess cognition of patients with MS in the daily clinic. It does not take long to apply and does not require special skills or equipment

Firm networks: external relationships as sources for the growth and competitiveness of entrepreneurial firms

Inter-firm networks, as an inter-organizational form, are increasingly perceived as a model for entrepreneurial firm growth. We study egocentric networks of high-growth entrepreneurial firms in the IT industry and explore how these firms grow through the use of external relations and become competitive. Based on case study research, we identify that firms are using relations for a variety of purposes and that every firm has an individual relational mix. This relational mix changes with the development of the firms. While the relative importance of social and reputational networks decrease with the firms' development, co-opetition networks increase over time. Knowledge and innovation networks are a function of reputation and management capacity while the development of marketing networks depends on the firm's culture and management style. Both weak ties and strong ties are important for the growth of the firm since they fulfil different functions. Firm growth is determined by path-dependent relational capability that eventually reaches its limits and leads to the reconfiguration of a rather stable network. Additionally, firm growth depends not only on the building of egocentric networks but also on the existence and development of healthy sociocentric networks