Pooling fMRI Data: Meta-Analysis, Mega-Analysis and Multi-Center Studies

The quantitative analysis of pooled data from related functional magnetic resonance imaging (fMRI) experiments has the potential to significantly accelerate progress in brain mapping. Such data-pooling can be achieved through meta-analysis (the pooled analysis of published results), mega-analysis (the pooled analysis of raw data) or multi-site studies, which can be seen as designed mega-analyses. Current limitations in function-location brain mapping and how data-pooling can be used to remediate them are reviewed, with particular attention to power aggregation and mitigation of false positive results. Some recently developed analysis tools for meta- and mega-analysis are also presented, and recommendations for the conduct of valid fMRI data pooling are formulated

Random graph model with power-law distributed triangle subgraphs

Clustering is well-known to play a prominent role in the description and understanding of complex networks, and a large spectrum of tools and ideas have been introduced to this end. In particular, it has been recognized that the abundance of small subgraphs is important. Here, we study the arrangement of triangles in a model for scale-free random graphs and determine the asymptotic behavior of the clustering coefficient, the average number of triangles, as well as the number of triangles attached to the vertex of maximum degree. We prove that triangles are power-law distributed among vertices and characterized by both vertex and edge coagulation when the degree exponent satisfies $2<\beta<2.5$; furthermore, a finite density of triangles appears as $\beta=2+1/3$.Comment: 4 pages, 2 figure; v2: major conceptual change

Acute Partial Sleep Deprivation and High-Intensity Exercise Effects on Cardiovascular Autonomic Regulation and Lipemia Network

Autonomic nervous system imbalance demonstrated by decreased heart rate variability (HRV) is linked to acute partial sleep deprivation (ASPD) and cardiovascular disease (CVD). Cardiometabolic lipemia has been linked to changes in HRV. Habitually active individuals exercising in the morning hours under APSD and consuming afterwards a high-fat breakfast, may disrupt the network coordination of both the cardiovascular autonomic regulation and cardiometabolic lipemic systems jeopardizing their health. The human organism is comprised by an integrated network of interconnected organ systems and functions, therefore, a disruption/failure of one system can trigger a cascade of failures manifested as disease state. PURPOSE: To investigate the postprandial network interactions of autonomic regulation assessed by heart rate variability (HRV) and cardiometabolic lipemia assessed by low-density lipoprotein (LDL) cholesterol under APSD and after a high-intensity interval exercise (HIIE). METHODS: Fifteen healthy males (age 31 ± 5 years) participated in: (a) reference sleep (RS) (~ 9.5 h) and HIIE (RSX) and (b) APSD and HIIE (SSX). HIIE was performed in 3:2 min intervals at 90% and 40% of VO2reserve. HRV selected time and frequency domain indices were recorded the night before (D1), the morning of the next day (D2), 1 hr post-HIEE (1hrPE), 2 hr (2hrPE)-, 4hr (4hrPE), and 6-hr post-HIIE (6hrPE). Postprandial LDL was assessed at D1, D2, 1hrPE and 4hrPE. Pearson correlation coefficients and correlation matrices were used to investigate the physiologic network during RSX and SSX. Interactions within each network were computed by the number of links (i.e. number of significant Pearson correlations) and presented as positive and negative links. RESULTS: The total number of links increased by 90% under SSX compared to RSX due to: (i) manifestation of weak and intermediate negative links between the HRV and the LDL sub-networks and (ii) a 100% increase of positive links within the LDL sub-network. CONCLUSION: This study shows a complex network of interactions between autonomic regulation and cardiometabolic lipemia. Our results uncover how this physiological network reorganizes in response to APSD confirming the inverse relationship between HRV and LDL. HRV can be used as an alternative non-invasive marker of CVD

Towards digital society management and 'capitalism 4.0' in contemporary Russia

AbstractConceptualizing the complexities of the Russian political economy strikingly illustrates the challenging but essential role of the State in the new process of capitalist reforms initiated in the 1990s. A missing ingredient in this discourse has been considering the extraordinary impact technology has on society and how it affects the process. Accordingly, this paper focuses on the current development of culturally unique capitalist theory in Russia, together with the practical application of proven quantitative landmarks and policy implications for managing digital society's development to optimize capitalism in Russia. The paper performs a quantitative analysis of the considerable influence that the digital society has on Russian capitalism and how the latter can be systemically optimized through the former's development. This contribution's originality lies in its consideration of the consequences of digital culture on the unique model of capitalism shaping contemporary Russia. Currently, Russia is implementing a particular and unique model of capitalism model where the digital society's influence is limited and contradictory. We argue that the Russian model of capitalism could experience rapid development in the foreseeable future with effective digital society management

On the Geometry and Entropy of Non-Hamiltonian Phase Space

We analyze the equilibrium statistical mechanics of canonical, non-canonical and non-Hamiltonian equations of motion by throwing light into the peculiar geometric structure of phase space. Some fundamental issues regarding time translation and phase space measure are clarified. In particular, we emphasize that a phase space measure should be defined by means of the Jacobian of the transformation between different types of coordinates since such a determinant is different from zero in the non-canonical case even if the phase space compressibility is null. Instead, the Jacobian determinant associated with phase space flows is unity whenever non-canonical coordinates lead to a vanishing compressibility, so that its use in order to define a measure may not be always correct. To better illustrate this point, we derive a mathematical condition for defining non-Hamiltonian phase space flows with zero compressibility. The Jacobian determinant associated with time evolution in phase space is altogether useful for analyzing time translation invariance. The proper definition of a phase space measure is particularly important when defining the entropy functional in the canonical, non-canonical, and non-Hamiltonian cases. We show how the use of relative entropies can circumvent some subtle problems that are encountered when dealing with continuous probability distributions and phase space measures. Finally, a maximum (relative) entropy principle is formulated for non-canonical and non-Hamiltonian phase space flows.Comment: revised introductio