A Formal Approach to Modeling the Cost of Cognitive Control

This paper introduces a formal method to model the level of demand on control when executing cognitive processes. The cost of cognitive control is parsed into an intensity cost which encapsulates how much additional input information is required so as to get the specified response, and an interaction cost which encapsulates the level of interference between individual processes in a network. We develop a formal relationship between the probability of successful execution of desired processes and the control signals (additive control biases). This relationship is also used to specify optimal control policies to achieve a desired probability of activation for processes. We observe that there are boundary cases when finding such control policies which leads us to introduce the interaction cost. We show that the interaction cost is influenced by the relative strengths of individual processes, as well as the directionality of the underlying competition between processes.Comment: 6 pages, 3 figures, Conference pape

Deeper but smaller: Higher-order interactions increase linear stability but shrink basins

A key challenge of nonlinear dynamics and network science is to understand how higher-order interactions influence collective dynamics. Although many studies have approached this question through linear stability analysis, less is known about how higher-order interactions shape the global organization of different states. Here, we shed light on this issue by analyzing the rich patterns supported by identical Kuramoto oscillators on hypergraphs. We show that higher-order interactions can have opposite effects on linear stability and basin stability: they stabilize twisted states (including full synchrony) by improving their linear stability, but also make them hard to find by dramatically reducing their basin size. Our results highlight the importance of understanding higher-order interactions from both local and global perspectives.Comment: Comments welcome! Code at https://github.com/maximelucas/basins_and_triangle

Microbiological pathogen analysis in native versus periprosthetic joint infections: a retrospective study

Background The presence or absence of an implant has a major impact on the type of joint infection therapy. Thus, the aim of this study was the examination of potential differences in the spectrum of pathogens in patients with periprosthetic joint infections (PJI) as compared to patients with native joint infections (NJI). Methods In this retrospective study, we evaluated culture-positive synovial fluid samples of 192 consecutive patients obtained from January 2018 to January 2020 in a tertiary care university hospital. For metrically distributed parameters, Mann–Whitney U was used for comparison between groups. In case of nominal data, crosstabs and Chi-squared tests were implemented. Results Overall, 132 patients suffered from periprosthetic joint infections and 60 patients had infections of native joints. The most commonly isolated bacteria were coagulase-negative Staphylococci (CNS, 28%), followed by Staphylococcus aureus (S. aureus, 26.7%), and other bacteria, such as Streptococci (26.3%). We observed a significant dependence between the types of bacteria and the presence of a joint replacement (p < 0.05). Accordingly, detections of CNS occurred 2.5-fold more frequently in prosthetic as compared to native joint infections (33.9% vs. 13.4% p < 0.05). In contrast, S. aureus was observed 3.2-fold more often in NJIs as compared to PJIs (52.2% vs. 16.4%, p < 0.05). Conclusion The pathogen spectra of periprosthetic and native joint infections differ considerably. However, CNS and S. aureus are the predominant microorganisms in both, PJIs and NJIs, which may guide antimicrobial therapy until microbiologic specification of the causative pathogen

A centriole- and RanGTP-independent spindle assembly pathway in meiosis I of vertebrate oocytes

Spindle formation is essential for stable inheritance of genetic material. Experiments in various systems indicate that Ran GTPase is crucial for meiotic and mitotic spindle assembly. Such an important role for Ran in chromatin-induced spindle assembly was initially demonstrated in Xenopus laevis egg extracts. However, the requirement of RanGTP in living meiotic cells has not been shown. In this study, we used a fluorescence resonance energy transfer probe to measure RanGTP-regulated release of importin β. A RanGTP-regulated gradient was established during meiosis I and was centered on chromosomes throughout mouse meiotic maturation. Manipulating levels of RanGTP in mice and X. laevis oocytes did not inhibit assembly of functional meiosis I spindles. However, meiosis II spindle assembly did not tolerate changes in the level of RanGTP in both species. These findings suggest that a mechanism common to vertebrates promotes meiosis I spindle formation in the absence of chromatin-induced microtubule production and centriole-based microtubule organizing centers

A modelling study of OH, NO3 and H2SO4 in 2007– 2018 at SMEAR II, Finland : analysis of long-term trends

Major atmospheric oxidants (OH, O3 and NO3) dominate the atmospheric oxidation capacity, while H2SO4 is considered as a main driver for new particle formation. Although numerous studies have investigated the long-term trend of ozone in Europe, the trends of OH, NO3 and H2SO4 at specific sites are to a large extent unknown. The one-dimensional model SOSAA has been applied in several studies at the SMEAR II station and has been validated by measurements in several projects. Here, we applied the SOSAA model for the years 2007–2018 to simulate the atmospheric chemical components, especially the atmospheric oxidants OH and NO3, as well as H2SO4 at SMEAR II. The simulations were evaluated with observations from several shorter and longer campaigns at SMEAR II. Our results show that daily OH increased by 2.39% per year and NO3 decreased by 3.41% per year, with different trends of these oxidants during day and night. On the contrary, daytime sulfuric acid concentrations decreased by 2.78% per year, which correlated with the observed decreasing concentration of newly formed particles in the size range of 3– 25 nm with 1.4% per year at SMEAR II during the years 1997–2012. Additionally, we compared our simulated OH, NO3 and H2SO4 concentrations with proxies, which are commonly applied in case a limited number of parameters are measured and no detailed model simulations are available.Peer reviewe