Multiscale Bayesian State Space Model for Granger Causality Analysis of Brain Signal

Modelling time-varying and frequency-specific relationships between two brain signals is becoming an essential methodological tool to answer heoretical questions in experimental neuroscience. In this article, we propose to estimate a frequency Granger causality statistic that may vary in time in order to evaluate the functional connections between two brain regions during a task. We use for that purpose an adaptive Kalman filter type of estimator of a linear Gaussian vector autoregressive model with coefficients evolving over time. The estimation procedure is achieved through variational Bayesian approximation and is extended for multiple trials. This Bayesian State Space (BSS) model provides a dynamical Granger-causality statistic that is quite natural. We propose to extend the BSS model to include the \`{a} trous Haar decomposition. This wavelet-based forecasting method is based on a multiscale resolution decomposition of the signal using the redundant \`{a} trous wavelet transform and allows us to capture short- and long-range dependencies between signals. Equally importantly it allows us to derive the desired dynamical and frequency-specific Granger-causality statistic. The application of these models to intracranial local field potential data recorded during a psychological experimental task shows the complex frequency based cross-talk between amygdala and medial orbito-frontal cortex. Keywords: \`{a} trous Haar wavelets; Multiple trials; Neuroscience data; Nonstationarity; Time-frequency; Variational methods The published version of this article is Cekic, S., Grandjean, D., Renaud, O. (2018). Multiscale Bayesian state-space model for Granger causality analysis of brain signal. Journal of Applied Statistics. https://doi.org/10.1080/02664763.2018.145581

Gait variability while dual-tasking: fall predictor in older inpatients?

Background and aims: Increased gait variability is associated with a high risk of falling in older community-dwellers, but no information exists about the relationship between increased gait variability and falls occurring in older hospitalized patients. We therefore sought to determine, in an acute geriatric setting, whether gait variability in single- (i.e., usual walking) or dual-task conditions can predict inpatient falls. Methods: Stride time variability was calculated in both single-task (i.e., usual walking) and dual-task conditions with a GAITRite®-System in 13 male and 44 female patients (mean age=85.0, SD=6.6 yrs) consecutively admitted to the acute care geriatric department of Geneva University Hospitals, Switzerland. All participants were able to walk without assistive devices at day 3 post-admission. Falls during hospital stay were identified through the hospital accident reporting system. Results: Ten fallers and 47 non-fallers were identified. The first fall events were significantly associated with the coefficient of variation of stride time in both walking conditions during hospital stay (OR 13.3, (95% CI 1.6-113.6), p=0.018 for usual walking; OR 8.6, (95% CI 1.9-39.6), p=0.006 for dual-task walking). Furthermore, the time elapsing between the first day of hospitalization and the first fall was significantly shorter when the cut-off value of stride time variability was calculated for dual-tasking compared with usual walking. The Cox regression model revealed that only the coefficient of variation of stride time during dual-task walking was significantly associated with the occurrence of the first fall event (p=0.006). Conclusion: Our results suggest that the degree of stride time variability in dual-task walking conditions distinguished fallers from non-fallers in a group of independently walking, older inpatient

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Are Major Histocompatibility Complex Molecules Involved in the Survival of Naive CD4+ T Cells?

The exact role of major histocompatibility complex (MHC) molecules in the peripheral survival of naive T cells is controversial, as some studies have suggested that they are critically required whereas others have suggested that they are not. Here we controlled for some of the features that differed among the earlier studies, and analyzed both the survival and expansion of naive CD4+ T cells transferred into MHC syngeneic, allogeneic, or MHC negative environments. We found that naive T cells transferred into MHC negative or allogeneic environments often fail to survive because of rejection and/or competition by natural killer (NK) cells, rather than failure to recognize a particular MHC allele. In the absence of NK cells, naive CD4+ T cells survived equally well regardless of the MHC type of the host. There was, however, an MHC requirement for extensive space-induced “homeostatic” expansion. Although the first few divisions occurred in the absence of MHC molecules, the cells did not continue to divide or transit to a CD44hi phenotype. Surprisingly, this MHC requirement could be satisfied by alleles other than the restricting haplotype. Therefore, space-induced expansion and survival are two different phenomena displaying different MHC requirements. Memory CD4+ T cells, whose survival and expansion showed no requirements for MHC molecules at all, dampened the space-induced expansion of naive cells, showing that the two populations are not independent in their requirements for peripheral niches

Fundamental strings in Dp-Dq brane systems

We study conformal field theory correlation functions relevant for string diagrams with open strings that stretch between several parallel branes of different dimensions. In the framework of conformal field theory, they involve boundary condition changing twist fields which intertwine between Neumann and Dirichlet conditions. A Knizhnik-Zamolodchikov-like differential equation for correlators of such boundary twist fields and ordinary string vertex operators is derived, and explicit integral formulas for its solutions are provided.Comment: 30 pages, Plain TeX, 2 ps-figures; references adde

Pain, Parental Involvement, and Oxytocin in the Neonatal Intensive Care Unit

Preterm infants (PTI) typically experience many painful and stressful procedures or events during their first weeks of life in a neonatal intensive care unit, and these can profoundly impact subsequent brain development and function. Several protective interventions during this sensitive period stimulate the oxytocin system, reduce pain and stress, and improve brain development. This review provides an overview of the environmental risk factors experienced by PTI during hospitalization, with a focus on the effects of pain, and early maternal separation. We also describe the long-term adverse effects of the simultaneous experiences of pain and maternal separation, and the potential beneficial effects of maternal vocalizations, parental contact, and several related processes, which appear to be mediated by the oxytocin system