On directed information theory and Granger causality graphs

Directed information theory deals with communication channels with feedback. When applied to networks, a natural extension based on causal conditioning is needed. We show here that measures built from directed information theory in networks can be used to assess Granger causality graphs of stochastic processes. We show that directed information theory includes measures such as the transfer entropy, and that it is the adequate information theoretic framework needed for neuroscience applications, such as connectivity inference problems.Comment: accepted for publications, Journal of Computational Neuroscienc

Contribution of Each Leg to the Control of Unperturbed Bipedal Stance in Lower Limb Amputees: New Insights Using Entropy

The present study was designed to assess the relative contribution of each leg to unperturbed bipedal posture in lower limb amputees. To achieve this goal, eight unilateral traumatic trans-femoral amputees (TFA) were asked to stand as still as possible on a plantar pressure data acquisition system with their eyes closed. Four dependent variables were computed to describe the subject's postural behavior: (1) body weight distribution, (2) amplitude, (3) velocity and (4) regularity of centre of foot pressure (CoP) trajectories under the amputated (A) leg and the non-amputated (NA) leg. Results showed a larger body weight distribution applied to the NA leg than to the A leg and a more regular CoP profiles (lower sample entropy values) with greater amplitude and velocity under the NA leg than under the A leg. Taken together, these findings suggest that the NA leg and the A leg do not equally contribute to the control of unperturbed bipedal posture in TFA. The observation that TFA do actively control unperturbed bipedal posture with their NA leg could be viewed as an adaptive process to the loss of the lower leg afferents and efferents because of the unilateral lower-limb amputation. From a methodological point of view, these results demonstrate the suitability of computing bilateral CoP trajectories regularity for the assessment of lateralized postural control under pathological conditions

Transfer entropy—a model-free measure of effective connectivity for the neurosciences

Understanding causal relationships, or effective connectivity, between parts of the brain is of utmost importance because a large part of the brain’s activity is thought to be internally generated and, hence, quantifying stimulus response relationships alone does not fully describe brain dynamics. Past efforts to determine effective connectivity mostly relied on model based approaches such as Granger causality or dynamic causal modeling. Transfer entropy (TE) is an alternative measure of effective connectivity based on information theory. TE does not require a model of the interaction and is inherently non-linear. We investigated the applicability of TE as a metric in a test for effective connectivity to electrophysiological data based on simulations and magnetoencephalography (MEG) recordings in a simple motor task. In particular, we demonstrate that TE improved the detectability of effective connectivity for non-linear interactions, and for sensor level MEG signals where linear methods are hampered by signal-cross-talk due to volume conduction

Symbolic Dynamic Analysis of Relations Between Cardiac and Breathing Cycles in Patients on Weaning Trials

Traditional time-domain techniques of data analysis are often not sufficient to characterize the complex dynamics of the cardiorespiratory interdependencies during the weaning trials. In this paper, the interactions between the heart rate (HR) and the breathing rate (BR) were studied using joint symbolic dynamic analysis. A total of 133 patients on weaning trials from mechanical ventilation were analyzed: 94 patients with successful weaning (group S) and 39 patients that failed to maintain spontaneous breathing (group F). The word distribution matrix enabled a coarse-grained quantitative assessment of short-term nonlinear analysis of the cardiorespiratory interactions. The histogram of the occurrence probability of the cardiorespiratory words presented a higher homogeneity in group F than in group S, measured with a higher number of forbidden words in group S as well as a higher number of words whose probability of occurrence is higher than a probability threshold in group S. The discriminant analysis revealed the best results when applying symbolic dynamic variables. Therefore, we hypothesize that joint symbolic dynamic analysis provides enhanced information about different interactions between HR and BR, when comparing patients with successful weaning and patients that failed to maintain spontaneous breathing in the weaning procedure

Catalyzing Transcriptomics Research in Cardiovascular Disease : The CardioRNA COST Action CA17129

Cardiovascular disease (CVD) remains the leading cause of death worldwide and, despite continuous advances, better diagnostic and prognostic tools, as well as therapy, are needed. The human transcriptome, which is the set of all RNA produced in a cell, is much more complex than previously thought and the lack of dialogue between researchers and industrials and consensus on guidelines to generate data make it harder to compare and reproduce results. This European Cooperation in Science and Technology (COST) Action aims to accelerate the understanding of transcriptomics in CVD and further the translation of experimental data into usable applications to improve personalized medicine in this field by creating an interdisciplinary network. It aims to provide opportunities for collaboration between stakeholders from complementary backgrounds, allowing the functions of different RNAs and their interactions to be more rapidly deciphered in the cardiovascular context for translation into the clinic, thus fostering personalized medicine and meeting a current public health challenge. Thus, this Action will advance studies on cardiovascular transcriptomics, generate innovative projects, and consolidate the leadership of European research groups in the field.COST (European Cooperation in Science and Technology) is a funding organization for research and innovation networks (www.cost.eu)

Effects of different lower-limb sensory stimulation strategies on postural regulation – A systematic review and meta-analysis

Systematic reviews of balance control have tended to only focus on the effects of single lower-limb stimulation strategies, and a current limitation is the lack of comparison between different relevant stimulation strategies. The aim of this systematic review and meta-analysis was to examine evidence of effects of different lower-limb sensory stimulation strategies on postural regulation and stability. Moderate- to high- pooled effect sizes (Unbiased (Hedges’ g) standardized mean differences (SMD) = 0.31 – 0.66) were observed with the addition of noise in a Stochastic Resonance Stimulation Strategy (SRSS), in three populations (i.e., healthy young adults, older adults, and individuals with lower-limb injuries), and under different task constraints (i.e., unipedal, bipedal, and eyes open). A Textured Material Stimulation Strategy (TMSS) enhanced postural control in the most challenging condition – eyes-closed on a stable surface (SMD = 0.61), and in older adults (SMD = 0.30). The Wearable Garments Stimulation Strategy (WGSS) showed no or adverse effects (SMD = -0.68 – 0.05) under all task constraints and in all populations, except in individuals with lower-limb injuries (SMD = 0.20). Results of our systematic review and meta-analysis revealed that future research could consider combining two or more stimulation strategies in intervention treatments for postural regulation and balance problems, depending on individual need

G-protein-coupled receptor oligomers: two or more for what? Lessons from mGlu and GABAB receptors

G-protein-coupled receptors (GPCRs) are key players in the precise tuning of intercellullar communication. In the brain, both major neurotransmitters, glutamate and GABA, act on specific GPCRs [the metabotropic glutamate (mGlu) and GABAB receptors] to modulate synaptic transmission. These receptors are encoded by the largest gene family, and have been found to associate into both homo- and hetero-oligomers, which increases the complexity of this cell communication system. Here we show that dimerization is required for mGlu and GABAB receptors to function, since the activation process requires a relative movement between the subunits to occur. We will also show that, in contrast to the mGlu receptors, which form strict dimers, the GABAB receptors assemble into larger complexes, both in transfected cells and in the brain, resulting in a decreased G-protein coupling efficacy. We propose that GABAB receptor oligomerization offers a way to increase the possibility of modulating receptor signalling and activity, allowing the same receptor protein to have specific properties in neurons at different locations