Influence of antenatal physical exercise on haemodynamics in pregnant women: a flexible randomisation approach

Background: Normal pregnancy is associated with marked changes in haemodynamic function, however theinfluence and potential benefits of antenatal physical exercise at different stages of pregnancy and postpartumremain unclear. The aim of this study was therefore to characterise the influence of regular physical exercise onhaemodynamic variables at different stages of pregnancy and also in the postpartum period.Methods: Fifty healthy pregnant women were recruited and randomly assigned (2 × 2 × 2 design) to a land orwater-based exercise group or a control group. Exercising groups attended weekly classes from the 20th week ofpregnancy onwards. Haemodynamic assessments (heart rate, cardiac output, stroke volume, total peripheralresistance, systolic and diastolic blood pressure and end diastolic index) were performed using the Task Forcehaemodynamic monitor at 12–16, 26–28, 34–36 and 12 weeks following birth, during a protocol including posturalmanoeurvres (supine and standing) and light exercise.Results: In response to an acute bout of exercise in the postpartum period, stroke volume and end diastolic indexwere greater in the exercise group than the non-exercising control group (p = 0.041 and p = 0.028 respectively).Total peripheral resistance and diastolic blood pressure were also lower (p = 0.015 and p = 0.007, respectively) in theexercise group. Diastolic blood pressure was lower in the exercise group during the second trimester (p = 0.030).Conclusions: Antenatal exercise does not appear to substantially alter maternal physiology with advancinggestation, speculating that the already vast changes in maternal physiology mask the influences of antenatalexercise, however it does appear to result in an improvement in a woman’s haemodynamic function (enhancedventricular ejection performance and reduced blood pressure) following the end of pregnancy

Neural processing of natural sounds

Natural sounds include animal vocalizations, environmental sounds such as wind, water and fire noises and non-vocal sounds made by animals and humans for communication. These natural sounds have characteristic statistical properties that make them perceptually salient and that drive auditory neurons in optimal regimes for information transmission.Recent advances in statistics and computer sciences have allowed neuro-physiologists to extract the stimulus-response function of complex auditory neurons from responses to natural sounds. These studies have shown a hierarchical processing that leads to the neural detection of progressively more complex natural sound features and have demonstrated the importance of the acoustical and behavioral contexts for the neural responses.High-level auditory neurons have shown to be exquisitely selective for conspecific calls. This fine selectivity could play an important role for species recognition, for vocal learning in songbirds and, in the case of the bats, for the processing of the sounds used in echolocation. Research that investigates how communication sounds are categorized into behaviorally meaningful groups (e.g. call types in animals, words in human speech) remains in its infancy.Animals and humans also excel at separating communication sounds from each other and from background noise. Neurons that detect communication calls in noise have been found but the neural computations involved in sound source separation and natural auditory scene analysis remain overall poorly understood. Thus, future auditory research will have to focus not only on how natural sounds are processed by the auditory system but also on the computations that allow for this processing to occur in natural listening situations.The complexity of the computations needed in the natural hearing task might require a high-dimensional representation provided by ensemble of neurons and the use of natural sounds might be the best solution for understanding the ensemble neural code

Modularity induced gating and delays in neuronal networks

Abstract: Neural networks, despite their highly interconnected nature, exhibit distinctly localized and gated activation. Modularity, a distinctive feature of neural networks, has been recently proposed as an important parameter determining the manner by which networks support activity propagation. Here we use an engineered biological model, consisting of engineered rat cortical neurons, to study the role of modular topology in gating the activity between cell populations. We show that pairs of connected modules support conditional propagation (transmitting stronger bursts with higher probability), long delays and propagation asymmetry. Moreover, large modular networks manifest diverse patterns of both local and global activation. Blocking inhibition decreased activity diversity and replaced it with highly consistent transmission patterns. By independently controlling modularity and disinhibition, experimentally and in a model, we pose that modular topology is an important parameter affecting activation localization and is instrumental for population-level gating by disinhibition. Author Summary: The capacity to transmit information between connected parts of a neuronal network is fundamental to its function. The organization of network connections (the topology of the network) is therefore expected to play an important role in determining network transmission. Since modular topology characterizes many brain circuits on multiple scales, investigating the role of modularity in activity gating is clearly desirable. By engineering such modular networks in vitro, we were able to perform such an investigation. Under these experimental conditions, we can independently control the degree of modularity, as well as inhibition in the network. We show that a combination of these two properties is highly beneficial from a communication perspective. Namely, it equips connected modules and large modular networks with the capacity to gate and temporally coordinate activity between the different parts of the network