The role of sleep in changing our minds: A psychologist's discussion of papers on memory reactivation and consolidation in sleep

The group of papers on memory reactivation and consolidation during sleep included in this volume represents cutting edge work in both animals and humans. They support that the two types of sleep serve different necessary functions. The role of slow wave sleep (SWS) is reactivation of the hippocampal-neocortical circuits activated during a waking learning period, while REM sleep is responsible for the consolidation of this new learning into long-term memory. These studies provide further insights into mechanisms involved in brain plasticity. Robeiro has demonstrated the upregulation of an immediate-early gene (IEG zif 268) to waking levels, which occurs only in REM and only in connection with new learning. McNaughton and his group have identified electrical indicators that the hippocampus and neocortex are talking to each other by testing the coactivation of hippocampal sharp wave bursts in SWS and shifts from down to up states of activation in the neocortex. In human studies Smith's group reports work on individual differences such as intelligence and presleep alcohol that affect postsleep performance, and Stickgold and collaborators report that a short nap will improve performance if it contains REM sleep. Payne and Nadel suggest that the recall benefit associated with REM sleep may be due to its association with increased cortisol levels. These papers are important not only in their individual contributions but also in revitalizing the work coordinating waking and sleep. This promises to further the understanding of how our unique capacity to learn from experience and modify our behavior takes place

Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling

International audienceEvidence is mounting that influenza virus interacts with other pathogens colonising or infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. This is particularly true for mathematical modelling studies, which have become critical in public health decision-making. Yet models usually focus on influenza virus acquisition and infection alone, thereby making broad oversimplifications of pathogen ecology. Herein, we report evidence of influenza virus interactions with bacteria and viruses and systematically review the modelling studies that have incorporated interactions. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitidis, respiratory syncytial virus (RSV), human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. The notable exception is the pneumococcus-influenza interaction, for which several recent modelling studies demonstrate the power of dynamic modelling as an approach to test biological hypotheses on interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and possible misinterpretation, and we illustrate the impact of interactions on public health surveillance using simple transmission models. We demonstrate that the development of multipathogen models is essential to assessing the true public health burden of influenza and that it is needed to help improve planning and evaluation of control measures. Finally, we identify the public health, surveillance, modelling, and biological challenges and propose avenues of research for the coming years