A Conversation about Healthy Eating

What constitutes a healthy diet? Mainstream media and advertisers would like you to think that the answer to this question is complicated and controversial. But science, fortunately, tells us otherwise. A Conversation about Healthy Eating brings together all the relevant science about healthy eating in one place, and it’s exactly that – a conversation; an informal discussion between a scientist and a friend about their eating habits, keeping the science firmly rooted in everyday life. The conversation moves from topics such as metabolism and digestion to gut bacteria, hormones, neuroscience and the immune system. All of these concepts are explained in accessible terms to help you understand the roles they play in maintaining a healthy diet. The conversation leads to the conclusion that staying lean and healthy simply requires avoiding the overconsumption of processed foods. While this is, of course, easier said than done, science also provides clear recommendations for how you can adapt your environment and lifestyle to make it possible. Rather than simply presenting you with the principles of healthy eating, this book will help you to develop a comprehensive understanding of the science behind the principles, including the evolutionary facts that affect the way we eat today. This understanding will allow you to ignore the noise in the media and to move forward with a healthy lifestyle that work for you

Harnessing the power of artificial intelligence to transform hearing healthcare and research

The advances in artificial intelligence that are transforming many fields have yet to make an impact in hearing. Hearing healthcare continues to rely on a labour-intensive service model that fails to provide access to the majority of those in need, while hearing research suffers from a lack of computational tools with the capacity to match the complexities of auditory processing. This Perspective is a call for the artificial intelligence and hearing communities to come together to bring about a technological revolution in hearing. We describe opportunities for rapid clinical impact through the application of existing technologies and propose directions for the development of new technologies to create true artificial auditory systems. There is an urgent need to push hearing towards a future in which artificial intelligence provides critical support for the testing of hypotheses, the development of therapies and the effective delivery of care worldwide

Estimating Receptive Fields from Responses to Natural Stimuli with Asymmetric Intensity Distributions

The reasons for using natural stimuli to study sensory function are quickly mounting, as recent studies have revealed important differences in neural responses to natural and artificial stimuli. However, natural stimuli typically contain strong correlations and are spherically asymmetric (i.e. stimulus intensities are not symmetrically distributed around the mean), and these statistical complexities can bias receptive field (RF) estimates when standard techniques such as spike-triggered averaging or reverse correlation are used. While a number of approaches have been developed to explicitly correct the bias due to stimulus correlations, there is no complementary technique to correct the bias due to stimulus asymmetries. Here, we develop a method for RF estimation that corrects reverse correlation RF estimates for the spherical asymmetries present in natural stimuli. Using simulated neural responses, we demonstrate how stimulus asymmetries can bias reverse-correlation RF estimates (even for uncorrelated stimuli) and illustrate how this bias can be removed by explicit correction. We demonstrate the utility of the asymmetry correction method under experimental conditions by estimating RFs from the responses of retinal ganglion cells to natural stimuli and using these RFs to predict responses to novel stimuli

Divisive Gain Modulation with Dynamic Stimuli in Integrate-and-Fire Neurons

The modulation of the sensitivity, or gain, of neural responses to input is an important component of neural computation. It has been shown that divisive gain modulation of neural responses can result from a stochastic shunting from balanced (mixed excitation and inhibition) background activity. This gain control scheme was developed and explored with static inputs, where the membrane and spike train statistics were stationary in time. However, input statistics, such as the firing rates of pre-synaptic neurons, are often dynamic, varying on timescales comparable to typical membrane time constants. Using a population density approach for integrate-and-fire neurons with dynamic and temporally rich inputs, we find that the same fluctuation-induced divisive gain modulation is operative for dynamic inputs driving nonequilibrium responses. Moreover, the degree of divisive scaling of the dynamic response is quantitatively the same as the steady-state responses—thus, gain modulation via balanced conductance fluctuations generalizes in a straight-forward way to a dynamic setting

Are beavers a solution to the freshwater biodiversity crisis?

Aim To determine whether reintroduced beavers, as an example of native herbivorous megafauna, can increase freshwater biodiversity at the landscape scale and to compare effects on two contrasting taxonomic groups. Location South‐central Sweden. Methods We collected data on plant and water beetle composition and supporting environmental variables from 20 closely located wetlands, half created from the damming of streams by beavers—beaver ponds (BP), and half by other, mainly natural (e.g. topographic, river migration) means—other wetlands (OW). Differences in species composition and plant growth strategy (i.e. competitor, stress tolerator or ruderal) between wetland types were assessed using multivariate analyses. Results The species pool of both taxonomic groups was higher in BP than OW (plants + 17%; beetles + 15%). For both groups, the number of species unique to BP was 50% higher than those unique to OW. Plant and beetle compositions differed significantly between wetlands, most strongly for plants, while rarity scores showed no difference, and the incidence of invasive species was negligible. Plant composition was mostly influenced by open water, bare ground and woody debris in BP, and plant cover, height and leaf litter in OW. This was consistent with the characterization of BP vegetation by ruderal plants and OW by competitors and stress tolerators. A significant residual effect of wetland type on plant, but not beetle composition, suggests that beavers exert important direct effects on some biota (e.g. via herbivory) independent of the indirect effects they exert via environmental change. Main conclusions Beaver‐created ponds support novel biodiversity that is not merely a subset of that found elsewhere in the same landscape. As such, re‐establishing beaver populations where they are native should benefit freshwater biodiversity, but effects may be context and taxon specific. Beavers alone cannot solve the freshwater biodiversity crisis, but recognizing the widespread importance of herbivorous megafauna in maintaining heterogeneity and creating novel habitat will be a positive step

Frequency-Invariant Representation of Interaural Time Differences in Mammals

Interaural time differences (ITDs) are the major cue for localizing low-frequency sounds. The activity of neuronal populations in the brainstem encodes ITDs with an exquisite temporal acuity of about . The response of single neurons, however, also changes with other stimulus properties like the spectral composition of sound. The influence of stimulus frequency is very different across neurons and thus it is unclear how ITDs are encoded independently of stimulus frequency by populations of neurons. Here we fitted a statistical model to single-cell rate responses of the dorsal nucleus of the lateral lemniscus. The model was used to evaluate the impact of single-cell response characteristics on the frequency-invariant mutual information between rate response and ITD. We found a rough correspondence between the measured cell characteristics and those predicted by computing mutual information. Furthermore, we studied two readout mechanisms, a linear classifier and a two-channel rate difference decoder. The latter turned out to be better suited to decode the population patterns obtained from the fitted model

Encoding of Naturalistic Stimuli by Local Field Potential Spectra in Networks of Excitatory and Inhibitory Neurons

Recordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely unknown. To understand the rules of translation between the structure of sensory stimuli and the fluctuations of cortical responses, we simulated a sparsely connected network of excitatory and inhibitory neurons modeling a local cortical population, and we determined how the LFPs generated by the network encode information about input stimuli. We first considered simple static and periodic stimuli and then naturalistic input stimuli based on electrophysiological recordings from the thalamus of anesthetized monkeys watching natural movie scenes. We found that the simulated network produced stimulus-related LFP changes that were in striking agreement with the LFPs obtained from the primary visual cortex. Moreover, our results demonstrate that the network encoded static input spike rates into gamma-range oscillations generated by inhibitory–excitatory neural interactions and encoded slow dynamic features of the input into slow LFP fluctuations mediated by stimulus–neural interactions. The model cortical network processed dynamic stimuli with naturalistic temporal structure by using low and high response frequencies as independent communication channels, again in agreement with recent reports from visual cortex responses to naturalistic movies. One potential function of this frequency decomposition into independent information channels operated by the cortical network may be that of enhancing the capacity of the cortical column to encode our complex sensory environment

Identifying predictors of translocation success in rare plant species

The fundamental goal of a rare plant translocation is to create self-sustaining populations with the evolutionary resilience to persist in the long term. Yet, most plant translocation syntheses focus on a few factors influencing short-term benchmarks of success (e.g., survival and reproduction). Short-term benchmarks can be misleading when trying to infer future growth and viability because the factors that promote establishment may differ from those required for long-term persistence. We assembled a large (n = 275) and broadly representative data set of well-documented and monitored (7.9 years on average) at-risk plant translocations to identify the most important site attributes, management techniques, and species' traits for six life-cycle benchmarks and population metrics of translocation success. We used the random forest algorithm to quantify the relative importance of 29 predictor variables for each metric of success. Drivers of translocation outcomes varied across time frames and success metrics. Management techniques had the greatest relative influence on the attainment of life-cycle benchmarks and short-term population trends, whereas site attributes and species' traits were more important for population persistence and long-term trends. Specifically, large founder sizes increased the potential for reproduction and recruitment into the next generation, whereas declining habitat quality and the outplanting of species with low seed production led to increased extinction risks and a reduction in potential reproductive output in the long-term, respectively. We also detected novel interactions between some of the most important drivers, such as an increased probability of next-generation recruitment in species with greater seed production rates, but only when coupled with large founder sizes. Because most significant barriers to plant translocation success can be overcome by improving techniques or resolving site-level issues through early intervention and management, we suggest that by combining long-term monitoring with adaptive management, translocation programs can enhance the prospects of achieving long-term success

Temporal and spatial instability in neutral and adaptive (MHC) genetic variation in marginal salmon populations

The role of marginal populations for the long-term maintenance of species’ genetic diversity and evolutionary potential is particularly timely in view of the range shifts caused by climate change. The Centre-Periphery hypothesis predicts that marginal populations should bear reduced genetic diversity and have low evolutionary potential. We analysed temporal stability at neutral microsatellite and adaptive MHC genetic variation over five decades in four marginal Atlantic salmon populations located at the southern limit of the species’ distribution with a complicated demographic history, which includes stocking with foreign and native salmon for at least 2 decades. We found a temporal increase in neutral genetic variation, as well as temporal instability in population structuring, highlighting the importance of temporal analyses in studies that examine the genetic diversity of peripheral populations at the margins of the species’ range, particularly in face of climate change

Beyond climate envelopes: effects of weather on regional population trends in butterflies

Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change