Information transmission in oscillatory neural activity

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.Comment: 18 pages, 8 figures, to appear in Biological Cybernetic

Can computational efficiency alone drive the evolution of modularity in neural networks?

Some biologists have abandoned the idea that computational efficiency in processing multipart tasks or input sets alone drives the evolution of modularity in biological networks. A recent study confirmed that small modular (neural) networks are relatively computationally-inefficient but large modular networks are slightly more efficient than non-modular ones. The present study determines whether these efficiency advantages with network size can drive the evolution of modularity in networks whose connective architecture can evolve. The answer is no, but the reason why is interesting. All simulations (run in a wide variety of parameter states) involving gradualistic connective evolution end in non-modular local attractors. Thus while a high performance modular attractor exists, such regions cannot be reached by gradualistic evolution. Non-gradualistic evolutionary simulations in which multi-modularity is obtained through duplication of existing architecture appear viable. Fundamentally, this study indicates that computational efficiency alone does not drive the evolution of modularity, even in large biological networks, but it may still be a viable mechanism when networks evolve by non-gradualistic means

Quantifying variation in the ability of yeasts to attract Drosophila melanogaster

Yeasts that invade and colonise fruit significantly enhance the volatile chemical diversity of this ecosystem. These modified bouquets are thought to be more attractive to Drosophila flies than the fruit alone, but the variance of attraction in natural yeast populations is uncharacterised. Here we investigate how a range of yeast isolates affect the attraction of female D. melanogaster to fruit in a simple two choice assay comparing yeast to sterile fruit. Of the 43 yeast isolates examined, 33 were attractive and seven repellent to the flies. The results of isolate-versus-isolate comparisons provided the same relative rankings. Attractiveness varied significantly by yeast, with the strongly fermenting Saccharomyces species generally being more attractive than the mostly respiring non-Saccharomyces species (P = 0.0035). Overall the habitat (fruit or other) from which the isolates were directly sampled did not explain attraction (P = 0.2352). However, yeasts isolated from fruit associated niches were more attractive than those from non-fruit associated niches (P = 0.0188) regardless of taxonomic positioning. These data suggest that while attractiveness is primarily correlated with phylogenetic status, the ability to attract Drosophila is a labile trait among yeasts that is potentially associated with those inhabiting fruit ecosystems. Preliminary analysis of the volatiles emitted by four yeast isolates in grape juice show the presence/absence of ethanol and acetic acid were not likely explanations for the observed variation in attraction. These data demonstrate variation among yeasts for their ability to attract Drosophila in a pattern that is consistent with the hypothesis that certain yeasts are manipulating fruit odours to mediate interactions with their Drosophila dispersal agent. © 2013 Palanca et al

Estimates of adherence and error analysis of physical activity data collected via accelerometry in a large study of free-living adults

<p>Abstract</p> <p>Background</p> <p>Activity monitors (AM) are small, electronic devices used to quantify the amount and intensity of physical activity (PA). Unfortunately, it has been demonstrated that data loss that occurs when AMs are not worn by subjects (removals during sleeping and waking hours) tend to result in biased estimates of PA and total energy expenditure (TEE). No study has reported the degree of data loss in a large study of adults, and/or the degree to which the estimates of PA and TEE are affected. Also, no study in adults has proposed a methodology to minimize the effects of AM removals.</p> <p>Methods</p> <p>Adherence estimates were generated from a pool of 524 women and men that wore AMs for 13 – 15 consecutive days. To simulate the effect of data loss due to AM removal, a reference dataset was first compiled from a subset consisting of 35 highly adherent subjects (24 HR; minimum of 20 hrs/day for seven consecutive days). AM removals were then simulated during sleep and between one and ten waking hours using this 24 HR dataset. Differences in the mean values for PA and TEE between the 24 HR reference dataset and the different simulations were compared using paired <it>t</it>-tests and/or coefficients of variation.</p> <p>Results</p> <p>The estimated average adherence of the pool of 524 subjects was 15.8 ± 3.4 hrs/day for approximately 11.7 ± 2.0 days. Simulated data loss due to AM removals during sleeping hours in the 24 HR database (n = 35), resulted in biased estimates of PA (p < 0.05), but not TEE. Losing as little as one hour of data from the 24 HR dataset during waking hours results in significant biases (p < 0.0001) and variability (coefficients of variation between 7 and 21%) in the estimates of PA. Inserting a constant value for sleep and imputing estimates for missing data during waking hours significantly improved the estimates of PA.</p> <p>Conclusion</p> <p>Although estimated adherence was good, measurements of PA can be improved by relatively simple imputation of missing AM data.</p

The Drosophila neural lineages: a model system to study brain development and circuitry

In Drosophila, neurons of the central nervous system are grouped into units called lineages. Each lineage contains cells derived from a single neuroblast. Due to its clonal nature, the Drosophila brain is a valuable model system to study neuron development and circuit formation. To better understand the mechanisms underlying brain development, genetic manipulation tools can be utilized within lineages to visualize, knock down, or over-express proteins. Here, we will introduce the formation and development of lineages, discuss how one can utilize this model system, offer a comprehensive list of known lineages and their respective markers, and then briefly review studies that have utilized Drosophila neural lineages with a look at how this model system can benefit future endeavors

Unc-51/ATG1 Controls Axonal and Dendritic Development via Kinesin-Mediated Vesicle Transport in the Drosophila Brain

Background:Members of the evolutionary conserved Ser/Thr kinase Unc-51 family are key regulatory proteins that control neural development in both vertebrates and invertebrates. Previous studies have suggested diverse functions for the Unc-51 protein, including axonal elongation, growth cone guidance, and synaptic vesicle transport.Methodology/Principal Findings:In this work, we have investigated the functional significance of Unc-51-mediated vesicle transport in the development of complex brain structures in Drosophila. We show that Unc-51 preferentially accumulates in newly elongating axons of the mushroom body, a center of olfactory learning in flies. Mutations in unc-51 cause disintegration of the core of the developing mushroom body, with mislocalization of Fasciclin II (Fas II), an IgG-family cell adhesion molecule important for axonal guidance and fasciculation. In unc-51 mutants, Fas II accumulates in the cell bodies, calyx, and the proximal peduncle. Furthermore, we show that mutations in unc-51 cause aberrant overshooting of dendrites in the mushroom body and the antennal lobe. Loss of unc-51 function leads to marked accumulation of Rab5 and Golgi components, whereas the localization of dendrite-specific proteins, such as Down syndrome cell adhesion molecule (DSCAM) and No distributive disjunction (Nod), remains unaltered. Genetic analyses of kinesin light chain (Klc) and unc-51 double heterozygotes suggest the importance of kinesin-mediated membrane transport for axonal and dendritic development. Moreover, our data demonstrate that loss of Klc activity causes similar axonal and dendritic defects in mushroom body neurons, recapitulating the salient feature of the developmental abnormalities caused by unc-51 mutations.Conclusions/Significance:Unc-51 plays pivotal roles in the axonal and dendritic development of the Drosophila brain. Unc-51-mediated membrane vesicle transport is important in targeted localization of guidance molecules and organelles that regulate elongation and compartmentalization of developing neurons

Carbone des sols en Afrique

Les sols sont une ressource essentielle à préserver pour la production d’aliments, de fibres, de biomasse, pour la filtration de l’eau, la préservation de la biodiversité et le stockage du carbone. En tant que réservoirs de carbone, les sols sont par ailleurs appelés à jouer un rôle primordial dans la lutte contre l’augmentation de la concentration de gaz à effet de serre. Ils sont ainsi au centre des objectifs de développement durable (ODD) des Nations unies, notamment les ODD 2 « Faim zéro », 13 « Lutte contre le changement climatique », 15 « Vie terrestre », 12 « Consommation et production responsables » ou encore 1 « Pas de pauvreté ». Cet ouvrage présente un état des lieux des sols africains dans toute leur diversité, mais au-delà, il documente les capacités de stockage de carbone selon les types de sols et leurs usages en Afrique. Il propose également des recommandations autour de l’acquisition et de l’interprétation des données, ainsi que des options pour préserver, voire augmenter les stocks de carbone dans les sols. Tous les chercheurs et acteurs du développement impliqués dans les recherches sur le rôle du carbone des sols sont concernés par cette synthèse collective. Fruit d’une collaboration entre chercheurs africains et européens, ce livre insiste sur la nécessité de prendre en compte la grande variété des contextes agricoles et forestiers africains pour améliorer nos connaissances sur les capacités de stockage de carbone des sols et lutter contre le changement climatique