An integrated brain-behavior model for working memory.

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Female preference for blue in Japan blue guppies (Poecilia reticulata)

Guppies (Poecilia reticulata) are widely used as a model species in mate choice studies. Although native to South America, guppies have been introduced to natural water bodies in disparate regions of the globe. Here, for the first time, we examine guppies from one such introduced population in Japan where males have evolved a predominantly blue color pattern. Previous studies of wild-type guppies have shown blue to play a relatively minor role in the mate choice decisions of females compared to other traits, such as orange, and the importance of blue is not universally supported by all studies. The Japanese population therefore presents an ideal opportunity to re-examine the potential significance of blue as a mate choice cue in guppies. Mate choice experiments, in which female Japan blue guppies were given a choice between pairs of males that differed in their area of blue coloration but were matched for other traits, revealed that females prefer males with proportionately larger amounts of blue in their color patterns. We discuss possible factors, including sexual and ecological selection, which may have led to the evolution of unusually large areas of blue at the expense of other colors in Japan blue guppies. However, further studies are needed to distinguish between these scenarios.Web of Scienc

The comparative osmoregulatory ability of two water beetle genera whose species span the fresh-hypersaline gradient in inland waters (Coleoptera: Dytiscidae, Hydrophilidae).

A better knowledge of the physiological basis of salinity tolerance is essential to understanding the ecology and evolutionary history of organisms that have colonized inland saline waters. Coleoptera are amongst the most diverse macroinvertebrates in inland waters, including saline habitats; however, the osmoregulatory strategies they employ to deal with osmotic stress remain unexplored. Survival and haemolymph osmotic concentration at different salinities were examined in adults of eight aquatic beetle species which inhabit different parts of the fresh-hypersaline gradient. Studied species belong to two unrelated genera which have invaded saline waters independently from freshwater ancestors; Nebrioporus (Dytiscidae) and Enochrus (Hydrophilidae). Their osmoregulatory strategy (osmoconformity or osmoregulation) was identified and osmotic capacity (the osmotic gradient between the animal's haemolymph and the external medium) was compared between species pairs co-habiting similar salinities in nature. We show that osmoregulatory capacity, rather than osmoconformity, has evolved independently in these different lineages. All species hyperegulated their haemolymph osmotic concentration in diluted waters; those living in fresh or low-salinity waters were unable to hyporegulate and survive in hyperosmotic media (> 340 mosmol kg(-1)). In contrast, the species which inhabit the hypo-hypersaline habitats were effective hyporegulators, maintaining their haemolymph osmolality within narrow limits (ca. 300 mosmol kg(-1)) across a wide range of external concentrations. The hypersaline species N. ceresyi and E. jesusarribasi tolerated conductivities up to 140 and 180 mS cm(-1), respectively, and maintained osmotic gradients over 3500 mosmol kg(-1), comparable to those of the most effective insect osmoregulators known to date. Syntopic species of both genera showed similar osmotic capacities and in general, osmotic responses correlated well with upper salinity levels occupied by individual species in nature. Therefore, osmoregulatory capacity may mediate habitat segregation amongst congeners across the salinity gradient

Quantifying Variability of Avian Colours: Are Signalling Traits More Variable?

Background Increased variability in sexually selected ornaments, a key assumption of evolutionary theory, is thought to be maintained through condition-dependence. Condition-dependent handicap models of sexual selection predict that (a) sexually selected traits show amplified variability compared to equivalent non-sexually selected traits, and since males are usually the sexually selected sex, that (b) males are more variable than females, and (c) sexually dimorphic traits more variable than monomorphic ones. So far these predictions have only been tested for metric traits. Surprisingly, they have not been examined for bright coloration, one of the most prominent sexual traits. This omission stems from computational difficulties: different types of colours are quantified on different scales precluding the use of coefficients of variation. Methodology/Principal Findings Based on physiological models of avian colour vision we develop an index to quantify the degree of discriminable colour variation as it can be perceived by conspecifics. A comparison of variability in ornamental and non-ornamental colours in six bird species confirmed (a) that those coloured patches that are sexually selected or act as indicators of quality show increased chromatic variability. However, we found no support for (b) that males generally show higher levels of variability than females, or (c) that sexual dichromatism per se is associated with increased variability. Conclusions/Significance We show that it is currently possible to realistically estimate variability of animal colours as perceived by them, something difficult to achieve with other traits. Increased variability of known sexually-selected/quality-indicating colours in the studied species, provides support to the predictions borne from sexual selection theory but the lack of increased overall variability in males or dimorphic colours in general indicates that sexual differences might not always be shaped by similar selective forces

Geographic variation in breeding system and environment predicts melanin-based plumage ornamentation of male and female Kentish plovers

Sexual selection determines the elaboration of morphological and behavioural traits and thus drives the evolution of phenotypes. Sexual selection on males and females can differ between populations, especially when populations exhibit different breeding systems. A substantial body of literature describes how breeding systems shape ornamentation across species, with a strong emphasis on male ornamentation and female preference. However, whether breeding system predicts ornamentation within species and whether similar mechanisms as in males also shape the phenotype of females remains unclear. Here, we investigate how different breeding systems are associated with male and female ornamentation in five geographically distinct populations of Kentish plovers Charadrius alexandrinus. We predicted that polygamous populations would exhibit more elaborate ornaments and stronger sexual dimorphism than monogamous populations. By estimating the size and intensity of male (n = 162) and female (n = 174) melanin-based plumage ornaments, i.e. breast bands and ear coverts, we show that plumage ornamentation is predicted by breeding system in both sexes. A difference in especially male ornamentation between polygamous (darker and smaller ornaments) and monogamous (lighter and larger) populations causes the greatest sexual dimorphism to be associated with polygamy. The non-social environment, however, may also influence the degree of ornamentation, for instance through availability of food. We found that, in addition to breeding system, a key environmental parameter, rainfall, predicted a seasonal change of ornamentation in a sex-specific manner. Our results emphasise that to understand the phenotype of animals, it is important to consider both natural and sexual selection acting on both males and females

Probabilistic machine learning and artificial intelligence.

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

Chemical PARP Inhibition Enhances Growth of Arabidopsis and Reduces Anthocyanin Accumulation and the Activation of Stress Protective Mechanisms

Poly-ADP-ribose polymerase (PARP) post-translationally modifies proteins through the addition of ADP-ribose polymers, yet its role in modulating plant development and stress responses is only poorly understood. The experiments presented here address some of the gaps in our understanding of its role in stress tolerance and thereby provide new insights into tolerance mechanisms and growth. Using a combination of chemical and genetic approaches, this study characterized phenotypes associated with PARP inhibition at the physiological level. Molecular analyses including gene expression analysis, measurement of primary metabolites and redox metabolites were used to understand the underlying processes. The analysis revealed that PARP inhibition represses anthocyanin and ascorbate accumulation under stress conditions. The reduction in defense is correlated with enhanced biomass production. Even in unstressed conditions protective genes and molecules are repressed by PARP inhibition. The reduced anthocyanin production was shown to be based on the repression of transcription of key regulatory and biosynthesis genes. PARP is a key factor for understanding growth and stress responses of plants. PARP inhibition allows plants to reduce protection such as anthocyanin, ascorbate or Non-Photochemical-Quenching whilst maintaining high energy levels likely enabling the observed enhancement of biomass production under stress, opening interesting perspectives for increasing crop productivity

Evidence for a Fourteenth mtDNA-Encoded Protein in the Female-Transmitted mtDNA of Marine Mussels (Bivalvia: Mytilidae)

BACKGROUND: A novel feature for animal mitochondrial genomes has been recently established: i.e., the presence of additional, lineage-specific, mtDNA-encoded proteins with functional significance. This feature has been observed in freshwater mussels with doubly uniparental inheritance of mtDNA (DUI). The latter unique system of mtDNA transmission, which also exists in some marine mussels and marine clams, is characterized by one mt genome inherited from the female parent (F mtDNA) and one mt genome inherited from the male parent (M mtDNA). In freshwater mussels, the novel mtDNA-encoded proteins have been shown to be mt genome-specific (i.e., one novel protein for F genomes and one novel protein for M genomes). It has been hypothesized that these novel, F- and M-specific, mtDNA-encoded proteins (and/or other F- and/or M-specific mtDNA sequences) could be responsible for the different modes of mtDNA transmission in bivalves but this remains to be demonstrated. METHODOLOGY/PRINCIPAL FINDINGS: We investigated all complete (or nearly complete) female- and male-transmitted marine mussel mtDNAs previously sequenced for the presence of ORFs that could have functional importance in these bivalves. Our results confirm the presence of a novel F genome-specific mt ORF, of significant length (>100aa) and located in the control region, that most likely has functional significance in marine mussels. The identification of this ORF in five Mytilus species suggests that it has been maintained in the mytilid lineage (subfamily Mytilinae) for ∼13 million years. Furthermore, this ORF likely has a homologue in the F mt genome of Musculista senhousia, a DUI-containing mytilid species in the subfamily Crenellinae. We present evidence supporting the functionality of this F-specific ORF at the transcriptional, amino acid and nucleotide levels. CONCLUSIONS/SIGNIFICANCE: Our results offer support for the hypothesis that "novel F genome-specific mitochondrial genes" are involved in key biological functions in bivalve species with DUI

Multichannel Online Blind Speech Dereverberation with Marginalization of Static Observation Parameters in a Rao-Blackwellized Particle Filter

Room reverberation leads to reduced intelligibility of audio signals and spectral coloration of audio signals. Enhancement of acoustic signals is thus crucial for high-quality audio and scene analysis applications. Multiple sensors can be used to exploit statistical evidence from multiple observations of the same event to improve enhancement. Whilst traditional beamforming techniques suffer from interfering reverberant reflections with the beam path, other approaches to dereverberation often require at least partial knowledge of the room impulse response which is not available in practice, or rely on inverse filtering of a channel estimate to obtain a clean speech estimate, resulting in difficulties with non-minimum phase acoustic impulse responses. This paper proposes a multi-sensor approach to blind dereverberation in which both the source signal and acoustic channel are directly estimated from the distorted observations using their optimal estimators. The remaining model parameters are sampled from hypothesis distributions using a particle filter, thus facilitating real-time dereverberation. This approach was previously successfully applied to single-sensor blind dereverberation. In this paper, the single-channel approach is extended to multiple sensors. Performance improvements due to the use of multiple sensors are demonstrated on synthetic and baseband speech examples