Sequence learning in Associative Neuronal-Astrocytic Network

The neuronal paradigm of studying the brain has left us with limitations in both our understanding of how neurons process information to achieve biological intelligence and how such knowledge may be translated into artificial intelligence and its most brain-derived branch, neuromorphic computing. Overturning our fundamental assumptions of how the brain works, the recent exploration of astrocytes is revealing that these long-neglected brain cells dynamically regulate learning by interacting with neuronal activity at the synaptic level. Following recent experimental evidence, we designed an associative, Hopfield-type, neuronal-astrocytic network and analyzed the dynamics of the interaction between neurons and astrocytes. We show that astrocytes were sufficient to trigger transitions between learned memories in the neuronal component of the network. Further, we mathematically derived the timing of the transitions that was governed by the dynamics of the calcium-dependent slow-currents in the astrocytic processes. Overall, we provide a brain-morphic mechanism for sequence learning that is inspired by, and aligns with, recent experimental findings. To evaluate our model, we emulated astrocytic atrophy and showed that memory recall becomes significantly impaired after a critical point of affected astrocytes was reached. This brain-inspired and brain-validated approach supports our ongoing efforts to incorporate non-neuronal computing elements in neuromorphic information processing.Comment: 8 pages, 5 figure

Bio-Inspired Multi-Layer Spiking Neural Network Extracts Discriminative Features from Speech Signals

Spiking neural networks (SNNs) enable power-efficient implementations due to their sparse, spike-based coding scheme. This paper develops a bio-inspired SNN that uses unsupervised learning to extract discriminative features from speech signals, which can subsequently be used in a classifier. The architecture consists of a spiking convolutional/pooling layer followed by a fully connected spiking layer for feature discovery. The convolutional layer of leaky, integrate-and-fire (LIF) neurons represents primary acoustic features. The fully connected layer is equipped with a probabilistic spike-timing-dependent plasticity learning rule. This layer represents the discriminative features through probabilistic, LIF neurons. To assess the discriminative power of the learned features, they are used in a hidden Markov model (HMM) for spoken digit recognition. The experimental results show performance above 96% that compares favorably with popular statistical feature extraction methods. Our results provide a novel demonstration of unsupervised feature acquisition in an SNN

Diffusion Tensor Imaging for Diagnosing Root Avulsions in Traumatic Adult Brachial Plexus Injuries: A Proof-of-Concept Study

Cross-sectional MRI has modest diagnostic accuracy for diagnosing traumatic brachial plexus root avulsions. Consequently, patients either undergo major exploratory surgery or months of surveillance to determine if and what nerve reconstruction is needed. This study aimed to develop a diffusion tensor imaging (DTI) protocol at 3 Tesla to visualize normal roots and identify traumatic root avulsions of the brachial plexus. Seven healthy adults and 12 adults with known (operatively explored) unilateral traumatic brachial plexus root avulsions were scanned. DTI was acquired using a single-shot echo-planar imaging sequence at 3 Tesla. The brachial plexus was visualized by deterministic tractography. Fractional anisotropy (FA) and mean diffusivity (MD) were calculated for injured and avulsed roots in the lateral recesses of the vertebral foramen. Compared to healthy nerves roots, the FA of avulsed nerve roots was lower (mean difference 0.1 [95% CI 0.07, 0.13]; p < 0.001) and the MD was greater (mean difference 0.32 × 10−3 mm2/s [95% CI 0.11, 0.53]; p < 0.001). Deterministic tractography reconstructed both normal roots and root avulsions of the brachial plexus; the negative-predictive value for at least one root avulsion was 100% (95% CI 78, 100). Therefore, DTI might help visualize both normal and injured roots of the brachial plexus aided by tractography. The precision of this technique and how it relates to neural microstructure will be further investigated in a prospective diagnostic accuracy study of patients with acute brachial plexus injuries

Secondary fluorescence in WDS:the role of spectrometer positioning

Secondary fluorescence, typically a minor error in routine electron probe microanalysis (EPMA), may not be negligible when performing high precision trace element analyses in multiphase samples. Other factors, notably wavelength dispersive spectrometer defocusing, may introduce analytical artefacts. To explore these issues, we measured EPMA transects across two material couples chosen for their high fluorescence yield. We measured transects away from the fluorescent phase, and at various orientations with respect to the spectrometer focal line. Compared to calculations using both the Monte Carlo simulation code PENEPMA and the semi-analytical model FANAL, both codes estimate the magnitude of SF, but accurate correction requires knowledge of the position of the spectrometer with respect to the couple interface. Positioned over the fluorescent phase or otherwise here results in a factor of 1.2-1.8 of apparent change in SF yield. SF and spectrometer defocusing may introduce systematic errors into trace element analyses, both may be adequately accounted for by modelling. Of the two, however, SF is the dominant error, resulting in 0.1 wt% Zn apparently present in Al at 100 m away from the Zn boundary in an Al/Zn couple. Of this, around 200 ppm Zn can be attributed to spectrometer defocusing.</p

Draft Whole-Genome Sequences of Periodontal Pathobionts Porphyromonas gingivalis, Prevotella intermedia, and Tannerella forsythia Contain Phase-Variable Restriction-Modification Systems.

Periodontal disease comprises mild to severe inflammatory host responses to oral bacteria that can cause destruction of the tooth-supporting tissue. We report genome sequences for 18 clinical isolates of Porphyromonas gingivalis, Prevotella intermedia, and Tannerella forsythia, Gram-negative obligate anaerobes that play a role in the periodontal disease process.This work was in part funded by a grant from the BBSRC (BB/N002903/1) to M.R.O

X-Ray Spectroscopy of Stars

(abridged) Non-degenerate stars of essentially all spectral classes are soft X-ray sources. Low-mass stars on the cooler part of the main sequence and their pre-main sequence predecessors define the dominant stellar population in the galaxy by number. Their X-ray spectra are reminiscent, in the broadest sense, of X-ray spectra from the solar corona. X-ray emission from cool stars is indeed ascribed to magnetically trapped hot gas analogous to the solar coronal plasma. Coronal structure, its thermal stratification and geometric extent can be interpreted based on various spectral diagnostics. New features have been identified in pre-main sequence stars; some of these may be related to accretion shocks on the stellar surface, fluorescence on circumstellar disks due to X-ray irradiation, or shock heating in stellar outflows. Massive, hot stars clearly dominate the interaction with the galactic interstellar medium: they are the main sources of ionizing radiation, mechanical energy and chemical enrichment in galaxies. High-energy emission permits to probe some of the most important processes at work in these stars, and put constraints on their most peculiar feature: the stellar wind. Here, we review recent advances in our understanding of cool and hot stars through the study of X-ray spectra, in particular high-resolution spectra now available from XMM-Newton and Chandra. We address issues related to coronal structure, flares, the composition of coronal plasma, X-ray production in accretion streams and outflows, X-rays from single OB-type stars, massive binaries, magnetic hot objects and evolved WR stars.Comment: accepted for Astron. Astrophys. Rev., 98 journal pages, 30 figures (partly multiple); some corrections made after proof stag

In Vitro Cultivation of 'Unculturable' Oral Bacteria, Facilitated by Community Culture and Media Supplementation with Siderophores

Over a third of oral bacteria are as-yet-uncultivated in-vitro. Siderophores have been previously shown to enable in-vitro growth of previously uncultivated bacteria. The objective of this study was to cultivate novel oral bacteria in siderophore-supplemented culture media. Various compounds with siderophore activity, including pyoverdines-Fe-complex, desferricoprogen and salicylic acid, were found to stimulate the growth of difficult-to-culture strains Prevotella sp. HOT-376 and Fretibacterium fastidiosum. Furthermore, pyrosequencing analysis demonstrated increased proportions of the as-yet-uncultivated phylotypes Dialister sp. HOT-119 and Megasphaera sp. HOT-123 on mixed culture plates supplemented with siderophores. Therefore a culture model was developed, which incorporated 15 μg siderophore (pyoverdines-Fe-complex or desferricoprogen) or 150 μl neat subgingival-plaque suspension into a central well on agar plates that were inoculated with heavily-diluted subgingival-plaque samples from subjects with periodontitis. Colonies showing satellitism were passaged onto fresh plates in co-culture with selected helper strains. Five novel strains, representatives of three previously-uncultivated taxa (Anaerolineae bacterium HOT-439, the first oral taxon from the Chloroflexi phylum to have been cultivated; Bacteroidetes bacterium HOT-365; and Peptostreptococcaceae bacterium HOT-091) were successfully isolated. All novel isolates required helper strains for growth, implying dependence on a biofilm lifestyle. Their characterisation will further our understanding of the human oral microbiome

Low Operating Voltage Carbon-Graphene Hybrid E-textile for Temperature Sensing

This is the final version. Available on open access from the American Chemical Society via the DOI in this recordGraphene-coated polypropylene (PP) textile fibers are presented for their use as temperature sensors. These temperature sensors show a negative thermal coefficient of resistance (TCR) in a range between 30 and 45 °C with good sensitivity and reliability and can operate at voltages as low as 1 V. The analysis of the transient response of the temperature on resistance of different types of graphene produced by chemical vapor deposition (CVD) and shear exfoliation of graphite (SEG) shows that trilayer graphene (TLG) grown on copper by CVD displays better sensitivity due to the better thickness uniformity of the film and that carbon paste provides good contact for the measurements. Along with high sensitivity, TLG on PP shows not only the best response but also better transparency, mechanical stability, and washability compared to SEG. Temperature-dependent Raman analysis reveals that the temperature has no significant effect on the peak frequency of PP and expected effect on graphene in the demonstrated temperature range. The presented results demonstrate that these flexible, lightweight temperature sensors based on TLG with a negative TCR can be easily integrated in fabrics.European CommissionEngineering and Physical Sciences Research Council (EPSRC)University of ExeterPortuguese Foundation for Science and Technolog

Luminance, colour, viewpoint and border enhanced disparity energy model

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas.Portuguese Foundation for Science and Technology (FCT); LARSyS FCT [UID/EEA/50009/2013]; EU project NeuroDynamics [FP7-ICT-2009-6, PN: 270247]; FCT project SparseCoding [EXPL/EEI-SII/1982/2013]; FCT PhD grant [SFRH-BD-44941-2008