Odor-driven attractor dynamics in the antennal lobe allow for simple and rapid olfactory pattern classification

The antennal lobe plays a central role for odor processing in insects, as demonstrated by electrophysiological and imaging experiments. Here we analyze the detailed temporal evolution of glomerular activity patterns in the antennal lobe of honeybees. We represent these spatiotemporal patterns as trajectories in a multidimensional space, where each dimension accounts for the activity of one glomerulus. Our data show that the trajectories reach odor-specific steady states (attractors) that correspond to stable activity patterns at about 1 second after stimulus onset. As revealed by a detailed mathematical investigation, the trajectories are characterized by different phases: response onset, steady-state plateau, response offset, and periods of spontaneous activity. An analysis based on support-vector machines quantifies the odor specificity of the attractors and the optimal time needed for odor discrimination. The results support the hypothesis of a spatial olfactory code in the antennal lobe and suggest a perceptron-like readout mechanism that is biologically implemented in a downstream network, such as the mushroom body

Early forest fire detection by vision-enabled wireless sensor networks

Wireless sensor networks constitute a powerful technology particularly suitable for environmental monitoring. With regard to wildfires, they enable low-cost fine-grained surveillance of hazardous locations like wildland-urban interfaces. This paper presents work developed during the last 4 years targeting a vision-enabled wireless sensor network node for the reliable, early on-site detection of forest fires. The tasks carried out ranged from devising a robust vision algorithm for smoke detection to the design and physical implementation of a power-efficient smart imager tailored to the characteristics of such an algorithm. By integrating this smart imager with a commercial wireless platform, we endowed the resulting system with vision capabilities and radio communication. Numerous tests were arranged in different natural scenarios in order to progressively tune all the parameters involved in the autonomous operation of this prototype node. The last test carried out, involving the prescribed burning of a 95 x 20-m shrub plot, confirmed the high degree of reliability of our approach in terms of both successful early detection and a very low false-alarm rate. Journal compilationMinisterio de Ciencia e Innovación TEC2009-11812, IPT-2011-1625-430000Office of Naval Research (USA) N000141110312Centro para el Desarrollo Tecnológico e Industrial IPC-2011100

Sensory memory for odors is encoded in spontaneous correlated activity between olfactory glomeruli

Sensory memory is a short-lived persistence of a sensory stimulus in the nervous system, such as iconic memory in the visual system. However, little is known about the mechanisms underlying olfactory sensory memory. We have therefore analyzed the effect of odor stimuli on the first odor-processing network in the honeybee brain, the antennal lobe, which corresponds to the vertebrate olfactory bulb. We stained output neurons with a calcium-sensitive dye and measured across-glomerular patterns of spontaneous activity before and after a stimulus. Such a single-odor presentation changed the relative timing of spontaneous activity across glomeruli in accordance with Hebb's theory of learning. Moreover, during the first few minutes after odor presentation, correlations between the spontaneous activity fluctuations suffice to reconstruct the stimulus. As spontaneous activity is ubiquitous in the brain, modifiable fluctuations could provide an ideal substrate for Hebbian reverberations and sensory memory in other neural systems

Astrophysical parameters and orbital solution of the peculiar X-ray transient IGR J00370+6122

BD+6073 is the optical counterpart of the X-ray source IGR J00370+6122, a probable accretion-powered X-ray pulsar. The X-ray light curve of this binary system shows clear periodicity at 15.7 d, which has been interpreted as repeated outbursts around the periastron of an eccentric orbit. We obtained high-resolution spectra of BD+6073 at different epochs. We used the FASTWind code to generate a stellar atmosphere model to fit the observed spectrum and obtain physical magnitudes. The synthetic spectrum was used as a template for cross-correlation with the observed spectra to measure radial velocities. The radial velocity curve provided an orbital solution for the system. We have also analysed the RXTE/ASM and Swift/BAT light curves to confirm the stability of the periodicity. BD +6073 is a BN0.7 Ib low-luminosity supergiant located at an approximate distance of 3.1 kpc, in the CasOB4 association. We derive Teff=24000 K and log gc=3.0, and chemical abundances consistent with a moderately high level of evolution. The spectroscopic and evolutionary masses are consistent at the 1 sigma level with a mass of 15 solar masses. The recurrence time of the X-ray flares is the orbital period of the system. The NS is in a high eccentricity (e=0.56) orbit, and the X-ray emission is strongly peaked around orbital phase 0.2, though the observations are consistent with some level of X-ray activity happening at all orbital phases. The X-ray behaviour of IGR J00370+6122 is reminiscent of intermediate SFXTs, though its peak luminosity is rather low. The orbit is somewhat wider than those of classical persistent supergiant X-ray binaries, which, combined with the low luminosity of the mass donor, explains the low X-ray luminosity. IGR J00370+6122 will likely evolve towards a persistent supergiant system, highlighting the evolutionary connection between different classes of wind-accreting X-ray sources.Comment: Accepted for publication in A&

Improving classification for brain computer interfaces using transitions and a moving window

Proceeding of: Biosignals 2009. International Conference on Bio-inspired Systems and Signal Processing, BIOSTEC 2009. Porto (Portugal), 14-17 January 2009The context of this paper is the brain-computer interface (BCI), and in particular the classification of signals with machine learning methods. In this paper we intend to improve classification accuracy by taking advantage of a feature of BCIs: instances run in sequences belonging to the same class. In that case, the classiffication problem can be reformulated into two subproblems: detecting class transitions and determining the class for sequences of instances between transitions. We detect a transition when the Euclidean distance between the power spectra at two different times is larger than a threshold. To tackle the second problem, instances are classified by taking into account, not just the prediction for that instance, but a moving window of predictions for previous instances. Experimental results show that our transition detection method improves results for datasets of two out of three subjects of the BCI III competition. If the moving window is used, classification accuracy is further improved, depending on the window size.Publicad

Reconstruction of attosecond beating by interference of two-photon transitions in bulk solids

The reconstruction of attosecond beating by interference of two-photon transitions (RABBIT) is one of the most widely used techniques for resolving ultrafast electronic dynamics in atomic and molecular systems. As it relies on the interference of photo-electrons in vacuum, similar interference has never been contemplated in the bulk of crystals. Here we show that the interference of two-photon transitions can be recorded directly in the bulk of solids and read out with standard angle-resolved photo-emission spectroscopy. The phase of the RABBIT beating in the photoelectron spectra coming from the bulk of solids is sensitive to the relative phase of the Berry connection between bands and it experiences a shift of $\pi$ as one of the quantum paths crosses a band. For resonant interband transitions, the amplitude of the RABBIT oscillation decays as the pump and probe pulses are separated in time due to electronic decoherence, providing a simple interferometric method to extract dephasing times

All-optical valley switch and clock of electronic dephasing

2D materials with broken inversion symmetry posses an extra degree of freedom, the valley pseudospin, that labels in which of the two energy-degenerate crystal momenta, $K$ or $K'$, the conducting carriers are located. It has been shown that shining circularly-polarized light allows to achieve close to 100% of valley polarization, opening the way to valley-based transistors. Yet, switching of the valley polarization is still a key challenge for the practical implementation of such devices due to the short coherence lifetimes. Recent progress in ultrashort laser technology now allows to produce trains of attosecond pulses with controlled phase and polarization between the pulses. Taking advantage of such technology, we introduce a coherent control protocol to turn on, off and switch the valley polarization at faster timescales than electronic and valley decoherence, that is, an ultrafast optical valley switch. We theoretically demonstrate the protocol for hBN and MoS$_2$ monolayers calculated from first principles. Additionally, using two time-delayed linearly-polarized pulses with perpendicular polarization, we show that we can extract the electronic dephasing time $T_2$ from the valley Hall conductivity.Comment: 19 pages; 4 figure

On-site forest fire smoke detection by low-power autonomous vision sensor

Early detection plays a crucial role to prevent forest fires from spreading. Wireless vision sensor networks deployed throughout high-risk areas can perform fine-grained surveillance and thereby very early detection and precise location of forest fires. One of the fundamental requirements that need to be met at the network nodes is reliable low-power on-site image processing. It greatly simplifies the communication infrastructure of the network as only alarm signals instead of complete images are transmitted, anticipating thus a very competitive cost. As a first approximation to fulfill such a requirement, this paper reports the results achieved from field tests carried out in collaboration with the Andalusian Fire-Fighting Service (INFOCA). Two controlled burns of forest debris were realized (www.youtube.com/user/vmoteProject). Smoke was successfully detected on-site by the EyeRISTM v1.2, a general-purpose autonomous vision system, built by AnaFocus Ltd., in which a vision algorithm was programmed. No false alarm was triggered despite the significant motion other than smoke present in the scene. Finally, as a further step, we describe the preliminary laboratory results obtained from a prototype vision chip which implements, at very low energy cost, some image processing primitives oriented to environmental monitoring.Ministerio de Ciencia e Innovación 2006-TIC-2352, TEC2009-1181