Object localization in cluttered acoustical environments

In nature, sounds from objects of interest arrive at the ears accompanied by sound waves from other actively emitting objects and by reflections off of nearby surfaces. Despite the fact that all of these waveforms sum at the eardrums, humans with normal hearing effortlessly segregate one sound source from another. Our laboratory is investigating the neural basis of this perceptual feat, often called the "cocktail party effect", using the barn owl as an animal model. The barn owl, renowned for its ability to localize sounds and its spatiotopic representation of auditory space, is an established model for spatial hearing. Here, we briefly review the neural basis of sound-localization of a single sound source in an anechoic environment and then generalize the ideas developed therein to cases in which there are multiple, concomitant sound sources and acoustical reflection.     

Identification of sources of cerebral activity in the cat

The identification of sources of cerebral activity is investigated, and the resulting methodology is applied to the simple case of hippocampal afterdischarges in the cat. We develop an “imagery” technique which consists in defining, in a preliminary step, the number and the power spectrum density of unknown sources (identification of sources) assumed to emit independent signals in the ill-defined noisy cerebral medium. The technique assumes the medium to be quasilinear and quasistationary, and these assumptions have to be checked. It is based upon the interspectral matrix and its diagonal form. It makes it clear that (1) the problem of estimating the number of sources is closely dependent on the estimation method used to assess the power spectrum density, and (2) the coherence matrix should be preferred to the interspectral matrix for reasons linked with the estimation variance of its elements and the proximity of the sources and sensors. In order to assess the validity of the methodology, a source of hippocampal afterdischarges has been created by threshold stimulation of the ventral hippocampus of the cat. The resulting EEG signals are used to show that there is a single source and to estimate its power density spectrum, which can then be compared with the true one.     

Picomolar nitric oxide signals from central neurons recorded using ultrasensitive detector cells

Nitric oxide (NO) is a widespread signaling molecule with potentially multifarious actions of relevance to health and disease. A fundamental determinant of how it acts is its concentration, but there remains a lack of coherent information on the patterns of NO release from its sources, such as neurons or endothelial cells, in either normal or pathological conditions. We have used detector cells having the highest recorded NO sensitivity to monitor NO release from brain tissue quantitatively and in real time. Stimulation of NMDA receptors, which are coupled to activation of neuronal NO synthase, routinely generated NO signals from neurons in cerebellar slices. The average computed peak NO concentrations varied across the anatomical layers of the cerebellum, from 12 to 130 pm. The mean value found in the hippocampus was 200 pm. Much variation in the amplitudes recorded by individual detector cells was observed, this being attributable to their location at variable distances from the NO sources. From fits to the data, the NO concentrations at the source surfaces were 120 pm to 1.4 nm, and the underlying rates of NO generation were 36-350 nm/s, depending on area. Our measurements are 4-5 orders of magnitude lower than reported by some electrode recordings in cerebellum or hippocampus. In return, they establish coherence between the NO concentrations able to elicit physiological responses in target cells through guanylyl cyclase-linked NO receptors, the concentrations that neuronal NO synthase is predicted to generate locally, and the concentrations that neurons actually produce.     

Shifts in controls on the temporal coherence of throughfall chemical flux in Acadia National Park, Maine, USA

Major ion and mercury (Hg) inputs to terrestrial ecosystems include both wet and dry deposition (total deposition). Estimating total deposition to sensitive receptor sites is hampered by limited information regarding its spatial heterogeneity and seasonality. We used measurements of throughfall flux, which includes atmospheric inputs to forests and the net effects of canopy leaching or uptake, for ten major ions and Hg collected during 35 time periods in 1999–2005 at over 70 sites within Acadia National Park, Maine to (1) quantify coherence in temporal dynamics of seasonal throughfall deposition and (2) examine controls on these patterns at multiple scales. We quantified temporal coherence as the correlation between all possible site pairs for each solute on a seasonal basis. In the summer growing season and autumn, coherence among pairs of sites with similar vegetation was stronger than for site-pairs that differed in vegetation suggesting that interaction with the canopy and leaching of solutes differed in coniferous, deciduous, mixed, and shrub or open canopy sites. The spatial pattern in throughfall hydrologic inputs across Acadia National Park was more variable during the winter snow season, suggesting that snow re-distribution affects net hydrologic input, which consequently affects chemical flux. Sea-salt corrected calcium concentrations identified a shift in air mass sources from maritime in winter to the continental industrial corridor in summer. Our results suggest that the spatial pattern of throughfall hydrologic flux, dominant seasonal air mass source, and relationship with vegetation in winter differ from the spatial pattern of throughfall flux in these solutes in summer and autumn. The coherence approach applied here made clear the strong influence of spatial heterogeneity in throughfall hydrologic inputs and a maritime air mass source on winter patterns of throughfall flux. By contrast, vegetation type was the most important influence on throughfall chemical flux in summer and autumn.     

Validation of a laser driven plasma X-ray microfocus source for high resolution radiography imaging

Hard X-ray radiation with high brightness and high fluxes is nowadays available on the fourth generation of synchrotrons and X-FELs, but the large size and complexity of these sources makes its use difficult for widespread applications. New table top X-ray sources driven by ultrashort high power lasers offer a compelling route to expand the availability of hard X-ray sources. They can be used for advanced imaging techniques, due to its small source size and spatial coherence. We present in this paper the validation of a compact laser-driven X-ray microfocus source for high-resolution radiography imaging. This novel device was built at the Laser Laboratory for Acceleration and Applications (L2A2) at the University of Santiago de Compostela. This paper describes the laser-plasma X-ray source with improved stability and characterize some of its properties. We demonstrate the high-contrast and resolution of the images obtained with this source by using masks with well known geometries, and detailed analysis by using the modulation transfer function. Finally, we discuss the properties of this source in comparison to other compact microfocus X-ray sources.     

利用双SLD光源提高OCT纵向分辨率的理论研究

提高光学相干层析成像(OpticalCoherenceTomography:OCT)系统纵向分辨率的关键是选取合适的光源,本文将双SLD光源代替传统OCT系统中的单个SLD光源,通过理论分析和计算机仿真,表明双SLD光源能有效提高OCT系统纵向分辨率。     

Pattern detection in null model analysis

Synthesis The identification of distinctive patterns in species x site presence‐absence matrices is important for understanding meta‐community organisation. We compared the performance of a suite of null models and metrics that have been proposed to measure patterns of segregation, aggregation, nestedness, coherence, and species turnover. We found that any matrix with segregated species pairs can be re‐ordered to highlight aggregated pairs, indicating that these seemingly opposite patterns are closely related. Recently proposed classification schemes failed to correctly classify realistic matrices that included multiple co‐occurrence structures. We propose using a combination of metrics and decomposing matrix‐wide patterns into those of individual pairs of species and sites to pinpoint sources of non‐randomness. Null model analysis has been a popular tool for detecting pattern in binary presence–absence matrices, and previous tests have identified algorithms and metrics that have good statistical properties. However, the behavior of different metrics is often correlated, making it difficult to distinguish different patterns. We compared the performance of a suite of null models and metrics that have been proposed to measure patterns of segregation, aggregation, nestedness, coherence, and species turnover. We found that any matrix with segregated species pairs can be re‐ordered to highlight aggregated pairs. As a consequence, the same null model can identify a single matrix as being simultaneously aggregated, segregated or nested. These results cast doubt on previous conclusions of matrix‐wide species segregation based on the C‐score and the fixed‐fixed algorithm. Similarly, we found that recently proposed classification schemes based on patterns of coherence, nestedness, and segregation and aggregation cannot be uniquely distinguished using proposed metrics and null model algorithms. It may be necessary to use a combination of different metrics and to decompose matrix‐wide patterns into those of individual pairs of species or pairs of sites to pinpoint the sources of non‐randomness.     

Auditory segregation of competing voices: absence of effects of FM or AM coherence.

Four experiments sought evidence that listeners can use coherent changes in the frequency or amplitude of harmonics to segregate concurrent vowels. Segregation was not helped by giving the harmonics of competing vowels different patterns of frequency or amplitude modulation. However, modulating the frequencies of the components of one vowel was beneficial when the other vowel was not modulated, provided that both vowels were composed of components placed randomly in frequency. In addition, staggering the onsets of the two vowels, so that the amplitude of one vowel increased abruptly while the amplitude of the other was stationary, was also beneficial. Thus, the results demonstrate that listeners can group changing harmonics and can segregate them from stationary harmonics, but cannot use coherence of change to separate two sets of changing harmonics.     

"Either-or" two-slit interference: stable coherent propagation of individual photons through separate slits

In quantum theory, nothing that is observable, be it physical, chemical, or biological, is separable from the observer. Furthermore, ". all possible knowledge concerning that object is given by its wave function" (Wigner, E. 1967. Symmetries and Reflections. Indiana University Press, Bloomington, IN), which can only describe probabilities of future events. In physical systems, quantum mechanical probabilistic events that are microscopic must, in turn, account for macroscopic events that are associated with a greater degree of certainty. In biological systems, probabilistic statistical mechanical events, such as secretion of microscopic synaptic vesicles, must account for macroscopic postsynaptic potentials; probabilistic single-channel events sum to produce a macroscopic ionic current across a cell membrane; and bleaching of rhodopsin molecules (responsible for quantal potential "bumps") produces a photoreceptor generator potential. Among physical systems, a paradigmatic example of how quantum theory applies to the observation of events concerns the interactions of particles (e.g., photons, electrons) with the two-slit apparatus to generate an interference pattern from a single common light source. For two-slit systems that use two independent laser sources with brief (<1 ms) intervals of mutual coherence (Paul, H. 1986. Rev. Modern Phys. 58:209-231), each photon has been considered to arise from both beams and has a probability amplitude to pass through each of the two slits. Here, a single laser source two-slit interference system was constructed so that each photon has a probability amplitude to pass through only one or the other, but not both slits. Furthermore, all photons passing through one slit could be distinguished from all photons passing through the other slit before their passage. This "either-or" system produced a stable interference pattern indistinguishable from the interference produced when both slits were accessible to each photon. Because this system excludes the interaction of one photon with both slits, phase correlation of photon movements derives from the "entanglement" of all photon wave functions due to their dependence on a common laser source. Because a laser source (as well as Young's original point source) will have stable time-averaged spatial coherence even at low intensities, the "either-or" two-slit interference can result from distinct individual photons passing one at a time through one or the other slit-rather than wave-like behavior of individual photons. In this manner, single, successive photons passing through separate slits will assemble over time in phase-correlated wave distributions that converge in regions of low and high probability.     

基于混沌优化算法的MUSIC脑磁图源定位方法

如何利用实验测得的脑磁图数据准确定位脑磁图源的真实活动位置是脑功能研究和临床应用中的一个关键问题.在脑磁活动源定位问题中,多信号分类算法是被广泛研究和采用的一类方法.为了克服多信号分类算法及其改进算法--递归多信号分类算法全局扫描时速度太慢的缺点,提出了一种基于混沌优化算法的脑磁图源定位新方法.该方法利用混沌运动遍历性的特点估计目标函数的全局最大值,进行初步的脑磁图源定位;然后,在小范围内结合网格的方法,进一步进行精确的定位.实验结果表明,此方法可实现多个脑磁图源的定位,并且定位速度大大加快,同时又能达到所要求的定位精度.     

Genetics and physiology of proline utilization in Saccharomyces cerevisiae: enzyme induction by proline.

Proline is converted to glutamate in the yeast Saccharomyces cerevisiae by the sequential action of two enzymes, proline oxidase and delta 1-pyrroline-5-carboxylate (P5C) dehydrogenase. The levels of these enzymes appear to be controlled by the amount of proline in the cell. The capacity to transport proline is greatest when the cell is grown on poor nitrogen sources, such as proline or urea. Mutants have been isolated which can no longer utilize proline as the sole source of nitrogen. Mutants in put1 are deficient in proline oxidase, and those in put2 lack P5C dehydrogenase. The put1 and put2 mutations are recessive, segregate 2:2 in tetrads, and appear to be unlinked to one another. Proline induces both proline oxidase and P5C dehydrogenase. The arginine-degradative pathway intersects the proline-degradative pathway at P5C. The P5C formed from the breakdown of arginine or ornithine can induce both proline-degradative enzymes by virtue of its conversion to proline.     

Traveling Theta Waves along the Entire Septotemporal Axis of the Hippocampus

A topographical relationship exists between the hippocampus-entorhinal cortex and the neocortex. However, it is not known how these anatomical connections are utilized during information exchange and behavior. We recorded theta oscillations along the entire extent of the septotemporal axis of the hippocampal CA1 pyramidal layer. While the frequency of theta oscillation remained same along the entire long axis, the amplitude and coherence between recording sites decreased from dorsal to ventral hippocampus (VH). Theta phase shifted monotonically with distance along the longitudinal axis, reaching ～180° between the septal and temporal poles. The majority of concurrently recorded units were phase-locked to the local field theta at all dorsoventral segments. The power of VH theta had only a weak correlation with locomotion velocity, and its amplitude varied largely independently from theta in the dorsal part. Thus, theta oscillations can temporally combine or segregate neocortical representations along the septotemporal axis of the hippocampus.     

Influence of visual targets and landmarks on honey bee foraging and waggle dancing

Animals use diverse sensory stimuli to navigate their environment and to recognize rewarding food sources.Honey bees use visual atributes of the targeted food source,such as its color,shape,size,direction and distance from the hive,and the landmarks around it to navigate during foraging.They transmit the location information of the food source to other bees if it is highly rewarding.To investigate the relative importance of these attributes,we trained bees to feeders in two different experiments.In the first experiment,we asked whether bees prefer to land on(a)a similar feeder at a different distance on the same heading or on(b)a visually distinct feeder located at the exact same location.We found that,within a short foraging range,bees relied heavily on the color and the shape of the food source and to a lesser extent on its distance from the hive.In the second experiment,we asked if moving the main landmark or the feeder(visual target)influenced recruitment dancing for the feeder.We found that foragers took longer to land and danced fewer circuits when the location of the food source,or a major landmark associated with it,changed.These results demonstrate that prominent visual atributes of food sources and landmarks are evidently more reliable than distance information and that foraging bees heavily utilize these visual cues at the later stages of their journey.     

Coherence and phase locking in the scalp EEG and between LORETA model sources, and microstates as putative mechanisms of brain temporo-spatial functional organization.

Brain electric mechanisms of temporary, functional binding between brain regions are studied using computation of scalp EEG coherence and phase locking, sensitive to time differences of few milliseconds. However, such results if computed from scalp data are ambiguous since electric sources are spatially oriented. Non-ambiguous results can be obtained using calculated time series of strength of intracerebral model sources. This is illustrated applying LORETA modeling to EEG during resting and meditation. During meditation, time series of LORETA model sources revealed a tendency to decreased left-right intracerebral coherence in the delta band, and to increased anterior-posterior intracerebral coherence in the theta band. An alternate conceptualization of functional binding is based on the observation that brain electric activity is discontinuous, i.e., that it occurs in chunks of up to about 100 ms duration that are detectable as quasi-stable scalp field configurations of brain electric activity, called microstates. Their functional significance is illustrated in spontaneous and event-related paradigms, where microstates associated with imagery- versus abstract-type mentation, or while reading positive versus negative emotion words showed clearly different regions of cortical activation in LORETA tomography. These data support the concept that complete brain functions of higher order such as a momentary thought might be incorporated in temporal chunks of processing in the range of tens to about 100 ms as quasi-stable brain states; during these time windows, subprocesses would be accepted as members of the ongoing chunk of processing.     

Electro/magnetoencephalography beamforming with spatial restrictions based on sparsity

We present a source localization method for electroencephalographic (EEG) and magnetoencephalographic (MEG) data which is based on an estimate of the sparsity obtained through the eigencanceler (EIG), which is a spatial filter whose weights are constrained to lie in the noise subspace. The EIG provides rejection of directional interferences while minimizing noise contributions and maintaining specified beam pattern constraints. In our case, the EIG is used to estimate the sparsity of the signal as a function of the position, then we use this information to spatially restrict the neural sources to locations out of the sparsity maxima. As proof of the concept, we incorporate this restriction in the “classical” linearly constrained minimum variance (LCMV) source localization approach in order to enhance its performance. We present numerical examples to evaluate the proposed method using realistically simulated EEG/MEG data for different signal-to-noise (SNR) conditions and various levels of correlation between sources, as well as real EEG/MEG measurements of median nerve stimulation. Our results show that the proposed method has the potential of reducing the bias on the search of neural sources in the classical approach, as well as making it more effective in localizing correlated sources.     

Disentangling water sources in a gypsum plant community. Gypsum crystallization water is a key source of water for shallow-rooted plants

Background and AimsGypsum drylands are widespread worldwide. In these arid ecosystems, the ability of different species to access different water sources during drought is a key determining factor of the composition of plant communities. Gypsum crystallization water could be a relevant source of water for shallow-rooted plants, but the segregation in the use of this source of water among plants remains unexplored. We analysed the principal water sources used by 20 species living in a gypsum hilltop, the effect of rooting depth and gypsum affinity, and the interaction of the plants with the soil beneath them.MethodsWe characterized the water stable isotope composition, δ ²H and δ ¹⁸O, of plant xylem water and related it to the free and gypsum crystallization water extracted from different depths throughout the soil profile and the groundwater, in both spring and summer. Bayesian isotope mixing models were used to estimate the contribution of water sources to plant xylem sap.Key ResultsIn spring, all species used free water from the top soil as the main source. In summer, there was segregation in water sources used by different species depending on their rooting depth, but not on their gypsum affinity. Gypsum crystallization water was the main source for most shallow-rooted species, whereas free water from 50 to 100 cm depth was the main source for deep-rooted species. We detected plant–soil interactions in spring, and indirect evidence of possible hydraulic lift by deep-rooted species in summer.ConclusionsPlants coexisting in gypsum communities segregate their hydrological niches according to their rooting depth. Crystallization water of gypsum represents an unaccounted for, vital source for most of the shallow-rooted species growing on gypsum drylands. Thus, crystallization water helps shallow-rooted species to endure arid conditions, which eventually accounts for the maintenance of high biodiversity in these specialized ecosystems.     

Deception Undermines the Stability of Cooperation in Games of Indirect Reciprocity

Indirect reciprocity is often claimed as one of the key mechanisms of human cooperation. It works only if there is a reputational score keeping and each individual can inform with high probability which other individuals were good or bad in the previous round. Gossip is often proposed as a mechanism that can maintain such coherence of reputations in the face of errors of transmission. Random errors, however, are not the only source of uncertainty in such situations. The possibility of deceptive communication, where the signallers aim to misinform the receiver cannot be excluded. While there is plenty of evidence for deceptive communication in humans the possibility of deception is not yet incorporated into models of indirect reciprocity. Here we show that when deceptive strategies are allowed in the population it will cause the collapse of the coherence of reputations and thus in turn it results the collapse of cooperation. This collapse is independent of the norms and the cost and benefit values. It is due to the fact that there is no selection for honest communication in the framework of indirect reciprocity. It follows that indirect reciprocity can be only proposed plausibly as a mechanism of human cooperation if additional mechanisms are specified in the model that maintains honesty.     

Can We Identify Non-Stationary Dynamics of Trial-to-Trial Variability?

Identifying sources of the apparent variability in non-stationary scenarios is a fundamental problem in many biological data analysis settings. For instance, neurophysiological responses to the same task often vary from each repetition of the same experiment (trial) to the next. The origin and functional role of this observed variability is one of the fundamental questions in neuroscience. The nature of such trial-to-trial dynamics however remains largely elusive to current data analysis approaches. A range of strategies have been proposed in modalities such as electro-encephalography but gaining a fundamental insight into latent sources of trial-to-trial variability in neural recordings is still a major challenge. In this paper, we present a proof-of-concept study to the analysis of trial-to-trial variability dynamics founded on non-autonomous dynamical systems. At this initial stage, we evaluate the capacity of a simple statistic based on the behaviour of trajectories in classification settings, the trajectory coherence, in order to identify trial-to-trial dynamics. First, we derive the conditions leading to observable changes in datasets generated by a compact dynamical system (the Duffing equation). This canonical system plays the role of a ubiquitous model of non-stationary supervised classification problems. Second, we estimate the coherence of class-trajectories in empirically reconstructed space of system states. We show how this analysis can discern variations attributable to non-autonomous deterministic processes from stochastic fluctuations. The analyses are benchmarked using simulated and two different real datasets which have been shown to exhibit attractor dynamics. As an illustrative example, we focused on the analysis of the rat''s frontal cortex ensemble dynamics during a decision-making task. Results suggest that, in line with recent hypotheses, rather than internal noise, it is the deterministic trend which most likely underlies the observed trial-to-trial variability. Thus, the empirical tool developed within this study potentially allows us to infer the source of variability in in-vivo neural recordings.