Modelling the Emergence and Dynamics of Perceptual Organisation in Auditory Streaming

Many sound sources can only be recognised from the pattern of sounds they emit, and not from the individual sound events that make up their emission sequences. Auditory scene analysis addresses the difficult task of interpreting the sound world in terms of an unknown number of discrete sound sources (causes) with possibly overlapping signals, and therefore of associating each event with the appropriate source. There are potentially many different ways in which incoming events can be assigned to different causes, which means that the auditory system has to choose between them. This problem has been studied for many years using the auditory streaming paradigm, and recently it has become apparent that instead of making one fixed perceptual decision, given sufficient time, auditory perception switches back and forth between the alternatives—a phenomenon known as perceptual bi- or multi-stability. We propose a new model of auditory scene analysis at the core of which is a process that seeks to discover predictable patterns in the ongoing sound sequence. Representations of predictable fragments are created on the fly, and are maintained, strengthened or weakened on the basis of their predictive success, and conflict with other representations. Auditory perceptual organisation emerges spontaneously from the nature of the competition between these representations. We present detailed comparisons between the model simulations and data from an auditory streaming experiment, and show that the model accounts for many important findings, including: the emergence of, and switching between, alternative organisations; the influence of stimulus parameters on perceptual dominance, switching rate and perceptual phase durations; and the build-up of auditory streaming. The principal contribution of the model is to show that a two-stage process of pattern discovery and competition between incompatible patterns can account for both the contents (perceptual organisations) and the dynamics of human perception in auditory streaming

Secure certification of mixed quantum states with application to two-party randomness generation

We investigate sampling procedures that certify that an arbitrary quantum state on $n$ subsystems is close to an ideal mixed state $\varphi^{\otimes n}$ for a given reference state $\varphi$, up to errors on a few positions. This task makes no sense classically: it would correspond to certifying that a given bitstring was generated according to some desired probability distribution. However, in the quantum case, this is possible if one has access to a prover who can supply a purification of the mixed state. In this work, we introduce the concept of mixed-state certification, and we show that a natural sampling protocol offers secure certification in the presence of a possibly dishonest prover: if the verifier accepts then he can be almost certain that the state in question has been correctly prepared, up to a small number of errors. We then apply this result to two-party quantum coin-tossing. Given that strong coin tossing is impossible, it is natural to ask "how close can we get". This question has been well studied and is nowadays well understood from the perspective of the bias of individual coin tosses. We approach and answer this question from a different---and somewhat orthogonal---perspective, where we do not look at individual coin tosses but at the global entropy instead. We show how two distrusting parties can produce a common high-entropy source, where the entropy is an arbitrarily small fraction below the maximum (except with negligible probability)

Secure certification of mixed quantum states with application to two-party randomness generation

We investigate sampling procedures that certify that an arbitrary quantum state on n subsystems is close to an ideal mixed state ⊗ for a given reference state , up to errors on a few positions. This task makes no sense classically: it would correspond to certifying that a given bitstring was generated according to some desired probability distribution. However, in the quantum case, this is possible if one has access to a prover who can supply a purification of the mixed state. In this work, we introduce the concept of mixed-state certification, and we show that a natural sampling protocol offers secure certification in the presence of a possibly dishonest prover: if the verifier accepts then he can be almost certain that the state in question has been correctly prepared, up to a small number of errors. We then apply this result to two-party quantum coin-tossing. Given that strong coin tossing is impossible, it is natural to ask “how close can we get”. This question has been well studied and is nowadays well understood from the perspective of the bias of individual coin tosses. We approach and answer this question from a different—and somewhat orthogonal—perspective, where we do not look at individual coin tosses but at the global entropy instead. We show how two distrusting parties can produce a common high-entropy source, where the entropy is an arbitrarily small fraction below the maximum

A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences

Stimulus-specific adaptation (SSA) occurs when the spike rate of a neuron decreases with repetitions of the same stimulus, but recovers when a different stimulus is presented. It has been suggested that SSA in single auditory neurons may provide information to change detection mechanisms evident at other scales (e.g., mismatch negativity in the event related potential), and participate in the control of attention and the formation of auditory streams. This article presents a spiking-neuron model that accounts for SSA in terms of the convergence of depressing synapses that convey feature-specific inputs. The model is anatomically plausible, comprising just a few homogeneously connected populations, and does not require organised feature maps. The model is calibrated to match the SSA measured in the cortex of the awake rat, as reported in one study. The effect of frequency separation, deviant probability, repetition rate and duration upon SSA are investigated. With the same parameter set, the model generates responses consistent with a wide range of published data obtained in other auditory regions using other stimulus configurations, such as block, sequential and random stimuli. A new stimulus paradigm is introduced, which generalises the oddball concept to Markov chains, allowing the experimenter to vary the tone probabilities and the rate of switching independently. The model predicts greater SSA for higher rates of switching. Finally, the issue of whether rarity or novelty elicits SSA is addressed by comparing the responses of the model to deviants in the context of a sequence of a single standard or many standards. The results support the view that synaptic adaptation alone can explain almost all aspects of SSA reported to date, including its purported novelty component, and that non-trivial networks of depressing synapses can intensify this novelty response

Cryoelectron Tomography of HIV-1 Envelope Spikes: Further Evidence for Tripod-Like Legs

A detailed understanding of the morphology of the HIV-1 envelope (Env) spike is key to understanding viral pathogenesis and for informed vaccine design. We have previously presented a cryoelectron microscopic tomogram (cryoET) of the Env spikes on SIV virions. Several structural features were noted in the gp120 head and gp41 stalk regions. Perhaps most notable was the presence of three splayed legs projecting obliquely from the base of the spike head toward the viral membrane. Subsequently, a second 3D image of SIV spikes, also obtained by cryoET, was published by another group which featured a compact vertical stalk. We now report the cryoET analysis of HIV-1 virion-associated Env spikes using enhanced analytical cryoET procedures. More than 2,000 Env spike volumes were initially selected, aligned, and sorted into structural classes using algorithms that compensate for the “missing wedge” and do not impose any symmetry. The results show varying morphologies between structural classes: some classes showed trimers in the head domains; nearly all showed two or three legs, though unambiguous three-fold symmetry was not observed either in the heads or the legs. Subsequently, clearer evidence of trimeric head domains and three splayed legs emerged when head and leg volumes were independently aligned and classified. These data show that HIV-1, like SIV, also displays the tripod-like leg configuration, and, unexpectedly, shows considerable gp41 leg flexibility/heteromorphology. The tripod-like model for gp41 is consistent with, and helps explain, many of the unique biophysical and immunological features of this region

Computational Lipidology: Predicting Lipoprotein Density Profiles in Human Blood Plasma

Monitoring cholesterol levels is strongly recommended to identify patients at risk for myocardial infarction. However, clinical markers beyond “bad” and “good” cholesterol are needed to precisely predict individual lipid disorders. Our work contributes to this aim by bringing together experiment and theory. We developed a novel computer-based model of the human plasma lipoprotein metabolism in order to simulate the blood lipid levels in high resolution. Instead of focusing on a few conventionally used predefined lipoprotein density classes (LDL, HDL), we consider the entire protein and lipid composition spectrum of individual lipoprotein complexes. Subsequently, their distribution over density (which equals the lipoprotein profile) is calculated. As our main results, we (i) successfully reproduced clinically measured lipoprotein profiles of healthy subjects; (ii) assigned lipoproteins to narrow density classes, named high-resolution density sub-fractions (hrDS), revealing heterogeneous lipoprotein distributions within the major lipoprotein classes; and (iii) present model-based predictions of changes in the lipoprotein distribution elicited by disorders in underlying molecular processes. In its present state, the model offers a platform for many future applications aimed at understanding the reasons for inter-individual variability, identifying new sub-fractions of potential clinical relevance and a patient-oriented diagnosis of the potential molecular causes for individual dyslipidemia

Fast Homozygosity Mapping and Identification of a Zebrafish ENU-Induced Mutation by Whole-Genome Sequencing

Forward genetics using zebrafish is a powerful tool for studying vertebrate development through large-scale mutagenesis. Nonetheless, the identification of the molecular lesion is still laborious and involves time-consuming genetic mapping. Here, we show that high-throughput sequencing of the whole zebrafish genome can directly locate the interval carrying the causative mutation and at the same time pinpoint the molecular lesion. The feasibility of this approach was validated by sequencing the m1045 mutant line that displays a severe hypoplasia of the exocrine pancreas. We generated 13 Gb of sequence, equivalent to an eightfold genomic coverage, from a pool of 50 mutant embryos obtained from a map-cross between the AB mutant carrier and the WIK polymorphic strain. The chromosomal region carrying the causal mutation was localized based on its unique property to display high levels of homozygosity among sequence reads as it derives exclusively from the initial AB mutated allele. We developed an algorithm identifying such a region by calculating a homozygosity score along all chromosomes. This highlighted an 8-Mb window on chromosome 5 with a score close to 1 in the m1045 mutants. The sequence analysis of all genes within this interval revealed a nonsense mutation in the snapc4 gene. Knockdown experiments confirmed the assertion that snapc4 is the gene whose mutation leads to exocrine pancreas hypoplasia. In conclusion, this study constitutes a proof-of-concept that whole-genome sequencing is a fast and effective alternative to the classical positional cloning strategies in zebrafish

Predictive regularity representations in deviance detection and auditory stream segregation: from conceptual to computational models

Predictive accounts of perception have received increasing attention in the past twenty years. Detecting violations of auditory regularities, as reflected by the Mismatch Negativity (MMN) auditory event-related potential, is amongst the phenomena seamlessly fitting this approach. Largely based on the MMN literature, we propose a psychological conceptual framework called the Auditory Event Representation System (AERS), which is based on the assumption that auditory regularity violation detection and the formation of auditory perceptual objects are based on the same predictive regularity representations. Based on this notion, a computational model of auditory stream segregation, called CHAINS, has been developed. In CHAINS, the auditory sensory event representation of each incoming sound is considered for being the continuation of likely combinations of the preceding sounds in the sequence, thus providing alternative interpretations of the auditory input. Detecting repeating patterns allows predicting upcoming sound events, thus providing a test and potential support for the corresponding interpretation. Alternative interpretations continuously compete for perceptual dominance. In this paper, we briefly describe AERS and deduce some general constraints from this conceptual model. We then go on to illustrate how these constraints are computationally specified in CHAINS

The Association between Intrauterine Inflammation and Spontaneous Vaginal Delivery at Term: A Cross-Sectional Study

BACKGROUND:Different factors contribute to the onset of labor at term. In animal models onset of labor is characterized by an inflammatory response. The role of intrauterine inflammation, although implicated in preterm birth, is not yet established in human term labor. We hypothesized that intrauterine inflammation at term is associated with spontaneous onset of labor. METHODS/RESULTS:In two large urban hospitals in the Netherlands, a cross-sectional study of spontaneous onset term vaginal deliveries and elective caesarean sections (CS), without signs of labor, was carried out. Placentas and amniotic fluid samples were collected during labor and/or at delivery. Histological signs of placenta inflammation were determined. Amniotic fluid proinflammatory cytokine concentrations were measured using ELISA. A total of 375 women were included. In term vaginal deliveries, more signs of intrauterine inflammation were found than in elective CS: the prevalence of chorioamnionitis was higher (18 vs 4%, p = 0.02) and amniotic fluid concentration of IL-6 was higher (3.1 vs 0.37 ng/mL, p<0.001). Similar results were obtained for IL-8 (10.93 vs 0.96 ng/mL, p<0.001) and percentage of detectable TNF-alpha (50 vs 4%, p<0.001). CONCLUSIONS:This large cross-sectional study shows that spontaneous term delivery is characterized by histopathological signs of placenta inflammation and increased amniotic fluid proinflammatory cytokines