Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory

Epithelial damage and tissue γδ T cells promote a unique tumor-protective IgE response

IgE is an ancient and conserved immunoglobulin isotype with potent immunological function. Nevertheless, the regulation of IgE responses remains an enigma, and evidence of a role for IgE in host defense is limited. Here we report that topical exposure to a common environmental DNA-damaging xenobiotic initiated stress surveillance by γδTCR+ intraepithelial lymphocytes that resulted in class switching to IgE in B cells and the accumulation of autoreactive IgE. High-throughput antibody sequencing revealed that γδ T cells shaped the IgE repertoire by supporting specific variable-diversity-joining (VDJ) rearrangements with unique characteristics of the complementarity-determining region CDRH3. This endogenous IgE response, via the IgE receptor FcεRI, provided protection against epithelial carcinogenesis, and expression of the gene encoding FcεRI in human squamous-cell carcinoma correlated with good disease prognosis. These data indicate a joint role for immunosurveillance by T cells and by B cells in epithelial tissues and suggest that IgE is part of the host defense against epithelial damage and tumor development

Hepatic teratoma and peritoneal gliomatosis: a case report

The hepatic teratoma is a very rare entity of which only 25 cases have been published so far. In our case the hepatic teratoma is associated with peritoneal gliomatosis, which is an indicator for an ongoing peritoneal spread of a teratoma. Wall calcifications and the homogeneity as well as the well defined border misled the radiologist to the diagnosis of an echinococcal cyst, which is the most common differential diagnosis, however the hepatic teratoma has to be taking into consideration when dealing with unclear hepatic cysts, although it is very rare

STEM education in the twenty-first century: learning at work-an exploration of design and technology teacher perceptions and practices

Teachers’ knowledge of STEM education, their understanding, and pedagogical application of that knowledge is intrinsically linked to the subsequent effectiveness of STEM delivery within their own practice; where a teacher’s knowledge and understanding is deficient, the potential for pupil learning is ineffective and limited. Set within the context of secondary age phase education in England and Wales (11–16 years old), this paper explores how teachers working within the field of design and technology education acquire new knowledge in STEM; how understanding is developed and subsequently embedded within their practice to support the creation of a diverse STEM-literate society. The purpose being to determine mechanisms by which knowledge acquisition occurs, to reconnoitre potential implications for education and learning at work, including consideration of the role which new technologies play in the development of STEM knowledge within and across contributory STEM subject disciplines. Underpinned by an interpretivist ontology, work presented here builds upon the premise that design and technology is an interdisciplinary educational construct and not viewed as being of equal status to other STEM disciplines including maths and science. Drawing upon the philosophical field of symbolic interactionism and constructivist grounded theory, work embraces an abductive methodology where participants are encouraged to relate design and technology within the context of STEM education. Emergent findings are discussed in relation to their potential to support teachers’ educational development for the advancement of STEM literacy, and help secure design and technology’s place as a subject of value within a twenty-first Century curriculum

A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition

Memories are believed to be represented in the synaptic pathways of vastly interconnected networks of neurons. The plasticity of synapses, that is, their strengthening and weakening depending on neuronal activity, is believed to be the basis of learning and establishing memories. An increasing number of studies indicate that endocannabinoids have a widespread action on brain function through modulation of synap–tic transmission and plasticity. Recent experimental studies have characterised the role of endocannabinoids in mediating both short- and long-term synaptic plasticity in various brain regions including the hippocampus, a brain region strongly associated with cognitive functions, such as learning and memory. Here, we present a biophysically plausible model of cannabinoid retrograde signalling at the synaptic level and investigate how this signalling mediates depolarisation induced suppression of inhibition (DSI), a prominent form of shortterm synaptic depression in inhibitory transmission in hippocampus. The model successfully captures many of the key characteristics of DSI in the hippocampus, as observed experimentally, with a minimal yet sufficient mathematical description of the major signalling molecules and cascades involved. More specifically, this model serves as a framework to test hypotheses on the factors determining the variability of DSI and investigate under which conditions it can be evoked. The model reveals the frequency and duration bands in which the post-synaptic cell can be sufficiently stimulated to elicit DSI. Moreover, the model provides key insights on how the state of the inhibitory cell modulates DSI according to its firing rate and relative timing to the post-synaptic activation. Thus, it provides concrete suggestions to further investigate experimentally how DSI modulates and is modulated by neuronal activity in the brain. Importantly, this model serves as a stepping stone for future deciphering of the role of endocannabinoids in synaptic transmission as a feedback mechanism both at synaptic and network level

Search for rare quark-annihilation decays, B --> Ds(*) Phi

We report on searches for B- --> Ds- Phi and B- --> Ds*- Phi. In the context of the Standard Model, these decays are expected to be highly suppressed since they proceed through annihilation of the b and u-bar quarks in the B- meson. Our results are based on 234 million Upsilon(4S) --> B Bbar decays collected with the BABAR detector at SLAC. We find no evidence for these decays, and we set Bayesian 90% confidence level upper limits on the branching fractions BF(B- --> Ds- Phi) Ds*- Phi)<1.2x10^(-5). These results are consistent with Standard Model expectations.Comment: 8 pages, 3 postscript figues, submitted to Phys. Rev. D (Rapid Communications

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

Expression of glycolytic enzymes in ovarian cancers and evaluation of the glycolytic pathway as a strategy for ovarian cancer treatment

Table S2. Spearman correlation of the expression of four glycolytic enzymes in a cohort of 380 ovarian cancers. Spearman rho correlation values (top value) along with the respective adjusted P value (bottom value) of statistically significant correlations thresholded at FDR P < 0.01 are summarised. (DOCX 21 kb

Regulation of early steps of GPVI signal transduction by phosphatases: a systems biology approach

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation