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Humans have long wondered about the function of mental imagery and its relationship to vision. Although visual representations are utilized during imagery, the computations they subserve are unclear. Building on a theory that treats vision as inference about the causes of sensory stimulation in an internal generative model, we propose that mental imagery is inference about the sensory consequences of predicted or remembered causes. The relation between these complementary inferences yields a relation between the brain activity patterns associated with imagery and vision. We show that this relation has the formal structure of an echo that makes encoding of imagined stimuli in low-level visual areas resemble the encoding of seen stimuli in higher areas. To test for evidence of this echo effect we developed imagery encoding models—a new tool for revealing how imagined stimuli are encoded in brain activity. We estimated imagery encoding models from brain activity measured with fMRI while human subjects imagined complex visual stimuli, and then compared these to visual encoding models estimated from a matched viewing experiment. Consistent with an echo effect, imagery encoding models in low-level visual areas exhibited decreased spatial frequency preference and larger, more foveal receptive fields, thus resembling visual encoding models in high-level visual areas where imagery and vision appeared to be almost interchangeable. Our findings support an interpretation of mental imagery as a predictive inference that is conditioned on activity in high-level visual cortex, and is related to vision through shared dependence on an internal model of the visual world.

Oocytes collected from prepubertal animals are known to be less developmentally competent than those from adult animals. There is evidence suggesting that acquisition of developmental competence in bovine oocytes may be linked to the expression profile of genes in the granulosa cells (GCs). Cumulus-oocyte complexes (COC) and GCs were collected from 12 Holstein heifers between 2 and 6 months of age (nine follicle-stimulating hormone [FSH] treated and three untreated) and eight FSH-treated cows. The COCs from prepubertal animals were matured, fertilized, and cultured in vitro to assess development to the blastocyst stage. The relative messenger RNA (mRNA) abundance of FSHR, StAR, CYP19A1, HSD3B1, CX43, FOXO1, and XIAP in GCs were quantified by real-time quantitative polymerase chain reaction. Results from this study revealed that GCs of prepubertal animals respond to FSH treatment by increasing mRNA levels of genes promoting estradiol synthesis and follicular growth ( FSHR and CYP19A1), and preventing cell apoptosis ( XIAP), and by decreasing mRNA levels of genes promoting progesterone production ( StAR and HSD3B1). This study also revealed that the relative mRNA abundance of FOXO1 in GCs is associated with oocyte competence to support embryo development to the blastocyst stage in prepubertal Holstein heifers.

We consider the inference problem of reconstructing a visual stimulus from brain activity measurements (e.g. fMRI) that encode this stimulus. Recovering a complete image is complicated by the fact that neural representations are noisy, high-dimensional, and contain incomplete information about image details. Thus, reconstructions of complex images from brain activity require a strong prior. Here we propose to train generative adversarial networks (GANs) to learn a generative model of images that is conditioned on measurements of brain activity. We consider two challenges of this approach: First, given that GANs require far more data to train than is typically collected in an fMRI experiment, how do we obtain enough samples to train a GAN that is conditioned on brain activity? Secondly, how do we ensure that our generated samples are robust against noise present in fMRI data? Our strategy to surmount both of these problems centers around the creation of surrogate brain activity samples that are generated by an encoding model. We find that the generative model thus trained generalizes to real fRMI data measured during perception of images and is able to reconstruct the basic outline of the stimuli.

Qu'est-ce qui pousse un individu à commettre un meurtre sexuel ? Quelles étaient les intentions du meurtrier au moment des faits ? Pourquoi une agression sexuelle dévie-t-elle vers l'homicide ? Cette étude, qui repose sur une analyse comparative des violeurs et des meurtriers sexuels, démontre que le meurtre sexuel dépend de la combinaison de facteurs développementaux, intentionnels et situationnels. La colère, la consommation d'alcool, la motivation sexuelle dans l'agression, le sadisme sont autant d'indices qui permettent de comprendre le meurtre sexuel. Cet ouvrage remet en question nombre d'idées reçues sur les meurtriers sexuels. Contrairement à ce que l'on aurait tendance à croire, les sadiques ne représentent qu'une minorité de meurtriers sexuels et les violeurs ont souvent la même histoire criminelle et les mêmes troubles de la personnalité que les meurtriers sexuels. En fait, le parcours criminel des meurtriers sexuels ressemble étrangement à celui des délinquants récidivistes et il apparaît difficile de tracer un profil précis qui les identifierait hors de tout doute possible. Théorique mais aussi pratique, cet ouvrage propose des stratégies d'enquêtes et d'interrogatoires en matière de meurtre sexuel.

À notre connaissance, sept typologies de meurtriers sexuels ont été publiées. Le tableau 8.1 présente les principales caractéristiques de ces études typologiques. Nous avons précisé (lorsque l’information était connue) le nombre de sujets, le type de sujets, les sources des données, les variables incluses, ainsi que la méthode de construction de chacune des typologies relevées. En ce qui a trait au nombre de sujets inclus dans les différentes études, seules les typologies du FBI (Ressler, Bur...

Manipulating the coupling coefficient at subwavelength scales provides an additional degree of freedom in designing integrated Bragg gratings. We demonstrate asymmetric contradirectional couplers (contra-DCs) using sidewall-corrugated subwavelength grating (SWG) waveguides for broadband add-drop Bragg filters. We show that a SWG can effectively increase the overlap of coupled modes and thus the photonic band gap. The measured spectra show good agreement with the prediction of photonic band structure simulations. A record bandwidth of 4.07 THz (33.4 nm) has been achieved experimentally. A four-port Bragg resonating filter made of a phase-shifted Bragg grating SWG contra-DC is also demonstrated for narrow-band (near 100 GHz) filtering. All these devices are achieved on the 220-nm silicon-on-insulator platform with a compact length of less than 150 μm. These large stopband filters may find important applications such as band splitting, reconfigurable channel band switching, bandwidth-tunable filtering, and dispersion engineering.

We propose an analytical time-domain model for microring and microdisk modulators, which considers both their electrical and optical properties. Theory of the dynamics of microring/microdisk is discussed, and general solutions to the transfer matrix representation are presented. Both static and dynamic predictions from the model are compared to measurement results to demonstrate the accuracy of our model. Static predictions and measurements are presented for power and phase responses, whereas dynamic predictions and measurements are presented for small-signal and large-signal operations. The model verifies that the chirping and modulation bandwidth of the modulators depend on the detuning state. Finally, the accuracy and scalability of several techniques employed in the model are discussed.

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map—a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: “where” parameters that characterize the location and extent of pooling over visual features, and “what” parameters that characterize tuning to visual features. The “where” parameters are analogous to classical receptive fields, while “what” parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation.We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model’s application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep convolutional networks against brain activity. The ability to use whole networks in a single encoding model yields state-of-the-art prediction accuracy. Our results suggest a wide variety of uses for the feature-weighted receptive field model, from retinotopic mapping with natural scenes, to regressing the activities of whole deep neural networks onto measured brain activity.

Next-generation passive optical networks require integrated, polarization-insensitive wavelength-division multiplexing solutions, for which the recently emerging low-loss silicon nitride nanophotonic platforms hold great potential. A novel polarization-insensitive arrayed waveguide grating (AWG) built with silicon nitride waveguides is presented in this Letter. Polarization insensitivity is obtained when both the channel spacing and the center wavelength of the two orthogonal polarization states (i.e., the TE and TM waveguide modes) are simultaneously aligned. In our design, the channel spacing alignment between the polarization states is obtained by optimizing the geometry of the arrayed waveguides, whereas the central wavelength polarization insensitivity is obtained by splitting the two polarization states and adjusting their angle of incidence at the input star coupler to compensate for the polarization mode dispersion of the AWG. A 100 GHz 1×8 wavelength-division multiplexer with crosstalk levels below -16 dB is demonstrated experimentally.

International audience; Six coatings containing different ratios of polysaccharides and antimicrobials were prepared and tested in vitro against Listeria monocytogenes. Best coating mixtures were then applied on vegetables and submitted to a sensorial analysis. Finally, their effect on the quality, the color and the consistency of vegetables during a one-week storage was determined. All selected coatings showed a total in vitro inhibition of bacteria at concentrations of 8–10 mL L−1. One formulation containing the antimicrobials induced vegetables to have similar characteristics (smell, taste and texture) as compared to the non-treated vegetables. Treatments with this coating generated minor changes concerning the respiration rate and no differences were visually observed on cauliflowers. Finally, in situ analyses showed a good antimicrobial effect and allowed a complete inhibition of Listeria innocua after seven days of storage at 4 °C.

Low-power, high-speed optical interconnects are essential to future high-performance computers and data centers for the cloud. Using CMOS-compatible silicon photonics processes, we have developed integrated photonic devices, such as 80 Gb/s optical modulators with ultralow power consumption at the level of femtojoule per bit and O-band on-chip wavelength multiplexers. These devices are promising for next-generation 400 Gb/s optical interconnects.

Entering pregnancy with overweight, obesity or gaining excessive gestational weight could increase the risk of gestational diabetes mellitus (GDM), which is associated with negative consequences for both the mother and the offspring. The objective of this article was to review scientific evidence regarding the association between obesity and GDM, and how weight management through nutritional prevention strategies could prove successful in reducing the risk for GDM. Studies published between January 1975 and January 2009 on the relationship between GDM, pre-pregnancy body mass index (BMI), gestational weight gain and nutritional prevention strategies were included in this review. Results from these reports suggest that maternal obesity assessed by pre-pregnancy BMI is associated with an increased risk of GDM. They also show an association between gestational weight gain and increased risk for GDM. Higher dietary fat and lower carbohydrate intakes during pregnancy appear to be associated with a higher risk for GDM, independent of pre-pregnancy BMI. Some studies showed that restricting energy and carbohydrates could minimize gestational weight gain. However, a firm conclusion on the most effective nutritional intervention for the control of gestational weight gain and glycaemic responses could not be reached based on available studies. In light of the studies reviewed, we conclude that weight management through nutritional prevention strategies could be successful in reducing the risk of GDM. Further studies are required to identify the most effective diet composition to prevent GDM and excessive gestational weight gain.

Confessions are crucial to successful police investigations but scholars have significantly overlooked factors that contribute to an offender’s decision to confess a crime. This study aims to examine a large array of factors that play a role in the offender’s decision to confess a crime to the police and potential interaction effect among them. A total of 221 adult males incarcerated in a federal Canadian penitentiary were recruited. Correctional files, police reports, and offenders’ self‐reported data were collected and analyzed. Controlling for sociodemographic, criminological, and contextual factors, a series of logistic regression analyses were conducted. Findings highlighted the predominant role of police evidence over and above other factors analyzed. Furthermore, sociodemographic and criminological factors played a more important role in the offender’s decision to confess when police evidence was weak. Findings are discussed in light of the current scientific literature on the determinants of offen...

The study examined 534 hostage and barricade incidents. Its objective was to present an integrated and formalized vision of current conceptualizations of critical incidents to optimize decision making. To this end, logistic regression and recursive partitioning models are presented and compared. In all, 18 distinct static and dynamic individual and situational factors were used to predict various outputs during this type of situation. Results highlight the importance of considering the origin of the emergency call and being barricaded in one's home in the assessment of perpetrator's propensity for violence, the fact that time is not always on the police's side during critical incidents, and the relatively minor importance of hostage taking in the general comprehension of these high-risk events.

Next-generation high-capacity optical networks require flexible allocation of spectrum resources, for which low-cost optical filters with an ultra-wide bandwidth tunability beyond 100 GHz are desired. We demonstrate an integrated band-pass filter with the bandwidth continuously tuned across 670 GHz (117-788 GHz) which, to the best of our knowledge, is the widest tuning span ever demonstrated on a silicon chip. The filter also features simultaneous wavelength tuning and an unlimited free spectral range. We measured an out-of-band contrast of up to 55 dB, low in-band ripples of less than 0.3 dB, and in-band group delay variation of less than 8 ps. This result was achieved using cascaded Bragg-grating-assisted contra-directional couplers and micro-heaters on the 220 nm silicon-on-insulator platform with a very compact footprint of less than 7000 μm2. Another design with the bandwidth continuously tunable from 50 GHz to 1 THz is also presented.

Active shooter-scenarios, terrorist attacks and kidnapping, both domestic and abroad, has increased the need for effective tactical crisis communication. In this chapter we discuss resolution through dialogue and will argue that the models presented can change unfolding events in high-stress situations and alter presumably unnegotiable scenarios. Starting with a backdrop on the evolution of hostage and crisis negotiation, we provide an overview of contemporary approaches following both a forensic psychology, law enforcement and linguistic perspective. You will learn how a communicator in a high-stress situation can adapt a coherent strategy of behavioural change and how active listening is used as a vital tool in negotiations. In the last section you will be presented with an excerpt from an active shooter situation and how the dialogue with the perpetrator unfolded.