The relationship between gambling event frequency, motor response inhibition, arousal, and dissociative experience

Speed of play has been identified as a key structural characteristic in gambling behaviour, where games involving higher playing speeds enhance the experience of gambling. Of interest in the present study is the consistent finding that games with higher event frequencies are preferred by problem gamblers and are associated with more negative gambling outcomes, such as difficulty quitting the game and increased monetary loss. The present study investigated the impact of gambling speed of play on executive control functioning, focusing on how increased speeds of play impact motor response inhibition, and the potential mediating role arousal and dissociative experience play in this relationship. Fifty regular non-problem gamblers took part in a repeated-measures experiment where they gambled with real money on a simulated slot machine across five speed of play conditions. Response inhibition was measured using an embedded Go/No-Go task, where participants had to withhold motor responses, rather than operating the spin button on the slot machine when a specific colour cue was present. Results indicated that response inhibition performance was significantly worse during faster speeds of play, and that the role of arousal in this relationship was independent of any motor priming affect. The implications of these findings for gambling legislation and gambling harm-minimisation approaches are discussed

Partitioning of on-demand electron pairs

We demonstrate the high fidelity splitting of electron pairs emitted on demand from a dynamic quantum dot by an electronic beam splitter. The fidelity of pair splitting is inferred from the coincidence of arrival in two detector paths probed by a measurement of the partitioning noise. The emission characteristic of the on-demand electron source is tunable from electrons being partitioned equally and independently to electron pairs being split with a fidelity of 90%. For low beam splitter transmittance we further find evidence of pair bunching violating statistical expectations for independent fermions

Chances and Limitations of Wild Bird Monitoring for the Avian Influenza Virus H5N1 — Detection of Pathogens Highly Mobile in Time and Space

Highly pathogenic influenza virus (HPAIV) H5N1 proved to be remarkably mobile in migratory bird populations where it has led to extensive outbreaks for which the true number of affected birds usually cannot be determined. For the evaluation of avian influenza monitoring and HPAIV early warning systems, we propose a time-series analysis that includes the estimation of confidence intervals for (i) the prevalence in outbreak situations or (ii) in the apparent absence of disease in time intervals for specified regional units. For the German outbreak regions in 2006 and 2007, the upper 95% confidence limit allowed the detection of prevalences below 1% only for certain time intervals. Although more than 25,000 birds were sampled in Germany per year, the upper 95% confidence limit did not fall below 5% in the outbreak regions for most of the time. The proposed analysis can be used to monitor water bodies and high risk areas, also as part of an early-warning system. Chances for an improved targeting of the monitoring system as part of a risk-based approach are discussed with the perspective of reducing sample sizes

Farm Area Segmentation in Satellite Images Using DeepLabv3+ Neural Networks

Farm detection using low resolution satellite images is an important part of digital agriculture applications such as crop yield monitoring. However, it has not received enough attention compared to high-resolution images. Although high resolution images are more efficient for detection of land cover components, the analysis of low-resolution images are yet important due to the low-resolution repositories of the past satellite images used for timeseries analysis, free availability and economic concerns. In this paper, semantic segmentation of farm areas is addressed using low resolution satellite images. The segmentation is performed in two stages; First, local patches or Regions of Interest (ROI) that include farm areas are detected. Next, deep semantic segmentation strategies are employed to detect the farm pixels. For patch classification, two previously developed local patch classification strategies are employed; a two-step semi-supervised methodology using hand-crafted features and Support Vector Machine (SVM) modelling and transfer learning using the pretrained Convolutional Neural Networks (CNNs). For the latter, the high-level features learnt from the massive filter banks of deep Visual Geometry Group Network (VGG-16) are utilized. After classifying the image patches that contain farm areas, the DeepLabv3+ model is used for semantic segmentation of farm pixels. Four different pretrained networks, resnet18, resnet50, resnet101 and mobilenetv2, are used to transfer their learnt features for the new farm segmentation problem. The first step results show the superiority of the transfer learning compared to hand-crafted features for classification of patches. The second step results show that the model trained based on resnet50 achieved the highest semantic segmentation accuracy.acceptedVersionPeer reviewe

The modulation of adult neuroplasticity is involved in the mood-improving actions of atypical antipsychotics in an animal model of depression

Depression is a prevalent psychiatric disorder with an increasing impact in global public health. However, a large proportion of patients treated with currently available antidepressant drugs fail to achieve remission. Recently, antipsychotic drugs have received approval for the treatment of antidepressant-resistant forms of major depression. The modulation of adult neuroplasticity, namely hippocampal neurogenesis and neuronal remodeling, has been considered to have a key role in the therapeutic effects of antidepressants. However, the impact of antipsychotic drugs on these neuroplastic mechanisms remains largely unexplored. In this study, an unpredictable chronic mild stress protocol was used to induce a depressive-like phenotype in rats. In the last 3 weeks of stress exposure, animals were treated with two different antipsychotics: haloperidol (a classical antipsychotic) and clozapine (an atypical antipsychotic). We demonstrated that clozapine improved both measures of depressive-like behavior (behavior despair and anhedonia), whereas haloperidol aggravated learned helplessness in the forced-swimming test and behavior flexibility in a cognitive task. Importantly, an upregulation of adult neurogenesis and neuronal survival was observed in animals treated with clozapine, whereas haloperidol promoted a downregulation of these processes. Furthermore, clozapine was able to re-establish the stress-induced impairments in neuronal structure and gene expression in the hippocampus and prefrontal cortex. These results demonstrate the modulation of adult neuroplasticity by antipsychotics in an animal model of depression, revealing that the atypical antipsychotic drug clozapine reverts the behavioral effects of chronic stress by improving adult neurogenesis, cell survival and neuronal reorganization.This work was co-funded by the Life and Health Sciences Research Institute (ICVS), and Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (Projects NORTE-01-0145-FEDER-000013 and NORTE-01-0145-FEDER-000023). This work has been also funded by FEDER funds, through the Competitiveness Factors Operational Programme (COMPETE) and by National funds, through the FCT, under the scope of the project POCI-01-0145-FEDER-007038. We thank Luís Martins and Ana Lima for the technical assistanceinfo:eu-repo/semantics/publishedVersio

Seeing Emotion with Your Ears: Emotional Prosody Implicitly Guides Visual Attention to Faces

Interpersonal communication involves the processing of multimodal emotional cues, particularly facial expressions (visual modality) and emotional speech prosody (auditory modality) which can interact during information processing. Here, we investigated whether the implicit processing of emotional prosody systematically influences gaze behavior to facial expressions of emotion. We analyzed the eye movements of 31 participants as they scanned a visual array of four emotional faces portraying fear, anger, happiness, and neutrality, while listening to an emotionally-inflected pseudo-utterance (Someone migged the pazing) uttered in a congruent or incongruent tone. Participants heard the emotional utterance during the first 1250 milliseconds of a five-second visual array and then performed an immediate recall decision about the face they had just seen. The frequency and duration of first saccades and of total looks in three temporal windows ([0–1250 ms], [1250–2500 ms], [2500–5000 ms]) were analyzed according to the emotional content of faces and voices. Results showed that participants looked longer and more frequently at faces that matched the prosody in all three time windows (emotion congruency effect), although this effect was often emotion-specific (with greatest effects for fear). Effects of prosody on visual attention to faces persisted over time and could be detected long after the auditory information was no longer present. These data imply that emotional prosody is processed automatically during communication and that these cues play a critical role in how humans respond to related visual cues in the environment, such as facial expressions

Cardiac abnormalities in adults with the attenuated form of mucopolysaccharidosis type I

Background: Cardiac involvement in mucopolysaccharidosis type I (MPS I) has been studied primarily in its most severe forms. Cardiac involvement, particularly left ventricular (LV) systolic and diastolic function, in the attenuated form of MPS I is less well known. Methods: Cardiac function was prospectively investigated in 9 adult patients with the attenuated form of MPS I. All patients underwent 12-lead electrocardiography, 24 h Holter monitoring and two-dimensional echocardiography including tissue Doppler imaging (TDI). Eighteen age- and sex-matched healthy volunteers served as a control group. Results: Aortic, mitral and tricuspid valve thickening was seen in, respectively, 5 (56%), 4 (44%) and 2 (22%) patients. Moderate mitral valve stenosis was seen in 1 patient and moderate aortic stenosis in 2 patients. All patients had mild-to-moderate aortic and mitral valve regurgitation and 6 patients (67%) had mild-to-moderate tricuspid valve regurgitation. Despite normal LV dimensions, ejection fraction and mass index, MPS patients had lower mean systolic mitral annular velocities (6.1±0.6 vs 9.1±1.4 cm/s, p<0.01) compared to normal control subjects. Similarly, mean early diastolic mitral annular velocities were lower in MPS patients (7.8±0.9 vs 13.3±3.3 cm/s, p<0.01). Conclusion: MPS I patients with the attenuated phenotype have not only valvular abnormalities but also LV diastolic and systolic abnormalities

Baseline mitral regurgitation predicts outcome in patients referred for dobutamine stress echocardiography

Purpose: A number of parameters recorded during dobutamine stress echocardiography (DSE) are associated with worse outcome. However, the relative importance of baseline mitral regurgitation (MR) is unknown. The aim of this study was to assess the prevalence and associated implications of functional MR with long-term mortality in a large cohort of patients referred for DSE. Methods: 6745 patients (mean age 64.9±12.2 years) were studied. Demographic, baseline and peak DSE data were collected. All-cause mortality was retrospectively analyzed. DSE was successfully completed in all patients with no adverse outcomes. Results: MR was present in 1019 (15.1%) patients. During a mean follow up of 5.1±1.8 years, 1642 (24.3%) patients died and MR was significantly associated with increased all-cause mortality (p<0.001). With Kaplan-Meier analysis, survival was significantly worse for patients with moderate and severe MR (p<0.001). With multivariate Cox regression analysis, moderate and severe MR (HR 2.78; 95% CI 2.17 - 3.57; and HR 3.62; 95% CI 2.89 - 4.53, respectively) were independently associated with all-cause mortality. The addition of MR to C statistic models significantly improved discrimination. Conclusions: MR is associated with all-cause mortality and adds incremental prognostic information among patients referred for DSE. The presence of MR should be taken into account when evaluating the prognostic significance of DSE results

The generation of phase differences and frequency changes in a network model of inferior olive subthreshold oscillations

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedicationIt is commonly accepted that the Inferior Olive (IO) provides a timing signal to the cerebellum. Stable subthreshold oscillations in the IO can facilitate accurate timing by phase-locking spikes to the peaks of the oscillation. Several theoretical models accounting for the synchronized subthreshold oscillations have been proposed, however, two experimental observations remain an enigma. The first is the observation of frequent alterations in the frequency of the oscillations. The second is the observation of constant phase differences between simultaneously recorded neurons. In order to account for these two observations we constructed a canonical network model based on anatomical and physiological data from the IO. The constructed network is characterized by clustering of neurons with similar conductance densities, and by electrical coupling between neurons. Neurons inside a cluster are densely connected with weak strengths, while neurons belonging to different clusters are sparsely connected with stronger connections. We found that this type of network can robustly display stable subthreshold oscillations. The overall frequency of the network changes with the strength of the inter-cluster connections, and phase differences occur between neurons of different clusters. Moreover, the phase differences provide a mechanistic explanation for the experimentally observed propagating waves of activity in the IO. We conclude that the architecture of the network of electrically coupled neurons in combination with modulation of the inter-cluster coupling strengths can account for the experimentally observed frequency changes and the phase differences.Peer reviewedFinal Published versio