bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scene complexity modulates degree of feedback activity during object recognition in natural scenes
Authors: Groen Iris I. A. , Jahfari Sara , Seijdel Noor , Ghebreab Sennary , Lamme Victor A. F. , Scholte H. Steven 
Published: April 2018

AbstractObject recognition is thought to be mediated by rapid feed-forward activation of object-selective cortex, with limited contribution of feedback. However, disruption of visual evoked activity beyond feed-forward processing stages has been demonstrated to affect object recognition performance. Here, we unite these findings by reporting that the detection of target objects in natural scenes is selectively characterized by enhanced feedback when these objects are embedded in high complexity scenes. Human participants performed an animal target detection task on scenes with low, medium or high complexity as determined by a biologically plausible computational model of low-level contrast statistics. Three converging lines of evidence indicate that feedback was enhanced during categorization of scenes with high, but not low or medium complexity. First, functional magnetic resonance imaging (fMRI) activity in early visual cortex (V1) was selectively enhanced for target objects in scenes with high complexity. Second, event-related potentials (ERPs) evoked by high complexity scenes were selectively enhanced from 220 ms after stimulus-onset. Third, behavioral performance deteriorated for highly complex scenes when participants were pressed for time, but not when they could process the scenes fully and thereby benefit from the enhanced feedback. Formal modeling of the reaction time distributions revealed that object information accumulated more slowly for high complexity scenes (resulting in more errors especially for fast decisions), and directly related to the build-up of the feedback activity that was observed exclusively for high complexity scenes. Together, these results suggest that while feed-forward activity may suffice for simple scenes, the brain employs recurrent processing more adaptively in naturalistic settings, using minimal feedback for sparse, coherent scenes and increasing feedback for complex, fragmented scenes.Author summaryHow much neural processing is required to detect objects of interest in natural scenes? The astonishing speed of object recognition suggests that fast feed-forward buildup of perceptual activity is sufficient. However, this view is contradicted by findings that show that disruption of slower neural feedback leads to decreased detection performance. Our study unites these discrepancies by identifying scene complexity as a critical driver of neural feedback. We show how feedback is enhanced for complex, cluttered scenes compared to simple, well-organized scenes. Moreover, for complex scenes, more feedback is associated with better performances. These findings relate the flexibility of neural processes to perceptual decision-making by demonstrating that the brain dynamically directs neural resources based on the complexity of real-world visual inputs.
Velocity and Diameter Measurements of Penetrating Arteries by Model Based Analysis of Complex Difference Images in Phase Contrast MRI
Authors: Zong Xiaopeng , Lin Weili 
Published: April 2018

AbstractPathological changes of penetrating arteries (PAs) within deep white matter (WM) may be an important contributing factor of cerebral small vessel disease (SVD). Quantitative characterization of the PAs is important for further illuminating their roles in SVD but remains challenging due to their sub-voxel sizes. We propose a quantitative MRI approach for measuring the diameters and flow velocities of PAs based on model based analysis of complex difference images in phase contrast MRI. The complex difference image of each PA is fitted by a model image calculated by taking into account the partial volume effect and signal enhancement due to in flow effects to obtain velocity , diameter (D), and volume flow rate (VFR) of the PAs. Simulation, phantom, and in vivo studies were carried out to evaluate the accuracy and measurement errors of the proposed method. Our results suggest that PAs with velocities ≥ 0.8 cm/s can be accurately measured with , D, and VFR errors of 0.28 cm/s, 20 μm, and 0.024 mm3/s, respectively, although the mean lumen area occupies only 18% of the acquired pixel area. The PAs have a distribution peak at ~1.2 cm/s and diameters distribution mostly in the range of 88 – 200 μm Quantitative measurements of PAs with the MBAC method may serve as an invaluable tool for illuminating the role of PAs in the aetiopathogenesis of cerebral SVD.
Hippocampal Pattern Separation Supports Reinforcement Learning
Authors: Ballard Ian , Wagner Anthony D. , McClure Samuel M. 
Published: April 2018

1ABSTRACTAnimals rely on learned associations to make decisions. Associations can be based on relationships between object features (e.g., the three-leaflets of poison ivy leaves) and outcomes (e.g., rash). More often, outcomes are linked to multidimensional states (e.g., poison ivy is green in summer but red in spring). Feature-based reinforcement learning fails when the values of individual features depend on the other features present. One solution is to assign value to multifeatural conjunctive representations. We tested if the hippocampus formed separable conjunctive representations that enabled learning of response contingencies for stimuli of the form: AB+, B-, AC-, C+. Pattern analyses on functional MRI data showed the hippocampus formed conjunctive representations that were dissociable from feature components and that these representations influenced striatal PEs. Our results establish a novel role for hippocampal pattern separation and conjunctive representation in reinforcement learning.
Tissue dependent expression of bitter receptorTAS2R38mRNA
Authors: Douglas Jennifer E. , Lin Cailu , Mansfield Corrine J. , Arayata Charles J. , Cowart Beverly J. , Spielman Andrew I. , Adappa Nithin D. , Palmer James N. , Reed Danielle R. , Cohen Noam A. 
Published: April 2018

AbstractTAS2R38is a human bitter receptor gene with a common but inactive allele and people homozygous for the inactive form cannot perceive certain bitter compounds. The frequency of the inactive and active form of this receptor is nearly equal in many human populations and heterozygotes (with one copy of the active form and another copy of the inactive form) have the most common diplotype. However, heterozygotes differ markedly in their perception of bitterness, in part perhaps because of differences inTAS2R38mRNA expression. Other tissues including the nasal sinuses express this receptor, where it contributes to pathogen defense. We asked whether heterozygotes with highTAS2R38mRNA expression in taste tissue were also likely to express moreTAS2R38mRNA in sinonasal tissue. To that end, we measuredTAS2R38bitter taste receptor mRNA by qPCR in biopsied tissue, and learned that expression amount of one is not related to the other. We confirmed the general independence of expression in other tissue expressingTAS2R38mRNA using autopsy data from the GTEx project. Taste tissueTAS2R38mRNA expression among heterozygotes is unlikely to predict expression in other tissues, perhaps reflecting tissue-dependent function and hence regulation of this protein.
Concurrent Atomic Force Spectroscopy
Authors: Pimenta-Lopes Carolina , Suay-Corredera Carmen , Velázquez-Carreras Diana , Sánchez-Ortiz David , Alegre-Cebollada Jorge 
Published: April 2018

ABSTRACTForce-spectroscopy by Atomic Force Microscopy (AFM) is the technique of choice to measure mechanical properties of molecules, cells, tissues and materials at the nano and micro scales. However, unavoidable calibration errors of AFM probes make it cumbersome to quantify modulation of mechanics. Here, we show that concurrent AFM force measurements enable relative mechanical characterization with an accuracy that is independent of calibration uncertainty, even when averaging data from multiple, independent experiments. Compared to traditional AFM, we estimate that concurrent strategies can measure differences in protein mechanical unfolding forces with a 6-fold improvement in accuracy and a 30-fold increase in throughput. Prompted by our results, we demonstrate widely applicable orthogonal fingerprinting strategies for concurrent single-molecule nanomechanical profiling of proteins.
A Nested 2-Level Cross-validation Ensemble Learning Pipeline Suggests a Negative Pressure Against Crosstalk snoRNA-mRNA Interactions in Saccharomyces Cerevisae
Authors: Soulé Antoine , Steyaert Jean-Marc , Waldispuühl Jéerôme 
Published: April 2018

AbstractThe growing number of RNA-mediated regulation mechanisms identified in the last decades suggests a widespread impact of RNA-RNA interactions. The efficiency of the regulation relies on highly specific and coordinated interactions, while simultaneously repressing the formation of opportunistic complexes. However, the analysis of RNA interactomes is highly challenging due to the large number of potential partners, discrepancy of the size of RNA families, and the inherent noise in interaction predictions.We designed a recursive 2-step cross-validation pipeline to capture the specificity of ncRNA-mRNA interactomes. Our method has been designed to detect significant loss or gain of specificity between ncRNA-mRNA interaction profiles. Applied to snoRNA-mRNA in Saccharomyces Cerevisae, our results suggest the existence of a repression of ncRNA affinities with mRNAs, and thus the existence of an evolutionary pressure inhibiting such interactions.
Deletion of the Creatine Transporter in dopaminergic neurons leads to hyperactivity in mice
Authors: Abdulla Zuhair I. , Pahlevani Bahar , Pennington Jordan L. , Latushka Nikita , R. Skelton Matthew 
Published: April 2018

AbstractCreatine (Cr) is required for proper neuronal function, as evidenced by the intellectual disability and epileptic phenotype seen in patients with cerebral Cr deficiency syndromes (CCDS). In addition, attention-deficit hyperactivity disorder (ADHD) is a frequent co-morbidity of Cr transporter (Crt) deficiency, the leading cause of CCDS. While the effects of the loss of Cr in the whole brain is clear, it is unknown if Cr is required for the proper function of all neurons. Of particular interest are dopaminergic neurons, as many CCDS patients have ADHD and Cr has been implicated in dopamine-associated neurodegenerative disorders, such as Parkinson’s and Huntington’s diseases. The purpose of this study was to examine the effect of a loss of the Slc6a8 (Cr transporter; Crt) gene in cells expressing the dopamine transporter (Slc6a3; DAT) on activity levels and motor function as the animals age. DAT-specific Crt-knockout (DAT-Crt) mice were tested along with control (Crt-FLOX) mice monthly from 3 to 12 months of age in locomotor activity, the challenging beam test, and spontaneous activity. DAT-Crt mice were hyperactive compared with controls and this finding persisted throughout the lifetime of the mice. No changes were observed in errors to cross a narrow bridge in the challenging beam test. In a measurement of spontaneous activity, DAT-Crt mice showed increased rearing and hind limb steps, suggesting the hyperactivity carried over to this task. Taken together, these data suggest that the lack of Cr in dopaminergic neurons causes hyperactivity while sparing motor function.AbbreviationsCrCreatineCKCreatine KinaseP-CrPhosphocreatinePDParkinson’s DiseaseMPTP1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine6-OHDA6-hydroxydopamineCrtCreatine TransporterCrt-/yubiquitous creatine transporter knockout mouseDAT-Crt-/ydopamine-specific creatine transporter knockout mouse ADHD: Attention-deficit hyperactivity disorder
Corticostriatal oscillations predict high vs. low drinkers in a preclinical model of limited access alcohol consumption
Authors: Henricks Angela M. , Dwiel Lucas L. , Deveau Nicholas H. , Simon Amanda A. , Ruiz-Jaquez Metztli J. , Green Alan I. , Doucette Wilder T. 
Published: April 2018

AbstractIndividuals differ in their vulnerability to develop alcohol dependence that are determined by innate and environmental factors. The corticostriatal circuit is heavily involved in the development of alcohol dependence and may contain neural information regarding vulnerability to drink excessively. In the current experiment, we hypothesized that we could characterize high and low alcohol-drinking rats (HD and LD, respectively) based on corticostriatal oscillations, and that these subgroups would differentially respond to corticostriatal brain stimulation. Rats were trained to drink 10% alcohol in a limited access paradigm. In separate sessions, local field potentials (LFPs) were recorded from the nucleus accumbens shell (NAcSh) and medial prefrontal cortex (mPFC) of male Sprague-Dawley rats (n=13). Based on training alcohol consumption levels, we classified rats using a median split as HD or LD. Then, using machine-learning, we built predictive models to classify rats as HD or LD by corticostriatal LFPs and compared the model performance from real data to the performance of models built on data permutations. Additionally, we explored the impact of NAcSh or mPFC stimulation on alcohol consumption in HD vs. LD. Corticostriatal LFPs were able predict HD vs. LD group classification with greater accuracy than expected by chance (>80% accuracy). Additionally, NAcSh stimulation significantly reduced alcohol consumption in HD, but not LD (p<0.05), while mPFC stimulation did not alter drinking behavior in either HD or LD (p>0.05). These data collectively show that the corticostriatal circuit is differentially involved in regulating alcohol intake in HD vs. LD rats, and suggests that corticostriatal activity may have the potential to predict a vulnerability to develop alcohol dependence in a clinical population.
Stability Criteria for Complex Microbial Communities
Authors: Butler Stacey , O’Dwyer James 
Published: April 2018

AbstractCompetition and mutualism are inevitable processes in microbial ecology, and a central question is which and how many taxa will persist in the face of these interactions. Ecological theory has demonstrated that when direct, pairwise interactions among a group of species are too numerous, or too strong, then the coexistence of these species will be unstable to any slight perturbation. This instability worsens when mutualistic interactions complement competition. Here, we refine and to some extent overturn that understanding, by considering explicitly the resources that microbes consume and produce. In contrast to more complex organisms, microbial cells consume primarily abiotic resources, and mutualistic interactions are often mediated by these same abiotic resources through the mechanism of cross-feeding. Our model therefore considers the consumption and production of a set of abiotic resources by a group of microbial species. We show that if microbes consume, but do not produce resources, then any positive equilibrium will always be stable to small perturbations. We go on to show that in the presence of crossfeeding, stability is no longer guaranteed. However, stability still holds when mutualistic interations are either symmetric, or sufficiently weak.
Forecasting Future Humphrey Visual Fields Using Deep Learning
Authors: Wen Joanne C. , Lee Cecilia S. , Keane Pearse A. , Xiao Sa , Wu Yue , Rokem Ariel , Chen Philip P. , Lee Aaron Y. 
Published: April 2018

ABSTRACTPurposeTo determine if deep learning networks could be trained to forecast a future 24-2 Humphrey Visual Field (HVF).DesignRetrospective database study.ParticipantsAll patients who obtained a HVF 24-2 at the University of Washington.MethodsAll datapoints from consecutive 24-2 HVFs from 1998 to 2018 were extracted from a University of Washington database. Ten-fold cross validation with a held out test set was used to develop the three main phases of model development: model architecture selection, dataset combination selection, and time-interval model training with transfer learning, to train a deep learning artificial neural network capable of generating a point-wise visual field prediction.Main outcome measuresMean absolute error (MAE) and difference in Mean Deviation (MD) between predicted and actual future HVF.ResultsMore than 1.7 million perimetry points were extracted to the hundredth decibel from 32,443 24-2 HVFs. The best performing model with 20 million trainable parameters, CascadeNet-5, was selected. The overall MAE for the test set was 2.47 dB (95% CI: 2.45 dB to 2.48 dB). The 100 fully trained models were able to successfully predict progressive field loss in glaucomatous eyes up to 5.5 years in the future with a correlation of 0.92 between the MD of predicted and actual future HVF (p < 2.2 = 10−16) and an average difference of 0.41 dB.ConclusionsUsing unfiltered real-world datasets, deep learning networks show an impressive ability to not only learn spatio-temporal HVF changes but also to generate predictions for future HVFs up to 5.5 years, given only a single HVF.
Predicting landscape‐level distribution and abundance: Integrating demography, fire, elevation and landscape habitat configuration
Authors: Quintana‐Ascencio Pedro F. , Koontz Stephanie M. , Smith Stacy A. , Sclater Vivienne L. , David Aaron S. , Menges Eric S. 
Published: April 2018

Abstract

Demography varies in response to multiple interactive drivers at varying scales. However, these relationships are often assessed piecemeal, particularly without consideration of drivers at the landscape level.

We developed a model to predict population dynamics of an endangered, perennial herb Hypericum cumulicola across a range of landscape drivers. We estimated vital rates using 22 years of annual census data from 15 populations (10,910 and 38,313 unique observations) and additional seeding experiments, considering four landscape drivers (time‐since‐fire, patch area, patch aggregation and patch elevation).

We combined these models into integral projection models to assess population parameters. Predictions of occupancy and density were compared with an independent dataset of 33 habitat patches. We also evaluated the effect of fire‐return interval on population persistence.

The landscape drivers had interactive effects on vital rates and demography. Occupancy was predicted for most patches, including many that were unoccupied. Abundances were poorly predicted, primarily because projections were unreliable for patches having intermediate areas and aggregation. When these patches were removed, the model explained 42% of the variance in abundance. Projected population growth was greater and extinction risk lower under more frequent fire‐return intervals, at higher elevations, and in larger and more aggregated patches. Our modelling suggests that fire can be prescribed less often in larger than smaller patches to support a viable metapopulation of H. cumulicola.

Synthesis. The integration of landscape‐level drivers and detailed demographic data is a valuable tool for understanding species abundances, distributions and dynamics at large scales. We evaluated the effect of interactions among fire, patch elevation, area and aggregation on the demography of a rare and endangered plant. Our findings reinforce the importance of regional dynamics. These drivers and their interactions suggest locations that can support higher vital rates, occupancy and abundance, and what fire‐return intervals are optimal depending on landscape characteristics. This approach demonstrates a link between plant demography and landscape variables, although further work is needed to improve ecological predictions.
Review article: A primer for clinical researchers in the emergency department: Part VI. Measuring what matters: Core outcome sets in emergency medicine research
Authors: Craig Simon , Graudins Andis , Dalziel Stuart R , Powell Colin VE , Babl Franz E 
Published: April 2018

AbstractIn this series we address important topics for clinicians who participate in research as part of their work in the ED. The overarching goal of clinical research is to improve care and determine which treatment is best. Yet, defining and measuring outcomes – what is ‘best’ – can be one of the most difficult steps in the design of a study, in particular when answers to research questions cannot be captured in simple binary results. This article addresses how to choose outcome measures and highlights the increasingly important concept of core outcome sets.
microRNA‐181a inhibits ocular neovascularization by interfering with vascular endothelial growth factor expression
Authors: Yang Chun , Tahiri Houda , Cai Chenrongrong , Gu Muqing , Gagnon Carmen , Hardy Pierre 
Published: April 2018

SummaryAimExcess angiogenesis or neovascularization plays a key role in the pathophysiology of several ocular diseases such as retinopathy of prematurity, diabetic retinopathy, and exudative age‐related macular degeneration. microRNA‐181a (miR‐181a) was found highly expressed in retina and choroidal tissues. This study intends to investigate the role of miR‐181a in the regulation of ocular neovascularization in different pathophysiological conditions.MethodWe performed the RNA sequence to identify the microRNAs components of anti‐angiogenic lymphocyte‐derived microparticles (LMPs). The effect of miR‐181a on human retinal endothelial cells proliferation was assessed in vitro. The impact of miR‐181a on angiogenesis was confirmed using in vitro angiogenesis assay, ex vivo choroidal explant, and in vivo retinal neovascularization. The expression of major angiogenic factors was assessed by real‐time qPCR.ResultsRNA sequence revealed that miR‐181a is selectively enriched in LMPs. Importantly, the inhibition of miR‐181a significantly abrogated the effect of LMPs on endothelial viability, but overexpression of miR‐181a reduced endothelial cell viability in a dose‐dependent manner. miR‐181a strongly inhibited in vitro angiogenesis and ex vivo choroidal neovascularization. The strong anti‐angiogenic effect of miR‐181a was also displayed on the retinal neovascularization of the in vivo mouse model of oxygen‐induced retinopathy. In keeping with its effect, several angiogenesis‐related genes were dysregulated in the miR‐181a overexpressed endothelial cells.ConclusionThese data may open unexpected avenues for the development of miR‐181a as a novel therapeutic strategy that would be particularly useful and relevant for the treatment of neovascular diseases.