Cue-target contingencies modulate voluntary orienting of spatial attention: dissociable effects for speed and accuracy

Voluntary orienting of spatial attention is typically investigated by visually presented directional cues, which are called predictive when they indicate where the target is more likely to appear. In this study, we investigated the nature of the potential link between cue predictivity (the proportion of valid trials) and the strength of the resulting covert orienting of attention. Participants judged the orientation of a unilateral Gabor grating preceded by a centrally presented, non-directional, color cue, arbitrarily prompting a leftwards or rightwards shift of attention. Unknown to them, cue predictivity was manipulated across blocks, whereby the cue was only predictive for either the first or the second half of the experiment. Our results show that the cueing effects were strongly influenced by the change in predictivity. This influence differently emerged in response speed and accuracy. The speed difference between valid and invalid trials was significantly larger when cues were predictive, and the amplitude of this effect was modulated at the single trial level by the recent trial history. Complementary to these findings, accuracy revealed a robust effect of block history and also a different time-course compared with speed, as if it mainly mirrored voluntary processes. These findings, obtained with a new manipulation and using arbitrary non-directional cueing, demonstrate that cue-target contingencies strongly modulate the way attention is deployed in space

Evaluation of O2PLS in Omics data integration

Background: Rapid computational and technological developments made large amounts of omics data available in different biological levels. It is becoming clear that simultaneous data analysis methods are needed for better interpretation and understanding of the underlying systems biology. Different methods have been proposed for this task, among them Partial Least Squares (PLS) related methods. To also deal with orthogonal variation, systematic variation in the data unrelated to one another, we consider the Two-way Orthogonal PLS (O2PLS): an integrative data analysis method which is capable of modeling systematic variation, while providing more parsimonious models aiding interpretation. Results: A simulation study to assess the performance of O2PLS showed positive results in both low and higher dimensions. More noise (50 % of the data) only affected the systematic part estimates. A data analysis was conducted using data on metabolomics and transcriptomics from a large Finnish cohort (DILGOM). A previous sequential study, using the same data, showed significant correlations between the Lipo-Leukocyte (LL) module and lipoprotein metabolites. The O2PLS results were in agreement with these findings, identifying almost the same set of co-varying variables. Moreover, our integrative approach identified other associative genes and metabolites, while taking into account systematic variation in the data. Including orthogonal components enhanced overall fit, but the orthogonal variation was difficult to interpret. Conclusions: Simulations showed that the O2PLS estimates were close to the true parameters in both low and higher dimensions. In the presence of more noise (50 %), the orthogonal part estimates could not distinguish well between joint and unique variation. The joint estimates were not systematically affected. Simultaneous analysis with O2PLS on metabolome and transcriptome data showed that the LL module, together with VLDL and HDL metabolites, were important for the metabolomic and transcriptomic relation. This is in agreement with an earlier study. In addition more gene expression and metabolites are identified being important for the joint covariation

oA novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology

<p>Abstract</p> <p>Background</p> <p>Epidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator.</p> <p>Methods</p> <p>Using data from a representative large multistage longitudinal epidemiological study in a primary care setting in Germany, this paper explores a novel approach for estimating optimal cut-offs of anthropomorphic parameters for predicting type 2 diabetes based on a discontinuity of a regression function in a nonparametric regression framework.</p> <p>Results</p> <p>The resulting cut-off corresponded to values obtained by the Youden Index (maximum of the sum of sensitivity and specificity, minus one), often considered the optimal cut-off in epidemiological and biomedical research. The nonparametric regression based estimator was compared to results obtained by the established methods of the Receiver Operating Characteristic plot in various simulation scenarios and based on bias and root mean square error, yielded excellent finite sample properties.</p> <p>Conclusion</p> <p>It is thus recommended that this nonparametric regression approach be considered as valuable alternative when a continuous indicator has to be dichotomized at the Youden Index for prediction or decision purposes.</p

Toward a model-based predictive controller design in brain-computer interfaces

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.Grants K25NS061001 (MK) and K02MH01493 (SJS) from the National Institute of Neurological Disorders And Stroke (NINDS) and the National Institute of Mental Health (NIMH), the Portuguese Foundation for Science and Technology (FCT) Grant SFRH/BD/21529/2005 (NSD), the Pennsylvania Department of Community and Economic Development Keystone Innovation Zone Program Fund (SJS), and the Pennsylvania Department of Health using Tobacco Settlement Fund (SJS)

Cohesin Proteins Promote Ribosomal RNA Production and Protein Translation in Yeast and Human Cells

Cohesin is a protein complex known for its essential role in chromosome segregation. However, cohesin and associated factors have additional functions in transcription, DNA damage repair, and chromosome condensation. The human cohesinopathy diseases are thought to stem not from defects in chromosome segregation but from gene expression. The role of cohesin in gene expression is not well understood. We used budding yeast strains bearing mutations analogous to the human cohesinopathy disease alleles under control of their native promoter to study gene expression. These mutations do not significantly affect chromosome segregation. Transcriptional profiling reveals that many targets of the transcriptional activator Gcn4 are induced in the eco1-W216G mutant background. The upregulation of Gcn4 was observed in many cohesin mutants, and this observation suggested protein translation was reduced. We demonstrate that the cohesinopathy mutations eco1-W216G and smc1-Q843Δ are associated with defects in ribosome biogenesis and a reduction in the actively translating fraction of ribosomes, eiF2α-phosphorylation, and 35S-methionine incorporation, all of which indicate a deficit in protein translation. Metabolic labeling shows that the eco1-W216G and smc1-Q843Δ mutants produce less ribosomal RNA, which is expected to constrain ribosome biogenesis. Further analysis shows that the production of rRNA from an individual repeat is reduced while copy number remains unchanged. Similar defects in rRNA production and protein translation are observed in a human Roberts syndrome cell line. In addition, cohesion is defective specifically at the rDNA locus in the eco1-W216G mutant, as has been previously reported for Roberts syndrome. Collectively, our data suggest that cohesin proteins normally facilitate production of ribosomal RNA and protein translation, and this is one way they can influence gene expression. Reduced translational capacity could contribute to the human cohesinopathies

Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018.

Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field