Feature-Based Attentional Weighting and Re-weighting in the Absence of Visual Awareness

Published: 29 January 2021.Visual attention evolved as an adaptive mechanism allowing us to cope with a rapidly changing environment. It enables the facilitated processing of relevant information, often automatically and governed by implicit motives. However, despite recent advances in understanding the relationship between consciousness and visual attention, the functional scope of unconscious attentional control is still under debate. Here, we present a novel masking paradigm in which volunteers were to distinguish between varying orientations of a briefly presented, masked grating stimulus. Combining signal detection theory and subjective measures of awareness, we show that performance on unaware trials was consistent with visual selection being weighted towards repeated orientations of Gabor patches and reallocated in response to a novel unconsciously processed orientation. This was particularly present in trials in which the prior feature was strongly weighted and only if the novel feature was invisible. Thus, our results provide evidence that invisible orientation stimuli can trigger the reallocation of history-guided visual selection weights.The project was funded in part by DFG-grant SFB1436-C02 to SP. DS acknowledges support from project grant PSI2016-76443-P from the Spanish Ministry of Science and the “Severo Ochoa” Programme for Centres/Units of Excellence in R & D (SEV-2015-490)

MINT-Lehrkräfte gesucht. Wo bleibt der Nachwuchs?

In der Bedarfskrise nehmen die MINT-Fächer eine zentrale Rolle ein und werden auch perspektivisch eine Herausforderung in der Bewältigung dieser Krise bleiben (vgl. Klemm 2020). Eine Ursache dafür liegt in der geringen Anzahl der Nachwuchslehrkräfte und damit der Ausbildung begründet. Tatsächlich weisen gerade die MINT-Fächer einen hohen Ersatzbedarf in den Schulen, jedoch teilweise wenige Studienanfänger:innen, hohen Schwund und geringe Absolvent:innenzahlen auf. Dabei zeigt sich sowohl bei den Bedarfen als auch bei der Betrachtung der Studiengänge, dass innerhalb der MINT-Fächer große Unterschiede bestehen (vgl. KMK 2020a, Heublein u. a. 2017). Dies konnte auch für Mecklenburg-Vorpommern bestätigt werden, wo seit 2017 die Studienverläufe der Lehramtsstudierenden betrachtet werden. Ausgehend von diesen Studien werden im Beitrag die Unterschiede zwischen den MINT-Fächern sowie die Verläufe der Studierenden in den verschiedenen Lehramtstypen genauer betrachtet und mögliche Maßnahmen diskutiert. (DIPF/Orig.

MPact: the MIPS protein interaction resource on yeast

In recent years, the Munich Information Center for Protein Sequences (MIPS) yeast protein–protein interaction (PPI) dataset has been used in numerous analyses of protein networks and has been called a gold standard because of its quality and comprehensiveness [H. Yu, N. M. Luscombe, H. X. Lu, X. Zhu, Y. Xia, J. D. Han, N. Bertin, S. Chung, M. Vidal and M. Gerstein (2004) Genome Res., 14, 1107–1118]. MPact and the yeast protein localization catalog provide information related to the proximity of proteins in yeast. Beside the integration of high-throughput data, information about experimental evidence for PPIs in the literature was compiled by experts adding up to 4300 distinct PPIs connecting 1500 proteins in yeast. As the interaction data is a complementary part of CYGD, interactive mapping of data on other integrated data types such as the functional classification catalog [A. Ruepp, A. Zollner, D. Maier, K. Albermann, J. Hani, M. Mokrejs, I. Tetko, U. Güldener, G. Mannhaupt, M. Münsterkötter and H. W. Mewes (2004) Nucleic Acids Res., 32, 5539–5545] is possible. A survey of signaling proteins and comparison with pathway data from KEGG demonstrates that based on these manually annotated data only an extensive overview of the complexity of this functional network can be obtained in yeast. The implementation of a web-based PPI-analysis tool allows analysis and visualization of protein interaction networks and facilitates integration of our curated data with high-throughput datasets. The complete dataset as well as user-defined sub-networks can be retrieved easily in the standardized PSI-MI format. The resource can be accessed through

FGDB: a comprehensive fungal genome resource on the plant pathogen Fusarium graminearum

The MIPS Fusarium graminearum Genome Database (FGDB) is a comprehensive genome database on one of the most devastating fungal plant pathogens of wheat and barley. FGDB provides information on two gene sets independently derived by automated annotation of the F.graminearum genome sequence. A complete manually revised gene set will be completed within the near future. The initial results of systematic manual correction of gene calls are already part of the current gene set. The database can be accessed to retrieve information from bioinformatics analyses and functional classifications of the proteins. The data are also organized in the well established MIPS catalogs and novel query techniques are available to search the data. The comprehensive set of gene calls was also used for the design of an Affymetrix GeneChip. The resource is accessible on

Endophytic Life Strategies Decoded by Genome and Transcriptome Analyses of the Mutualistic Root Symbiont Piriformospora indica

Recent sequencing projects have provided deep insight into fungal lifestyle-associated genomic adaptations. Here we report on the 25 Mb genome of the mutualistic root symbiont Piriformospora indica (Sebacinales, Basidiomycota) and provide a global characterization of fungal transcriptional responses associated with the colonization of living and dead barley roots. Extensive comparative analysis of the P. indica genome with other Basidiomycota and Ascomycota fungi that have diverse lifestyle strategies identified features typically associated with both, biotrophism and saprotrophism. The tightly controlled expression of the lifestyle-associated gene sets during the onset of the symbiosis, revealed by microarray analysis, argues for a biphasic root colonization strategy of P. indica. This is supported by a cytological study that shows an early biotrophic growth followed by a cell death-associated phase. About 10% of the fungal genes induced during the biotrophic colonization encoded putative small secreted proteins (SSP), including several lectin-like proteins and members of a P. indica-specific gene family (DELD) with a conserved novel seven-amino acids motif at the C-terminus. Similar to effectors found in other filamentous organisms, the occurrence of the DELDs correlated with the presence of transposable elements in gene-poor repeat-rich regions of the genome. This is the first in depth genomic study describing a mutualistic symbiont with a biphasic lifestyle. Our findings provide a significant advance in understanding development of biotrophic plant symbionts and suggest a series of incremental shifts along the continuum from saprotrophy towards biotrophy in the evolution of mycorrhizal association from decomposer fungi

PEDANT covers all complete RefSeq genomes

The PEDANT genome database provides exhaustive annotation of nearly 3000 publicly available eukaryotic, eubacterial, archaeal and viral genomes with more than 4.5 million proteins by a broad set of bioinformatics algorithms. In particular, all completely sequenced genomes from the NCBI's Reference Sequence collection (RefSeq) are covered. The PEDANT processing pipeline has been sped up by an order of magnitude through the utilization of precalculated similarity information stored in the similarity matrix of proteins (SIMAP) database, making it possible to process newly sequenced genomes immediately as they become available. PEDANT is freely accessible to academic users at http://pedant.gsf.de. For programmatic access Web Services are available at http://pedant.gsf.de/webservices.jsp

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

A centrality measure for cycles and subgraphs II

In a recent work we introduced a measure of importance for groups of vertices in a complex network. This centrality for groups is always between 0 and 1 and induces the eigenvector centrality over vertices. Furthermore, its value over any group is the fraction of all network flows intercepted by this group. Here we provide the rigorous mathematical constructions underpinning these results via a semi-commutative extension of a number theoretic sieve. We then established further relations between the eigenvector centrality and the centrality proposed here, showing that the latter is a proper extension of the former to groups of nodes. We finish by comparing the centrality proposed here with the notion of group-centrality introduced by Everett and Borgatti on two real-world networks: the Wolfe’s dataset and the protein-protein interaction network of the yeast Saccharomyces cerevisiae. In this latter case, we demonstrate that the centrality is able to distinguish protein complexe

Genome analysis of the necrotrophic fungal pathogens Sclerotinia sclerotiorum and Botrytis cinerea

Sclerotinia sclerotiorum and Botrytis cinerea are closely related necrotrophic plant pathogenic fungi notable for their wide host ranges and environmental persistence. These attributes have made these species models for understanding the complexity of necrotrophic, broad host-range pathogenicity. Despite their similarities, the two species differ in mating behaviour and the ability to produce asexual spores. We have sequenced the genomes of one strain of S. sclerotiorum and two strains of B. cinerea. The comparative analysis of these genomes relative to one another and to other sequenced fungal genomes is provided here. Their 38–39 Mb genomes include 11,860–14,270 predicted genes, which share 83% amino acid identity on average between the two species. We have mapped the S. sclerotiorum assembly to 16 chromosomes and found large-scale co-linearity with the B. cinerea genomes. Seven percent of the S. sclerotiorum genome comprises transposable elements compared t