@article{DumontWeberLassalleJolyBeauparlantetal.2022, author = {Dumont, Martine and Weber-Lassalle, Nana and Joly-Beauparlant, Charles and Ernst, Corinna and Droit, Arnaud and Feng, Bing-Jian and Dubois, St{\´e}phane and Collin-Deschesnes, Annie-Claude and Soucy, Penny and Vall{\´e}e, Maxime and Fournier, Fr{\´e}d{\´e}ric and Lema{\c{c}}on, Audrey and Adank, Muriel A. and Allen, Jamie and Altm{\"u}ller, Janine and Arnold, Norbert and Ausems, Margreet G. E. M. and Berutti, Riccardo and Bolla, Manjeet K. and Bull, Shelley and Carvalho, Sara and Cornelissen, Sten and Dufault, Michael R. and Dunning, Alison M. and Engel, Christoph and Gehrig, Andrea and Geurts-Giele, Willemina R. R. and Gieger, Christian and Green, Jessica and Hackmann, Karl and Helmy, Mohamed and Hentschel, Julia and Hogervorst, Frans B. L. and Hollestelle, Antoinette and Hooning, Maartje J. and Horv{\´a}th, Judit and Ikram, M. Arfan and Kaulfuß, Silke and Keeman, Renske and Kuang, Da and Luccarini, Craig and Maier, Wolfgang and Martens, John W. M. and Niederacher, Dieter and N{\"u}rnberg, Peter and Ott, Claus-Eric and Peters, Annette and Pharoah, Paul D. P. and Ramirez, Alfredo and Ramser, Juliane and Riedel-Heller, Steffi and Schmidt, Gunnar and Shah, Mitul and Scherer, Martin and St{\"a}bler, Antje and Strom, Tim M. and Sutter, Christian and Thiele, Holger and van Asperen, Christi J. and van der Kolk, Lizet and van der Luijt, Rob B. and Volk, Alexander E. and Wagner, Michael and Waisfisz, Quinten and Wang, Qin and Wang-Gohrke, Shan and Weber, Bernhard H. F. and Devilee, Peter and Tavtigian, Sean and Bader, Gary D. and Meindl, Alfons and Goldgar, David E. and Andrulis, Irene L. and Schmutzler, Rita K. and Easton, Douglas F. and Schmidt, Marjanka K. and Hahnen, Eric and Simard, Jacques}, title = {Uncovering the contribution of moderate-penetrance susceptibility genes to breast cancer by whole-exome sequencing and targeted enrichment sequencing of candidate genes in women of European ancestry}, series = {Cancers}, volume = {14}, journal = {Cancers}, number = {14}, issn = {2072-6694}, doi = {10.3390/cancers14143363}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281768}, year = {2022}, abstract = {Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.}, language = {en} } @article{MusselUlrichAllenetal.2016, author = {Mussel, Patrick and Ulrich, Nathalie and Allen, John J. B. and Osinsky, Roman and Hewig, Johannes}, title = {Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation}, series = {Scientific Reports}, volume = {6}, journal = {Scientific Reports}, doi = {10.1038/srep29245}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-146957}, pages = {29245}, year = {2016}, abstract = {Theta oscillations in the EEG have been shown to reflect ongoing cognitive processes related to mental effort. Here, we show that the pattern of theta oscillation in response to varying cognitive demands reflects stable individual differences in the personality trait epistemic motivation: Individuals with high levels of epistemic motivation recruit relatively more cognitive resources in response to situations possessing high, compared to low, cognitive demand; individuals with low levels do not show such a specific response. Our results provide direct evidence for the theory of the construct need for cognition and add to our understanding of the neural processes underlying theta oscillations. More generally, we provide an explanation how individual differences in personality traits might be represented on a neural level.}, language = {en} } @article{WuPuAllenetal.2012, author = {Wu, Lingdan and Pu, Jie and Allen, John J. B. and Pauli, Paul}, title = {Recognition of facial expressions in individuals with elevated levels of depressive symptoms: an eye-movement study}, series = {Depression Research and Treatment}, volume = {2012}, journal = {Depression Research and Treatment}, number = {249030}, doi = {10.1155/2012/249030}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-123153}, year = {2012}, abstract = {Previous studies consistently reported abnormal recognition of facial expressions in depression. However, it is still not clear whether this abnormality is due to an enhanced or impaired ability to recognize facial expressions, and what underlying cognitive systems are involved. The present study aimed to examine how individuals with elevated levels of depressive symptoms differ from controls on facial expression recognition and to assess attention and information processing using eye tracking. Forty participants (18 with elevated depressive symptoms) were instructed to label facial expressions depicting one of seven emotions. Results showed that the high-depression group, in comparison with the low-depression group, recognized facial expressions faster and with comparable accuracy. Furthermore, the high-depression group demonstrated greater leftwards attention bias which has been argued to be an indicator of hyperactivation of right hemisphere during facial expression recognition.}, language = {en} } @article{RodriguesWeissHewigetal.2021, author = {Rodrigues, Johannes and Weiß, Martin and Hewig, Johannes and Allen, John J. B.}, title = {EPOS: EEG Processing Open-Source Scripts}, series = {Frontiers in Neuroscience}, volume = {15}, journal = {Frontiers in Neuroscience}, issn = {1662-453X}, doi = {10.3389/fnins.2021.660449}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-240221}, year = {2021}, abstract = {Background: Since the replication crisis, standardization has become even more important in psychological science and neuroscience. As a result, many methods are being reconsidered, and researchers' degrees of freedom in these methods are being discussed as a potential source of inconsistencies across studies. New Method: With the aim of addressing these subjectivity issues, we have been working on a tutorial-like EEG (pre-)processing pipeline to achieve an automated method based on the semi-automated analysis proposed by Delorme and Makeig. Results: Two scripts are presented and explained step-by-step to perform basic, informed ERP and frequency-domain analyses, including data export to statistical programs and visual representations of the data. The open-source software EEGlab in MATLAB is used as the data handling platform, but scripts based on code provided by Mike Cohen (2014) are also included. Comparison with existing methods: This accompanying tutorial-like article explains and shows how the processing of our automated pipeline affects the data and addresses, especially beginners in EEG-analysis, as other (pre)-processing chains are mostly targeting rather informed users in specialized areas or only parts of a complete procedure. In this context, we compared our pipeline with a selection of existing approaches. Conclusion: The need for standardization and replication is evident, yet it is equally important to control the plausibility of the suggested solution by data exploration. Here, we provide the community with a tool to enhance the understanding and capability of EEG-analysis. We aim to contribute to comprehensive and reliable analyses for neuro-scientific research.}, language = {en} }