Fakultät für Naturwissenschaften

Browse

Recent Submissions

Now showing 1 - 4 of 4
  • Item
    Fluid fibers in ferroelectric liquids
    (Otto-von-Guericke Universität Magdeburg, 2024) Eremin, Alexey
    Supplementary data for the publication "Fluid fibers in true 3D ferroelectric liquids” in PNAS
  • Item
    Data and analysis scripts for "Unbiased post-error slowing in interference tasks: A confound and a simple solution
    (Otto-von-Guericke Universität Magdeburg, 2021) Derrfuss, Jan; Danielmeier, Claudia; Klein, Tilmann A.; Fischer, Adrian G.; Ullsperger, Markus
    We typically slow down after committing an error, an effect termed post-error slowing (PES). Traditionally, PES has been calculated by subtracting post-correct from post-error RTs. Dutilh and colleagues (2012), however, showed PES values calculated in this way are potentially biased. Therefore, they proposed to compute robust PES scores by subtracting pre-error RTs from post-error RTs. Based on data from a large-scale study using the flanker task, we show that both traditional and robust PES estimates can be biased. The source of the bias are differential imbalances in the percentage of congruent vs. incongruent post-correct, pre-error and post-error trials. Specifically, we found that post-correct, pre-error and post-error trials were more likely to be congruent than incongruent, with the size of the imbalance depending on the trial type as well as the length of the response-stimulus interval (RSI). In our study, for trials preceded by a 700-ms RSI, the percentages of congruent trials were 62% for post-correct trials, 66% for pre-error trials and 56% for post-error trials. Relative to unbiased estimates, these imbalances inflated traditional PES estimates by 37% (9 ms) and robust PES estimates by 42% (16 ms) when individual-participant means were calculated. When individual-participant medians were calculated, the biases were even more pronounced (40% and 50% inflation, respectively). To obtain unbiased PES scores for interference tasks, we propose to compute unweighted individual-participant means by initially calculating mean RTs for congruent and incongruent trials separately, before averaging congruent and incongruent mean RTs to calculate means for post-correct, pre-error and post-error trials.
  • Item
    Data from: Comprehensive ultrahigh resolution whole brain in vivo MRI dataset as a human phantom
    (Otto-von-Guericke Universität Magdeburg, 2020) Lüsebrink, Falk; Mattern, Hendrik; Yakupov, Renat; Acosta-Cabronero, Julio; Ashtarayeh, Mohammad; Oeltze-Jafra, Steffen; Speck, Oliver
    Here, we present an extension to our previously published structural ultrahigh resolution T1- weighted magnetic resonance imaging (MRI) dataset with an isotropic resolution of 250 µm, consisting of multiple additional ultrahigh resolution contrasts. Included are up to 150 µm Time-of-Flight angiography, an updated 250 µm structural T1-weighted reconstruction, 330 µm quantitative susceptibility mapping, up to 450 µm structural T2-weighted imaging, 700 µm T1-weighted back-to-back scans, 800 µm diffusion tensor imaging, one hour continuous resting-state functional MRI with an isotropic spatial resolution of 1.8 mm as well as more than 120 other structural T1-weighted volumes together with multiple corresponding proton density weighted acquisitions collected over ten years. All data are from the same participant and were acquired on the same 7 T scanner. The repository contains the unprocessed data as well as (pre-)processing results. The data were acquired in multiple studies with individual goals. This is a unique and comprehensive collection comprising a “human phantom” dataset. Therefore, we compiled, processed, and structured the data, making them publicly available for further investigation.
  • Item
    Impact of the Exhibition Tropic Ice - the connection between global human identity and the intention for collective actions
    (Otto-von-Guericke Universität Magdeburg, 2019) Lennart, Victor
    Forschungsdaten zur Masterarbeit am Institut für Psychologie, Abteilung für Umweltpsychologie