Theo A. J. Schäfer

Theo A. J. Schäfer
Max Planck Institute for Human Cognitive and Brain Sciences | CBS · Department of Psychology

Master of Science

About

7
Publications
890
Reads
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73
Citations
Citations since 2017
4 Research Items
68 Citations
201720182019202020212022202302468101214
201720182019202020212022202302468101214
201720182019202020212022202302468101214
201720182019202020212022202302468101214
Additional affiliations
March 2019 - March 2020
Max Planck Institute for Human Cognitive and Brain Sciences
Position
  • PhD Student
Description
  • Research Group: Prof. Christian Doeller
November 2017 - September 2018
Technische Universität Dresden
Position
  • Research Assistant
Description
  • Research Group: Prof. Stefan Scherbaum
July 2015 - October 2015
Max Planck Institute for Human Cognitive and Brain Sciences
Position
  • Visiting Student
Description
  • Research Group: Prof. Tania Singer
Education
October 2016 - December 2018
Technische Universität Dresden
Field of study
  • Cognitive-Affective Neuroscience
October 2012 - September 2016
Philipps University of Marburg
Field of study
  • Psychology

Publications

Publications (7)
Article
Full-text available
The incentive structure of a scientist's life is increasingly mimicking economic principles. While intensely criticized, the journal impact factor (JIF) has taken a role as the new currency for scientists. Successful goal-directed behavior in academia thus requires knowledge about the JIF. Using functional neuroimaging we examined how the JIF, as a...
Article
Conflict-adaptation effects (i.e., reduced response-time costs on high-conflict trials following high-conflict trials) supposedly represent our cognitive system’s ability to regulate itself according to current processing demands. However, currently it is not clear whether these effects reflect conflict-triggered, active regulation, or passive carr...
Article
Full-text available
Recent work has highlighted that multi-voxel pattern analysis (MVPA) can be severely biased when BOLD response estimation involves systematic imbalance in model regressor correlations. This problem occurs in situations where trial types of interest are temporally dependent and the associated BOLD activity overlaps. For example, in learning paradigm...
Article
Full-text available
By following explicit instructions, humans instantaneously get the hang of tasks they have never performed before. We used a specially calibrated multivariate analysis technique to uncover the elusive representational states during the first few implementations of arbitrary rules such as ‘for coffee, press red button’ following their first-time ins...
Preprint
Full-text available
By following explicit instructions humans can instantaneously get the hang of tasks they have never performed before. Here, we used a specially calibrated multivariate analysis technique to uncover the elusive representational states following newly instructed arbitrary behavioural rules such as 'for coffee, press red button', while transitioning f...

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