Hello,

My name is Benedikt Ehinger. I’m a Tenure-Track Professor for Computational Cognitive Sciences at the SimTech and VIS at University of Stuttgart

Send me a message: science@benediktehinger.de

My studies and interests involve cognitive psychology, visual perception, categorization and cortocortical interactions. I am working with EEG, Bayesian statistics, eye tracking and slowly diving into VR/mobile EEG.


Education

2018: Doktor rer. nat. / PhD Cognitive Science .
PhD Thesis Predictions, Decisions and Learning in the visual sense

2013: Master of Science in Cognitive Science.
Masterthesis „Filling in Blind-Spots: A psychophysical and an EEG study.“

2012: Research-Project: Mobile EEG: Comparing Real Environments with Laboratory Settings

2011: Bachelor of Science in Cogntive Science
Bachelorthesis: „Electrophysiological Correlates of Category Learning

2010: Abroad at Norwegian University of Technology, Trondheim.

Publications

Pavlov, Y.G. et al. (2021) ‘#EEGManyLabs: Investigating the replicability of influential EEG experiments’, Cortex [Preprint]. http://doi.org/10.1016/j.cortex.2021.03.013. Cite
Czeszumski, A. et al. (2021) ‘Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing’, bioRxiv, p. 2021.03.26.437133. http://doi.org/10.1101/2021.03.26.437133. Cite
Dimigen, O. and Ehinger, B.V. (2021) ‘Regression-based analysis of combined EEG and eye-tracking data: Theory and applications’, Journal of Vision, 21(1), pp. 3–3. http://doi.org/10.1167/jov.21.1.3. Cite
Gert, A.L. et al. (2020) ‘Faces strongly attract early fixations in naturally sampled real-world stimulus materials’, in ACM Symposium on Eye Tracking Research and Applications. New York, NY, USA: Association for Computing Machinery (ETRA ’20 Short Papers), pp. 1–5. http://doi.org/10.1145/3379156.3391377. Cite
Bosch, E. et al. (2020) ‘Opposite effects of choice history and stimulus history resolve a paradox of sequential choice bias’, Journal of Vision, p. 2020.02.14.948919. http://doi.org/(accepted). Cite
Heilbron, M. et al. (2019) ‘Tracking Naturalistic Linguistic Predictions with Deep Neural Language Models’, arXiv:1909.04400 [q-bio] [Preprint]. http://doi.org/10.32470/CCN.2019.1096-0. Cite
Ehinger, B.V. et al. (2019) ‘A new comprehensive eye-tracking test battery concurrently evaluating the Pupil Labs glasses and the EyeLink 1000’, PeerJ, 7, p. e7086. http://doi.org/10.7717/peerj.7086. Cite
Ehinger, B.V. (2019) ‘Unmixed: Linear Mixed Models combined with Overlap Correction for M/EEG analyses. An Extension to the unfold Toolbox’, in 2019 Conference on Cognitive Computational Neuroscience. 2019 Conference on Cognitive Computational Neuroscience, Berlin, Germany: Cognitive Computational Neuroscience. http://doi.org/10.32470/CCN.2019.1102-0. Cite
Ehinger, B.V. and Dimigen, O. (2019) ‘Unfold: An integrated toolbox for overlap correction, non-linear modeling, and regression-based EEG analysis’, peerJ [Preprint]. doi:https://doi.org/10.7717/peerj.7838. Cite
Czeszumski, A. et al. (2019) ‘The Social Situation Affects How We Process Feedback About Our Actions’, Frontiers in Psychology, 10. http://doi.org/10.3389/fpsyg.2019.00361. Cite
Sütfeld, L.R. et al. (2019) ‘How does the method change what we measure? Comparing virtual reality and text-based surveys for the assessment of moral decisions in traffic dilemmas’. http://doi.org/10.31234/osf.io/h2z7p. Cite
Ehinger, B.V., Kaufhold, L. and König, P. (2018) ‘Probing the temporal dynamics of the exploration–exploitation dilemma of eye movements’, Journal of Vision, 18(3), pp. 6–6. http://doi.org/10.1167/18.3.6. Cite
Ehinger, B.V. (2018) EEGVIS Toolbox. doi:10.5281/zenodo.1312813. Cite
Ehinger, B.V. et al. (2017) ‘Humans treat unreliable filled-in percepts as more real than veridical ones’, eLife. Edited by P. Latham, 6, p. e21761. http://doi.org/10.7554/eLife.21761. Cite
Kietzmann, T.C. et al. (2016) ‘Extensive training leads to temporal and spatial shifts of cortical activity underlying visual category selectivity’, NeuroImage, 134, pp. 22–34. http://doi.org/10.1016/j.neuroimage.2016.03.066. Cite
Spoida, K. et al. (2016) ‘Melanopsin Variants as Intrinsic Optogenetic On and Off Switches for Transient versus Sustained Activation of G Protein Pathways’, Current Biology, 26(9), pp. 1206–1212. http://doi.org/10.1016/j.cub.2016.03.007. Cite
König, P. et al. (2016) ‘Eye movements as a window to cognitive processes’, Journal of Eye Movement Research, 9, pp. 1–16. http://doi.org/https://bop.unibe.ch/index.php/jemr/article/view/3383. Cite
Ehinger, B.V. et al. (2016) ‘Understanding melanopsin using bayesian generative models- an Introduction’, bioRxiv [Preprint]. http://doi.org/10.1101/043273. Cite
Ehinger, B.V., König, P. and Ossandón, J.P. (2015) ‘Predictions of Visual Content across Eye Movements and Their Modulation by Inferred Information’, Journal of Neuroscience, 35(19), pp. 7403–7413. http://doi.org/10.1523/JNEUROSCI.5114-14.2015. Cite
Ehinger, B.V. et al. (2014) ‘Kinesthetic and vestibular information modulate alpha activity during spatial navigation: a mobile EEG study’, Frontiers in Human Neuroscience, 8. http://doi.org/10.3389/fnhum.2014.00071. Cite

Courses

2019 (single Lecture) Introduction to ERP analysis (EEG)
2019 (Workshop)
Statistics (Linear Model) & Deconvolution
2018
Statistical rethinking
2018 Applied Generalized Linear Mixed Models
2017 Generalized Linear Mixed Models
2017 (Workshop) Combined EEG/Eyetracking at the ECEM
2016 Bayesian Data Analysis
2015 Advanced Methods for M/EEG Data Analysis
2013 Basic and Advanced MatLab Exercises in Data Analysis
2012
Basic and Advanced MatLab Exercises in Data Analysis