PD Dr. habil. Alexander (Sasha) Pastukhov

1. Bergner-Koether, Ralf, Lasse Peschka, Alexander Pastukhov, Claus-Christian Carbon, Sabine Steins-Loeber, Göran Hajak, and Martin Rettenberger (2025). The Relevance of Hypersexuality and Impulsivity in Different Groups of Treatment-Seekers With and Without (Exclusive) Pedophilia. In: Sexual Abuse 37.4, pp. 371–398. DOI: 10.1177/10790632241271204.
2. Döbler, Niklas A., Alexander Pastukhov, and Claus‐Christian Carbon (2025). Exploring the Hypothetical Impact of Genetic Engineering on Ethnicity: An Analysis of a Large‐Scale Data Set Retrieved From a Museal Setting. In: Bioethics, p. bioe.70005. DOI: 10.1111/bioe.70005.
3. Förster, Henry, Felix Klesen, Tim Dwyer, Peter Eades, Seok-Hee Hong, Stephen Kobourov, Giuseppe Liotta, Kazuo Misue, Fabrizio Montecchiani, Alexander Pastukhov, and Falk Schreiber (2025). GraphTrials: Visual Proofs of Graph Properties. In: IEEE Transactions on Visualization and Computer Graphics 31.10, pp. 8767–8781. DOI: 10.1109/TVCG.2025.3577533.
4. Goetz, Itay, Lara Bernhardt, Friederike Margareta Karg, Alexander (Sasha) Pastukhov, and Claus-Christian Carbon (2025). Art for art’s sake? The influence of art framing and context on the evaluation of immoral behaviour. In: Frontiers in Communication 10, p. 1655343. DOI: 10.3389/fcomm.2025.1655343.
5. Pastukhov, Alexander, Malin Styrnal, Claus-Christian Carbon, and Árni Kristjánsson (2025). Two routes to a target: Visual priming for direct and indirect attentional sets. In: Memory & Cognition. DOI: 10.3758/s13421-025-01826-6.
6. Leder, Johannes, Astrid Schütz, and Alexander Pastukhov (2023). Keeping the Kids Home: Increasing Concern for Others in Times of Crisis. In: Social Psychology 54.1-2, pp. 27–39. DOI: 10.1027/1864-9335/a000463.
7. Pastukhov, Alexander, Lisa Koßmann, and Claus-Christian Carbon (2023). Reconstructing a disambiguation sequence that forms perceptual memory of multistable displays via reverse correlation method: Bias onset perception but gently. In: Journal of Vision 23.3, p. 10. DOI: 10.1167/jov.23.3.10.
8. Pastukhov, Alexander, Malin Styrnal, and Claus-Christian Carbon (2023). History-dependent changes to distribution of dominance phases in multistable perception. In: Journal of Vision 23.3, p. 16. DOI: 10.1167/jov.23.3.16.
9. Styrnal, Malin, Claus-Christian Carbon, and Alexander Pastukhov (2023). When a bank becomes a bank, and a bank is the bank but not the bank: Multistability of homonyms’ meaning. In: i-Perception 14.4, p. 20416695231194210. DOI: 10.1177/20416695231194210.
10. Breitschaft, Stefan Josef, Alexander Pastukhov, and Claus-Christian Carbon (2022). Where’s My Button? Evaluating the User Experience of Surface Haptics in Featureless Automotive User Interfaces. In: IEEE Transactions on Haptics 15.2, pp. 292–303. DOI: 10.1109/TOH.2021.3131058.
11. Pastukhov, Alexander (2022). bistablehistory: an R package for history-dependent analysis of perceptual time series. In: Journal of Open Source Software 7.70, p. 3901. DOI: 10.21105/joss.03901.
12. Pastukhov, Alexander and Claus-Christian Carbon (2022). Change not State: Perceptual coupling in multistable displays reflects transient bias induced by perceptual change. In: Psychonomic Bulletin & Review 29.1, pp. 97–107. DOI: 10.3758/s13423-021-01960-7.
13. Pastukhov, Alexander, Lisa Koßmann, and Claus-Christian Carbon (2022). When perception is stronger than physics: Perceptual similarities rather than laws of physics govern the perception of interacting objects. In: Attention, Perception, & Psychophysics 84.1, pp. 124–137. DOI: 10.3758/s13414-021-02383-1.
14. Cao, Robin, Alexander Pastukhov, Stepan Aleshin, Maurizio Mattia, and Jochen Braun (2021). Binocular rivalry reveals an out-of-equilibrium neural dynamics suited for decision-making. In: eLife 10, p. e61581. DOI: 10.7554/eLife.61581.
15. Pastukhov, Alexander (2021). Multistable Perception. In: Oxford Research Encyclopedia of Psychology. Oxford University Press. ISBN: 978-0-19-023655-7. DOI: 10.1093/acrefore/9780190236557.013.893.
16. Pastukhov, Alexander and Claus-Christian Carbon (2021). Clever Cats: Do They Utilize Change Blindness as a Covered Approaching Strategy? In: i-Perception 12.1, p. 204166952199459. DOI: 10.1177/2041669521994597.
17. Leder, Johannes, Alexander Pastukhov, and Astrid Schütz (2020). Sharing with a stranger: people are more generous with time than money. In: Comprehensive Results in Social Psychology 4.2, pp. 109–138. DOI: 10.1080/23743603.2020.1831377.
18. Leder, Johannes, Alexander Pastukhov, and Astrid Schütz (2020). Social value orientation, subjective effectiveness, perceived cost, and the use of protective measures during the COVID-19 pandemic in Germany. In: Comprehensive Results in Social Psychology 4.3, pp. 227–249. DOI: 10.1080/23743603.2020.1828850.
19. Pastukhov, Alexander, Kristina Burkel, and Claus-Christian Carbon (2020). Shape specificity of neural persistence for the kinetic-depth effect matches perceptual adaptation but not sensory memory. In: Attention, Perception, & Psychophysics 82.4, pp. 1942–1948. DOI: 10.3758/s13414-019-01954-7.
20. Pastukhov, Alexander, Philipp Kastrup, Isabel Friederike Abs, and Claus-Christian Carbon (2019). Switch rates for orthogonally oriented kinetic-depth displays are correlated across observers. In: Journal of Vision 19.6, pp. 1, 1–13. DOI: 10.1167/19.6.1.
21. Carbon, Claus-Christian and Alexander Pastukhov (2018). Reliable Top-Left Light Convention Starts With Early Renaissance: An Extensive Approach Comprising 10k Artworks. In: Frontiers in Psychology 9.April, pp. 1–7. DOI: 10.3389/fpsyg.2018.00454.
22. Devyatko, Dina and Alexander Pastukhov (2018). Extrinsic grouping factors in motion-induced blindness. In: PLoS ONE 13.1. Ed. by Piers Douglas Lionel Howe, p. e0192133. DOI: 10.1371/journal.pone.0192133.
23. Nalis, Dario, Astrid Schütz, and Alexander Pastukhov (2018). The Bamberg Trucking Game: A Paradigm for Assessing the Detection of Win–Win Solutions in a Potential Conflict Scenario. In: Frontiers in Psychology 9.February, pp. 1–13. DOI: 10.3389/fpsyg.2018.00138.
24. Pastukhov, Alexander, Johanna Prasch, and Claus-Christian Carbon (2018). Out of sight, out of mind: Occlusion and eye closure destabilize moving bistable structure-from-motion displays. In: Attention, Perception, & Psychophysics 80.5, pp. 1193–1204. DOI: 10.3758/s13414-018-1505-z.
25. Pastukhov, Alexander and Christina Rita Zaus (2018). Perceptual coupling induces co-rotation and speeds up alternations in adjacent bi-stable structure-from-motion objects. In: Journal of Vision 18, pp. 1–14. DOI: 10.1167/18.4.21.
26. Pastukhov, Alexander (2017). First, you need a Gestalt: An interaction of bottom-up and top-down streams during the perception of the ambiguously rotating human walker. In: Scientific Reports 7.1, p. 1158. DOI: 10.1038/s41598-017-01376-1.
27. Cao, R., A. Pastukhov, M. Mattia, and J. Braun (2016). Collective Activity of Many Bistable Assemblies Reproduces Characteristic Dynamics of Multistable Perception. In: Journal of Neuroscience 36.26, pp. 6957–6972. DOI: 10.1523/JNEUROSCI.4626-15.2016.
28. Pastukhov, Alexander (2016). Perception and the strongest sensory memory trace of multi-stable displays both form shortly after the stimulus onset. In: Attention, Perception, & Psychophysics 78.2, pp. 674–684. DOI: 10.3758/s13414-015-1004-4.
29. Pastukhov, Alexander and Jan-Nikolas Klanke (2016). Exogenously triggered perceptual switches in multistable structure-from-motion occur in the absence of visual awareness. In: Journal of Vision 16.3, p. 14. DOI: 10.1167/16.3.14.
30. Pastukhov, Alexander, Solveiga Vivian-Griffiths, and Jochen Braun (2015). Transformation priming helps to disambiguate sudden changes of sensory inputs. In: Vision Research 116, pp. 36–44. DOI: 10.1016/j.visres.2015.09.005.
31. Pastukhov, Alexander, Anna Lissner, and Jochen Braun (2014). Perceptual adaptation to structure-from-motion depends on the size of adaptor and probe objects, but not on the similarity of their shapes. In: Attention, Perception, & Psychophysics 76.2, pp. 473–488. DOI: 10.3758/s13414-013-0567-1.
32. Pastukhov, Alexander, Anna Lissner, Jana Füllekrug, and Jochen Braun (2014). Sensory memory of illusory depth in structure-from-motion. In: Attention, Perception, & Psychophysics 76.1, pp. 123–32. DOI: 10.3758/s13414-013-0557-3.
33. Pastukhov, Alexander and Jochen Braun (2013). Disparate time-courses of adaptation and facilitation in multi-stable perception. In: Learning & Perception 5.Supplement 2, pp. 101–118. DOI: 10.1556/LP.5.2013.Suppl2.7.
34. Pastukhov, Alexander and Jochen Braun (2013). Structure-from-motion: dissociating perception, neural persistence, and sensory memory of illusory depth and illusory rotation. In: Attention, Perception, & Psychophysics 75.2, pp. 322–340. DOI: 10.3758/s13414-012-0390-0.
35. Pastukhov, Alexander, Jana Füllekrug, and Jochen Braun (2013). Sensory memory of structure-from-motion is shape-specific. In: Attention, Perception, & Psychophysics 75.6, pp. 1215–1229. DOI: 10.3758/s13414-013-0471-8.
36. Pastukhov, Alexander, Pedro E García-Rodríguez, Joachim Haenicke, Antoni Guillamon, Gustavo Deco, and Jochen Braun (2013). Multi-stable perception balances stability and sensitivity. In: Frontiers in Computational Neuroscience 7.17, p. 17. DOI: 10.3389/fncom.2013.00017.
37. Pastukhov, Alexander, Victoria Vonau, Solveiga Stonkute, and Jochen Braun (2013). Spatial and temporal attention revealed by microsaccades. In: Vision Research 85.0, pp. 45–57. DOI: 10.1016/j.visres.2012.11.004.
38. Pastukhov, Alexander, Victoria Vonau, and Jochen Braun (2012). Believable change: Bistable reversals are governed by physical plausibility. In: Journal of Vision 12.1, pp. 17–17. DOI: 10.1167/12.1.17.
39. Stonkute, Solveiga, Jochen Braun, and Alexander Pastukhov (2012). The Role of Attention in Ambiguous Reversals of Structure-From-Motion. In: PLoS ONE 7.5. Ed. by Suliann Ben Hamed, p. e37734. DOI: 10.1371/journal.pone.0037734.
40. Hudak, Mariann (2011). Increased readiness for adaptation and faster alternation rates under binocular rivalry in children. In: Frontiers in Human Neuroscience 5. DOI: 10.3389/fnhum.2011.00128.
41. Pastukhov, Alexander and Jochen Braun (2011). Cumulative history quantifies the role of neural adaptation in multistable perception. In: Journal of Vision 11.10, pp. 12–12. DOI: 10.1167/11.10.12.
42. Pastukhov, Alexander and Jochen Braun (2010). Rare but precious: Microsaccades are highly informative about attentional allocation. In: Vision Research 50.12, pp. 1173–1184. DOI: 10.1016/j.visres.2010.04.007.
43. Pastukhov, Alexander, Victoria Vonau, and Jochen Braun (2010). No Stopping and No Slowing: Removing Visual Attention with No Effect on Reversals of Phenomenal Appearance. In: Artificial Neural Networks – ICANN 2010. Ed. by Konstantinos Diamantaras, Wlodek Duch and Lazaros S. Iliadis. Vol. 6354. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 510–515. ISBN: 978-3-642-15824-7 978-3-642-15825-4. DOI: 10.1007/978-3-642-15825-4_70.
44. Pastukhov, Alexander, Laura Fischer, and Jochen Braun (2009). Visual attention is a single, integrated resource. In: Vision Research 49.10, pp. 1166–1173. DOI: 10.1016/j.visres.2008.04.011.
45. Pastukhov, A. and J. Braun (2008). A short-term memory of multi-stable perception. In: Journal of Vision 8.13, pp. 7–7. DOI: 10.1167/8.13.7.
46. Pastukhov, Alexander and Jochen Braun (2007). Perceptual reversals need no prompting by attention. In: Journal of Vision 7.10, p. 5. DOI: 10.1167/7.10.5.

You should write an R package. It is easier than you think, and I’ll show you how.

ECVP 2025

In our research, we generate innovative and useful analysis methods. Yet, reusing these methods across projects or sharing them as plain R scripts or notebooks can often be challenging or awkward. Packaging your code as an open-source library available at Github and CRAN not only facilitates reuse in new projects but also simplifies collaboration by ensuring your tools are accessible to the broader scientific community.The task may initially seem daunting, and you might feel that package-writing is best left to trained programmers. However, R and RStudio offer an excellent suite of tools that make transforming your code into a well-functioning, well-documented, and easy-to-install package surprisingly straightforward (or, at least, easier than you might think). Moreover, converting your code into a package – especially one that meets CRAN standards – encourages you to address aspects that might not be part of your usual workflow. This process will push you to write clear documentation complete with practical examples, prepare illustrative datasets, and test your code not only to confirm that it works but also to ensure it fails gracefully when expected.This workshop aims to provide a comprehensive overview of the entire package creation process. We will cover everything from creating an empty project and adding functions or classes to writing comprehensive documentation and practical examples (since poorly structured documentation is often the primary barrier to using your methods), as well as including and documenting example data, creating vignettes, and testing your package. Additionally, you will learn how to make your package installable from GitHub, publish documentation via GitPages, prepare it for CRAN submission, and ensure that your package is properly cited. I will introduce you to the tools R and RStudio provide for each step and how to automate tasks to streamline package creation. Together, we will build a simple yet feature-complete library that you can use as a stepping stone for your future packages.

You should program your statistical models in Stan. It is easier than you think, and I’ll show you how.

ECVP 2026

In our research, we constantly rely on statistical models. Multiple R and Python packages provide models of various complexity from a basic t-test to generalized linear mixed models. However, they are limited in their design structure and flexibility of models that you can use. In this workshop, I will introduce an alternative approach of programming a statistical model from scratch using Stan probabilistic programming language. I will introduce syntax and walk you through an example of programming a basic two-group/condition comparison (a.k.a. a t-test), showing how it can be extended to allow for different distribution families, regularization. Next, I will show how Stan simplifies working with interactions using a two-way ANOVA. Finally, I will explain the underlying mechanisms of the MCMC engine, its limitations, how to diagnose the problems and ways to side-step them. This workshop is aimed at a broad audience and requires basic knowledge of statistics and programming (either R or Python). Its aim is to introduce a flexible method that allows to program virtually any statistical model that you are interested in.

• Python for social and experimental psychology: Lehrmaterialien
• Applied data analysis for psychology using the open-source software R: Lehrmaterialien

• Bayesian Statistics: Lehrmaterialien

   

Bistable History

Estimates cumulative history for time-series for continuously viewed bistable perceptual rivalry displays. Computes cumulative history via a homogeneous first order differential process. I.e., it assumes exponential growth/decay of the history as a function time and perceptually dominant state. Supports Gamma, log normal, and normal distribution families. A package to compute a cumulative history for time-series of perceptual dominance in bistable displays.

eyelinkReader

R package to import eye tracking recording generated by SR Research Eyelink eye tracker from EDF-files. It includes options to import events and/or recorded samples and extract individual events such as saccades, fixations, blinks, and recorded variables.

saccadr

The package uses an ensemble of methods approach to label individual samples and then applies a majority vote approach to identify saccades. It uses several methods to label individual samples as belonging to a saccade, classifies a sample as a potential saccade if its proportion of votes exceeds a preset threshold, and then identifies saccades based on minimal saccade duration and minimal time between the saccades. Currently, the library implements saccade detection using methods proposed in Engbert and Kliegl (2003), Otero-Millan et al. (2014), and Nyström and Holmqvist (2010). For binocular data, 1) samples can be averaged before velocity computation, 2) votes can be merged so that function returns binocular saccades, or 3) saccades are extracted for each eye separately. The package can be extended via custom methods and it also uses a modular approach to compute velocity and acceleration from noisy samples with the possibility of using custom differentiation methods. Finally, you can obtain methods votes per gaze sample instead of saccades.

TriDimRegression

Package to calculate the bidimensional and tridimensional regression between two 2D/3D configurations. Uses Stan engine to provide posterior distribution of fits. Individual fits can be evaluated based on Bayesian R² and compared via widely applicable information criteria (WAIC) or leave-one out cross-validation criteria (LOO).

BiDimRegression

Package to calculate the bidimensional regression between two 2D configurations following the approach by Tobler (1965). Provides fits and statistics for Eucledian, affine, and projective transformation. Individual fits can be compared via ANOVA.

edfImport

The library provides a simple interface to import contents of the EDF files generated by Eyelink eye-tracker into Matlab. It imports events and/or samples, automatically parsing them into separate trials. In addition to that, several post-processing functions can be used to extract selected events (fixations, saccades and blinks), variable values (TRIAL_VAR events) and microsaccades.

• Python for social and experimental psychology I
  (Otto-Friedrich-Universität Bamberg, Ostbayerische Technische Hochschule Amberg-Weiden)
• Python for social and experimental psychology II
  (Otto-Friedrich-Universität Bamberg)
• Applied data analysis for psychology using the open-source software R 
  (Otto-Friedrich-Universität Bamberg, Kutaisi International University)
• Bayesian Statistics
  (Otto-Friedrich-Universität Bamberg, Kutaisi International University)
• Statistical Rethinking I
  (Otto-Friedrich-Universität Bamberg)
• Statistical Rethinking II
  (Otto-Friedrich-Universität Bamberg)
• Machine Learning for Psychology and Social Sciences (ML for Psychology)
  (Otto-Friedrich-Universität Bamberg)
• Empirisches Praktikum (Empra)
  (Otto-Friedrich-Universität Bamberg)
• Neuroscience of Conciousness
  (Otto-Friedrich-Universität Bamberg, Otto-von-Guericke Universität Magdeburg)
• Non-visual Perception
  (Otto-Friedrich-Universität Bamberg, Otto-von-Guericke Universität Magdeburg)
• Introduction to neurobiology of perception and cognition
  (Otto-Friedrich-Universität Bamberg, Otto-von-Guericke Universität Magdeburg) 

• Psychonomic Bulletin & Review
• eLife
• Attention, Perception, & Psychophysics
• Behavioural Brain Research
• Computation Intelligence and Neuroscience
• Frontiers in Physiology
• iPerception; Journal of General Psychology
• Journal of Vision
• Journal of the American Aging Association
• Journal of Experimental Child Psychology
• Perception
• PLOS Computational Biology
• PLOS ONE
• Vision Research
• Behavioral Sciences