Dr. Alexander (Sasha) Pastukhov

Akademischer Rat/Lab Manager

Kontakt:

Alexander.Pastukhov(at)uni-bamberg.de
Raum M3/330
Tel.: 863-1887

Sprechstunde:

Nach Vereinbarung.

Around the web:

Persönliche Website: alexander-pastukhov.github.io
Google scholar: https://scholar.google.de/citations?user=j7xgtUQAAAAJ
ResearchGate: researchgate.net/profile/Alexander_Pastukhov 
ORCID: https://orcid.org/0000-0002-8738-8591

Forschungsinteressen:

  • multistabile Wahrnehmung
  • Vorwissen und Wahrnehmung als Inferenz
  • historische Effekte in der Wahrnehmung
  • Bewusstsein und Aufmerksamkeit

Preise:

2013 “Auszeichnung "Best of the Year" von der Psychonomic Society für in Attention, Perception, and Psychophysics veröffentlichte Arbeiten für zwei Publikationen (link)

Reviewer für:

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

Veröffentlichungen

Veröffentlichungen (umgekehrt chronologisch):

Pastukhov, A., Burkel, K., & Carbon, C.-C. (2020). Shape specificity of neural persistence for the kinetic-depth effect matches perceptual adaptation but not sensory memory. Attention, Perception, & Psychophysics. https://doi.org/10.3758/s13414-019-01954-7

Pastukhov, A., Kastrup, P., Abs, I. F., & Carbon, C.-C. (2019). Switch rates for orthogonally oriented kinetic-depth displays are correlated across observers. Journal of Vision, 19(6), 1, 1–13. https://doi.org/10.1167/19.6.1

Carbon, C.-C., & Pastukhov, A. (2018). Reliable Top-Left Light Convention Starts With Early Renaissance: An Extensive Approach Comprising 10k Artworks. Frontiers in Psychology, 9(April), 1–7. https://doi.org/10.3389/fpsyg.2018.00454

Nalis, D., Schütz, A., & Pastukhov, A. (2018). The Bamberg Trucking Game: A Paradigm for Assessing the Detection of Win–Win Solutions in a Potential Conflict Scenario. Frontiers in Psychology, 9(February), 1–13. https://doi.org/10.3389/fpsyg.2018.00138

Devyatko, D., & Pastukhov, A. (2018). Extrinsic grouping factors in motion-induced blindness. PLOS ONE, 13(1), e0192133. https://doi.org/10.1371/journal.pone.0192133

Pastukhov, A., Zaus, C. R., Aleshin, S., Braun, J., & Carbon, C.-C. (2018). Perceptual coupling induces co-rotation and speeds up alternations in adjacent bi-stable structure-from-motion objects. Journal of Vision, 18(4), 21. https://doi.org/10.1167/18.4.21

Pastukhov, A., Prasch, J., & Carbon, C.-C. (2018). Out of sight, out of mind: Occlusion and eye closure destabilize moving bistable structure-from-motion displays. Attention, Perception, & Psychophysics, 80(5), 1193–1204. https://doi.org/10.3758/s13414-018-1505-z

Pastukhov, A. (2017). First, you need a Gestalt: An interaction of bottom-up and top-down streams during the perception of the ambiguously rotating human walker. Scientific Reports, 7(1), 1158. doi: 10.1038/s41598-017-01376-1

Cao, R., Pastukhov, A., Mattia, M., & Braun, J. (2016). Collective Activity of Many Bistable Assemblies Reproduces Characteristic Dynamics of Multistable Perception. Journal of Neuroscience, 36(26), 6957–6972. doi: 10.1523/JNEUROSCI.4626-15.2016

Pastukhov, A., & Klanke, J.-N. (2016). Exogenously triggered perceptual switches in multistable structure-from-motion occur in the absence of visual awareness. Journal of Vision, 16(3), 14. doi: 10.1167/16.3.14

Pastukhov, A. (2015). Perception and the strongest sensory memory trace of multi-stable displays both form shortly after the stimulus onset. Attention, Perception, & Psychophysics, 1–11. JOUR. doi: 10.3758/s13414-015-1004-4

Pastukhov, A., Vivian-Griffiths, S., & Braun, J. (2015). Transformation priming helps to disambiguate sudden changes of sensory inputs. Vision Research, 116, 36–44. Journal Article. doi: 10.1016/j.visres.2015.09.005

Pastukhov, A., Lissner, A., & Braun, J. (2014). Perceptual adaptation to structure-from-motion depends on the size of adaptor and probe objects, but not on the similarity of their shapes. Attention, perception & psychophysics, 76(2), 478–88. doi:10.3758/s13414-013-0567-1

Pastukhov, A., Lissner, A., Füllekrug, J., & Braun, J. (2014). Sensory memory of illusory depth in structure-from-motion. Attention, Perception, & Psychophysics, 76(1), 123-32. doi:10.3758/s13414-013-0557-3

Pastukhov, A., Füllekrug, J., & Braun, J. (2013). Sensory memory of structure-from-motion is shape-specific. Attention, perception & psychophysics, 75(6), 1215–1229. doi:10.3758/s13414-013-0471-8 (“Best of the Year” 2013 from the Psychonomic Society)

Pastukhov, A., & Braun, J. (2013). Structure-from-motion: dissociating perception, neural persistence, and sensory memory of illusory depth and illusory rotation. Attention, perception & psychophysics, 75(2), 322–40. doi:10.3758/s13414-012-0390-0 (“Best of the Year” 2013 from the Psychonomic Society)

Pastukhov, A., Rodriguez, P. E. G., Haenicke, J., Guillamon, A., Deco, G., & Braun, J. (2013). Multi-stable perception balances stability and sensitivity. Frontiers in Computational Neuroscience, 7(17). doi:10.3389/fncom.2013.00017

Pastukhov, A., Vonau, V., Stonkute, S., & Braun, J. (2013). Spatial and temporal attention revealed by microsaccades. Vision research, 85(0), 45–57. doi:10.1016/j.visres.2012.11.004

Pastukhov, A., & Braun, J. (2013). Disparate time-courses of adaptation and facilitation in multi-stable perception. Learning & Perception, 5(s2), 101–118. doi:10.1556/LP.5.2013.Suppl2.7

Pastukhov, A., Vonau, V., & Braun, J. (2012). Believable change: bistable reversals are governed by physical plausibility. Journal of vision, 12(1), 17. doi:10.1167/12.1.17

Stonkute, S., Braun, J., & Pastukhov, A. (2012). The role of attention in ambiguous reversals of structure-from-motion. (S. Ben Hamed, Ed.)PloS one, 7(5), e37734. doi:10.1371/journal.pone.0037734

Hudak, M., Gervan, P., Friedrich, B., Pastukhov, A., Braun, J., & Kovacs, I. (2011). Increased readiness for adaptation and faster alternation rates under binocular rivalry in children. Frontiers in Human Neuroscience, 5(128). doi:10.3389/fnhum.2011.00128

Pastukhov, A., & Braun, J. (2011). Cumulative history quantifies the role of neural adaptation in multistable perception. Journal of vision, 11(10), 12. doi:10.1167/11.10.12

Pastukhov, A., & Braun, J. (2010). Rare but precious: Microsaccades are highly informative about attentional allocation. Vision research, 50, 1173–1184. doi:10.1016/j.visres.2010.04.007

Pastukhov, A., Vonau, V., & Braun, J. (2010). No Stopping and No Slowing: Removing Visual Attention with No Effect on Reversals of Phenomenal Appearance. In K. Diamantaras, W. Duch, & L. Iliadis (Eds.), Artificial Neural Networks – ICANN 2010 (Vol. 6354, pp. 510–515). Springer Berlin / Heidelberg. doi:10.1007/978-3-642-15825-4_70

Pastukhov, A., Fischer, L., & Braun, J. (2009). Visual attention is a single, integrated resource. Vision research, 49(10), 1166–73. doi:10.1016/j.visres.2008.04.011

Pastukhov, A., & Braun, J. (2008). A short-term memory of multi-stable perception. Journal of vision, 8(13), 7.1–14. doi:10.1167/8.13.7

Pastukhov, A., & Braun, J. (2007). Perceptual reversals need no prompting by attention. Journal of vision, 7(10), 5.1–17. doi:10.1167/7.10.5

Teaching material

Scientific Software

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.