@misc{GlasauerMedendorp, author = {Glasauer, Stefan and Medendorp, W. Pieter}, title = {Explaining attractive and repulsive biases in the subjective visual vertical}, series = {bioRxiv}, journal = {bioRxiv}, number = {2025.09.18.677071}, publisher = {Cold Spring Harbor Laboratory}, address = {Cold Spring Harbor}, doi = {10.1101/2025.09.18.677071}, pages = {1 -- 15}, abstract = {Perception of gravity can be assessed by measuring the subjective visual vertical (SVV), the visually indicated spatial direction that appears earth-vertical to an observer. When the SVV is measured in darkness while the observer is roll-tilted, it shows substantial biases. At tilts larger than 45°, the bias is attractive, that is, the visual indicator appears vertical when rotated toward the observer. At smaller tilts, however, a repulsive bias is observed. The attractive bias has been explained within the Bayesian framework as the effect of a prior for upright posture. The repulsive bias has so far been considered anti-Bayesian, suboptimal, or as the result of uncompensated ocular counterroll. Here we show that both biases can be explained within a purely Bayesian model. More specifically, the repulsive bias at small roll-tilts is a consequence of the known tilt-dependent variability of the SVV, which is hypothesized to reflect different levels of sensory noise of the otolith organs. We thus provide a solution to a century-old question of why there is a repulsive bias in vertical perception.}, language = {en} } @misc{ShirzhiyanGlasauer, author = {Shirzhiyan, Zahra and Glasauer, Stefan}, title = {Neural correlates of perceptual biases in duration perception}, series = {bioRxiv}, journal = {bioRxiv}, editor = {Glasauer, Stefan}, publisher = {Cold Spring Harbor Laboratory}, address = {Cold Spring Harbor}, doi = {10.1101/2025.09.13.675931}, pages = {1 -- 48}, abstract = {How we perceive a current event depends not only on its immediate context, but also on how our internal expectations are shaped by prior experience. In time perception, these expectations manifest as systematic biases, namely sequential dependence, where the current percept is influenced by the previous stimulus, and central tendency, the overestimation of short durations and underestimation of long ones. Both perceptual biases, corresponding to individual beliefs about stimulus generation, can vary substantially between participants. However, the neural correlates of these individual beliefs and their effects are unknown. Here, we investigate how these biases and their individual variations are reflected in neural responses in a duration reproduction task. Our EEG results show that in the frontocentral region, the Contingent Negative Variation (CNV) while experiencing the current stimulus depends on the previous stimulus regardless of whether sequential dependence is high or low. In contrast, in the right parietal region, CNV significantly correlated with the amount of sequential dependence. Central tendency was associated with frontocentral CNV amplitude and post-stimulus P2 components. A Bayesian model of time perception reproduced the observed neural dynamics, suggesting that internal estimates and expectations of stimulus offset are reflected in EEG responses. Our results demonstrate that both forms of perceptual bias, sequential dependence and central tendency, are reflected in neural activity while experiencing the ongoing stimulus, suggesting that both biases directly affect the measurement of time.}, language = {en} } @misc{JahrmannBrandstetterGlasauer, author = {Jahrmann, Margarete and Brandstetter, Thomas and Glasauer, Stefan}, title = {ROBOPSY PL[AI] : using role-play to investigate how LLMs present collective memory}, series = {arXiv}, journal = {arXiv}, publisher = {arXiv}, doi = {10.48550/arXiv.2510.09874}, pages = {1 -- 17}, abstract = {The paper presents the first results of an artistic research project investigating how Large Language Models (LLMs) curate and present collective memory. In a public installation exhibited during two months in Vienna in 2025, visitors could interact with five different LLMs (ChatGPT with GPT 4o and GPT 4o mini, Mistral Large, DeepSeek-Chat, and a locally run Llama 3.1 model), which were instructed to act as narrators, implementing a role-playing game revolving around the murder of Austrian philosopher Moritz Schlick in 1936. Results of the investigation include protocols of LLM-user interactions during the game and qualitative conversations after the play experience to get insight into the players' reactions to the game. In a quantitative analysis 115 introductory texts for role-playing generated by the LLMs were examined by different methods of natural language processing, including semantic similarity and sentiment analysis. While the qualitative player feedback allowed to distinguish three distinct types of users, the quantitative text analysis showed significant differences between how the different LLMs presented the historical content. Our study thus adds to ongoing efforts to analyse LLM performance, but also suggests a way of how these efforts can be disseminated in a playful way to a general audience.}, language = {en} } @misc{ZangWuZhuetal., author = {Zang, Xuelian and Wu, Jiao and Zhu, Xiuna and Allenmark, Fredrik and M{\"u}ller, Hermann J. and Glasauer, Stefan and Shi, Zhuanghua}, title = {Duration reproduction under memory pressure : modeling the roles of visual memory set size in duration encoding and reproduction}, series = {Cognition}, volume = {271}, journal = {Cognition}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {0010-0277}, doi = {10.1016/j.cognition.2026.106479}, pages = {1 -- 17}, abstract = {Duration estimates are systematically biased toward the mean of recently sampled intervals, a central-tendency effect typically attributed to the integration of sensory evidence with prior expectation. Yet the role of concurrent cognitive demands in shaping these biases has remained largely unexplored. Across five experiments, we investigated how visual working-memory set size influences duration estimation when imposed during encoding, reproduction, or both phases of a duration-reproduction task. Participants reproduced visual intervals while maintaining one, three, or five colors in memory. Increasing memory set size during encoding consistently shortened reproductions and strengthened central-tendency effect, whereas increasing set size during reproduction lengthened reproductions without altering central tendency. To account for these opposing effects, we developed a hierarchical Bayesian model incorporating attention-sharing mechanisms, which captured how increasing set size alters both bias and precision across experimental contexts. The model identifies encoding as the critical locus at which larger set sizes elevate uncertainty and enhances reliance on prior information. Our findings reveal that working-memory demands modulate duration estimation through stage-specific interference and highlight broader implications for magnitude perception under cognitive load.}, language = {en} } @article{PolezhaevaGlasauerAmorim, author = {Polezhaeva, Olga and Glasauer, Stefan and Amorim, Michel-Ange}, title = {Prediction of uncertain visual trajectories is biased toward motion continuity}, series = {Attention, perception, \& psychophysics : AP\&P}, volume = {88}, journal = {Attention, perception, \& psychophysics : AP\&P}, number = {3}, publisher = {Springer Science and Business Media LLC}, address = {New York, NY}, issn = {1943-3921}, doi = {10.3758/s13414-025-03210-7}, pages = {1 -- 21}, abstract = {Visual motion prediction under uncertainty must rely on both statistical and kinematic properties of the stimulus. Here, we investigated how decision-making processes and psychophysical parameters are modulated during extrapolation of random trajectories with different noise characteristics (Random Walk, RDW, or Independently and Identically Distributed, IID). Noise was applied to the horizontal position of a dot moving downward with constant vertical speed and vanishing before reaching the edge of the screen. Participants had to judge whether the dot would reach the edge right or left of the center. In Experiment 1 we varied the side of the last visible horizontal position, optimal for RDW extrapolation, and the mean of all visible positions, optimal for IID, to be either on the same or on opposite sides of the screen center. Experiment 2 investigated how the final segment of an IID path impacts the trajectory extrapolation when the last visible position and the mean of the last segment are on opposite sides of the center. Experiment 3 focused on assessing the accuracy of trajectory perception amid varying levels of noise. Behavioral and DDM (Diffusion Decision Model) analyses revealed that for RDW trajectories, participants relied on the last visible position, reflecting the temporal continuity of the path and leading to faster and more accurate decision making. IID trajectories showed greater variability in prediction strategies, with participants also focusing more on the last segment, as with RDW, rather than the mean position of the whole previous trajectory. However, this strategy works well even for IID paths despite being a suboptimal solution. These findings suggest that the perceptual system favors smooth motion for visual interpretation, aiding in the prediction of uncertain visual trajectories.}, language = {en} } @misc{StefanMedendorp, author = {Stefan, Glasauer and Medendorp, W. Pieter}, title = {Bayesian model explaining repulsive and attractive biases of the subjective visual vertical}, abstract = {Matlab scripts for the figures published in the paper, including the digitized data from Van Beuzekom AD, Van Gisbergen JA (2000) Properties of the internal representation of gravity inferred from spatial-direction and body-tilt estimates. J Neurophysiol 84(1):11-27. Files: beuzekomsvverr.mat : digitized SVV error data from Van Beuzekom \& Van Gisbergen (2000). beuzekomsvvvar.mat : digitized SVV intra-subject variability data from Van Beuzekom \& Van Gisbergen (2000). model_svv_fit.m : Matlab script for fitting the Bayesian model to the idiotropic model and generating most figures. test2AFCSVV.m : Matlab script for testing SVV adjustment vs. two-alternative forced-choice task. svvfit_beuzekom.m : fitting the model to data from Van Beuzekom \& Van Gisbergen (2000).}, language = {en} }