Institut für Psychologie
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Item type:Publication, How categories master variability: Insights into category learning and generalization(2025-06-27); Variability permeates every aspect of our environment and categories help us navigate this variability. This thesis presents three projects that leverage variability to deepen our understanding of category learning and generalization. Project 1 investigates how different types of variability, learned in a prior relationally structured category learning task, affect later category generalization. The findings show that categories experienced as more diverse lead to broader generalization than homogeneous ones. Specifically, generalization widens when category exemplars exhibit heterogeneity, but not when participants encounter many different exemplars within a diverse category. In Project 2, I use variability to explore category learning processes, focusing on how the immediate context of a category—specifically its counter-category—shapes learning. By manipulating category variability in a newly developed self-regulated category learning task, I show that greater variability prompts participants to draw more samples until their category representation suffices. Interestingly, not only the category's variability but also the variability of the counter-category influences the number of samples drawn. In Project 3, I explore how category learning in the self-regulated task can be modeled within the sequential sampling framework. Our findings suggest that category variability determines the accumulation rate, while the counter-category influences the decision to stop sampling exemplars. Within this framework, I examine variability perception and the shape of the accumulation rate. I also model how between-category processes impact learning, finding that learning assimilates to the counter-category’s characteristics. In summary, this thesis provides new insights into how category variability shapes generalization, influences the category learning process, and highlights the intricate link between a category and its counter-category.doctoral thesis66 37 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Overt and covert attention to emotional faces in realistic social situations(2025-06-24); 59 54 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Influence of underlying structure on human behavior in sequential categorization and object search(2026-03-30); ; ; Human cognition can fundamentally detect, learn, and exploit underlying structure from repeated exposure to information. Everyday behavior relies on extracting temporal and spatial regularities from the environment. This dissertation investigates how humans learn and generalize underlying regularities across sequential decisions, and how such patterns in the information presented can influence search behavior when expectations are violated. Across three chapters, this work examines (1) whether people learn and generalize temporal regularity across a sequence of decision-making tasks within and between different modalities of decision-making tasks, (2) whether learning and generalization of sequential tasks are possible in complex temporal regularity structures and whether the implementation of a formal exemplar based category learning model account for the behavior observed in sequential decision making task with temporal regularity, and (3) though based on underlying patterns this chapter makes a conceptual shift from temporal regularity to examining how prior experience of underlying pattern, with utility and effort trade-off, guides object search in everyday tasks. Chapters 1 and Part I of Chapter 2 introduce a novel sequential decision-making task based on a real-world table-setting scenario. Rather than categorizing isolated stimuli into categorical outcomes based on feature inference, as in classical categorization tasks, participants completed sequences of categorization and estimation tasks within a single trial with the same stimulus, in which the outcome of one decision could predict the next. Across multiple studies, we manipulated temporal regularity (Type I, Type II, Type VI), motivated by the category structure proposed by Shepard, Hovland, and Jenkins (1961); temporal proximity (adjacent vs. non-adjacent) (Wilson et al., 2020); and learning modality (categorization vs. estimation). Results reveal that humans, as reported in research in other domains (Lazartigues, Mathy, & Lavigne, 2022; Shepard et al., 1961), easily learn simple rules such as Type I regularity, in which one categorical outcome predicts the other (category-category association), but fail to acquire more complex rules such as Type II. Temporal proximity also makes learning difficult when intervening tasks separate the predicted tasks. Generalization was observed for regularities in category-category association structures, such as Type I and Type II, but was diminished for category-criterion association temporal structures. Chapter 2, Part II, focused on evaluating whether classical exemplar-based categorization models can account for sequential decision learning under complex temporal regularity. The dissertation aimed to adapt the ALCOVE model (Kruschke, 1992) with a temporal decay mechanism (Simple Temporal Decay Mechanism: Brown, Neath, & Chater, 2007) and attention-based weighting. Simulations of the experimental setup and model fits showed that models incorporating a decay mechanism best captured the learning difficulty of temporally distant adjacent and non-adjacent sequential tasks, while maintaining the theoretical category structure and observed human behavior. Chapter 3 examines how prior knowledge influences object search during everyday activity, for example, when a mug is missing from its usual location. The aim was to investigate how search behavior is affected, especially with respect to (1) spatial proximity: do people search closer to their current location or based on prior knowledge? (2) Does the presence of an alternative object with varying utility provide a suitable trade-off between selecting the alternative object or continuing search, and (3) does the effort of object search (virtual reality-based physical search vs. desktop environment) affect search behavior?. The chapter illustrates that, although the search environment influences overall search behavior, the critical finding is that participants tend to search in a location proximal to their current location when the search requires greater physical effort. Overall, the chapters provide an initial framework for investigating the learning of underlying patterns in an abstract temporal domain and in an everyday, task-oriented, naturalistic setting.doctoral thesis45 29 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, How to (not) disentangle personality constructs: scrutinizing longitudinal, multi-rater, and behavioral genetic approaches(2025-05-12)106 65 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Adaptive behavior in optimal sequential search(American Psychological Association, 2023-03); ; Sequential decision making - making a decision where available options are encountered successively - is a hallmark of everyday life. Such decisions require deciding to accept or reject an alternative without knowing potential future options. Prior work focused on understanding choice behavior by developing decision models that capture human choices in such tasks. We investigated people’s adaptive behavior in changing environments in light of their cognitive strategies. We present two studies in which we modified (1) outcome variance and (2) the time horizon and provide empirical evidence that people adapt to both context manipulations. Furthermore, we apply a recently developed threshold model of optimal stopping to our data to disentangle different cognitive processes involved in optimal stopping behavior. The results from Study 1 show that participants adaptively scaled the values of the sampling distribution to its variance, suggesting that the value of an option is perceived in relative rather than absolute terms. The results from Study 2 suggest that increasing the time horizon decreases the initial acceptance level, but less strongly than would be optimal. Furthermore, for longer sequences, participants more weakly adjusted this acceptance threshold over time than for shorter sequences. Further correlations between individual estimates in each condition indicate that individual differences between the participants’ thresholds remain fairly stable between the conditions, pointing toward an additive effect of our manipulations.journal articleBand:152Heft:3138 189 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Neural correlates of acute-induced stress and decision-making under risk: an fMRI study(2025-10-29); ; Many situations in daily life require making risky decisions under stressful conditions. In the current behavioral literature, the effects of stress on risky decision-making are inconsistent, and there is limited research investigating post-stress risky decisions from a neural perspective. Identifying neural correlates of post-stress risky decision-making might help to improve the targeted behavioral interventions for risk adjustment. Furthermore, the investigation of post-stress risky decisions from a neuroscientific perspective might shed light on underlying neural/cognitive mechanisms that can moderate the impact of stress on decision-making and offer insights unattainable through behavioral methods alone. Thus, in this dissertation, functional Magnetic Resonance Imaging (fMRI) was employed to assess the neural correlates of stress as well as post-stress risky decision-making. The study consisted of four experimental blocks: stress, post-stress decision-making, control, and post control decision-making. The design was within-subject and all participants were subjected to stress and control conditions in a counterbalanced order. Both stress and control conditions were followed by a “decision-making under risk” task directly after the stress exposure in a single fMRI session with a concurrent Electrodermal Activity (EDA) measurement to confirm the stress manipulation. Stress was induced by asking participants to solve mental arithmetic tasks under time pressure & social-evaluative threat while receiving negative feedback. During the decision-making task, participants chose between a safe and a risky option (binary lottery task) with monetary incentives and known probabilities of winning. Self-reported stress levels and EDA data confirmed that the stress induction was successfully implemented. Participants took less risky decisions post-stress than post-control. An fMRI contrast analysis revealed that the right fronto-opercular and the left anterior part of the dorsolateral prefrontal cortex (dlPFC; an area critical for executive functioning and cognitive control) exhibited significantly lower activation during decisions post-stress than decisions post-control. The results indicate that decisions taken immediately after exposure to the acute stressor are associated with reduced activation in the regions of the dlPFC, possibly leading to less deliberate and less risky decision-making post-stress. Interventions to increase dlPFC activation might be suitable to improve the quality of decision-making post-stress, alleviating the effects of stress.doctoral thesis27 35 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Individual differences in effects of life events on personality trait change(2026-01-19); 30 33 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The heritability of well-being across contexts: exploring variation in genetic and environmental sources of mental health(2026-03-06); 30 40