Fiser J. & Garber D. (2025). Emergence, consolidation, and transfer of structured memory in visual implicit learning, 3rd Conference on “Generative Episodic Memory: Interdisciplinary perspectives from neuroscience, psychology and philosophy” Bochum, Germany
Apart from its traditional definition as an autobiographical and temporally dated experience that can be consciously recollected, episodic memory can also refer to a trace of a momentary sensory input—a snippet of information that may serve either as a building block for developing more abstract representations or as a subconsciously accessed piece of memory. In […]
Pesonen, L. Lengyel, M. & Fiser, J. (2025) Exploring Recognition Memory for Non- Semantic Visual Stimuli, 3rd Conference on “Generative Episodic Memory: Interdisciplinary perspectives from neuroscience, psychology and philosophy” Bochum, Germany
Statistical learning—extracting the underlying structure of complex environments from ongoing exposure to sensory inputs—is a key mechanism by which humans and other animals acquire generalizable internal representations of the world (i.e., a form of semantic memory). While the kinds of statistical structures that are extracted from stimuli over the course of statistical learning, and the […]
Koblinger A. & Fiser J. (2025) Approximate Bayesian computation with a complex internal model naturally combines probabilistic inference and heuristics, Annual conference on Computational Cognitive Science,Amsterdam, the Netherlands
Proposals differ on how the brain accounts for the uncertainty of perceptual variables–either by representing them as probability distributions that explicitly encode uncertainty in their width (Knill & Pouget, 2004), or by exploiting the correlation between the uncertainty of one variable (e.g., orientation) and the value of others (e.g., contrast), using the latter’s point estimates […]
Szabó, T. & Fiser, J. (2025) Decoupling levels of learning: behavioral evidence for dissociable low- and high-level structure learning, Annual conference on Computational Cognitive Science, Amsterdam, the Netherlands [Abstract]
Hierarchical Bayesian models offer a unified framework for understanding both learning and meta-learning — the transfer of abstract knowledge across tasks. We investigate whether these two processes are dissociable through a novel statistical learning paradigm that combines low-level shape pair structures with a higher-order color-based rule. Participants viewed shape scenes organized into covert pairs with […]
Molnar B., Koblinger A., & Fiser J. (2025) The impact of confidence measurement and its methodology on long term biases in perceptual decision-making tasks humans Perception 54 47th ECVP Abstract Supplement [Abstract]
Biases in perceptual decision-making tasks serve as indicators of both short-term serial effects and long-term inferential strategies. While recent studies have provided mixed results on how adding a secondary confidence measurement task affects decision accuracy, there is little information on how such confidence measurements influence the reasoning behavior that underlies perceptual biases. Recently, we reported […]
Garber D. & Fiser J. (2025) Spatio-temporal visual statistical learning in context. Cognition (under revision) 2025, 266.
Visual Statistical Learning (VSL) is classically investigated in a restricted format, either as temporal or spatial VSL, and void of any effect or bias due to context. However, in real-world environments, spatial patterns unfold over time, leading to a fundamental intertwining between spatial and temporal regularities. In addition, their interpretation is heavily influenced by contextual […]
Fiser J., & Rácskay Z. (2025) Invariance of visual statistical learning Journal of Vision 25(9) [Abstract]
A staple feature of object representation and perception is invariance: stable representation of new objects is learned from perpetually varying visual inputs and objects are identified as same despite of large differences in the appearance of their local features. Yet, visual statistical learning (VSL) paradigms investigating the formation of such object representations typically use static […]
Pesonen L., Fiser J., & Lengyel M. (2025) Contributions of familiarity and recall to recognizing non-semantic visual stimuli Journal of Vision 25(9) [Abstract]
Understanding the relationship between statistical learning and recognition memory is essential for explaining how environmental input is encoded and recalled. While statistical learning has been extensively studied in visual paradigms, recognition memory research has typically involved semantically rich stimuli such as words and images of natural scenes. The present study bridges these fields by examining […]
Magas D. & Fiser J. (2024) Probabilistic coding of simple and structured episodic memories 15th Dubrovnik Conference on Cognitive Science [Abstract]
Recently, we provided evidence that similarly to simple visual stimuli, such as Gabor patches, rich episodic stimuli are also encoded in and recalled from long-term memory with their subjective uncertainty, indicating a probabilistic representation of memory details. However, it is unknown how this probabilistic form of representation and episodic recall accuracy are affected at various […]
Szabo T., Markus B., & Fiser J. (2024) Common principles in statistical learning of spatio-temporal structures in the visual and auditory domain Conference on Interdisciplinary Advances in Statistical Learning San Sebastian, Spain [Abstract]
Traditionally, statistical learning (SL) studies in the auditory domain have been linked to language processing and, therefore, to sequential predictability or “temporal” structure learning. In contrast, research on visual SL has focused more on discovering general spatio-temporal patterns, which requires spatial structure learning. We asked whether this dichotomy is justified or if auditory SL should […]