Garber D., & Fiser J. (2024) Structure transfer and consolidation in visual implicit learning. (preprint, bioRxiv)
Transfer learning, the re-application of previously learned higher-level regularities to novel input, is a key challenge in cognition. While previous empirical studies investigated human transfer learning in supervised or reinforcement learning for explicit knowledge, it is unknown whether such transfer occurs during naturally more common implicit and unsupervised learning and if so, how it is […]
Jellinek, S. & Fiser, J. (2024) Neural correlates tracking different aspects of the emerging representation of novel visual categories. Cerebral Cortex, 2024 (1), pp. bhad544
Current studies investigating electroencephalogram correlates associated with categorization of sensory stimuli (P300 event-related potential, alpha event-related desynchronization, theta event-related synchronization) typically use an oddball paradigm with few, familiar, highly distinct stimuli providing limited insight about the aspects of categorization (e.g., difficulty, membership, uncertainty) that the correlates are linked to. Using a more complex task, we […]
Seitz, A. R., Sekuler, A., Dosher, B., Wright, B. A., Huang, C.-B., Green, C. S., Pack, C. C., Sagi, D., Levi, D., Tadin, D., Quinlan, E., Jiang, F., Diaz, G. J., Ghose, G., Fiser, J., Banai, K., Visscher, K., Huxlin, K., Shams, L., Battelli, L., Carrasco, M., Herzog, M., Webster, M., Eckstein, M., Turk-Browne, N. B., Censor, N., De Weerd, P., Vogels, R., Hochstein, S., Watanabe, T., Sasaki, Y., Polat, U., Lu, Z.-L., Kourtzi, Z. (2023). Perceptual Learning: Policy Insights From Basic Research to Real-World Applications. Policy Insights from the Behavioral and Brain Sciences, 10(2), pp. 324-332. SAGE Publications.
Perceptual learning is the process by which experience alters how incoming sensory information is processed by the brain to give rise to behavior—it is critical for how humans educate children, train experts, treat diseases, and promote health and well-being throughout the lifespan. Knowledge of perceptual learning requires basic and applied research in humans and nonhuman […]
Arató, J., Rothkopf, C. A., & Fiser, J. (2024). Eye movements reflect active statistical learning. Journal of Vision, 24(5):17, 1–18, https://doi.org/10.1167/jov.24.5.17.
What is the link between eye movements and sensory learning? Although some theories have argued for an automatic interaction between what we know and where we look that continuously modulates human information gathering behavior during both implicit and explicit learning, there exists limited experimental evidence supporting such an ongoing interplay. To address this issue, we […]
Roy A., Christie IK., Escobar GM., Osik JJ., Popovic M., Ritter NJ., Stacy AK., Wang S., Fiser J., Miller P. & Van Hooser SD. (2018) Does experience provide a permissive or instructive influence on the development of direction selectivity in visual cortex? Neural development 13 (1), 16
In principle, the development of sensory receptive fields in cortex could arise from experience-independent mechanisms that have been acquired through evolution, or through an online analysis of the sensory experience of the individual animal. Here we review recent experiments that suggest that the development of direction selectivity in carnivore visual cortex requires experience, but also […]
Fiser J. (2009) The other kind of perceptual learning. Learning & Perception 1 (1), 69-87
In the present review we discuss an extension of classical perceptual learning called the observational learning paradigm. We propose that studying the process how humans develop internal representation of their environment requires modifications of the original perceptual learning paradigm which lead to observational learning. We relate observational learning to other types of learning, mention some […]
Mel BW. & Fiser J. (2000) Minimizing binding errors using learned conjunctive features. Neural Computation 12 (4), 731-762
We have studied some of the design trade-offs governing visual representations based on spatially invariant conjunctive feature detectors, with an emphasis on the susceptibility of such systems to false-positive recognition errors — Malsburg’s classical binding problem. We begin by deriving an analytical model that makes explicit how recognition performance is affected by the number of […]
McDevitt E. A., Zhang J., MacKenzie K. J., Fiser J. & Mednick S. C. (2022) The effect of interference, offline sleep, and wake on spatial statistical learning. Neurobiology of Learning And Memory 2022, 193
Statistical learning, the ability of the human brain to uncover patterns organized according to probabilistic relationships between elements and events of the environment, is a powerful learning mechanism underlying many cognitive processes. Here we examined how memory for statistical learning of probabilistic spatial configurations is impacted by interference at the time of initial exposure and […]
Karuza EA., Emberson LL., Roser ME., Cole D., Aslin RN. & Fiser J. (2017) Neural signatures of spatial statistical learning: characterizing the extraction of structure from complex visual scenes. Journal of cognitive neuroscience 29 (12), 1963-1976
Behavioral evidence has shown that humans automatically develop internal representations adapted to the temporal and spatial statistics of the environment. Building on prior fMRI studies that have focused on statistical learning of temporal sequences, we investigated the neural substrates and mechanisms underlying statistical learning from scenes with a structured spatial layout. Our goals were twofold: […]
Berkes P., Turner RE. & Sahani M. (2009) A structured model of video reproduces primary visual cortical organisation, PLoS Computational Biology, 2009. 5(9): e1000495
The visual system must learn to infer the presence of objects and features in the world from the images it encounters, and as such it must, either implicitly or explicitly, model the way these elements interact to create the image. Do the response properties of cells in the mammalian visual system reflect this constraint? To […]