Orbán G., Berkes P., Fiser J. & Lengyel M. (2016) Neural variability and sampling-based probabilistic representations in the visual cortex. Neuron 92 (2), 530-543
Neural responses in the visual cortex are variable, and there is now an abundance of data characterizing how the magnitude and structure of this ariability depends on the stimulus. Current theories of cortical computation fail to account for these data; they either ignore variability altogether or only model its unstructured Poisson-like aspects. We develop a […]
Orbán G., Fiser J., Aslin RN. & Lengyel M. (2008) Bayesian learning of visual chunks by human observers. Proceedings of the National Academy of Sciences 105 (7), 2745-2750
Efficient and versatile processing of any hierarchically structured information requires a learning mechanism that combines lower-level features into higher-level chunks. We investigated this chunking mechanism in humans with a visual pattern-learning paradigm. We developed an ideal learner based on Bayesian model comparison that extracts and stores only those chunks of information that are minimally sufficient […]
Fiser J., Biederman I. & Cooper EE. (1996) To what extent can matching algorithms based on direct outputs of spatial filters account for human object recognition? Spatial Vision 10 (3), 237-271
A number of recent successful models of face recognition posit only two layers, an input layer consisting of a lattice of spatial filters and a single subsequent stage by which those descriptor values are mapped directly onto an object representation layer by standard matching methods such as stochastic optimization. Is this approach sufficient for modeling […]
Fiser J., & Koblinger Á. (2021) A probabilistic hammer for nailing complex neural data analyses. Neuron 109 (7), pp. 1077-1079
In this issue of Neuron, Młynarski et al. (2021) provide a maxent-based normative method for flexible neural data analysis by combining data-driven and theory-driven approaches. The next challenge is identifying the right frameworks to use this method at its best. PDF | REFERS TO
Haefner RM., Berkes P. & Fiser J. (2016) Perceptual decision-making as probabilistic inference by neural sampling. Neuron 90 (3), 649-660
We address two main challenges facing systems neuroscience today: understanding the nature and function of cortical feedback between sensory areas and of correlated variability. Starting from the old idea of perception as probabilistic inference, we show how to use knowledge of the physical task to make testable predictions for the influence of feedback signals on […]
Fiser J., Scholl BJ. & Aslin RN. (2007) Perceived object trajectories during occlusion constrain visual statistical learning. Psychonomic bulletin & review 14 (1), 173-178
Visual statistical learning of shape sequences was examined in the context of occluded object trajectories. In a learning phase, participants viewed a sequence of moving shapes whose trajectories and speed profiles elicited either a bouncing or a streaming percept: The sequences consisted of a shape moving toward and then passing behind an occluder, after which […]
Fiser J. & Biederman I. (1995) Size invariance in visual object priming of gray-scale images. Perception 24 (7), 741-748
The strength of visual priming of briefly presented gray scale pictures of real world objects, measured by naming reaction times and errors, was independent of whether the primed picture of the object was presented in the same or different size than the original picture. These findings replicate Biederman & Cooper’s (1992) results on size invariance […]
Koblinger, Á. Fiser J., & Lengyel M. (2021) Representations of uncertainty: where art thou? Current Opinion in Behavioral Sciences 38, pp. 150-162
Perception is often described as probabilistic inference requiring an internal representation of uncertainty. However, it is unknown whether uncertainty is represented in a task-dependent manner, solely at the level of decisions, or in a fully Bayesian manner, across the entire perceptual pathway. To address this question, we first codify and evaluate the possible strategies the […]
Roser ME., Aslin RN., McKenzie R., Zahra D. & Fiser J. (2015) Enhanced visual statistical learning in adults with autism. Neuropsychology 29 (2), 163
Objective: Individuals with autism spectrum disorder (ASD) are often characterized as having social engagement and language deficiencies, but a sparing of visuospatial processing and short-term memory (STM), with some evidence of supranormal levels of performance in these domains. The present study expanded on this evidence by investigating the observational learning of visuospatial concepts from patterns […]
Aslin RN. & Fiser J. (2005) Methodological challenges for understanding cognitive development in infants. Trends in cognitive sciences 9 (3), 92-98
Studies of cognitive development in human infants have relied almost entirely on descriptive data at the behavioral level – the age at which a particular ability emerges. The underlying mechanisms of cognitive development remain largely unknown, despite attempts to correlate behavioral states with brain states. We argue that research on cognitive development must focus on […]