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 […]
Biederman I., Subramaniam S., Bar M., Kalocsai P. & Fiser J. (1999) Subordinate-level object classification reexamined. Psychological Research 62 (2-3), 131-153
The classication of a table as round rather than square, a car as a Mazda rather than a Ford, a drill bit as 3/8-inch rather than 1/4-inch, and a face as Tom have all been regarded as a single process termed “subordinate classification”. Despite the common label, the considerable heterogeneity of the perceptual processing required […]
Fiser J. & Lengyel G. (2022) Statistical Learning in Vision. Annual Review Vision Science 2022, 8:265-290
Vision and learning have long been considered to be two areas of research linked only distantly. However, recent developments in vision research have changed the conceptual definition of vision from a signal-evaluating process to a goal-oriented interpreting process, and this shift binds learning, together with the resulting internal representations, intimately to vision. In this review, […]
Roy A., Osik JJ., Ritter NJ., Wang S., Shaw JT., Fiser J. & Van Hooser SD. (2016) Optogenetic spatial and temporal control of cortical circuits on a columnar scale. Journal of neurophysiology 115 (2), 1043-1062
Many circuits in the mammalian brain are organized in a topographic or columnar manner. These circuits could be activated-in ways that reveal circuit function or restore function after disease-by an artificial stimulation system that is capable of independently driving local groups of neurons. Here we present a simple custom microscope called ProjectorScope 1 that incorporates […]
Zito T., Wilbert N., Wiskott L. & Berkes P. (2009) Modular toolkit for data processing (MDP): a Python data processing framework. Frontiers in Neuroinformatics 2:8
Modular toolkit for Data Processing (MDP) is a data processing framework written in Python. From the user’s perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. Computations are performed efficiently in terms of speed […]
Dobbins AC., Jeo RM., Fiser J. & Allman JM. (1998) Distance modulation of neural activity in the visual cortex. Science 281 (5376), 552-555
Humans use distance information to scale the size of objects. Earlier studies demonstrated changes in neural response as a function of gaze direction and gaze distance in the dorsal visual cortical pathway to parietal cortex. These findings have been interpreted as evidence of the parietal pathway’s role in spatial representation. Here, distance-dependent changes in neural […]
Bernacchia A., Fiser J, Hennequin G. & Lengyel M. (2022) Adaptive erasure of spurious sequences in sensory cortical circuits. Neuron 110, pp. 1-12
Sequential activity reflecting previously experienced temporal sequences is considered a hallmark of learning across cortical areas. However, it is unknown how cortical circuits avoid the converse problem: producing spurious sequences that are not reflecting sequences in their inputs. We develop methods to quantify and study sequentiality in neural responses. We show that recurrent circuit responses […]