Predisposed and learned preferences for multipoint visual statistics in visually naïve newly hatched chicks
Zanon M, Lemaire BS, Piasini E, Caramellino E, Nallet C, Balasubramanian V, Gervain J, Zoccolan D, Vallortigara G (2026)
Proc. R. Soc. B: 293, 2066
Stretching Beyond the Obvious: A Gradient-Free Framework to Unveil the Hidden Landscape of Visual Invariance
Tausani L, Muratore P, Talbot MB, Amerio G, Kreiman G, Zoccolan G (2026)
International Conference on Learning Representations: 14th
Seeing what you hear: compression of rat visual perceptual space by task-irrelevant sounds
Zanzi M, Rinaldi FG, Fornasaro S, Piasini E, Zoccolan D (2025)
Plos Comp Biology: 21 (10), e1013608
Unraveling the complexity of rat object vision requires a full convolutional network and beyond
Muratore P, Alemi A, Zoccolan D (2025)
Unsupervised learning of mid-level visual representations
Matteucci G, Piasini E & Zoccolan D (2024)
Curr. Opin. Neurobiol.: 84:102834
Truly pattern: Nonlinear integration of motion signals is required to account for the responses of pattern cells in rat visual cortex
Matteucci G, Bellacosa Marotti R, Zattera B, Zoccolan D (2023)
Science Adv.: 9 (45), eadh4690
Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks
Muratore P, Tafazoli S, Piasini E, Laio A, Zoccolan D (2022)
Adv. Neural Info. Processing Systems (NeurIPS): 35
Editorial: Sensory Adaptation
Adibi M, Zoccolan D & Clifford CWG (2021)
Front. Syst. Neurosci.: 15: 809000
Rat sensitivity to multipoint statistics is predicted by efficient coding of natural scenes
Caramellino R*, Piasini E*, Buccellato A, Carboncino A, Balasubramanian V & Zoccolan D (2021)
Rats spontaneously perceive global motion direction of drifting plaids
Matteucci G*, Zattera B*, Bellacosa Marotti R, & Zoccolan D (2021)
Plos Comp. Biol.: 17(9): e1009415
Temporal stability of stimulus representation increases along rodent visual cortical hierarchies
Piasini E*, Soltuzu L*, Muratore P, Caramellino R, Vinken K, Op De Beeck H, Balasubramanian V & Zoccolan D (2021)
A machine learning framework to optimize optic nerve electrical stimulation for vision restoration
Romeni S, Zoccolan D & Micera S (2021)
A general-purpose mechanism of visual feature association in visual word identification and beyond.
Vidal Y, Viviani E, Zoccolan D & Crepaldi D (2021)
Curr. Biol.: 31(6), 1261-1267
A template-matching algorithm for laminar identification of cortical recording sites from evoked response potentials.
Matteucci G*, Riggi M* & Zoccolan D (2020)
J. Neurophys.: 124, 102-114
Unsupervised experience with temporal continuity of the visual environment is causally involved in the development of V1 complex cells.
Matteucci G & Zoccolan D (2020)
Science Adv.: 6(22), eaba3742
A passive, camera-based head-tracking system for real-time, three-dimensional estimation of head position and orientation in rodents.
Vanzella W*, Grion N*, Bertolini D*, Perissinotto A, Gigante M & Zoccolan D (2019)
J. Neurophys. : 122, 2220-2242
Nonlinear processing of shape information in rat lateral extrastriate cortex.
Matteucci G, Bellacosa Marotti R, Riggi M, Rosselli FB & Zoccolan D (2019)
J. Neurosci. : 39, 1649-1670
Characterization of visual object representations in rat primary visual cortex.
Vascon S*, Parin Y*, Annavini E*, D’Andola M, Zoccolan D & Pelillo M (2019)
ECCV 2018, Lect. Notes Comp. Science: 11131, 577-586
Intrinsic dimension of data representations in deep neural networks.
Ansuini A, Laio A, Macke J & Zoccolan D (2019)
Adv. Neural Info. Processing Systems (NeurIPS): 32
Accuracy of rats in discriminating visual objects is explained by the complexity of their perceptual strategy.
Djurdjevic V*, Ansuini A*, Bertolini D, Macke JH & Zoccolan D (2018)
Curr. Biol. : 28(7), 1005-1015
Supralinear and supramodal integration of visual and tactile signals in rats: psychophysics and neuronal mechanisms.
Nikbakht N, Tafreshiha A, Zoccolan D & Diamond ME (2018)
Methodological approaches to the behavioral investigation of visual perception in rodents.
Zoccolan D & Di Filippo A (2018)
Handbook of object novelty recognition.: Volume 27, 2018, Pages 69-101
Emergence of transformation-tolerant representations of visual objects in rat lateral extrastriate cortex.
Tafazoli S*, Safaai H*, De Franceschi G, Rosselli FB, Vanzella W, Riggi M, Buffolo F, Panzeri S & Zoccolan D (2017)
Editorial: What can simple brains teach us about how vision works.
Zoccolan D, Cox DD & Benucci A (2015)
Front. Neural Circuits: doi: 10.3389/fncir.2015.00051
Invariant visual object recognition and shape processing in rats.
Zoccolan D (2015)
Behav. Brain. Res. : 285, 10-33
Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats.
Rosselli FB*, Alemi A*, Ansuini A & Zoccolan D (2015)
Front. Neural Circuits : 9(10). doi: 10.3389/fncir.2015.00010
Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons.
Baldassi C*, Alemi-Neissi A*, Pagan M*, DiCarlo JJ, Zecchina R & Zoccolan D (2013)
PLoS Comput. Biol.: 9(8): e1003167
Multifeatural shape processing in rats engaged in invariant visual object recognition.
Alemi-Neissi A*, Rosselli BF* & Zoccolan D (2013)
J. Neurosci. : 33, 5939-5956
How does the brain solve visual object recognition?
DiCarlo JJ, Zoccolan D & Rust NC (2012)
Transformation-tolerant object recognition in rats revealed by visual priming.
Tafazoli S*, Di Filippo A* & Zoccolan D (2012)
A self-calibrating, camera-based eye tracker for the recording of rodent eye movement.
Zoccolan D, Graham JB & Cox DD (2010)
What response properties do individual neurons need to underlie object recognition in clutter?
Li N, Cox DD, Zoccolan D & DiCarlo JJ (2009)
J. Neurophys. : 102, 360-376
A rodent model for the study of invariant visual object recognition.
Zoccolan D*, Oertelt N*, DiCarlo JJ & Cox DD (2009)
Proc. Natl. Acad. Sci. USA : 106, 8748-53
Trade-off between object selectivity and tolerance in monkey inferotemporal cortex.
Zoccolan D, Kouh M, Poggio T & DiCarlo JJ (2007)
J. Neurosci. : 27, 12292-12307
Multiple object response normalization in monkey inferotemporal cortex.
Zoccolan D*, Cox DD* & DiCarlo JJ (2005)
J. Neurosci. : 25, 8150-64
Quantitative characterization and classification of leech behavior
Mazzoni A, Garcia-Perez E, Zoccolan D, Graziosi S, Torre V (2005)
J. Neurophysiol.: 93:580-93
Statistics of decision making in the leech
Garcia-Perez E, Mazzoni A, Zoccolan D, Robinson HP, Torre V (2005)
J. Neurosci.: 25, 2597-608
Dynamics and reproducibility of a moderately complex sensory-motor response in the medicinal leech
Garcia-Perez E, Zoccolan D, Pinato G, Torre V (2004)
Using optical flow to characterize sensory-motor interactions in a segment of the medicinal leech
Zoccolan D, Torre V (2002)
J. Neurosci.: 22, 2283-98
Highly variable spike trains underlie reproducible sensory-motor responses in the leech
Zoccolan D, Pinato G, Torre V (2002)
J. Neurosci.: 22, 10790-800
Distributed motor pattern underlying whole-body shortening in the medicinal leech
Arisi I, Zoccolan D, Torre V (2001)
J. Neurophys. : 86, 2475-88
The use of optical flow to characterize muscle contraction
Zoccolan D, Giachetti A, Torre V (2001)
J. Neurosci. Methods: 110, 65-80
